diff --git a/.claude/settings.json b/.claude/settings.json
index ac6b69b143..416bb2617f 100644
--- a/.claude/settings.json
+++ b/.claude/settings.json
@@ -27,7 +27,14 @@
       "WebFetch(domain:docs.sentry.io)",
       "WebFetch(domain:develop.sentry.dev)",
       "Bash(grep:*)",
-      "Bash(mv:*)"
+      "Bash(mv:*)",
+      "Bash(source .venv/bin/activate)",
+      "Bash(source tox.venv/bin/activate:*)",
+      "Bash(tox:*)",
+      "Bash(tox.venv/bin/tox:*)",
+      "Bash(.tox/*/bin/python:*)",
+      "Bash(.tox/*/bin/pytest:*)",
+      "Bash(.tox/*/bin/ruff:*)"
     ],
     "deny": []
   }
diff --git a/.github/workflows/ai-integration-test.yml b/.github/workflows/ai-integration-test.yml
index ed9a08642a..6827ebb7d2 100644
--- a/.github/workflows/ai-integration-test.yml
+++ b/.github/workflows/ai-integration-test.yml
@@ -19,12 +19,12 @@ jobs:
 
     steps:
       - name: Setup Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         with:
           python-version: 3.14t
 
       - name: Setup Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: '20'
 
@@ -34,7 +34,7 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Run Python SDK Tests
-        uses: getsentry/testing-ai-sdk-integrations@121da677853244cedfe11e95184b2b431af102eb
+        uses: getsentry/testing-ai-sdk-integrations@1dd9ee2a2d821f41473fc90809a758e8394c689c
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         with:
diff --git a/.github/workflows/changelog-preview.yml b/.github/workflows/changelog-preview.yml
index 3788b29609..0854abe5da 100644
--- a/.github/workflows/changelog-preview.yml
+++ b/.github/workflows/changelog-preview.yml
@@ -15,5 +15,5 @@ permissions:
 
 jobs:
   changelog-preview:
-    uses: getsentry/craft/.github/workflows/changelog-preview.yml@v2
+    uses: getsentry/craft/.github/workflows/changelog-preview.yml@97d0c4286f32a80d09c8b89366d762fecc3e27b6 # v2
     secrets: inherit
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 735930533b..c7d3a95915 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -5,10 +5,13 @@ on:
     branches:
       - master
       - release/**
-      - potel-base
 
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
 permissions:
   contents: read
 
@@ -25,7 +28,7 @@ jobs:
 
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         with:
           python-version: 3.14
 
@@ -40,11 +43,11 @@ jobs:
 
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         with:
           python-version: 3.12
       - name: Setup build cache
-        uses: actions/cache@v5
+        uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5
         id: build_cache
         with:
           path: ${{ env.CACHED_BUILD_PATHS }}
@@ -55,7 +58,7 @@ jobs:
           # This will also trigger "make dist" that creates the Python packages
           make aws-lambda-layer
       - name: Upload Python Packages
-        uses: actions/upload-artifact@v7
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
         with:
           name: artifact-build_lambda_layer
           path: |
@@ -69,7 +72,7 @@ jobs:
 
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         with:
           python-version: 3.12
 
@@ -77,7 +80,7 @@ jobs:
           make apidocs
           cd docs/_build && zip -r gh-pages ./
 
-      - uses: actions/upload-artifact@v7
+      - uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
         with:
           name: artifact-docs
           path: |
diff --git a/.github/workflows/codeql-analysis.yml b/.github/workflows/codeql-analysis.yml
deleted file mode 100644
index a8f3e199bd..0000000000
--- a/.github/workflows/codeql-analysis.yml
+++ /dev/null
@@ -1,80 +0,0 @@
-# For most projects, this workflow file will not need changing; you simply need
-# to commit it to your repository.
-#
-# You may wish to alter this file to override the set of languages analyzed,
-# or to provide custom queries or build logic.
-#
-# ******** NOTE ********
-# We have attempted to detect the languages in your repository. Please check
-# the `language` matrix defined below to confirm you have the correct set of
-# supported CodeQL languages.
-#
-name: "CodeQL"
-
-on:
-  push:
-    branches:
-      - master
-      - potel-base
-  pull_request:
-  schedule:
-    - cron: '18 18 * * 3'
-
-# Cancel in progress workflows on pull_requests.
-# https://docs.github.com/en/actions/using-jobs/using-concurrency#example-using-a-fallback-value
-concurrency:
-  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
-  cancel-in-progress: true
-
-permissions:
-  contents: read
-
-jobs:
-  analyze:
-    permissions:
-      actions: read  # for github/codeql-action/init to get workflow details
-      contents: read  # for actions/checkout to fetch code
-      security-events: write  # for github/codeql-action/autobuild to send a status report
-    name: Analyze
-    runs-on: ubuntu-latest
-
-    strategy:
-      fail-fast: false
-      matrix:
-        language: [ 'python' ]
-        # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python' ]
-        # Learn more:
-        # https://docs.github.com/en/free-pro-team@latest/github/finding-security-vulnerabilities-and-errors-in-your-code/configuring-code-scanning#changing-the-languages-that-are-analyzed
-
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-
-    # Initializes the CodeQL tools for scanning.
-    - name: Initialize CodeQL
-      uses: github/codeql-action/init@v4
-      with:
-        languages: ${{ matrix.language }}
-        # If you wish to specify custom queries, you can do so here or in a config file.
-        # By default, queries listed here will override any specified in a config file.
-        # Prefix the list here with "+" to use these queries and those in the config file.
-        # queries: ./path/to/local/query, your-org/your-repo/queries@main
-
-    # Autobuild attempts to build any compiled languages  (C/C++, C#, or Java).
-    # If this step fails, then you should remove it and run the build manually (see below)
-    - name: Autobuild
-      uses: github/codeql-action/autobuild@v4
-
-    # ℹ️ Command-line programs to run using the OS shell.
-    # 📚 https://docs.github.com/en/actions/reference/workflow-syntax-for-github-actions
-
-    # ✏️ If the Autobuild fails above, remove it and uncomment the following three lines
-    #    and modify them (or add more) to build your code if your project
-    #    uses a compiled language
-
-    #- run: |
-    #   make bootstrap
-    #   make release
-
-    - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v4
diff --git a/.github/workflows/enforce-license-compliance.yml b/.github/workflows/enforce-license-compliance.yml
index 5517e5347f..fece653550 100644
--- a/.github/workflows/enforce-license-compliance.yml
+++ b/.github/workflows/enforce-license-compliance.yml
@@ -6,7 +6,6 @@ on:
       - master
       - main
       - release/*
-      - potel-base
   pull_request:
 
 # Cancel in progress workflows on pull_requests.
@@ -19,6 +18,6 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: 'Enforce License Compliance'
-        uses: getsentry/action-enforce-license-compliance@main
+        uses: getsentry/action-enforce-license-compliance@48236a773346cb6552a7bda1ee370d2797365d87 # main
         with:
           fossa_api_key: ${{ secrets.FOSSA_API_KEY }}
diff --git a/.github/workflows/release-comment-issues.yml b/.github/workflows/release-comment-issues.yml
index e18aeab155..0203ff59ed 100644
--- a/.github/workflows/release-comment-issues.yml
+++ b/.github/workflows/release-comment-issues.yml
@@ -33,7 +33,7 @@ jobs:
           && !contains(steps.get_version.outputs.version, 'a')
           && !contains(steps.get_version.outputs.version, 'b')
           && !contains(steps.get_version.outputs.version, 'rc')
-        uses: getsentry/release-comment-issues-gh-action@v1
+        uses: getsentry/release-comment-issues-gh-action@52e08022ca721e701515ede89edd224b63b180eb # v1
         with:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           version: ${{ steps.get_version.outputs.version }}
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 1d8fdb1000..07ba7f50ee 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -22,16 +22,16 @@ jobs:
     steps:
     - name: Get auth token
       id: token
-      uses: actions/create-github-app-token@29824e69f54612133e76f7eaac726eef6c875baf # v2
+      uses: actions/create-github-app-token@1b10c78c7865c340bc4f6099eb2f838309f1e8c3 # v3.1.1
       with:
         app-id: ${{ vars.SENTRY_RELEASE_BOT_CLIENT_ID }}
         private-key: ${{ secrets.SENTRY_RELEASE_BOT_PRIVATE_KEY }}
-    - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
+    - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
       with:
         token: ${{ steps.token.outputs.token }}
         fetch-depth: 0
     - name: Prepare release
-      uses: getsentry/craft@d4cfac9d25d1fc72c9241e5d22aff559a114e4e9 # v2
+      uses: getsentry/craft@97d0c4286f32a80d09c8b89366d762fecc3e27b6 # v2.25.4
       env:
         GITHUB_TOKEN: ${{ steps.token.outputs.token }}
       with:
diff --git a/.github/workflows/test-integrations-agents.yml b/.github/workflows/test-integrations-agents.yml
index a05649a5f0..efa0b9480c 100644
--- a/.github/workflows/test-integrations-agents.yml
+++ b/.github/workflows/test-integrations-agents.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -74,11 +74,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Agents tests passed
diff --git a/.github/workflows/test-integrations-ai-workflow.yml b/.github/workflows/test-integrations-ai-workflow.yml
index 7cd4cb86df..d7025ce067 100644
--- a/.github/workflows/test-integrations-ai-workflow.yml
+++ b/.github/workflows/test-integrations-ai-workflow.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -78,11 +78,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All AI Workflow tests passed
diff --git a/.github/workflows/test-integrations-ai.yml b/.github/workflows/test-integrations-ai.yml
index 0b305a3775..6d09c0ef5f 100644
--- a/.github/workflows/test-integrations-ai.yml
+++ b/.github/workflows/test-integrations-ai.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -94,11 +94,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All AI tests passed
diff --git a/.github/workflows/test-integrations-cloud.yml b/.github/workflows/test-integrations-cloud.yml
index d57034d4e3..c61d0a49d8 100644
--- a/.github/workflows/test-integrations-cloud.yml
+++ b/.github/workflows/test-integrations-cloud.yml
@@ -45,8 +45,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -90,11 +90,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Cloud tests passed
diff --git a/.github/workflows/test-integrations-common.yml b/.github/workflows/test-integrations-common.yml
index 9b333435bd..c96d1adc0c 100644
--- a/.github/workflows/test-integrations-common.yml
+++ b/.github/workflows/test-integrations-common.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -70,11 +70,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Common tests passed
diff --git a/.github/workflows/test-integrations-dbs.yml b/.github/workflows/test-integrations-dbs.yml
index c27d728b98..15bee0cf2a 100644
--- a/.github/workflows/test-integrations-dbs.yml
+++ b/.github/workflows/test-integrations-dbs.yml
@@ -59,14 +59,14 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
           allow-prereleases: true
       - name: "Setup ClickHouse Server"
-        uses: getsentry/action-clickhouse-in-ci@v1.7
+        uses: getsentry/action-clickhouse-in-ci@5dc8a6a50d689bd6051db0241f34849e5a36490b # v1.7
       - name: Setup Test Env
         run: |
           pip install "coverage[toml]" tox
@@ -110,11 +110,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All DBs tests passed
diff --git a/.github/workflows/test-integrations-flags.yml b/.github/workflows/test-integrations-flags.yml
index cd20a6ec5e..f3cdf1f143 100644
--- a/.github/workflows/test-integrations-flags.yml
+++ b/.github/workflows/test-integrations-flags.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -82,11 +82,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Flags tests passed
diff --git a/.github/workflows/test-integrations-gevent.yml b/.github/workflows/test-integrations-gevent.yml
index 525140dfa7..1ecdac2953 100644
--- a/.github/workflows/test-integrations-gevent.yml
+++ b/.github/workflows/test-integrations-gevent.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -70,11 +70,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Gevent tests passed
diff --git a/.github/workflows/test-integrations-graphql.yml b/.github/workflows/test-integrations-graphql.yml
index 322a95ff54..01df240ad0 100644
--- a/.github/workflows/test-integrations-graphql.yml
+++ b/.github/workflows/test-integrations-graphql.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -82,11 +82,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All GraphQL tests passed
diff --git a/.github/workflows/test-integrations-mcp.yml b/.github/workflows/test-integrations-mcp.yml
index 4b576a897f..de70b5c04e 100644
--- a/.github/workflows/test-integrations-mcp.yml
+++ b/.github/workflows/test-integrations-mcp.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -74,11 +74,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All MCP tests passed
diff --git a/.github/workflows/test-integrations-misc.yml b/.github/workflows/test-integrations-misc.yml
index 021d6cda79..ee1ec4628a 100644
--- a/.github/workflows/test-integrations-misc.yml
+++ b/.github/workflows/test-integrations-misc.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -102,11 +102,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Misc tests passed
diff --git a/.github/workflows/test-integrations-network.yml b/.github/workflows/test-integrations-network.yml
index ee4579f50f..e93c60056a 100644
--- a/.github/workflows/test-integrations-network.yml
+++ b/.github/workflows/test-integrations-network.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -61,6 +61,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh "py${{ matrix.python-version }}-httpx"
+      - name: Test pyreqwest
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh "py${{ matrix.python-version }}-pyreqwest"
       - name: Test requests
         run: |
           set -x # print commands that are executed
@@ -78,11 +82,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Network tests passed
diff --git a/.github/workflows/test-integrations-tasks.yml b/.github/workflows/test-integrations-tasks.yml
index bab5ddf335..49910d3c72 100644
--- a/.github/workflows/test-integrations-tasks.yml
+++ b/.github/workflows/test-integrations-tasks.yml
@@ -41,16 +41,16 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
           allow-prereleases: true
       - name: Start Redis
-        uses: supercharge/redis-github-action@v2
+        uses: supercharge/redis-github-action@87f27ff1ab2d9e62db54b11ee5e7f78ff18f8933 # v2
       - name: Install Java
-        uses: actions/setup-java@v5
+        uses: actions/setup-java@be666c2fcd27ec809703dec50e508c2fdc7f6654 # v5
         with:
           distribution: 'temurin'
           java-version: '21'
@@ -105,11 +105,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Tasks tests passed
diff --git a/.github/workflows/test-integrations-web-1.yml b/.github/workflows/test-integrations-web-1.yml
index 82632632e7..362b98dad9 100644
--- a/.github/workflows/test-integrations-web-1.yml
+++ b/.github/workflows/test-integrations-web-1.yml
@@ -59,8 +59,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -100,11 +100,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Web 1 tests passed
diff --git a/.github/workflows/test-integrations-web-2.yml b/.github/workflows/test-integrations-web-2.yml
index 9dec6bff24..69076bf16b 100644
--- a/.github/workflows/test-integrations-web-2.yml
+++ b/.github/workflows/test-integrations-web-2.yml
@@ -41,8 +41,8 @@ jobs:
     # Use Docker container only for Python 3.6
     container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         if: ${{ matrix.python-version != '3.6' }}
         with:
           python-version: ${{ matrix.python-version }}
@@ -106,11 +106,12 @@ jobs:
           coverage xml
       - name: Parse and Upload Coverage
         if: ${{ !cancelled() }}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
   check_required_tests:
     name: All Web 2 tests passed
diff --git a/.github/workflows/update-tox.yml b/.github/workflows/update-tox.yml
index 914109eae8..105377cfd2 100644
--- a/.github/workflows/update-tox.yml
+++ b/.github/workflows/update-tox.yml
@@ -18,7 +18,7 @@ jobs:
 
     steps:
       - name: Setup Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         with:
           python-version: 3.14t
 
@@ -42,7 +42,7 @@ jobs:
         run: |
           COMMIT_TITLE="ci: 🤖 Update test matrix with new releases"
           DATE=`date +%m/%d`
-          BRANCH_NAME="toxgen/update"
+          BRANCH_NAME="toxgen/update-`date +%m-%d`"
 
           git checkout -B "$BRANCH_NAME"
           git add --all
@@ -54,7 +54,7 @@ jobs:
           echo "date=$DATE" >> $GITHUB_OUTPUT
 
       - name: Create pull request
-        uses: actions/github-script@v8
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
         with:
           script: |
             const branchName = '${{ steps.create-branch.outputs.branch_name }}';
@@ -78,20 +78,21 @@ jobs:
 
             // Close existing toxgen PRs as they're now obsolete
 
-            const { data: existingPRs } = await github.rest.pulls.list({
+            const existingPRs = await github.paginate(github.rest.pulls.list, {
                 owner: context.repo.owner,
                 repo: context.repo.repo,
-                head: `${context.repo.owner}:${branchName}`,
                 state: 'open'
             });
 
             for (const pr of existingPRs) {
-                await github.rest.pulls.update({
-                    owner: context.repo.owner,
-                    repo: context.repo.repo,
-                    pull_number: pr.number,
-                    state: 'closed'
-                })
+                if (pr.head.ref.startsWith('toxgen/')) {
+                    await github.rest.pulls.update({
+                        owner: context.repo.owner,
+                        repo: context.repo.repo,
+                        pull_number: pr.number,
+                        state: 'closed'
+                    })
+                }
             };
 
             const { data: pr } = await github.rest.pulls.create({
diff --git a/.github/workflows/validate-pr.yml b/.github/workflows/validate-pr.yml
new file mode 100644
index 0000000000..10fe894067
--- /dev/null
+++ b/.github/workflows/validate-pr.yml
@@ -0,0 +1,16 @@
+name: Validate PR
+
+on:
+  pull_request_target:
+    types: [opened, reopened]
+
+jobs:
+  validate-pr:
+    runs-on: ubuntu-24.04
+    permissions:
+      pull-requests: write
+    steps:
+      - uses: getsentry/github-workflows/validate-pr@71588ddf95134f804e82c5970a8098588e2eaecd
+        with:
+          app-id: ${{ vars.SDK_MAINTAINER_BOT_APP_ID }}
+          private-key: ${{ secrets.SDK_MAINTAINER_BOT_PRIVATE_KEY }}
diff --git a/.github/workflows/warden.yml b/.github/workflows/warden.yml
deleted file mode 100644
index f2ff05325a..0000000000
--- a/.github/workflows/warden.yml
+++ /dev/null
@@ -1,24 +0,0 @@
-name: Warden
-
-on:
-  pull_request:
-    types: [opened, synchronize, reopened]
-
-# contents: write required for resolving review threads via GraphQL
-# See: https://github.com/orgs/community/discussions/44650
-permissions:
-  contents: write
-  pull-requests: write
-  checks: write
-
-jobs:
-  review:
-    runs-on: ubuntu-latest
-    env:
-      WARDEN_MODEL: ${{ secrets.WARDEN_MODEL }}
-      WARDEN_SENTRY_DSN: ${{ secrets.WARDEN_SENTRY_DSN }}
-    steps:
-      - uses: actions/checkout@v4
-      - uses: getsentry/warden@v0
-        with:
-          anthropic-api-key: ${{ secrets.WARDEN_ANTHROPIC_API_KEY }}
diff --git a/.gitignore b/.gitignore
index 4e35d43fb5..c5ae46befa 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,6 +21,8 @@ sentry-python-serverless*.zip
 .eggs
 venv
 .venv
+tox.venv
+toxgen.venv
 .vscode/tags
 .pytest_cache
 .hypothesis
diff --git a/AGENTS.md b/AGENTS.md
index 6179106348..f1b5c696df 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -11,6 +11,8 @@ Use **tox** for testing (not pytest directly):
 - Test matrix configuration is in `tox.ini`
 - Integration tests: `tox -e py3.14-{integration}-v{version}`
 - Common tests: `tox -e py3.14-common`
+- Run specific test file: `TESTPATH=tests/integrations/logging/test_logging.py tox -e py3.14-common`
+- Run single test: `TESTPATH=tests/path/to/test_file.py tox -e py3.14-common -- -k "test_name"`
 
 ## Type Checking
 
diff --git a/CHANGELOG.md b/CHANGELOG.md
index f21da70dda..8892b397dd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,229 @@
 # Changelog
 
+## 2.58.0
+
+### New Features ✨
+
+- (ai) Redact base64 data URLs in image_url content blocks by @ericapisani in [#5953](https://github.com/getsentry/sentry-python/pull/5953)
+- (integrations) Instrument pyreqwest tracing by @servusdei2018 in [#5682](https://github.com/getsentry/sentry-python/pull/5682)
+- (litellm) Add async callbacks by @alexander-alderman-webb in [#5969](https://github.com/getsentry/sentry-python/pull/5969)
+
+### Bug Fixes 🐛
+
+#### Anthropic
+
+- Capture exceptions for `stream()` calls by @alexander-alderman-webb in [#5950](https://github.com/getsentry/sentry-python/pull/5950)
+- Stop setting transaction status when child span fails by @alexander-alderman-webb in [#5717](https://github.com/getsentry/sentry-python/pull/5717)
+- Only finish relevant spans in .create() patches by @alexander-alderman-webb in [#5716](https://github.com/getsentry/sentry-python/pull/5716)
+
+#### Pydantic Ai
+
+- Adapt import for new library versions by @alexander-alderman-webb in [#5984](https://github.com/getsentry/sentry-python/pull/5984)
+- Use first-class hooks when available by @alexander-alderman-webb in [#5947](https://github.com/getsentry/sentry-python/pull/5947)
+
+#### Other
+
+- (huggingface_hub) Stop setting transaction status when a child span fails by @Zenithatic in [#5952](https://github.com/getsentry/sentry-python/pull/5952)
+- (litellm) Avoid double span exits when streaming by @alexander-alderman-webb in [#5933](https://github.com/getsentry/sentry-python/pull/5933)
+- (wsgi) Respect HTTP_X_FORWARDED_PROTO in request.url construction by @sl0thentr0py in [#5963](https://github.com/getsentry/sentry-python/pull/5963)
+
+### Internal Changes 🔧
+
+#### Litellm
+
+- Replace mocks with `httpx` types in rate-limit test by @alexander-alderman-webb in [#5975](https://github.com/getsentry/sentry-python/pull/5975)
+- Replace mocks with `httpx` types in embedding tests by @alexander-alderman-webb in [#5970](https://github.com/getsentry/sentry-python/pull/5970)
+- Replace mocks with `httpx` types in nonstreaming `completion()` tests by @alexander-alderman-webb in [#5937](https://github.com/getsentry/sentry-python/pull/5937)
+- Remove dead attributes by @alexander-alderman-webb in [#5985](https://github.com/getsentry/sentry-python/pull/5985)
+
+#### Other
+
+- (ai) Remove `gen_ai.tool.type` span attribute by @ericapisani in [#5964](https://github.com/getsentry/sentry-python/pull/5964)
+- (anthropic) Separate sync and async .create() patches by @alexander-alderman-webb in [#5715](https://github.com/getsentry/sentry-python/pull/5715)
+- (openai) Split token counting by API for easier deprecation by @ericapisani in [#5930](https://github.com/getsentry/sentry-python/pull/5930)
+- (openai-agents) Remove error attributes by @alexander-alderman-webb in [#5986](https://github.com/getsentry/sentry-python/pull/5986)
+- (opentelemetry) Ignore mypy error by @alexander-alderman-webb in [#5927](https://github.com/getsentry/sentry-python/pull/5927)
+- 🤖 Update test matrix with new releases (04/13) by @github-actions in [#5983](https://github.com/getsentry/sentry-python/pull/5983)
+- Fix license metadata in setup.py by @sl0thentr0py in [#5934](https://github.com/getsentry/sentry-python/pull/5934)
+- Update validate-pr workflow by @stephanie-anderson in [#5931](https://github.com/getsentry/sentry-python/pull/5931)
+
+### Other
+
+- Handle `None` span context in the span processor and pin tokenizers version for anthropic tests on Python 3.8 by @alexander-alderman-webb in [#5967](https://github.com/getsentry/sentry-python/pull/5967)
+
+## 2.57.0
+
+### New Features ✨
+
+#### Langchain
+
+- Set `gen_ai.operation.name` and `gen_ai.pipeline.name` on LLM spans by @ericapisani in [#5849](https://github.com/getsentry/sentry-python/pull/5849)
+- Broaden AI provider detection beyond OpenAI and Anthropic by @ericapisani in [#5707](https://github.com/getsentry/sentry-python/pull/5707)
+- Update LLM span operation to `gen_ai.generate_text` by @ericapisani in [#5796](https://github.com/getsentry/sentry-python/pull/5796)
+
+#### Other
+
+- Add experimental async transport by @BYK in [#5646](https://github.com/getsentry/sentry-python/pull/5646)
+
+  See https://github.com/getsentry/sentry-python/discussions/5919 for details.
+
+### Bug Fixes 🐛
+
+#### Openai
+
+- Only wrap types with `_iterator` for streamed responses by @alexander-alderman-webb in [#5917](https://github.com/getsentry/sentry-python/pull/5917)
+- Always set `gen_ai.response.streaming` for Responses by @alexander-alderman-webb in [#5697](https://github.com/getsentry/sentry-python/pull/5697)
+- Simplify Responses input handling by @alexander-alderman-webb in [#5695](https://github.com/getsentry/sentry-python/pull/5695)
+- Use `max_output_tokens` for Responses API by @alexander-alderman-webb in [#5693](https://github.com/getsentry/sentry-python/pull/5693)
+- Always set `gen_ai.response.streaming` for Completions by @alexander-alderman-webb in [#5692](https://github.com/getsentry/sentry-python/pull/5692)
+- Simplify Completions input handling by @alexander-alderman-webb in [#5690](https://github.com/getsentry/sentry-python/pull/5690)
+- Simplify embeddings input handling by @alexander-alderman-webb in [#5688](https://github.com/getsentry/sentry-python/pull/5688)
+
+#### Other
+
+- (google-genai) Guard response extraction by @alexander-alderman-webb in [#5869](https://github.com/getsentry/sentry-python/pull/5869)
+- Add cycle detection to exceptions_from_error by @ericapisani in [#5880](https://github.com/getsentry/sentry-python/pull/5880)
+
+### Internal Changes 🔧
+
+#### Ai
+
+- Remove unused GEN_AI_PIPELINE operation constant by @ericapisani in [#5886](https://github.com/getsentry/sentry-python/pull/5886)
+- Rename generate_text to text_completion by @ericapisani in [#5885](https://github.com/getsentry/sentry-python/pull/5885)
+
+#### Langchain
+
+- Add text completion test by @alexander-alderman-webb in [#5740](https://github.com/getsentry/sentry-python/pull/5740)
+- Add tool execution test by @alexander-alderman-webb in [#5739](https://github.com/getsentry/sentry-python/pull/5739)
+- Add basic agent test with Responses call by @alexander-alderman-webb in [#5726](https://github.com/getsentry/sentry-python/pull/5726)
+- Replace mocks with `httpx` types by @alexander-alderman-webb in [#5724](https://github.com/getsentry/sentry-python/pull/5724)
+- Consolidate span origin assertion by @alexander-alderman-webb in [#5723](https://github.com/getsentry/sentry-python/pull/5723)
+- Consolidate available tools assertion by @alexander-alderman-webb in [#5721](https://github.com/getsentry/sentry-python/pull/5721)
+
+#### Openai
+
+- Replace mocks with httpx types for streaming Responses by @alexander-alderman-webb in [#5882](https://github.com/getsentry/sentry-python/pull/5882)
+- Replace mocks with httpx types for streaming Completions by @alexander-alderman-webb in [#5879](https://github.com/getsentry/sentry-python/pull/5879)
+- Move input handling code into API-specific functions by @alexander-alderman-webb in [#5687](https://github.com/getsentry/sentry-python/pull/5687)
+
+#### Other
+
+- (asyncpg) Normalize query whitespace in integration by @ericapisani in [#5855](https://github.com/getsentry/sentry-python/pull/5855)
+- Exclude compromised litellm versions by @alexander-alderman-webb in [#5876](https://github.com/getsentry/sentry-python/pull/5876)
+
+
+## 2.56.0
+
+### New Features ✨
+
+- (asgi) Add option to disable suppressing chained exceptions by @alexander-alderman-webb in [#5714](https://github.com/getsentry/sentry-python/pull/5714)
+- (logging) Separate ignore lists for events/breadcrumbs and sentry logs by @sl0thentr0py in [#5698](https://github.com/getsentry/sentry-python/pull/5698)
+
+### Bug Fixes 🐛
+
+#### Anthropic
+
+- Set exception info on streaming span when applicable by @alexander-alderman-webb in [#5683](https://github.com/getsentry/sentry-python/pull/5683)
+- Patch `AsyncStream.close()` and `AsyncMessageStream.close()` to finish spans by @alexander-alderman-webb in [#5675](https://github.com/getsentry/sentry-python/pull/5675)
+- Patch `Stream.close()` and `MessageStream.close()` to finish spans by @alexander-alderman-webb in [#5674](https://github.com/getsentry/sentry-python/pull/5674)
+
+#### Other
+
+- (starlette) Catch Jinja2Templates ImportError by @alexander-alderman-webb in [#5741](https://github.com/getsentry/sentry-python/pull/5741)
+
+### Documentation 📚
+
+- Add note on AI PRs to CONTRIBUTING.md by @sentrivana in [#5696](https://github.com/getsentry/sentry-python/pull/5696)
+
+### Internal Changes 🔧
+
+- Pin GitHub Actions to full-length commit SHAs by @joshuarli in [#5781](https://github.com/getsentry/sentry-python/pull/5781)
+- Add `-latest` alias for each integration test suite by @sentrivana in [#5706](https://github.com/getsentry/sentry-python/pull/5706)
+- Use date-based branch names for toxgen PRs by @sentrivana in [#5704](https://github.com/getsentry/sentry-python/pull/5704)
+- 🤖 Update test matrix with new releases (03/19) by @github-actions in [#5703](https://github.com/getsentry/sentry-python/pull/5703)
+- Add client report tests for span streaming by @sentrivana in [#5677](https://github.com/getsentry/sentry-python/pull/5677)
+
+### Other
+
+- Update CHANGELOG.md by @sentrivana in [#5685](https://github.com/getsentry/sentry-python/pull/5685)
+
+## 2.55.0
+
+### New Features ✨
+
+#### Anthropic
+
+- Record finish reasons in AI monitoring spans by @ericapisani in [#5678](https://github.com/getsentry/sentry-python/pull/5678)
+- Emit `gen_ai.chat` spans for asynchronous `messages.stream()` by @alexander-alderman-webb in [#5572](https://github.com/getsentry/sentry-python/pull/5572)
+- Emit AI Client Spans for synchronous `messages.stream()` by @alexander-alderman-webb in [#5565](https://github.com/getsentry/sentry-python/pull/5565)
+- Set gen_ai.response.id span attribute by @ericapisani in [#5662](https://github.com/getsentry/sentry-python/pull/5662)
+- Add `gen_ai.system` attribute to spans by @ericapisani in [#5661](https://github.com/getsentry/sentry-python/pull/5661)
+
+#### Pydantic Ai
+
+- Support ImageUrl content type in span instrumentation by @ericapisani in [#5629](https://github.com/getsentry/sentry-python/pull/5629)
+- Add tool description to execute_tool spans by @ericapisani in [#5596](https://github.com/getsentry/sentry-python/pull/5596)
+
+#### Other
+
+- (crons) Add owner field to MonitorConfig by @julwhitney13 in [#5610](https://github.com/getsentry/sentry-python/pull/5610)
+- (otlp) Add collector_url option to OTLPIntegration by @sl0thentr0py in [#5603](https://github.com/getsentry/sentry-python/pull/5603)
+
+### Bug Fixes 🐛
+
+- (ai) Truncate list-based message content in AI monitoring by @ericapisani in [#5631](https://github.com/getsentry/sentry-python/pull/5631)
+- (anthropic) Close span on `GeneratorExit` by @alexander-alderman-webb in [#5643](https://github.com/getsentry/sentry-python/pull/5643)
+- (celery) Propagate user-set headers by @sentrivana in [#5581](https://github.com/getsentry/sentry-python/pull/5581)
+- (langchain) Wrap finish_reason in array for gen_ai span attribute by @ericapisani in [#5666](https://github.com/getsentry/sentry-python/pull/5666)
+- (logging) Fix deadlock in log batcher by @sentrivana in [#5684](https://github.com/getsentry/sentry-python/pull/5684)
+- (profiler) Prevent buffer race condition during rapid start/stop cycles by @ericapisani in [#5622](https://github.com/getsentry/sentry-python/pull/5622)
+- (utils) Avoid double serialization of strings in safe_serialize by @ericapisani in [#5587](https://github.com/getsentry/sentry-python/pull/5587)
+- Enable unused import ruff check and fix unused imports by @sentrivana in [#5652](https://github.com/getsentry/sentry-python/pull/5652)
+
+### Documentation 📚
+
+- (openai-agents) Remove inapplicable comment by @alexander-alderman-webb in [#5495](https://github.com/getsentry/sentry-python/pull/5495)
+- Add AGENTS.md by @sentrivana in [#5579](https://github.com/getsentry/sentry-python/pull/5579)
+- Add `set_attribute` example to changelog by @sentrivana in [#5578](https://github.com/getsentry/sentry-python/pull/5578)
+
+### Internal Changes 🔧
+
+#### Anthropic
+
+- Check system and response ID attributes on spans created by `stream()` by @alexander-alderman-webb in [#5665](https://github.com/getsentry/sentry-python/pull/5665)
+- Skip accumulation logic for unexpected types in streamed response by @alexander-alderman-webb in [#5564](https://github.com/getsentry/sentry-python/pull/5564)
+- Factor out streamed result handling by @alexander-alderman-webb in [#5563](https://github.com/getsentry/sentry-python/pull/5563)
+- Stream valid JSON by @alexander-alderman-webb in [#5641](https://github.com/getsentry/sentry-python/pull/5641)
+- Stop mocking response iterator by @alexander-alderman-webb in [#5573](https://github.com/getsentry/sentry-python/pull/5573)
+
+#### Openai Agents
+
+- Do not fail on new tool fields by @alexander-alderman-webb in [#5625](https://github.com/getsentry/sentry-python/pull/5625)
+- Stop expecting a specific function name by @alexander-alderman-webb in [#5623](https://github.com/getsentry/sentry-python/pull/5623)
+- Set streaming header when library uses `with_streaming_response()` by @alexander-alderman-webb in [#5583](https://github.com/getsentry/sentry-python/pull/5583)
+- Replace mocks with `httpx` for streamed responses by @alexander-alderman-webb in [#5580](https://github.com/getsentry/sentry-python/pull/5580)
+- Replace mocks with `httpx` in non-MCP tool tests by @alexander-alderman-webb in [#5602](https://github.com/getsentry/sentry-python/pull/5602)
+- Replace mocks with `httpx` in MCP tool tests by @alexander-alderman-webb in [#5605](https://github.com/getsentry/sentry-python/pull/5605)
+- Replace mocks with `httpx` in handoff tests by @alexander-alderman-webb in [#5604](https://github.com/getsentry/sentry-python/pull/5604)
+- Replace mocks with `httpx` in API error test by @alexander-alderman-webb in [#5601](https://github.com/getsentry/sentry-python/pull/5601)
+- Replace mocks with `httpx` in non-error single-response tests by @alexander-alderman-webb in [#5600](https://github.com/getsentry/sentry-python/pull/5600)
+- Remove test for unreachable state by @alexander-alderman-webb in [#5584](https://github.com/getsentry/sentry-python/pull/5584)
+- Expect `namespace` tool field for new `openai` versions by @alexander-alderman-webb in [#5599](https://github.com/getsentry/sentry-python/pull/5599)
+
+#### Other
+
+- (graphene) Simplify span creation by @sentrivana in [#5648](https://github.com/getsentry/sentry-python/pull/5648)
+- (httpx) Resolve type checking failures by @alexander-alderman-webb in [#5626](https://github.com/getsentry/sentry-python/pull/5626)
+- (pyramid) Support alpha suffixes in version parsing by @alexander-alderman-webb in [#5618](https://github.com/getsentry/sentry-python/pull/5618)
+- (rust) Don't implement separate scope management by @sentrivana in [#5639](https://github.com/getsentry/sentry-python/pull/5639)
+- (strawberry) Simplify span creation by @sentrivana in [#5647](https://github.com/getsentry/sentry-python/pull/5647)
+- 🤖 Update test matrix with new releases (03/16) by @github-actions in [#5671](https://github.com/getsentry/sentry-python/pull/5671)
+- Remove custom warden action by @sentrivana in [#5653](https://github.com/getsentry/sentry-python/pull/5653)
+- Add `httpx` to linting requirements by @alexander-alderman-webb in [#5644](https://github.com/getsentry/sentry-python/pull/5644)
+- Remove CodeQL action by @sentrivana in [#5616](https://github.com/getsentry/sentry-python/pull/5616)
+- Normalize dots in package names in `populate_tox.py` by @alexander-alderman-webb in [#5574](https://github.com/getsentry/sentry-python/pull/5574)
+- Do not run actions on `potel-base` by @sentrivana in [#5614](https://github.com/getsentry/sentry-python/pull/5614)
+
 ## 2.54.0
 
 ### New Features ✨
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 0286a3170e..6149d86336 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -4,18 +4,63 @@ We welcome contributions to `sentry-python` by the community.
 
 This file outlines the process to contribute to the SDK itself. For contributing to the documentation, please see the [Contributing to Docs](https://docs.sentry.io/contributing/) page.
 
+## Table of Contents
+
+- [How to Report a Problem](#how-to-report-a-problem)
+- [Submitting Changes](#submitting-changes)
+- [Development Environment](#development-environment)
+- [Running Tests](#running-tests)
+- [Debugging](#debugging)
+- [Adding a New Integration](#adding-a-new-integration)
+- [Releasing a New Version](#releasing-a-new-version)
+- [Contributing to Sentry AWS Lambda Layer](#contributing-to-sentry-aws-lambda-layer)
+
 ## How to Report a Problem
 
 Please search the [issue tracker](https://github.com/getsentry/sentry-python/issues) before creating a new issue (a problem or an improvement request). Please also ask in our [Sentry Community on Discord](https://discord.com/invite/Ww9hbqr) before submitting a new issue. There are a ton of great people in our Discord community ready to help you!
 
 ## Submitting Changes
 
+### Before You Start
+
+1. **Find or create an issue.** Every contribution must be tied to a GitHub issue. If one doesn't exist, open one describing the problem or feature.
+2. **Discuss your approach with a maintainer.** Comment on the issue and wait for a maintainer to respond before you start working. This avoids wasted effort on both sides.
+3. **Check the assignee.** If the issue is already assigned to someone else, coordinate with them in the issue before starting work.
+
+PRs that don't meet these requirements will be automatically closed. See [Automated Checks](#automated-checks) below.
+
+### Making Your Contribution
+
 - Fork the `sentry-python` repo and prepare your changes.
 - Add tests for your changes to `tests/`.
 - Run tests and make sure all of them pass.
-- Submit a pull request, referencing any issues your changes address. Please follow our [commit message format](https://develop.sentry.dev/commit-messages/#commit-message-format) when naming your pull request.
+- Submit a pull request, referencing the issue(s) your changes address. Please follow our [commit message format](https://develop.sentry.dev/commit-messages/#commit-message-format) when naming your pull request.
+
+### Pull Request Requirements
+
+All PRs must be created as **drafts**. Non-draft PRs will be automatically converted to draft. Mark your PR as "Ready for review" once:
+
+- CI passes
+- The PR description is complete (what, why, and links to relevant issues)
+- You've personally reviewed your own changes
+
+A PR should do one thing well. Don't mix functional changes with unrelated refactors or cleanup. Smaller, focused PRs are easier to review, reason about, and revert if needed.
+
+For the full set of PR standards, see the [code submission standard](https://develop.sentry.dev/sdk/getting-started/standards/code-submission/#pull-requests).
+
+### AI Use
+
+You are welcome to use whatever tools you prefer for making a contribution. However, any changes you propose have to be reviewed and tested by you, a human, first, before you submit a pull request with them for the Sentry team to review. If we feel like that didn't happen, we will close the PR outright. For example, we won't review visibly AI-generated PRs from an agent instructed to look for and "fix" open issues in the repo.
+
+### Automated Checks
+
+To maintain the quality of contributions, we use automated workflows that enforce the following rules for PRs from non-maintainers:
+
+- **Issue reference required.** Your PR body must reference a GitHub issue in the `getsentry` organization (e.g. `#123`, `getsentry/sentry#456`, or a full GitHub issue URL).
+- **Prior discussion required.** The referenced issue must show a conversation between you and a maintainer. Opening the issue counts as participation — but a maintainer must have also responded.
+- **Respect existing assignees.** If the referenced issue is assigned to someone other than you, the PR will be closed. Coordinate in the issue first.
 
-We will review your pull request as soon as possible. Thank you for contributing!
+PRs that don't meet these criteria are automatically closed and labeled `violating-contribution-guidelines`. If your PR was closed by mistake, comment on the issue to discuss with a maintainer and then open a new PR.
 
 ## Development Environment
 
diff --git a/docs/conf.py b/docs/conf.py
index a3ecc64b9b..59010b9a2e 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -31,7 +31,7 @@
 copyright = "2019-{}, Sentry Team and Contributors".format(datetime.now().year)
 author = "Sentry Team and Contributors"
 
-release = "2.54.0"
+release = "2.58.0"
 version = ".".join(release.split(".")[:2])  # The short X.Y version.
 
 
diff --git a/pyproject.toml b/pyproject.toml
index 4b3d72ea09..b090d9bd4d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -227,7 +227,6 @@ ignore = [
     "N804", # First argument of classmethod should be named cls
 
     # Additional ignores for codebase compatibility
-    "F401", # Unused imports - many in TYPE_CHECKING blocks used for type comments
     "E721", # Use isinstance instead of type() == - existing pattern in this codebase
 ]
 
diff --git a/requirements-linting.txt b/requirements-linting.txt
index 84f846021a..7e5c143133 100644
--- a/requirements-linting.txt
+++ b/requirements-linting.txt
@@ -19,3 +19,4 @@ UnleashClient
 typer
 strawberry-graphql
 setuptools<82
+httpx
diff --git a/requirements-testing.txt b/requirements-testing.txt
index 5cd669af9a..a6041972cd 100644
--- a/requirements-testing.txt
+++ b/requirements-testing.txt
@@ -4,6 +4,7 @@ tomli;python_version<"3.11"  # Only needed for pytest on Python < 3.11
 pytest-cov
 pytest-forked
 pytest-localserver
+pytest-timeout
 pytest-watch
 jsonschema
 executing
diff --git a/scripts/build_aws_lambda_layer.py b/scripts/build_aws_lambda_layer.py
index fce67080de..af85b8b96d 100644
--- a/scripts/build_aws_lambda_layer.py
+++ b/scripts/build_aws_lambda_layer.py
@@ -18,7 +18,7 @@ class LayerBuilder:
     def __init__(
         self,
         base_dir: str,
-        out_zip_filename: "Optional[str]"=None,
+        out_zip_filename: "Optional[str]" = None,
     ) -> None:
         self.base_dir = base_dir
         self.python_site_packages = os.path.join(self.base_dir, PYTHON_SITE_PACKAGES)
diff --git a/scripts/populate_tox/config.py b/scripts/populate_tox/config.py
index c6921754b4..457b52dbb2 100644
--- a/scripts/populate_tox/config.py
+++ b/scripts/populate_tox/config.py
@@ -18,6 +18,9 @@
         "deps": {
             "*": ["pytest-asyncio"],
             "<0.50": ["httpx<0.28.0"],
+            # tokenizers dropped Python 3.8 support, but didn't update package metadata.
+            # https://github.com/huggingface/tokenizers/commit/f4c9fd7f402fc794df8f1b547a95ee5305f9fe62
+            "py3.8": ["tokenizers<0.20.4"],
         },
         "python": ">=3.8",
     },
@@ -122,7 +125,8 @@
                 "pytest-asyncio",
                 "python-multipart",
                 "requests",
-                "anyio<4",
+                "anyio>=3,<5",
+                "jinja2",
             ],
             # There's an incompatibility between FastAPI's TestClient, which is
             # actually Starlette's TestClient, which is actually httpx's Client.
@@ -132,6 +136,7 @@
             # FastAPI versions we use older httpx which still supports the
             # deprecated argument.
             "<0.110.1": ["httpx<0.28.0"],
+            "<0.80": ["anyio<4"],
             "py3.6": ["aiocontextvars"],
         },
     },
@@ -170,7 +175,8 @@
     "httpx": {
         "package": "httpx",
         "deps": {
-            "*": ["anyio<4.0.0"],
+            "*": ["anyio>=3,<5"],
+            "<0.24": ["anyio<4"],
             ">=0.16,<0.17": ["pytest-httpx==0.10.0"],
             ">=0.17,<0.19": ["pytest-httpx==0.12.0"],
             ">=0.19,<0.21": ["pytest-httpx==0.14.0"],
@@ -231,6 +237,9 @@
     },
     "litellm": {
         "package": "litellm",
+        "deps": {
+            "*": ["anthropic", "google-genai", "pytest-asyncio"],
+        },
     },
     "litestar": {
         "package": "litestar",
@@ -305,6 +314,14 @@
         "deps": {
             "*": ["pytest-asyncio"],
         },
+        "python": ">=3.10",
+    },
+    "pyreqwest": {
+        "package": "pyreqwest",
+        "deps": {
+            "*": ["pytest-asyncio"],
+        },
+        "python": ">=3.11",
     },
     "pymongo": {
         "package": "pymongo",
diff --git a/scripts/populate_tox/package_dependencies.jsonl b/scripts/populate_tox/package_dependencies.jsonl
index 7166d22ce6..8625b727da 100644
--- a/scripts/populate_tox/package_dependencies.jsonl
+++ b/scripts/populate_tox/package_dependencies.jsonl
@@ -1,39 +1,43 @@
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diff --git a/scripts/populate_tox/populate_tox.py b/scripts/populate_tox/populate_tox.py
index 196a4d76fe..fa0c31a3d1 100644
--- a/scripts/populate_tox/populate_tox.py
+++ b/scripts/populate_tox/populate_tox.py
@@ -4,6 +4,7 @@
 See scripts/populate_tox/README.md for more info.
 """
 
+import re
 import functools
 import hashlib
 import json
@@ -19,7 +20,6 @@
 from packaging.specifiers import SpecifierSet
 from packaging.version import Version
 from pathlib import Path
-from textwrap import dedent
 from typing import Optional, Union
 
 # Adding the scripts directory to PATH. This is necessary in order to be able
@@ -724,6 +724,31 @@ def _render_dependencies(integration: str, releases: list[Version]) -> list[str]
     return rendered
 
 
+def _render_latest_dependencies(
+    integration: str, latest_release: Version
+) -> list[str]:
+    """Render version-specific dependencies for the 'latest' alias.
+
+    Dependencies with "*" or "py3.*" constraints already match the latest
+    env via tox factor matching, so only version-specific constraints need
+    to be duplicated here.
+    """
+    rendered = []
+
+    if TEST_SUITE_CONFIG[integration].get("deps") is None:
+        return rendered
+
+    for constraint, deps in TEST_SUITE_CONFIG[integration]["deps"].items():
+        if constraint == "*" or constraint.startswith("py3"):
+            continue
+        restriction = SpecifierSet(constraint, prereleases=True)
+        if latest_release in restriction:
+            for dep in deps:
+                rendered.append(f"{integration}-latest: {dep}")
+
+    return rendered
+
+
 def write_tox_file(packages: dict) -> None:
     template = ENV.get_template("tox.jinja")
 
@@ -735,15 +760,30 @@ def write_tox_file(packages: dict) -> None:
     for group, integrations in packages.items():
         context["groups"][group] = []
         for integration in integrations:
+            # Find the highest stable (non-prerelease) release for the
+            # -latest alias.  Prereleases are always appended last by
+            # pick_releases_to_test, so we walk backwards.
+            latest_stable = None
+            for rel in reversed(integration["releases"]):
+                if not rel.is_prerelease:
+                    latest_stable = rel
+                    break
+
             context["groups"][group].append(
                 {
                     "name": integration["name"],
                     "package": integration["package"],
                     "extra": integration["extra"],
                     "releases": integration["releases"],
+                    "latest_stable": latest_stable,
                     "dependencies": _render_dependencies(
                         integration["name"], integration["releases"]
                     ),
+                    "latest_dependencies": _render_latest_dependencies(
+                        integration["name"], latest_stable
+                    )
+                    if latest_stable
+                    else [],
                 }
             )
             context["testpaths"].append(
@@ -872,7 +912,10 @@ def get_last_updated() -> Optional[datetime]:
 
 
 def _normalize_name(package: str) -> str:
-    return package.lower().replace("-", "_")
+    # From https://peps.python.org/pep-0503/#normalized-names
+    # but normalizing to underscores instead of hyphens since tox-formatted packages
+    # use underscores.
+    return re.sub(r"[-_.]+", "_", package).lower()
 
 
 def _extract_wheel_info_to_cache(wheel: dict):
diff --git a/scripts/populate_tox/releases.jsonl b/scripts/populate_tox/releases.jsonl
index bac8961594..0349e7e1c6 100644
--- a/scripts/populate_tox/releases.jsonl
+++ b/scripts/populate_tox/releases.jsonl
@@ -5,9 +5,9 @@
 {"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Environment :: Web Environment", "Framework :: Django", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Topic :: Internet :: WWW/HTTP", "Topic :: Internet :: WWW/HTTP :: Dynamic Content", "Topic :: Internet :: WWW/HTTP :: WSGI", "Topic :: Software Development :: Libraries :: Application Frameworks", "Topic :: Software Development :: Libraries :: Python Modules"], "name": "Django", "requires_python": ">=3.5", "version": "2.2.28", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "Django-2.2.28-py3-none-any.whl"}, {"packagetype": "sdist", "filename": "Django-2.2.28.tar.gz"}]}
 {"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Environment :: Web Environment", "Framework :: Django", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Topic :: Internet :: WWW/HTTP", "Topic :: Internet :: WWW/HTTP :: Dynamic Content", "Topic :: Internet :: WWW/HTTP :: WSGI", "Topic :: Software Development :: Libraries :: Application Frameworks", "Topic :: Software Development :: Libraries :: Python Modules"], "name": "Django", "requires_python": ">=3.6", "version": "3.1.14", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "Django-3.1.14-py3-none-any.whl"}, {"packagetype": "sdist", "filename": "Django-3.1.14.tar.gz"}]}
 {"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Environment :: Web Environment", "Framework :: Django", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Topic :: Internet :: WWW/HTTP", "Topic :: Internet :: WWW/HTTP :: Dynamic Content", "Topic :: Internet :: WWW/HTTP :: WSGI", "Topic :: Software Development :: Libraries :: Application Frameworks", "Topic :: Software Development :: Libraries :: Python Modules"], "name": "Django", "requires_python": ">=3.6", "version": "3.2.25", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "Django-3.2.25-py3-none-any.whl"}, {"packagetype": "sdist", "filename": "Django-3.2.25.tar.gz"}]}
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+{"info": {"classifiers": ["Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy"], "name": "zope.interface", "requires_python": ">=3.10", "version": "8.3", "yanked": false}, "urls": [{"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp310-cp310-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp311-cp311-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp312-cp312-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp313-cp313-win_amd64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-macosx_10_9_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-macosx_11_0_arm64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl"}, {"packagetype": "bdist_wheel", "filename": "zope_interface-8.3-cp314-cp314-win_amd64.whl"}, {"packagetype": "sdist", "filename": "zope_interface-8.3.tar.gz"}]}
diff --git a/scripts/populate_tox/tox.jinja b/scripts/populate_tox/tox.jinja
index 1808a7c521..e386d87f1c 100755
--- a/scripts/populate_tox/tox.jinja
+++ b/scripts/populate_tox/tox.jinja
@@ -61,6 +61,9 @@ envlist =
     {% for release in integration.releases %}
     {{ release.rendered_python_versions }}-{{ integration.name }}-v{{ release }}
     {% endfor %}
+    {% if integration.latest_stable %}
+    {{ integration.latest_stable.rendered_python_versions }}-{{ integration.name }}-latest
+    {% endif %}
 
     {% endfor %}
 
@@ -75,14 +78,17 @@ deps =
 
     linters: -r requirements-linting.txt
     linters: werkzeug<2.3.0
+    linters: httpcore[asyncio]
 
     mypy: -r requirements-linting.txt
     mypy: werkzeug<2.3.0
+    mypy: httpcore[asyncio]
     ruff: -r requirements-linting.txt
 
     # === Common ===
     py3.8-common: hypothesis
     common: pytest-asyncio
+    common: httpcore[asyncio]
     # See https://github.com/pytest-dev/pytest/issues/9621
     # and https://github.com/pytest-dev/pytest-forked/issues/67
     # for justification of the upper bound on pytest
@@ -143,9 +149,19 @@ deps =
     {{ integration.name }}-v{{ release }}: {{ integration.package }}=={{ release }}
     {% endif %}
     {% endfor %}
+    {% if integration.latest_stable %}
+    {% if integration.extra %}
+    {{ integration.name }}-latest: {{ integration.package }}[{{ integration.extra }}]=={{ integration.latest_stable }}
+    {% else %}
+    {{ integration.name }}-latest: {{ integration.package }}=={{ integration.latest_stable }}
+    {% endif %}
+    {% endif %}
     {% for dep in integration.dependencies %}
     {{ dep }}
     {% endfor %}
+    {% for dep in integration.latest_dependencies %}
+    {{ dep }}
+    {% endfor %}
 
     {% endfor %}
 
@@ -168,22 +184,22 @@ setenv =
     gevent: PYTEST_ADDOPTS="--ignore=tests/test_shadowed_module.py"
 
     # TESTPATH definitions for test suites not managed by toxgen
-    common: TESTPATH=tests
-    gevent: TESTPATH=tests
-    integration_deactivation: TESTPATH=tests/test_ai_integration_deactivation.py
-    shadowed_module: TESTPATH=tests/test_shadowed_module.py
-    asgi: TESTPATH=tests/integrations/asgi
-    aws_lambda: TESTPATH=tests/integrations/aws_lambda
-    cloud_resource_context: TESTPATH=tests/integrations/cloud_resource_context
-    gcp: TESTPATH=tests/integrations/gcp
-    opentelemetry: TESTPATH=tests/integrations/opentelemetry
-    otlp: TESTPATH=tests/integrations/otlp
-    potel: TESTPATH=tests/integrations/opentelemetry
-    socket: TESTPATH=tests/integrations/socket
+    common: _TESTPATH=tests
+    gevent: _TESTPATH=tests
+    integration_deactivation: _TESTPATH=tests/test_ai_integration_deactivation.py
+    shadowed_module: _TESTPATH=tests/test_shadowed_module.py
+    asgi: _TESTPATH=tests/integrations/asgi
+    aws_lambda: _TESTPATH=tests/integrations/aws_lambda
+    cloud_resource_context: _TESTPATH=tests/integrations/cloud_resource_context
+    gcp: _TESTPATH=tests/integrations/gcp
+    opentelemetry: _TESTPATH=tests/integrations/opentelemetry
+    otlp: _TESTPATH=tests/integrations/otlp
+    potel: _TESTPATH=tests/integrations/opentelemetry
+    socket: _TESTPATH=tests/integrations/socket
 
     # These TESTPATH definitions are auto-generated by toxgen
     {% for integration, testpath in testpaths %}
-    {{ integration }}: TESTPATH={{ testpath }}
+    {{ integration }}: _TESTPATH={{ testpath }}
     {% endfor %}
 
 passenv =
@@ -191,6 +207,7 @@ passenv =
     SENTRY_PYTHON_TEST_POSTGRES_USER
     SENTRY_PYTHON_TEST_POSTGRES_PASSWORD
     SENTRY_PYTHON_TEST_POSTGRES_NAME
+    TESTPATH
 
 usedevelop = True
 
@@ -228,7 +245,7 @@ commands =
     ; Running `pytest` as an executable suffers from an import error
     ; when loading tests in scenarios. In particular, django fails to
     ; load the settings from the test module.
-    python -m pytest -W error::pytest.PytestUnraisableExceptionWarning {env:TESTPATH} -o junit_suite_name={envname} {posargs}
+    python -m pytest -W error::pytest.PytestUnraisableExceptionWarning {env:TESTPATH:{env:_TESTPATH}} -o junit_suite_name={envname} {posargs}
 
 [testenv:linters]
 commands =
diff --git a/scripts/runtox.sh b/scripts/runtox.sh
index bd6e954947..77aab28ae3 100755
--- a/scripts/runtox.sh
+++ b/scripts/runtox.sh
@@ -15,7 +15,12 @@ fi
 
 searchstring="$1"
 
-ENV="$($TOXPATH -l | grep -- "$searchstring" | tr $'\n' ',')"
+# Filter out -latest environments unless explicitly requested
+if [[ "$searchstring" == *-latest* ]]; then
+    ENV="$($TOXPATH -l | grep -- "$searchstring" | tr $'\n' ',')"
+else
+    ENV="$($TOXPATH -l | grep -- "$searchstring" | grep -v -- '-latest$' | tr $'\n' ',')"
+fi
 
 if [ -z "${ENV}" ]; then
     echo "No targets found. Skipping."
diff --git a/scripts/split_tox_gh_actions/split_tox_gh_actions.py b/scripts/split_tox_gh_actions/split_tox_gh_actions.py
index b59e768a56..122a02065d 100755
--- a/scripts/split_tox_gh_actions/split_tox_gh_actions.py
+++ b/scripts/split_tox_gh_actions/split_tox_gh_actions.py
@@ -124,6 +124,7 @@
     "Network": [
         "grpc",
         "httpx",
+        "pyreqwest",
         "requests",
     ],
     "Tasks": [
@@ -240,6 +241,11 @@ def parse_tox():
             raw_python_versions = groups["py_versions"]
             framework = groups["framework"]
 
+            # The -latest env is an alias for the highest version of the
+            # same framework, so merge it with the base framework.
+            if framework.endswith("-latest"):
+                framework = framework[: -len("-latest")]
+
             # collect python versions to test the framework in
             raw_python_versions = set(raw_python_versions.split(","))
             py_versions[framework] |= raw_python_versions
diff --git a/scripts/split_tox_gh_actions/templates/test_group.jinja b/scripts/split_tox_gh_actions/templates/test_group.jinja
index bec1a0f835..4b8f981789 100644
--- a/scripts/split_tox_gh_actions/templates/test_group.jinja
+++ b/scripts/split_tox_gh_actions/templates/test_group.jinja
@@ -42,8 +42,8 @@
     # Use Docker container only for Python 3.6
     {% raw %}container: ${{ matrix.python-version == '3.6' && 'python:3.6' || null }}{% endraw %}
     steps:
-      - uses: actions/checkout@v6.0.2
-      - uses: actions/setup-python@v6
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
         {% raw %}if: ${{ matrix.python-version != '3.6' }}{% endraw %}
         with:
           python-version: {% raw %}${{ matrix.python-version }}{% endraw %}
@@ -51,17 +51,17 @@
 
       {% if needs_clickhouse %}
       - name: "Setup ClickHouse Server"
-        uses: getsentry/action-clickhouse-in-ci@v1.7
+        uses: getsentry/action-clickhouse-in-ci@5dc8a6a50d689bd6051db0241f34849e5a36490b # v1.7
       {% endif %}
 
       {% if needs_redis %}
       - name: Start Redis
-        uses: supercharge/redis-github-action@v2
+        uses: supercharge/redis-github-action@87f27ff1ab2d9e62db54b11ee5e7f78ff18f8933 # v2
       {% endif %}
 
       {% if needs_java %}
       - name: Install Java
-        uses: actions/setup-java@v5
+        uses: actions/setup-java@be666c2fcd27ec809703dec50e508c2fdc7f6654 # v5
         with:
           distribution: 'temurin'
           java-version: '21'
@@ -96,9 +96,10 @@
 
       - name: Parse and Upload Coverage
         if: {% raw %}${{ !cancelled() }}{% endraw %}
-        uses: getsentry/codecov-action@main
+        uses: getsentry/codecov-action@fda17cfc37e16a0cc23f61685813390bfee7daf3 # main
         with:
           token: {% raw %}${{ secrets.GITHUB_TOKEN }}{% endraw %}
           files: coverage.xml
           junit-xml-pattern: .junitxml
+          base-branch: master
           verbose: true
diff --git a/sentry_sdk/__init__.py b/sentry_sdk/__init__.py
index fda2f18dd1..7fd0e1953d 100644
--- a/sentry_sdk/__init__.py
+++ b/sentry_sdk/__init__.py
@@ -25,6 +25,7 @@
     "configure_scope",
     "continue_trace",
     "flush",
+    "flush_async",
     "get_baggage",
     "get_client",
     "get_global_scope",
diff --git a/sentry_sdk/_batcher.py b/sentry_sdk/_batcher.py
index 4a6ee07e67..4ba8046814 100644
--- a/sentry_sdk/_batcher.py
+++ b/sentry_sdk/_batcher.py
@@ -4,7 +4,7 @@
 from datetime import datetime, timezone
 from typing import TYPE_CHECKING, TypeVar, Generic
 
-from sentry_sdk.utils import format_timestamp, safe_repr, serialize_attribute
+from sentry_sdk.utils import format_timestamp
 from sentry_sdk.envelope import Envelope, Item, PayloadRef
 
 if TYPE_CHECKING:
@@ -31,6 +31,7 @@ def __init__(
         self._record_lost_func = record_lost_func
         self._running = True
         self._lock = threading.Lock()
+        self._active: "threading.local" = threading.local()
 
         self._flush_event: "threading.Event" = threading.Event()
 
@@ -70,23 +71,40 @@ def _ensure_thread(self) -> bool:
         return True
 
     def _flush_loop(self) -> None:
+        # Mark the flush-loop thread as active for its entire lifetime so
+        # that any re-entrant add() triggered by GC warnings during wait(),
+        # flush(), or Event operations is silently dropped instead of
+        # deadlocking on internal locks.
+        self._active.flag = True
         while self._running:
             self._flush_event.wait(self.FLUSH_WAIT_TIME + random.random())
             self._flush_event.clear()
             self._flush()
 
     def add(self, item: "T") -> None:
-        if not self._ensure_thread() or self._flusher is None:
+        # Bail out if the current thread is already executing batcher code.
+        # This prevents deadlocks when code running inside the batcher (e.g.
+        # _add_to_envelope during flush, or _flush_event.wait/set) triggers
+        # a GC-emitted warning that routes back through the logging
+        # integration into add().
+        if getattr(self._active, "flag", False):
             return None
 
-        with self._lock:
-            if len(self._buffer) >= self.MAX_BEFORE_DROP:
-                self._record_lost(item)
+        self._active.flag = True
+        try:
+            if not self._ensure_thread() or self._flusher is None:
                 return None
 
-            self._buffer.append(item)
-            if len(self._buffer) >= self.MAX_BEFORE_FLUSH:
-                self._flush_event.set()
+            with self._lock:
+                if len(self._buffer) >= self.MAX_BEFORE_DROP:
+                    self._record_lost(item)
+                    return None
+
+                self._buffer.append(item)
+                if len(self._buffer) >= self.MAX_BEFORE_FLUSH:
+                    self._flush_event.set()
+        finally:
+            self._active.flag = False
 
     def kill(self) -> None:
         if self._flusher is None:
@@ -97,7 +115,12 @@ def kill(self) -> None:
         self._flusher = None
 
     def flush(self) -> None:
-        self._flush()
+        was_active = getattr(self._active, "flag", False)
+        self._active.flag = True
+        try:
+            self._flush()
+        finally:
+            self._active.flag = was_active
 
     def _add_to_envelope(self, envelope: "Envelope") -> None:
         envelope.add_item(
diff --git a/sentry_sdk/_log_batcher.py b/sentry_sdk/_log_batcher.py
index 1c59f7379c..d765236846 100644
--- a/sentry_sdk/_log_batcher.py
+++ b/sentry_sdk/_log_batcher.py
@@ -2,7 +2,7 @@
 
 from sentry_sdk._batcher import Batcher
 from sentry_sdk.utils import serialize_attribute
-from sentry_sdk.envelope import Envelope, Item, PayloadRef
+from sentry_sdk.envelope import Item, PayloadRef
 
 if TYPE_CHECKING:
     from typing import Any
diff --git a/sentry_sdk/_metrics_batcher.py b/sentry_sdk/_metrics_batcher.py
index e60a4c86ec..92cece209b 100644
--- a/sentry_sdk/_metrics_batcher.py
+++ b/sentry_sdk/_metrics_batcher.py
@@ -2,7 +2,6 @@
 
 from sentry_sdk._batcher import Batcher
 from sentry_sdk.utils import serialize_attribute
-from sentry_sdk.envelope import Item
 
 if TYPE_CHECKING:
     from typing import Any
diff --git a/sentry_sdk/_span_batcher.py b/sentry_sdk/_span_batcher.py
index 947eca3806..426d5d9629 100644
--- a/sentry_sdk/_span_batcher.py
+++ b/sentry_sdk/_span_batcher.py
@@ -4,21 +4,24 @@
 from typing import TYPE_CHECKING
 
 from sentry_sdk._batcher import Batcher
-from sentry_sdk.consts import SPANSTATUS
 from sentry_sdk.envelope import Envelope, Item, PayloadRef
-from sentry_sdk.utils import format_timestamp, serialize_attribute, safe_repr
+from sentry_sdk.utils import format_timestamp, serialize_attribute
 
 if TYPE_CHECKING:
     from typing import Any, Callable, Optional
     from sentry_sdk.traces import StreamedSpan
-    from sentry_sdk._types import SerializedAttributeValue
 
 
 class SpanBatcher(Batcher["StreamedSpan"]):
-    # TODO[span-first]: size-based flushes
-    # TODO[span-first]: adjust flush/drop defaults
+    # MAX_BEFORE_FLUSH should be lower than MAX_BEFORE_DROP, so that there is
+    # a bit of a buffer for spans that appear between setting the flush event
+    # and actually flushing the buffer.
+    #
+    # The max limits are all per trace.
+    MAX_ENVELOPE_SIZE = 1000  # spans
     MAX_BEFORE_FLUSH = 1000
-    MAX_BEFORE_DROP = 5000
+    MAX_BEFORE_DROP = 2000
+    MAX_BYTES_BEFORE_FLUSH = 5 * 1024 * 1024  # 5 MB
     FLUSH_WAIT_TIME = 5.0
 
     TYPE = "span"
@@ -35,47 +38,89 @@ def __init__(
         # envelope.
         # trace_id -> span buffer
         self._span_buffer: dict[str, list["StreamedSpan"]] = defaultdict(list)
+        self._running_size: dict[str, int] = defaultdict(lambda: 0)
         self._capture_func = capture_func
         self._record_lost_func = record_lost_func
         self._running = True
         self._lock = threading.Lock()
+        self._active: "threading.local" = threading.local()
 
         self._flush_event: "threading.Event" = threading.Event()
 
         self._flusher: "Optional[threading.Thread]" = None
         self._flusher_pid: "Optional[int]" = None
 
-    def get_size(self) -> int:
-        # caller is responsible for locking before checking this
-        return sum(len(buffer) for buffer in self._span_buffer.values())
-
     def add(self, span: "StreamedSpan") -> None:
-        if not self._ensure_thread() or self._flusher is None:
+        # Bail out if the current thread is already executing batcher code.
+        # This prevents deadlocks when code running inside the batcher (e.g.
+        # _add_to_envelope during flush, or _flush_event.wait/set) triggers
+        # a GC-emitted warning that routes back through the logging
+        # integration into add().
+        if getattr(self._active, "flag", False):
             return None
 
-        with self._lock:
-            size = self.get_size()
-            if size >= self.MAX_BEFORE_DROP:
-                self._record_lost_func(
-                    reason="queue_overflow",
-                    data_category="span",
-                    quantity=1,
-                )
+        self._active.flag = True
+
+        try:
+            if not self._ensure_thread() or self._flusher is None:
                 return None
 
-            self._span_buffer[span.trace_id].append(span)
-            if size + 1 >= self.MAX_BEFORE_FLUSH:
-                self._flush_event.set()
+            with self._lock:
+                size = len(self._span_buffer[span.trace_id])
+                if size >= self.MAX_BEFORE_DROP:
+                    self._record_lost_func(
+                        reason="queue_overflow",
+                        data_category="span",
+                        quantity=1,
+                    )
+                    return None
+
+                self._span_buffer[span.trace_id].append(span)
+                self._running_size[span.trace_id] += self._estimate_size(span)
+
+                if size + 1 >= self.MAX_BEFORE_FLUSH:
+                    self._flush_event.set()
+                    return
+
+                if self._running_size[span.trace_id] >= self.MAX_BYTES_BEFORE_FLUSH:
+                    self._flush_event.set()
+                    return
+        finally:
+            self._active.flag = False
+
+    @staticmethod
+    def _estimate_size(item: "StreamedSpan") -> int:
+        # Rough estimate of serialized span size that's quick to compute.
+        # 210 is the rough size of the payload without attributes, and then we
+        # estimate the attributes separately.
+        estimate = 210
+        for value in item._attributes.values():
+            estimate += 50
+
+            if isinstance(value, str):
+                estimate += len(value)
+            else:
+                estimate += len(str(value))
+
+        return estimate
 
     @staticmethod
     def _to_transport_format(item: "StreamedSpan") -> "Any":
-        # TODO[span-first]
         res: "dict[str, Any]" = {
+            "trace_id": item.trace_id,
             "span_id": item.span_id,
             "name": item._name,
             "status": item._status,
+            "is_segment": item._is_segment(),
+            "start_timestamp": item._start_timestamp.timestamp(),
         }
 
+        if item._timestamp:
+            res["end_timestamp"] = item._timestamp.timestamp()
+
+        if item._parent_span_id:
+            res["parent_span_id"] = item._parent_span_id
+
         if item._attributes:
             res["attributes"] = {
                 k: serialize_attribute(v) for (k, v) in item._attributes.items()
@@ -86,43 +131,47 @@ def _to_transport_format(item: "StreamedSpan") -> "Any":
     def _flush(self) -> None:
         with self._lock:
             if len(self._span_buffer) == 0:
-                return None
+                return
 
             envelopes = []
-            for trace_id, spans in self._span_buffer.items():
+            for spans in self._span_buffer.values():
                 if spans:
-                    # TODO[span-first]
-                    # dsc = spans[0].dynamic_sampling_context()
-                    dsc = None
-
-                    envelope = Envelope(
-                        headers={
-                            "sent_at": format_timestamp(datetime.now(timezone.utc)),
-                            "trace": dsc,
-                        }
-                    )
+                    dsc = spans[0]._dynamic_sampling_context()
 
-                    envelope.add_item(
-                        Item(
-                            type="span",
-                            content_type="application/vnd.sentry.items.span.v2+json",
+                    # Max per envelope is 1000, so if we happen to have more than
+                    # 1000 spans in one bucket, we'll need to separate them.
+                    for start in range(0, len(spans), self.MAX_ENVELOPE_SIZE):
+                        end = min(start + self.MAX_ENVELOPE_SIZE, len(spans))
+
+                        envelope = Envelope(
                             headers={
-                                "item_count": len(spans),
-                            },
-                            payload=PayloadRef(
-                                json={
-                                    "items": [
-                                        self._to_transport_format(span)
-                                        for span in spans
-                                    ]
-                                }
-                            ),
+                                "sent_at": format_timestamp(datetime.now(timezone.utc)),
+                                "trace": dsc,
+                            }
+                        )
+
+                        envelope.add_item(
+                            Item(
+                                type=self.TYPE,
+                                content_type=self.CONTENT_TYPE,
+                                headers={
+                                    "item_count": end - start,
+                                },
+                                payload=PayloadRef(
+                                    json={
+                                        "items": [
+                                            self._to_transport_format(spans[j])
+                                            for j in range(start, end)
+                                        ]
+                                    }
+                                ),
+                            )
                         )
-                    )
 
-                    envelopes.append(envelope)
+                        envelopes.append(envelope)
 
             self._span_buffer.clear()
+            self._running_size.clear()
 
         for envelope in envelopes:
             self._capture_func(envelope)
diff --git a/sentry_sdk/_types.py b/sentry_sdk/_types.py
index e5f791fdf0..baf5f6a2fd 100644
--- a/sentry_sdk/_types.py
+++ b/sentry_sdk/_types.py
@@ -1,3 +1,9 @@
+try:
+    from re import Pattern
+except ImportError:
+    # 3.6
+    from typing import Pattern
+
 from typing import TYPE_CHECKING, TypeVar, Union
 
 
@@ -103,7 +109,6 @@ def substituted_because_contains_sensitive_data(cls) -> "AnnotatedValue":
     from typing import Mapping
     from typing import NotRequired
     from typing import Optional
-    from typing import Tuple
     from typing import Type
     from typing_extensions import Literal, TypedDict
 
@@ -351,6 +356,7 @@ class SDKInfo(TypedDict):
             "max_runtime": int,
             "failure_issue_threshold": int,
             "recovery_threshold": int,
+            "owner": str,
         },
         total=False,
     )
@@ -360,3 +366,11 @@ class SDKInfo(TypedDict):
     class TextPart(TypedDict):
         type: Literal["text"]
         content: str
+
+    IgnoreSpansName = Union[str, Pattern[str]]
+    IgnoreSpansContext = TypedDict(
+        "IgnoreSpansContext",
+        {"name": IgnoreSpansName, "attributes": Attributes},
+        total=False,
+    )
+    IgnoreSpansConfig = list[Union[IgnoreSpansName, IgnoreSpansContext]]
diff --git a/sentry_sdk/_werkzeug.py b/sentry_sdk/_werkzeug.py
index cdc3026c08..1fa58f632b 100644
--- a/sentry_sdk/_werkzeug.py
+++ b/sentry_sdk/_werkzeug.py
@@ -38,6 +38,7 @@
     from typing import Dict
     from typing import Iterator
     from typing import Tuple
+    from typing import Optional
 
 
 #
@@ -62,35 +63,41 @@ def _get_headers(environ: "Dict[str, str]") -> "Iterator[Tuple[str, str]]":
             yield key.replace("_", "-").title(), value
 
 
-#
+def _strip_default_port(host: str, scheme: "Optional[str]") -> str:
+    """Strip the port from the host if it's the default for the scheme."""
+    if scheme == "http" and host.endswith(":80"):
+        return host[:-3]
+    if scheme == "https" and host.endswith(":443"):
+        return host[:-4]
+    return host
+
+
 # `get_host` comes from `werkzeug.wsgi.get_host`
 # https://github.com/pallets/werkzeug/blob/1.0.1/src/werkzeug/wsgi.py#L145
-#
+
+
 def get_host(environ: "Dict[str, str]", use_x_forwarded_for: bool = False) -> str:
     """
     Return the host for the given WSGI environment.
     """
+    scheme = environ.get("wsgi.url_scheme")
+    if use_x_forwarded_for:
+        scheme = environ.get("HTTP_X_FORWARDED_PROTO", scheme)
+
     if use_x_forwarded_for and "HTTP_X_FORWARDED_HOST" in environ:
-        rv = environ["HTTP_X_FORWARDED_HOST"]
-        if environ["wsgi.url_scheme"] == "http" and rv.endswith(":80"):
-            rv = rv[:-3]
-        elif environ["wsgi.url_scheme"] == "https" and rv.endswith(":443"):
-            rv = rv[:-4]
+        return _strip_default_port(environ["HTTP_X_FORWARDED_HOST"], scheme)
     elif environ.get("HTTP_HOST"):
-        rv = environ["HTTP_HOST"]
-        if environ["wsgi.url_scheme"] == "http" and rv.endswith(":80"):
-            rv = rv[:-3]
-        elif environ["wsgi.url_scheme"] == "https" and rv.endswith(":443"):
-            rv = rv[:-4]
+        return _strip_default_port(environ["HTTP_HOST"], scheme)
     elif environ.get("SERVER_NAME"):
+        # SERVER_NAME/SERVER_PORT describe the internal server, so use
+        # wsgi.url_scheme (not the forwarded scheme) for port decisions.
         rv = environ["SERVER_NAME"]
         if (environ["wsgi.url_scheme"], environ["SERVER_PORT"]) not in (
             ("https", "443"),
             ("http", "80"),
         ):
             rv += ":" + environ["SERVER_PORT"]
+        return rv
     else:
         # In spite of the WSGI spec, SERVER_NAME might not be present.
-        rv = "unknown"
-
-    return rv
+        return "unknown"
diff --git a/sentry_sdk/ai/__init__.py b/sentry_sdk/ai/__init__.py
index 7f0d9f92f7..3e5f13727b 100644
--- a/sentry_sdk/ai/__init__.py
+++ b/sentry_sdk/ai/__init__.py
@@ -1,8 +1,8 @@
 from .utils import (
-    set_data_normalized,
-    GEN_AI_MESSAGE_ROLE_MAPPING,
-    GEN_AI_MESSAGE_ROLE_REVERSE_MAPPING,
-    normalize_message_role,
-    normalize_message_roles,
-    set_conversation_id,
-)  # noqa: F401
+    set_data_normalized,  # noqa: F401
+    GEN_AI_MESSAGE_ROLE_MAPPING,  # noqa: F401
+    GEN_AI_MESSAGE_ROLE_REVERSE_MAPPING,  # noqa: F401
+    normalize_message_role,  # noqa: F401
+    normalize_message_roles,  # noqa: F401
+    set_conversation_id,  # noqa: F401
+)
diff --git a/sentry_sdk/ai/consts.py b/sentry_sdk/ai/consts.py
new file mode 100644
index 0000000000..35ee4bd788
--- /dev/null
+++ b/sentry_sdk/ai/consts.py
@@ -0,0 +1,6 @@
+import re
+
+# Matches data URLs with base64-encoded content, e.g. "data:image/png;base64,iVBORw0K..."
+DATA_URL_BASE64_REGEX = re.compile(
+    r"^data:(?:[a-zA-Z0-9][a-zA-Z0-9.+\-]*/[a-zA-Z0-9][a-zA-Z0-9.+\-]*)(?:;[a-zA-Z0-9\-]+=[^;,]*)*;base64,(?:[A-Za-z0-9+/\-_]+={0,2})$"
+)
diff --git a/sentry_sdk/ai/utils.py b/sentry_sdk/ai/utils.py
index 5acc501172..4103736969 100644
--- a/sentry_sdk/ai/utils.py
+++ b/sentry_sdk/ai/utils.py
@@ -1,11 +1,10 @@
 import inspect
 import json
-from collections import deque
 from copy import deepcopy
-from sys import getsizeof
 from typing import TYPE_CHECKING
 
 from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
+from sentry_sdk.ai.consts import DATA_URL_BASE64_REGEX
 
 if TYPE_CHECKING:
     from typing import Any, Callable, Dict, List, Optional, Tuple
@@ -14,6 +13,8 @@
 
 import sentry_sdk
 from sentry_sdk.utils import logger
+from sentry_sdk.traces import StreamedSpan
+from sentry_sdk.tracing_utils import has_span_streaming_enabled
 
 MAX_GEN_AI_MESSAGE_BYTES = 20_000  # 20KB
 # Maximum characters when only a single message is left after bytes truncation
@@ -525,7 +526,14 @@ def normalize_message_roles(messages: "list[dict[str, Any]]") -> "list[dict[str,
 
 
 def get_start_span_function() -> "Callable[..., Any]":
+    if has_span_streaming_enabled(sentry_sdk.get_client().options):
+        return sentry_sdk.traces.start_span
+
     current_span = sentry_sdk.get_current_span()
+    if isinstance(current_span, StreamedSpan):
+        # mypy
+        return sentry_sdk.traces.start_span
+
     transaction_exists = (
         current_span is not None and current_span.containing_transaction is not None
     )
@@ -543,10 +551,25 @@ def _truncate_single_message_content_if_present(
         return message
     content = message["content"]
 
-    if not isinstance(content, str) or len(content) <= max_chars:
+    if isinstance(content, str):
+        if len(content) <= max_chars:
+            return message
+        message["content"] = content[:max_chars] + "..."
+        return message
+
+    if isinstance(content, list):
+        remaining = max_chars
+        for item in content:
+            if isinstance(item, dict) and "text" in item:
+                text = item["text"]
+                if isinstance(text, str):
+                    if len(text) > remaining:
+                        item["text"] = text[:remaining] + "..."
+                        remaining = 0
+                    else:
+                        remaining -= len(text)
         return message
 
-    message["content"] = content[:max_chars] + "..."
     return message
 
 
@@ -566,6 +589,20 @@ def _find_truncation_index(messages: "List[Dict[str, Any]]", max_bytes: int) ->
     return 0
 
 
+def _is_image_type_with_blob_content(item: "Dict[str, Any]") -> bool:
+    """
+    Some content blocks contain an image_url property with base64 content as its value.
+    This is used to identify those while not leading to unnecessary copying of data when the image URL does not contain base64 content.
+    """
+    if item.get("type") != "image_url":
+        return False
+
+    image_url = item.get("image_url", {}).get("url", "")
+    data_url_match = DATA_URL_BASE64_REGEX.match(image_url)
+
+    return bool(data_url_match)
+
+
 def redact_blob_message_parts(
     messages: "List[Dict[str, Any]]",
 ) -> "List[Dict[str, Any]]":
@@ -618,7 +655,9 @@ def redact_blob_message_parts(
         content = message.get("content")
         if isinstance(content, list):
             for item in content:
-                if isinstance(item, dict) and item.get("type") == "blob":
+                if isinstance(item, dict) and (
+                    item.get("type") == "blob" or _is_image_type_with_blob_content(item)
+                ):
                     has_blobs = True
                     break
         if has_blobs:
@@ -639,8 +678,11 @@ def redact_blob_message_parts(
         content = message.get("content")
         if isinstance(content, list):
             for item in content:
-                if isinstance(item, dict) and item.get("type") == "blob":
-                    item["content"] = BLOB_DATA_SUBSTITUTE
+                if isinstance(item, dict):
+                    if item.get("type") == "blob":
+                        item["content"] = BLOB_DATA_SUBSTITUTE
+                    elif _is_image_type_with_blob_content(item):
+                        item["image_url"]["url"] = BLOB_DATA_SUBSTITUTE
 
     return messages_copy
 
diff --git a/sentry_sdk/api.py b/sentry_sdk/api.py
index bea22d8be7..105f531e5f 100644
--- a/sentry_sdk/api.py
+++ b/sentry_sdk/api.py
@@ -6,6 +6,7 @@
 from sentry_sdk._init_implementation import init
 from sentry_sdk.consts import INSTRUMENTER
 from sentry_sdk.scope import Scope, _ScopeManager, new_scope, isolation_scope
+from sentry_sdk.traces import StreamedSpan
 from sentry_sdk.tracing import NoOpSpan, Transaction, trace
 from sentry_sdk.crons import monitor
 
@@ -37,6 +38,7 @@
         LogLevelStr,
         SamplingContext,
     )
+    from sentry_sdk.traces import StreamedSpan
     from sentry_sdk.tracing import Span, TransactionKwargs
 
     T = TypeVar("T")
@@ -58,6 +60,7 @@ def overload(x: "T") -> "T":
     "configure_scope",
     "continue_trace",
     "flush",
+    "flush_async",
     "get_baggage",
     "get_client",
     "get_global_scope",
@@ -349,6 +352,14 @@ def flush(
     return get_client().flush(timeout=timeout, callback=callback)
 
 
+@clientmethod
+async def flush_async(
+    timeout: "Optional[float]" = None,
+    callback: "Optional[Callable[[int, float], None]]" = None,
+) -> None:
+    return await get_client().flush_async(timeout=timeout, callback=callback)
+
+
 @scopemethod
 def start_span(
     **kwargs: "Any",
@@ -409,7 +420,9 @@ def set_measurement(name: str, value: float, unit: "MeasurementUnit" = "") -> No
         transaction.set_measurement(name, value, unit)
 
 
-def get_current_span(scope: "Optional[Scope]" = None) -> "Optional[Span]":
+def get_current_span(
+    scope: "Optional[Scope]" = None,
+) -> "Optional[Union[Span, StreamedSpan]]":
     """
     Returns the currently active span if there is one running, otherwise `None`
     """
@@ -525,6 +538,16 @@ def update_current_span(
     if current_span is None:
         return
 
+    if isinstance(current_span, StreamedSpan):
+        warnings.warn(
+            "The `update_current_span` API isn't available in streaming mode. "
+            "Retrieve the current span with get_current_span() and use its API "
+            "directly.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        return
+
     if op is not None:
         current_span.op = op
 
diff --git a/sentry_sdk/client.py b/sentry_sdk/client.py
index f540a49f35..9f795d2489 100644
--- a/sentry_sdk/client.py
+++ b/sentry_sdk/client.py
@@ -8,8 +8,7 @@
 from typing import TYPE_CHECKING, List, Dict, cast, overload
 import warnings
 
-import sentry_sdk
-from sentry_sdk._compat import PY37, check_uwsgi_thread_support
+from sentry_sdk._compat import check_uwsgi_thread_support
 from sentry_sdk._metrics_batcher import MetricsBatcher
 from sentry_sdk._span_batcher import SpanBatcher
 from sentry_sdk.utils import (
@@ -23,7 +22,6 @@
     get_type_name,
     get_default_release,
     handle_in_app,
-    is_gevent,
     logger,
     get_before_send_log,
     get_before_send_metric,
@@ -33,7 +31,11 @@
 from sentry_sdk.serializer import serialize
 from sentry_sdk.tracing import trace
 from sentry_sdk.tracing_utils import has_span_streaming_enabled
-from sentry_sdk.transport import BaseHttpTransport, make_transport
+from sentry_sdk.transport import (
+    HttpTransportCore,
+    make_transport,
+    AsyncHttpTransport,
+)
 from sentry_sdk.consts import (
     SPANDATA,
     DEFAULT_MAX_VALUE_LENGTH,
@@ -253,6 +255,12 @@ def close(self, *args: "Any", **kwargs: "Any") -> None:
     def flush(self, *args: "Any", **kwargs: "Any") -> None:
         return None
 
+    async def close_async(self, *args: "Any", **kwargs: "Any") -> None:
+        return None
+
+    async def flush_async(self, *args: "Any", **kwargs: "Any") -> None:
+        return None
+
     def __enter__(self) -> "BaseClient":
         return self
 
@@ -474,7 +482,7 @@ def _record_lost_event(
             or self.metrics_batcher
             or self.span_batcher
             or has_profiling_enabled(self.options)
-            or isinstance(self.transport, BaseHttpTransport)
+            or isinstance(self.transport, HttpTransportCore)
         ):
             # If we have anything on that could spawn a background thread, we
             # need to check if it's safe to use them.
@@ -1001,6 +1009,32 @@ def get_integration(
 
         return self.integrations.get(integration_name)
 
+    def _has_async_transport(self) -> bool:
+        """Check if the current transport is async."""
+        return isinstance(self.transport, AsyncHttpTransport)
+
+    @property
+    def _batchers(self) -> "tuple[Any, ...]":
+        return tuple(
+            b
+            for b in (self.log_batcher, self.metrics_batcher, self.span_batcher)
+            if b is not None
+        )
+
+    def _close_components(self) -> None:
+        """Kill all client components in the correct order."""
+        self.session_flusher.kill()
+        for b in self._batchers:
+            b.kill()
+        if self.monitor:
+            self.monitor.kill()
+
+    def _flush_components(self) -> None:
+        """Flush all client components."""
+        self.session_flusher.flush()
+        for b in self._batchers:
+            b.flush()
+
     def close(
         self,
         timeout: "Optional[float]" = None,
@@ -1011,19 +1045,40 @@ def close(
         semantics as :py:meth:`Client.flush`.
         """
         if self.transport is not None:
-            self.flush(timeout=timeout, callback=callback)
-            self.session_flusher.kill()
-            if self.log_batcher is not None:
-                self.log_batcher.kill()
-            if self.metrics_batcher is not None:
-                self.metrics_batcher.kill()
-            if self.span_batcher is not None:
-                self.span_batcher.kill()
-            if self.monitor:
-                self.monitor.kill()
+            if self._has_async_transport():
+                warnings.warn(
+                    "close() used with AsyncHttpTransport. Use close_async() instead.",
+                    stacklevel=2,
+                )
+                self._flush_components()
+            else:
+                self.flush(timeout=timeout, callback=callback)
+            self._close_components()
             self.transport.kill()
             self.transport = None
 
+    async def close_async(
+        self,
+        timeout: "Optional[float]" = None,
+        callback: "Optional[Callable[[int, float], None]]" = None,
+    ) -> None:
+        """
+        Asynchronously close the client and shut down the transport. Arguments have the same
+        semantics as :py:meth:`Client.flush_async`.
+        """
+        if self.transport is not None:
+            if not self._has_async_transport():
+                logger.debug(
+                    "close_async() used with non-async transport, aborting. Please use close() instead."
+                )
+                return
+            await self.flush_async(timeout=timeout, callback=callback)
+            self._close_components()
+            kill_task = self.transport.kill()  # type: ignore
+            if kill_task is not None:
+                await kill_task
+            self.transport = None
+
     def flush(
         self,
         timeout: "Optional[float]" = None,
@@ -1037,23 +1092,55 @@ def flush(
         :param callback: Is invoked with the number of pending events and the configured timeout.
         """
         if self.transport is not None:
+            if self._has_async_transport():
+                warnings.warn(
+                    "flush() used with AsyncHttpTransport. Use flush_async() instead.",
+                    stacklevel=2,
+                )
+                return
             if timeout is None:
                 timeout = self.options["shutdown_timeout"]
-            self.session_flusher.flush()
-            if self.log_batcher is not None:
-                self.log_batcher.flush()
-            if self.metrics_batcher is not None:
-                self.metrics_batcher.flush()
-            if self.span_batcher is not None:
-                self.span_batcher.flush()
+            self._flush_components()
+
             self.transport.flush(timeout=timeout, callback=callback)
 
+    async def flush_async(
+        self,
+        timeout: "Optional[float]" = None,
+        callback: "Optional[Callable[[int, float], None]]" = None,
+    ) -> None:
+        """
+        Asynchronously wait for the current events to be sent.
+
+        :param timeout: Wait for at most `timeout` seconds. If no `timeout` is provided, the `shutdown_timeout` option value is used.
+
+        :param callback: Is invoked with the number of pending events and the configured timeout.
+        """
+        if self.transport is not None:
+            if not self._has_async_transport():
+                logger.debug(
+                    "flush_async() used with non-async transport, aborting. Please use flush() instead."
+                )
+                return
+            if timeout is None:
+                timeout = self.options["shutdown_timeout"]
+            self._flush_components()
+            flush_task = self.transport.flush(timeout=timeout, callback=callback)  # type: ignore
+            if flush_task is not None:
+                await flush_task
+
     def __enter__(self) -> "_Client":
         return self
 
     def __exit__(self, exc_type: "Any", exc_value: "Any", tb: "Any") -> None:
         self.close()
 
+    async def __aenter__(self) -> "_Client":
+        return self
+
+    async def __aexit__(self, exc_type: "Any", exc_value: "Any", tb: "Any") -> None:
+        await self.close_async()
+
 
 from typing import TYPE_CHECKING
 
diff --git a/sentry_sdk/consts.py b/sentry_sdk/consts.py
index e1cc00e156..25a50a12b2 100644
--- a/sentry_sdk/consts.py
+++ b/sentry_sdk/consts.py
@@ -52,8 +52,8 @@ class CompressionAlgo(Enum):
         Event,
         EventProcessor,
         Hint,
+        IgnoreSpansConfig,
         Log,
-        MeasurementUnit,
         Metric,
         ProfilerMode,
         TracesSampler,
@@ -78,11 +78,14 @@ class CompressionAlgo(Enum):
             "transport_compression_algo": Optional[CompressionAlgo],
             "transport_num_pools": Optional[int],
             "transport_http2": Optional[bool],
+            "transport_async": Optional[bool],
             "enable_logs": Optional[bool],
             "before_send_log": Optional[Callable[[Log, Hint], Optional[Log]]],
             "enable_metrics": Optional[bool],
             "before_send_metric": Optional[Callable[[Metric, Hint], Optional[Metric]]],
             "trace_lifecycle": Optional[Literal["static", "stream"]],
+            "ignore_spans": Optional[IgnoreSpansConfig],
+            "suppress_asgi_chained_exceptions": Optional[bool],
         },
         total=False,
     )
@@ -438,6 +441,12 @@ class SPANDATA:
     Example: myDatabase
     """
 
+    DB_DRIVER_NAME = "db.driver.name"
+    """
+    The name of the database driver being used for the connection.
+    Example: "psycopg2"
+    """
+
     DB_OPERATION = "db.operation"
     """
     The name of the operation being executed, e.g. the MongoDB command name such as findAndModify, or the SQL keyword.
@@ -633,12 +642,6 @@ class SPANDATA:
     Example: "rainy, 57°F"
     """
 
-    GEN_AI_TOOL_TYPE = "gen_ai.tool.type"
-    """
-    The type of tool being used.
-    Example: "function"
-    """
-
     GEN_AI_USAGE_INPUT_TOKENS = "gen_ai.usage.input_tokens"
     """
     The number of tokens in the input.
@@ -919,9 +922,8 @@ class OP:
     GEN_AI_CREATE_AGENT = "gen_ai.create_agent"
     GEN_AI_EMBEDDINGS = "gen_ai.embeddings"
     GEN_AI_EXECUTE_TOOL = "gen_ai.execute_tool"
-    GEN_AI_GENERATE_TEXT = "gen_ai.generate_text"
+    GEN_AI_TEXT_COMPLETION = "gen_ai.text_completion"
     GEN_AI_HANDOFF = "gen_ai.handoff"
-    GEN_AI_PIPELINE = "gen_ai.pipeline"
     GEN_AI_INVOKE_AGENT = "gen_ai.invoke_agent"
     GEN_AI_RESPONSES = "gen_ai.responses"
     GRAPHQL_EXECUTE = "graphql.execute"
@@ -1490,4 +1492,4 @@ def _get_default_options() -> "dict[str, Any]":
 del _get_default_options
 
 
-VERSION = "2.54.0"
+VERSION = "2.58.0"
diff --git a/sentry_sdk/envelope.py b/sentry_sdk/envelope.py
index 307fb26fd6..012b706938 100644
--- a/sentry_sdk/envelope.py
+++ b/sentry_sdk/envelope.py
@@ -255,6 +255,8 @@ def data_category(self) -> "EventDataCategory":
             return "attachment"
         elif ty == "transaction":
             return "transaction"
+        elif ty == "span":
+            return "span"
         elif ty == "event":
             return "error"
         elif ty == "log":
diff --git a/sentry_sdk/feature_flags.py b/sentry_sdk/feature_flags.py
index c9f3f303f9..de0cefbcad 100644
--- a/sentry_sdk/feature_flags.py
+++ b/sentry_sdk/feature_flags.py
@@ -1,6 +1,7 @@
 import copy
 import sentry_sdk
 from sentry_sdk._lru_cache import LRUCache
+from sentry_sdk.tracing import Span
 from threading import Lock
 
 from typing import TYPE_CHECKING, Any
@@ -61,5 +62,5 @@ def add_feature_flag(flag: str, result: bool) -> None:
     flags.set(flag, result)
 
     span = sentry_sdk.get_current_span()
-    if span:
+    if span and isinstance(span, Span):
         span.set_flag(f"flag.evaluation.{flag}", result)
diff --git a/sentry_sdk/integrations/__init__.py b/sentry_sdk/integrations/__init__.py
index dd12a6011f..599f0507d0 100644
--- a/sentry_sdk/integrations/__init__.py
+++ b/sentry_sdk/integrations/__init__.py
@@ -150,6 +150,7 @@ def iter_default_integrations(
     "openfeature": (0, 7, 1),
     "pydantic_ai": (1, 0, 0),
     "pymongo": (3, 5, 0),
+    "pyreqwest": (0, 11, 6),
     "quart": (0, 16, 0),
     "ray": (2, 7, 0),
     "requests": (2, 0, 0),
diff --git a/sentry_sdk/integrations/_asgi_common.py b/sentry_sdk/integrations/_asgi_common.py
index a8022c6bb1..525ca4b5b5 100644
--- a/sentry_sdk/integrations/_asgi_common.py
+++ b/sentry_sdk/integrations/_asgi_common.py
@@ -105,3 +105,35 @@ def _get_request_data(asgi_scope: "Any") -> "Dict[str, Any]":
         request_data["env"] = {"REMOTE_ADDR": _get_ip(asgi_scope)}
 
     return request_data
+
+
+def _get_request_attributes(asgi_scope: "Any") -> "dict[str, Any]":
+    """
+    Return attributes related to the HTTP request from the ASGI scope.
+    """
+    attributes: "dict[str, Any]" = {}
+
+    ty = asgi_scope["type"]
+    if ty in ("http", "websocket"):
+        if asgi_scope.get("method"):
+            attributes["http.request.method"] = asgi_scope["method"].upper()
+
+        headers = _filter_headers(_get_headers(asgi_scope), use_annotated_value=False)
+        for header, value in headers.items():
+            attributes[f"http.request.header.{header.lower()}"] = value
+
+        query = _get_query(asgi_scope)
+        if query:
+            attributes["http.query"] = query
+
+        attributes["url.full"] = _get_url(
+            asgi_scope, "http" if ty == "http" else "ws", headers.get("host")
+        )
+
+    client = asgi_scope.get("client")
+    if client and should_send_default_pii():
+        ip = _get_ip(asgi_scope)
+        attributes["client.address"] = ip
+        attributes["user.ip_address"] = ip
+
+    return attributes
diff --git a/sentry_sdk/integrations/_wsgi_common.py b/sentry_sdk/integrations/_wsgi_common.py
index 688e965be4..9f1b1399f0 100644
--- a/sentry_sdk/integrations/_wsgi_common.py
+++ b/sentry_sdk/integrations/_wsgi_common.py
@@ -3,6 +3,7 @@
 from copy import deepcopy
 
 import sentry_sdk
+from sentry_sdk._types import SENSITIVE_DATA_SUBSTITUTE
 from sentry_sdk.scope import should_send_default_pii
 from sentry_sdk.utils import AnnotatedValue, logger
 
@@ -211,16 +212,19 @@ def _is_json_content_type(ct: "Optional[str]") -> bool:
 
 def _filter_headers(
     headers: "Mapping[str, str]",
+    use_annotated_value: bool = True,
 ) -> "Mapping[str, Union[AnnotatedValue, str]]":
     if should_send_default_pii():
         return headers
 
+    substitute: "Union[AnnotatedValue, str]"
+    if use_annotated_value:
+        substitute = AnnotatedValue.removed_because_over_size_limit()
+    else:
+        substitute = SENSITIVE_DATA_SUBSTITUTE
+
     return {
-        k: (
-            v
-            if k.upper().replace("-", "_") not in SENSITIVE_HEADERS
-            else AnnotatedValue.removed_because_over_size_limit()
-        )
+        k: (v if k.upper().replace("-", "_") not in SENSITIVE_HEADERS else substitute)
         for k, v in headers.items()
     }
 
diff --git a/sentry_sdk/integrations/anthropic.py b/sentry_sdk/integrations/anthropic.py
index eca9e8bd3e..efc2f70ffd 100644
--- a/sentry_sdk/integrations/anthropic.py
+++ b/sentry_sdk/integrations/anthropic.py
@@ -14,10 +14,9 @@
     get_start_span_function,
     transform_anthropic_content_part,
 )
-from sentry_sdk.consts import OP, SPANDATA, SPANSTATUS
+from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations import _check_minimum_version, DidNotEnable, Integration
 from sentry_sdk.scope import should_send_default_pii
-from sentry_sdk.tracing_utils import set_span_errored
 from sentry_sdk.utils import (
     capture_internal_exceptions,
     event_from_exception,
@@ -37,7 +36,23 @@
     except ImportError:
         Omit = None
 
+    from anthropic import Stream, AsyncStream
     from anthropic.resources import AsyncMessages, Messages
+    from anthropic.lib.streaming import (
+        MessageStreamManager,
+        MessageStream,
+        AsyncMessageStreamManager,
+        AsyncMessageStream,
+    )
+
+    from anthropic.types import (
+        MessageStartEvent,
+        MessageDeltaEvent,
+        MessageStopEvent,
+        ContentBlockStartEvent,
+        ContentBlockDeltaEvent,
+        ContentBlockStopEvent,
+    )
 
     if TYPE_CHECKING:
         from anthropic.types import MessageStreamEvent, TextBlockParam
@@ -45,10 +60,26 @@
     raise DidNotEnable("Anthropic not installed")
 
 if TYPE_CHECKING:
-    from typing import Any, AsyncIterator, Iterator, List, Optional, Union
+    from typing import (
+        Any,
+        AsyncIterator,
+        Iterator,
+        Optional,
+        Union,
+        Callable,
+        Awaitable,
+    )
     from sentry_sdk.tracing import Span
     from sentry_sdk._types import TextPart
 
+    from anthropic.types import (
+        RawMessageStreamEvent,
+        MessageParam,
+        ModelParam,
+        TextBlockParam,
+        ToolUnionParam,
+    )
+
 
 class _RecordedUsage:
     output_tokens: int = 0
@@ -57,6 +88,55 @@ class _RecordedUsage:
     cache_read_input_tokens: "Optional[int]" = 0
 
 
+class _StreamSpanContext:
+    """
+    Sets accumulated data on the stream's span and finishes the span on exit.
+    Is a no-op if the stream has no span set, i.e., when the span has already been finished.
+    """
+
+    def __init__(
+        self,
+        stream: "Union[Stream, MessageStream, AsyncStream, AsyncMessageStream]",
+        # Flag to avoid unreachable branches when the stream state is known to be initialized (stream._model, etc. are set).
+        guaranteed_streaming_state: bool = False,
+    ) -> None:
+        self._stream = stream
+        self._guaranteed_streaming_state = guaranteed_streaming_state
+
+    def __enter__(self) -> "_StreamSpanContext":
+        return self
+
+    def __exit__(
+        self,
+        exc_type: "Optional[type[BaseException]]",
+        exc_val: "Optional[BaseException]",
+        exc_tb: "Optional[Any]",
+    ) -> None:
+        with capture_internal_exceptions():
+            if not hasattr(self._stream, "_span"):
+                return
+
+            if not self._guaranteed_streaming_state and not hasattr(
+                self._stream, "_model"
+            ):
+                self._stream._span.__exit__(exc_type, exc_val, exc_tb)
+                del self._stream._span
+                return
+
+            _set_streaming_output_data(
+                span=self._stream._span,
+                integration=self._stream._integration,
+                model=self._stream._model,
+                usage=self._stream._usage,
+                content_blocks=self._stream._content_blocks,
+                response_id=self._stream._response_id,
+                finish_reason=self._stream._finish_reason,
+            )
+
+            self._stream._span.__exit__(exc_type, exc_val, exc_tb)
+            del self._stream._span
+
+
 class AnthropicIntegration(Integration):
     identifier = "anthropic"
     origin = f"auto.ai.{identifier}"
@@ -69,13 +149,51 @@ def setup_once() -> None:
         version = package_version("anthropic")
         _check_minimum_version(AnthropicIntegration, version)
 
+        """
+        client.messages.create(stream=True) can return an instance of the Stream class, which implements the iterator protocol.
+        Analogously, the function can return an AsyncStream, which implements the asynchronous iterator protocol.
+        The private _iterator variable and the close() method are patched. During iteration over the _iterator generator,
+        information from intercepted events is accumulated and used to populate output attributes on the AI Client Span.
+
+        The span can be finished in two places:
+        - When the user exits the context manager or directly calls close(), the patched close() finishes the span.
+        - When iteration ends, the finally block in the _iterator wrapper finishes the span.
+
+        Both paths may run. For example, the context manager exit can follow iterator exhaustion.
+        """
         Messages.create = _wrap_message_create(Messages.create)
+        Stream.close = _wrap_close(Stream.close)
+
         AsyncMessages.create = _wrap_message_create_async(AsyncMessages.create)
+        AsyncStream.close = _wrap_async_close(AsyncStream.close)
+
+        """
+        client.messages.stream() patches are analogous to the patches for client.messages.create(stream=True) described above.
+        """
+        Messages.stream = _wrap_message_stream(Messages.stream)
+        MessageStreamManager.__enter__ = _wrap_message_stream_manager_enter(
+            MessageStreamManager.__enter__
+        )
 
+        # Before https://github.com/anthropics/anthropic-sdk-python/commit/b1a1c0354a9aca450a7d512fdbdeb59c0ead688a
+        # MessageStream inherits from Stream, so patching Stream is sufficient on these versions.
+        if not issubclass(MessageStream, Stream):
+            MessageStream.close = _wrap_close(MessageStream.close)
 
-def _capture_exception(exc: "Any") -> None:
-    set_span_errored()
+        AsyncMessages.stream = _wrap_async_message_stream(AsyncMessages.stream)
+        AsyncMessageStreamManager.__aenter__ = (
+            _wrap_async_message_stream_manager_aenter(
+                AsyncMessageStreamManager.__aenter__
+            )
+        )
 
+        # Before https://github.com/anthropics/anthropic-sdk-python/commit/b1a1c0354a9aca450a7d512fdbdeb59c0ead688a
+        # AsyncMessageStream inherits from AsyncStream, so patching Stream is sufficient on these versions.
+        if not issubclass(AsyncMessageStream, AsyncStream):
+            AsyncMessageStream.close = _wrap_async_close(AsyncMessageStream.close)
+
+
+def _capture_exception(exc: "Any") -> None:
     event, hint = event_from_exception(
         exc,
         client_options=sentry_sdk.get_client().options,
@@ -126,7 +244,9 @@ def _collect_ai_data(
     model: "str | None",
     usage: "_RecordedUsage",
     content_blocks: "list[str]",
-) -> "tuple[str | None, _RecordedUsage, list[str]]":
+    response_id: "str | None" = None,
+    finish_reason: "str | None" = None,
+) -> "tuple[str | None, _RecordedUsage, list[str], str | None, str | None]":
     """
     Collect model information, token usage, and collect content blocks from the AI streaming response.
     """
@@ -146,6 +266,7 @@ def _collect_ai_data(
             # https://github.com/anthropics/anthropic-sdk-python/blob/9c485f6966e10ae0ea9eabb3a921d2ea8145a25b/src/anthropic/lib/streaming/_messages.py#L433-L518
             if event.type == "message_start":
                 model = event.message.model or model
+                response_id = event.message.id
 
                 incoming_usage = event.message.usage
                 usage.output_tokens = incoming_usage.output_tokens
@@ -162,6 +283,8 @@ def _collect_ai_data(
                     model,
                     usage,
                     content_blocks,
+                    response_id,
+                    finish_reason,
                 )
 
             # Counterintuitive, but message_delta contains cumulative token counts :)
@@ -186,16 +309,17 @@ def _collect_ai_data(
                     usage.cache_read_input_tokens = cache_read_input_tokens
                 # TODO: Record event.usage.server_tool_use
 
-                return (
-                    model,
-                    usage,
-                    content_blocks,
-                )
+                if event.delta.stop_reason is not None:
+                    finish_reason = event.delta.stop_reason
+
+                return (model, usage, content_blocks, response_id, finish_reason)
 
     return (
         model,
         usage,
         content_blocks,
+        response_id,
+        finish_reason,
     )
 
 
@@ -241,27 +365,33 @@ def _transform_system_instructions(
     ]
 
 
-def _set_input_data(
-    span: "Span", kwargs: "dict[str, Any]", integration: "AnthropicIntegration"
+def _set_common_input_data(
+    span: "Span",
+    integration: "AnthropicIntegration",
+    max_tokens: "int",
+    messages: "Iterable[MessageParam]",
+    model: "ModelParam",
+    system: "Optional[Union[str, Iterable[TextBlockParam]]]",
+    temperature: "Optional[float]",
+    top_k: "Optional[int]",
+    top_p: "Optional[float]",
+    tools: "Optional[Iterable[ToolUnionParam]]",
 ) -> None:
     """
     Set input data for the span based on the provided keyword arguments for the anthropic message creation.
     """
+    span.set_data(SPANDATA.GEN_AI_SYSTEM, "anthropic")
     span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "chat")
-    system_instructions: "Union[str, Iterable[TextBlockParam]]" = kwargs.get("system")  # type: ignore
-    messages = kwargs.get("messages")
     if (
         messages is not None
-        and len(messages) > 0
+        and len(messages) > 0  # type: ignore
         and should_send_default_pii()
         and integration.include_prompts
     ):
-        if isinstance(system_instructions, str) or isinstance(
-            system_instructions, Iterable
-        ):
+        if isinstance(system, str) or isinstance(system, Iterable):
             span.set_data(
                 SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS,
-                json.dumps(_transform_system_instructions(system_instructions)),
+                json.dumps(_transform_system_instructions(system)),
             )
 
         normalized_messages = []
@@ -317,25 +447,101 @@ def _set_input_data(
                 span, SPANDATA.GEN_AI_REQUEST_MESSAGES, messages_data, unpack=False
             )
 
+    if max_tokens is not None and _is_given(max_tokens):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MAX_TOKENS, max_tokens)
+    if model is not None and _is_given(model):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model)
+    if temperature is not None and _is_given(temperature):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TEMPERATURE, temperature)
+    if top_k is not None and _is_given(top_k):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TOP_K, top_k)
+    if top_p is not None and _is_given(top_p):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TOP_P, top_p)
+
+    if tools is not None and _is_given(tools) and len(tools) > 0:  # type: ignore
+        span.set_data(SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools))
+
+
+def _set_create_input_data(
+    span: "Span", kwargs: "dict[str, Any]", integration: "AnthropicIntegration"
+) -> None:
+    """
+    Set input data for the span based on the provided keyword arguments for the anthropic message creation.
+    """
     span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, kwargs.get("stream", False))
 
-    kwargs_keys_to_attributes = {
-        "max_tokens": SPANDATA.GEN_AI_REQUEST_MAX_TOKENS,
-        "model": SPANDATA.GEN_AI_REQUEST_MODEL,
-        "temperature": SPANDATA.GEN_AI_REQUEST_TEMPERATURE,
-        "top_k": SPANDATA.GEN_AI_REQUEST_TOP_K,
-        "top_p": SPANDATA.GEN_AI_REQUEST_TOP_P,
-    }
-    for key, attribute in kwargs_keys_to_attributes.items():
-        value = kwargs.get(key)
-
-        if value is not None and _is_given(value):
-            span.set_data(attribute, value)
-
-    # Input attributes: Tools
-    tools = kwargs.get("tools")
-    if tools is not None and _is_given(tools) and len(tools) > 0:
-        span.set_data(SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools))
+    _set_common_input_data(
+        span=span,
+        integration=integration,
+        max_tokens=kwargs.get("max_tokens"),  # type: ignore
+        messages=kwargs.get("messages"),  # type: ignore
+        model=kwargs.get("model"),
+        system=kwargs.get("system"),
+        temperature=kwargs.get("temperature"),
+        top_k=kwargs.get("top_k"),
+        top_p=kwargs.get("top_p"),
+        tools=kwargs.get("tools"),
+    )
+
+
+def _wrap_synchronous_message_iterator(
+    stream: "Union[Stream, MessageStream]",
+    iterator: "Iterator[Union[RawMessageStreamEvent, MessageStreamEvent]]",
+) -> "Iterator[Union[RawMessageStreamEvent, MessageStreamEvent]]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Responsible for closing the AI Client Span unless the span has already been closed in the close() patch.
+    """
+    with _StreamSpanContext(stream, guaranteed_streaming_state=True):
+        for event in iterator:
+            # Message and content types are aliases for corresponding Raw* types, introduced in
+            # https://github.com/anthropics/anthropic-sdk-python/commit/bc9d11cd2addec6976c46db10b7c89a8c276101a
+            if not isinstance(
+                event,
+                (
+                    MessageStartEvent,
+                    MessageDeltaEvent,
+                    MessageStopEvent,
+                    ContentBlockStartEvent,
+                    ContentBlockDeltaEvent,
+                    ContentBlockStopEvent,
+                ),
+            ):
+                yield event
+                continue
+
+            _accumulate_event_data(stream, event)
+            yield event
+
+
+async def _wrap_asynchronous_message_iterator(
+    stream: "Union[AsyncStream, AsyncMessageStream]",
+    iterator: "AsyncIterator[Union[RawMessageStreamEvent, MessageStreamEvent]]",
+) -> "AsyncIterator[Union[RawMessageStreamEvent, MessageStreamEvent]]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Responsible for closing the AI Client Span unless the span has already been closed in the close() patch.
+    """
+    with _StreamSpanContext(stream, guaranteed_streaming_state=True):
+        async for event in iterator:
+            # Message and content types are aliases for corresponding Raw* types, introduced in
+            # https://github.com/anthropics/anthropic-sdk-python/commit/bc9d11cd2addec6976c46db10b7c89a8c276101a
+            if not isinstance(
+                event,
+                (
+                    MessageStartEvent,
+                    MessageDeltaEvent,
+                    MessageStopEvent,
+                    ContentBlockStartEvent,
+                    ContentBlockDeltaEvent,
+                    ContentBlockStopEvent,
+                ),
+            ):
+                yield event
+                continue
+
+            _accumulate_event_data(stream, event)
+            yield event
 
 
 def _set_output_data(
@@ -347,11 +553,16 @@ def _set_output_data(
     cache_read_input_tokens: "int | None",
     cache_write_input_tokens: "int | None",
     content_blocks: "list[Any]",
-    finish_span: bool = False,
+    response_id: "str | None" = None,
+    finish_reason: "str | None" = None,
 ) -> None:
     """
     Set output data for the span based on the AI response."""
     span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, model)
+    if response_id is not None:
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_ID, response_id)
+    if finish_reason is not None:
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS, [finish_reason])
     if should_send_default_pii() and integration.include_prompts:
         output_messages: "dict[str, list[Any]]" = {
             "response": [],
@@ -385,11 +596,11 @@ def _set_output_data(
         input_tokens_cache_write=cache_write_input_tokens,
     )
 
-    if finish_span:
-        span.__exit__(None, None, None)
 
-
-def _sentry_patched_create_common(f: "Any", *args: "Any", **kwargs: "Any") -> "Any":
+def _sentry_patched_create_sync(f: "Any", *args: "Any", **kwargs: "Any") -> "Any":
+    """
+    Creates and manages an AI Client Span for both non-streaming and streaming calls.
+    """
     integration = kwargs.pop("integration")
     if integration is None:
         return f(*args, **kwargs)
@@ -411,9 +622,28 @@ def _sentry_patched_create_common(f: "Any", *args: "Any", **kwargs: "Any") -> "A
     )
     span.__enter__()
 
-    _set_input_data(span, kwargs, integration)
+    _set_create_input_data(span, kwargs, integration)
+
+    try:
+        result = f(*args, **kwargs)
+    except Exception as exc:
+        exc_info = sys.exc_info()
+        with capture_internal_exceptions():
+            _capture_exception(exc)
+            span.__exit__(*exc_info)
+        reraise(*exc_info)
+
+    if isinstance(result, Stream):
+        result._span = span
+        result._integration = integration
+
+        _initialize_data_accumulation_state(result)
+        result._iterator = _wrap_synchronous_message_iterator(
+            result,
+            result._iterator,
+        )
 
-    result = yield f, args, kwargs
+        return result
 
     with capture_internal_exceptions():
         if hasattr(result, "content"):
@@ -442,94 +672,98 @@ def _sentry_patched_create_common(f: "Any", *args: "Any", **kwargs: "Any") -> "A
                 cache_read_input_tokens=cache_read_input_tokens,
                 cache_write_input_tokens=cache_write_input_tokens,
                 content_blocks=content_blocks,
-                finish_span=True,
+                response_id=getattr(result, "id", None),
+                finish_reason=getattr(result, "stop_reason", None),
             )
+            span.__exit__(None, None, None)
+        else:
+            span.set_data("unknown_response", True)
+            span.__exit__(None, None, None)
 
-        # Streaming response
-        elif hasattr(result, "_iterator"):
-            old_iterator = result._iterator
-
-            def new_iterator() -> "Iterator[MessageStreamEvent]":
-                model = None
-                usage = _RecordedUsage()
-                content_blocks: "list[str]" = []
-
-                for event in old_iterator:
-                    (
-                        model,
-                        usage,
-                        content_blocks,
-                    ) = _collect_ai_data(
-                        event,
-                        model,
-                        usage,
-                        content_blocks,
-                    )
-                    yield event
-
-                # Anthropic's input_tokens excludes cached/cache_write tokens.
-                # Normalize to total input tokens for correct cost calculations.
-                total_input = (
-                    usage.input_tokens
-                    + (usage.cache_read_input_tokens or 0)
-                    + (usage.cache_write_input_tokens or 0)
-                )
+    return result
 
-                _set_output_data(
-                    span=span,
-                    integration=integration,
-                    model=model,
-                    input_tokens=total_input,
-                    output_tokens=usage.output_tokens,
-                    cache_read_input_tokens=usage.cache_read_input_tokens,
-                    cache_write_input_tokens=usage.cache_write_input_tokens,
-                    content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
-                    finish_span=True,
-                )
 
-            async def new_iterator_async() -> "AsyncIterator[MessageStreamEvent]":
-                model = None
-                usage = _RecordedUsage()
-                content_blocks: "list[str]" = []
-
-                async for event in old_iterator:
-                    (
-                        model,
-                        usage,
-                        content_blocks,
-                    ) = _collect_ai_data(
-                        event,
-                        model,
-                        usage,
-                        content_blocks,
-                    )
-                    yield event
-
-                # Anthropic's input_tokens excludes cached/cache_write tokens.
-                # Normalize to total input tokens for correct cost calculations.
-                total_input = (
-                    usage.input_tokens
-                    + (usage.cache_read_input_tokens or 0)
-                    + (usage.cache_write_input_tokens or 0)
-                )
+async def _sentry_patched_create_async(
+    f: "Any", *args: "Any", **kwargs: "Any"
+) -> "Any":
+    """
+    Creates and manages an AI Client Span for both non-streaming and streaming calls.
+    """
+    integration = kwargs.pop("integration")
+    if integration is None:
+        return await f(*args, **kwargs)
 
-                _set_output_data(
-                    span=span,
-                    integration=integration,
-                    model=model,
-                    input_tokens=total_input,
-                    output_tokens=usage.output_tokens,
-                    cache_read_input_tokens=usage.cache_read_input_tokens,
-                    cache_write_input_tokens=usage.cache_write_input_tokens,
-                    content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
-                    finish_span=True,
-                )
+    if "messages" not in kwargs:
+        return await f(*args, **kwargs)
 
-            if str(type(result._iterator)) == "<class 'async_generator'>":
-                result._iterator = new_iterator_async()
-            else:
-                result._iterator = new_iterator()
+    try:
+        iter(kwargs["messages"])
+    except TypeError:
+        return await f(*args, **kwargs)
+
+    model = kwargs.get("model", "")
+
+    span = get_start_span_function()(
+        op=OP.GEN_AI_CHAT,
+        name=f"chat {model}".strip(),
+        origin=AnthropicIntegration.origin,
+    )
+    span.__enter__()
+
+    _set_create_input_data(span, kwargs, integration)
+
+    try:
+        result = await f(*args, **kwargs)
+    except Exception as exc:
+        exc_info = sys.exc_info()
+        with capture_internal_exceptions():
+            _capture_exception(exc)
+            span.__exit__(*exc_info)
+        reraise(*exc_info)
+
+    if isinstance(result, AsyncStream):
+        result._span = span
+        result._integration = integration
+
+        _initialize_data_accumulation_state(result)
+        result._iterator = _wrap_asynchronous_message_iterator(
+            result,
+            result._iterator,
+        )
+
+        return result
+
+    with capture_internal_exceptions():
+        if hasattr(result, "content"):
+            (
+                input_tokens,
+                output_tokens,
+                cache_read_input_tokens,
+                cache_write_input_tokens,
+            ) = _get_token_usage(result)
+
+            content_blocks = []
+            for content_block in result.content:
+                if hasattr(content_block, "to_dict"):
+                    content_blocks.append(content_block.to_dict())
+                elif hasattr(content_block, "model_dump"):
+                    content_blocks.append(content_block.model_dump())
+                elif hasattr(content_block, "text"):
+                    content_blocks.append({"type": "text", "text": content_block.text})
 
+            _set_output_data(
+                span=span,
+                integration=integration,
+                model=getattr(result, "model", None),
+                input_tokens=input_tokens,
+                output_tokens=output_tokens,
+                cache_read_input_tokens=cache_read_input_tokens,
+                cache_write_input_tokens=cache_write_input_tokens,
+                content_blocks=content_blocks,
+                response_id=getattr(result, "id", None),
+                finish_reason=getattr(result, "stop_reason", None),
+            )
+            span.__exit__(None, None, None)
         else:
             span.set_data("unknown_response", True)
             span.__exit__(None, None, None)
@@ -538,79 +772,308 @@ async def new_iterator_async() -> "AsyncIterator[MessageStreamEvent]":
 
 
 def _wrap_message_create(f: "Any") -> "Any":
-    def _execute_sync(f: "Any", *args: "Any", **kwargs: "Any") -> "Any":
-        gen = _sentry_patched_create_common(f, *args, **kwargs)
+    @wraps(f)
+    def _sentry_wrapped_create_sync(*args: "Any", **kwargs: "Any") -> "Any":
+        integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
+        kwargs["integration"] = integration
 
-        try:
-            f, args, kwargs = next(gen)
-        except StopIteration as e:
-            return e.value
+        return _sentry_patched_create_sync(f, *args, **kwargs)
+
+    return _sentry_wrapped_create_sync
+
+
+def _initialize_data_accumulation_state(stream: "Union[Stream, MessageStream]") -> None:
+    """
+    Initialize fields for accumulating output on the Stream instance.
+    """
+    if not hasattr(stream, "_model"):
+        stream._model = None
+        stream._usage = _RecordedUsage()
+        stream._content_blocks = []
+        stream._response_id = None
+        stream._finish_reason = None
 
-        try:
-            try:
-                result = f(*args, **kwargs)
-            except Exception as exc:
-                exc_info = sys.exc_info()
-                with capture_internal_exceptions():
-                    _capture_exception(exc)
-                reraise(*exc_info)
-
-            return gen.send(result)
-        except StopIteration as e:
-            return e.value
 
+def _accumulate_event_data(
+    stream: "Union[Stream, MessageStream]",
+    event: "Union[RawMessageStreamEvent, MessageStreamEvent]",
+) -> None:
+    """
+    Update accumulated output from a single stream event.
+    """
+    (model, usage, content_blocks, response_id, finish_reason) = _collect_ai_data(
+        event,
+        stream._model,
+        stream._usage,
+        stream._content_blocks,
+        stream._response_id,
+        stream._finish_reason,
+    )
+
+    stream._model = model
+    stream._usage = usage
+    stream._content_blocks = content_blocks
+    stream._response_id = response_id
+    stream._finish_reason = finish_reason
+
+
+def _set_streaming_output_data(
+    span: "Span",
+    integration: "AnthropicIntegration",
+    model: "Optional[str]",
+    usage: "_RecordedUsage",
+    content_blocks: "list[str]",
+    response_id: "Optional[str]",
+    finish_reason: "Optional[str]",
+) -> None:
+    """
+    Set output attributes on the AI Client Span.
+    """
+    # Anthropic's input_tokens excludes cached/cache_write tokens.
+    # Normalize to total input tokens for correct cost calculations.
+    total_input = (
+        usage.input_tokens
+        + (usage.cache_read_input_tokens or 0)
+        + (usage.cache_write_input_tokens or 0)
+    )
+
+    _set_output_data(
+        span=span,
+        integration=integration,
+        model=model,
+        input_tokens=total_input,
+        output_tokens=usage.output_tokens,
+        cache_read_input_tokens=usage.cache_read_input_tokens,
+        cache_write_input_tokens=usage.cache_write_input_tokens,
+        content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
+        response_id=response_id,
+        finish_reason=finish_reason,
+    )
+
+
+def _wrap_close(
+    f: "Callable[..., None]",
+) -> "Callable[..., None]":
+    """
+    Closes the AI Client Span unless the finally block in `_wrap_synchronous_message_iterator()` runs first.
+    """
+
+    def close(self: "Union[Stream, MessageStream]") -> None:
+        with _StreamSpanContext(self):
+            return f(self)
+
+    return close
+
+
+def _wrap_message_create_async(f: "Any") -> "Any":
     @wraps(f)
-    def _sentry_patched_create_sync(*args: "Any", **kwargs: "Any") -> "Any":
+    async def _sentry_wrapped_create_async(*args: "Any", **kwargs: "Any") -> "Any":
         integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
         kwargs["integration"] = integration
 
-        try:
-            return _execute_sync(f, *args, **kwargs)
-        finally:
-            span = sentry_sdk.get_current_span()
-            if span is not None and span.status == SPANSTATUS.INTERNAL_ERROR:
-                with capture_internal_exceptions():
-                    span.__exit__(None, None, None)
+        return await _sentry_patched_create_async(f, *args, **kwargs)
 
-    return _sentry_patched_create_sync
+    return _sentry_wrapped_create_async
 
 
-def _wrap_message_create_async(f: "Any") -> "Any":
-    async def _execute_async(f: "Any", *args: "Any", **kwargs: "Any") -> "Any":
-        gen = _sentry_patched_create_common(f, *args, **kwargs)
+def _wrap_async_close(
+    f: "Callable[..., Awaitable[None]]",
+) -> "Callable[..., Awaitable[None]]":
+    """
+    Closes the AI Client Span unless the finally block in `_wrap_asynchronous_message_iterator()` runs first.
+    """
+
+    async def close(self: "AsyncStream") -> None:
+        with _StreamSpanContext(self):
+            return await f(self)
+
+    return close
+
+
+def _wrap_message_stream(f: "Any") -> "Any":
+    """
+    Attaches user-provided arguments to the returned context manager.
+    The attributes are set on AI Client Spans in the patch for the context manager.
+    """
+
+    @wraps(f)
+    def _sentry_patched_stream(*args: "Any", **kwargs: "Any") -> "MessageStreamManager":
+        stream_manager = f(*args, **kwargs)
+
+        stream_manager._max_tokens = kwargs.get("max_tokens")
+        stream_manager._messages = kwargs.get("messages")
+        stream_manager._model = kwargs.get("model")
+        stream_manager._system = kwargs.get("system")
+        stream_manager._temperature = kwargs.get("temperature")
+        stream_manager._top_k = kwargs.get("top_k")
+        stream_manager._top_p = kwargs.get("top_p")
+        stream_manager._tools = kwargs.get("tools")
+
+        return stream_manager
+
+    return _sentry_patched_stream
+
+
+def _wrap_message_stream_manager_enter(f: "Any") -> "Any":
+    """
+    Creates and manages AI Client Spans.
+    """
+
+    @wraps(f)
+    def _sentry_patched_enter(self: "MessageStreamManager") -> "MessageStream":
+        if not hasattr(self, "_max_tokens"):
+            return f(self)
+
+        integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
+
+        if integration is None:
+            return f(self)
+
+        if self._messages is None:
+            return f(self)
 
         try:
-            f, args, kwargs = next(gen)
-        except StopIteration as e:
-            return await e.value
+            iter(self._messages)
+        except TypeError:
+            return f(self)
+
+        span = get_start_span_function()(
+            op=OP.GEN_AI_CHAT,
+            name="chat" if self._model is None else f"chat {self._model}".strip(),
+            origin=AnthropicIntegration.origin,
+        )
+        span.__enter__()
+
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
+        _set_common_input_data(
+            span=span,
+            integration=integration,
+            max_tokens=self._max_tokens,
+            messages=self._messages,
+            model=self._model,
+            system=self._system,
+            temperature=self._temperature,
+            top_k=self._top_k,
+            top_p=self._top_p,
+            tools=self._tools,
+        )
 
         try:
-            try:
-                result = await f(*args, **kwargs)
-            except Exception as exc:
-                exc_info = sys.exc_info()
-                with capture_internal_exceptions():
-                    _capture_exception(exc)
-                reraise(*exc_info)
-
-            return gen.send(result)
-        except StopIteration as e:
-            return e.value
+            stream = f(self)
+        except Exception as exc:
+            exc_info = sys.exc_info()
+            with capture_internal_exceptions():
+                _capture_exception(exc)
+                span.__exit__(*exc_info)
+            reraise(*exc_info)
+
+        stream._span = span
+        stream._integration = integration
+
+        _initialize_data_accumulation_state(stream)
+        stream._iterator = _wrap_synchronous_message_iterator(
+            stream,
+            stream._iterator,
+        )
+
+        return stream
+
+    return _sentry_patched_enter
+
+
+def _wrap_async_message_stream(f: "Any") -> "Any":
+    """
+    Attaches user-provided arguments to the returned context manager.
+    The attributes are set on AI Client Spans in the patch for the context manager.
+    """
 
     @wraps(f)
-    async def _sentry_patched_create_async(*args: "Any", **kwargs: "Any") -> "Any":
+    def _sentry_patched_stream(
+        *args: "Any", **kwargs: "Any"
+    ) -> "AsyncMessageStreamManager":
+        stream_manager = f(*args, **kwargs)
+
+        stream_manager._max_tokens = kwargs.get("max_tokens")
+        stream_manager._messages = kwargs.get("messages")
+        stream_manager._model = kwargs.get("model")
+        stream_manager._system = kwargs.get("system")
+        stream_manager._temperature = kwargs.get("temperature")
+        stream_manager._top_k = kwargs.get("top_k")
+        stream_manager._top_p = kwargs.get("top_p")
+        stream_manager._tools = kwargs.get("tools")
+
+        return stream_manager
+
+    return _sentry_patched_stream
+
+
+def _wrap_async_message_stream_manager_aenter(f: "Any") -> "Any":
+    """
+    Creates and manages AI Client Spans.
+    """
+
+    @wraps(f)
+    async def _sentry_patched_aenter(
+        self: "AsyncMessageStreamManager",
+    ) -> "AsyncMessageStream":
+        if not hasattr(self, "_max_tokens"):
+            return await f(self)
+
         integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
-        kwargs["integration"] = integration
+
+        if integration is None:
+            return await f(self)
+
+        if self._messages is None:
+            return await f(self)
 
         try:
-            return await _execute_async(f, *args, **kwargs)
-        finally:
-            span = sentry_sdk.get_current_span()
-            if span is not None and span.status == SPANSTATUS.INTERNAL_ERROR:
-                with capture_internal_exceptions():
-                    span.__exit__(None, None, None)
-
-    return _sentry_patched_create_async
+            iter(self._messages)
+        except TypeError:
+            return await f(self)
+
+        span = get_start_span_function()(
+            op=OP.GEN_AI_CHAT,
+            name="chat" if self._model is None else f"chat {self._model}".strip(),
+            origin=AnthropicIntegration.origin,
+        )
+        span.__enter__()
+
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
+        _set_common_input_data(
+            span=span,
+            integration=integration,
+            max_tokens=self._max_tokens,
+            messages=self._messages,
+            model=self._model,
+            system=self._system,
+            temperature=self._temperature,
+            top_k=self._top_k,
+            top_p=self._top_p,
+            tools=self._tools,
+        )
+
+        try:
+            stream = await f(self)
+        except Exception as exc:
+            exc_info = sys.exc_info()
+            with capture_internal_exceptions():
+                _capture_exception(exc)
+                span.__exit__(*exc_info)
+            reraise(*exc_info)
+
+        stream._span = span
+        stream._integration = integration
+
+        _initialize_data_accumulation_state(stream)
+        stream._iterator = _wrap_asynchronous_message_iterator(
+            stream,
+            stream._iterator,
+        )
+
+        return stream
+
+    return _sentry_patched_aenter
 
 
 def _is_given(obj: "Any") -> bool:
diff --git a/sentry_sdk/integrations/asgi.py b/sentry_sdk/integrations/asgi.py
index 6983af89ed..64dc3cc554 100644
--- a/sentry_sdk/integrations/asgi.py
+++ b/sentry_sdk/integrations/asgi.py
@@ -4,6 +4,7 @@
 Based on Tom Christie's `sentry-asgi <https://github.com/encode/sentry-asgi>`.
 """
 
+import sys
 import asyncio
 import inspect
 from copy import deepcopy
@@ -14,6 +15,7 @@
 from sentry_sdk.consts import OP
 from sentry_sdk.integrations._asgi_common import (
     _get_headers,
+    _get_request_attributes,
     _get_request_data,
     _get_url,
 )
@@ -22,10 +24,17 @@
     nullcontext,
 )
 from sentry_sdk.sessions import track_session
+from sentry_sdk.traces import (
+    StreamedSpan,
+    SegmentSource,
+    SOURCE_FOR_STYLE as SEGMENT_SOURCE_FOR_STYLE,
+)
 from sentry_sdk.tracing import (
     SOURCE_FOR_STYLE,
+    Transaction,
     TransactionSource,
 )
+from sentry_sdk.tracing_utils import has_span_streaming_enabled
 from sentry_sdk.utils import (
     ContextVar,
     event_from_exception,
@@ -34,18 +43,23 @@
     logger,
     transaction_from_function,
     _get_installed_modules,
+    reraise,
+    capture_internal_exceptions,
+    qualname_from_function,
 )
-from sentry_sdk.tracing import Transaction
 
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from typing import Any
+    from typing import ContextManager
     from typing import Dict
     from typing import Optional
     from typing import Tuple
+    from typing import Union
 
-    from sentry_sdk._types import Event, Hint
+    from sentry_sdk._types import Attributes, Event, Hint
+    from sentry_sdk.tracing import Span
 
 
 _asgi_middleware_applied = ContextVar("sentry_asgi_middleware_applied")
@@ -182,8 +196,22 @@ async def _run_app(
                     return await self.app(scope, receive, send)
 
             except Exception as exc:
-                self._capture_lifespan_exception(exc)
-                raise exc from None
+                suppress_chained_exceptions = (
+                    sentry_sdk.get_client()
+                    .options.get("_experiments", {})
+                    .get("suppress_asgi_chained_exceptions", True)
+                )
+                if suppress_chained_exceptions:
+                    self._capture_lifespan_exception(exc)
+                    raise exc from None
+
+                exc_info = sys.exc_info()
+                with capture_internal_exceptions():
+                    self._capture_lifespan_exception(exc)
+                reraise(*exc_info)
+
+        client = sentry_sdk.get_client()
+        span_streaming = has_span_streaming_enabled(client.options)
 
         _asgi_middleware_applied.set(True)
         try:
@@ -204,48 +232,111 @@ async def _run_app(
                     )
 
                     method = scope.get("method", "").upper()
-                    transaction = None
-                    if ty in ("http", "websocket"):
-                        if ty == "websocket" or method in self.http_methods_to_capture:
-                            transaction = continue_trace(
-                                _get_headers(scope),
-                                op="{}.server".format(ty),
+
+                    span_ctx: "ContextManager[Union[Span, StreamedSpan, None]]"
+                    if span_streaming:
+                        segment: "Optional[StreamedSpan]" = None
+                        attributes: "Attributes" = {
+                            "sentry.span.source": getattr(
+                                transaction_source, "value", transaction_source
+                            ),
+                            "sentry.origin": self.span_origin,
+                            "network.protocol.name": ty,
+                        }
+
+                        if ty in ("http", "websocket"):
+                            if (
+                                ty == "websocket"
+                                or method in self.http_methods_to_capture
+                            ):
+                                sentry_sdk.traces.continue_trace(_get_headers(scope))
+
+                                sentry_scope.set_custom_sampling_context(
+                                    {"asgi_scope": scope}
+                                )
+
+                                attributes["sentry.op"] = f"{ty}.server"
+                                segment = sentry_sdk.traces.start_span(
+                                    name=transaction_name, attributes=attributes
+                                )
+                        else:
+                            sentry_sdk.traces.new_trace()
+
+                            sentry_scope.set_custom_sampling_context(
+                                {"asgi_scope": scope}
+                            )
+
+                            attributes["sentry.op"] = OP.HTTP_SERVER
+                            segment = sentry_sdk.traces.start_span(
+                                name=transaction_name, attributes=attributes
+                            )
+
+                        span_ctx = segment or nullcontext()
+
+                    else:
+                        transaction = None
+                        if ty in ("http", "websocket"):
+                            if (
+                                ty == "websocket"
+                                or method in self.http_methods_to_capture
+                            ):
+                                transaction = continue_trace(
+                                    _get_headers(scope),
+                                    op="{}.server".format(ty),
+                                    name=transaction_name,
+                                    source=transaction_source,
+                                    origin=self.span_origin,
+                                )
+                        else:
+                            transaction = Transaction(
+                                op=OP.HTTP_SERVER,
                                 name=transaction_name,
                                 source=transaction_source,
                                 origin=self.span_origin,
                             )
-                    else:
-                        transaction = Transaction(
-                            op=OP.HTTP_SERVER,
-                            name=transaction_name,
-                            source=transaction_source,
-                            origin=self.span_origin,
-                        )
 
-                    if transaction:
-                        transaction.set_tag("asgi.type", ty)
+                        if transaction:
+                            transaction.set_tag("asgi.type", ty)
 
-                    transaction_context = (
-                        sentry_sdk.start_transaction(
-                            transaction,
-                            custom_sampling_context={"asgi_scope": scope},
+                        span_ctx = (
+                            sentry_sdk.start_transaction(
+                                transaction,
+                                custom_sampling_context={"asgi_scope": scope},
+                            )
+                            if transaction is not None
+                            else nullcontext()
                         )
-                        if transaction is not None
-                        else nullcontext()
-                    )
-                    with transaction_context:
+
+                    with span_ctx as span:
+                        if isinstance(span, StreamedSpan):
+                            for attribute, value in _get_request_attributes(
+                                scope
+                            ).items():
+                                span.set_attribute(attribute, value)
+
                         try:
 
                             async def _sentry_wrapped_send(
                                 event: "Dict[str, Any]",
                             ) -> "Any":
-                                if transaction is not None:
+                                if span is not None:
                                     is_http_response = (
                                         event.get("type") == "http.response.start"
                                         and "status" in event
                                     )
                                     if is_http_response:
-                                        transaction.set_http_status(event["status"])
+                                        if isinstance(span, StreamedSpan):
+                                            span.status = (
+                                                "error"
+                                                if event["status"] >= 400
+                                                else "ok"
+                                            )
+                                            span.set_attribute(
+                                                "http.response.status_code",
+                                                event["status"],
+                                            )
+                                        else:
+                                            span.set_http_status(event["status"])
 
                                 return await send(event)
 
@@ -257,9 +348,43 @@ async def _sentry_wrapped_send(
                                 return await self.app(
                                     scope, receive, _sentry_wrapped_send
                                 )
+
                         except Exception as exc:
-                            self._capture_request_exception(exc)
-                            raise exc from None
+                            suppress_chained_exceptions = (
+                                sentry_sdk.get_client()
+                                .options.get("_experiments", {})
+                                .get("suppress_asgi_chained_exceptions", True)
+                            )
+                            if suppress_chained_exceptions:
+                                self._capture_request_exception(exc)
+                                raise exc from None
+
+                            exc_info = sys.exc_info()
+                            with capture_internal_exceptions():
+                                self._capture_request_exception(exc)
+                            reraise(*exc_info)
+
+                        finally:
+                            if isinstance(span, StreamedSpan):
+                                already_set = (
+                                    span is not None
+                                    and span.name != _DEFAULT_TRANSACTION_NAME
+                                    and span.get_attributes().get("sentry.span.source")
+                                    in [
+                                        SegmentSource.COMPONENT.value,
+                                        SegmentSource.ROUTE.value,
+                                        SegmentSource.CUSTOM.value,
+                                    ]
+                                )
+                                with capture_internal_exceptions():
+                                    if not already_set:
+                                        name, source = (
+                                            self._get_segment_name_and_source(
+                                                self.transaction_style, scope
+                                            )
+                                        )
+                                        span.name = name
+                                        span.set_attribute("sentry.span.source", source)
         finally:
             _asgi_middleware_applied.set(False)
 
@@ -334,3 +459,40 @@ def _get_transaction_name_and_source(
             return name, source
 
         return name, source
+
+    def _get_segment_name_and_source(
+        self: "SentryAsgiMiddleware", segment_style: str, asgi_scope: "Any"
+    ) -> "Tuple[str, str]":
+        name = None
+        source = SEGMENT_SOURCE_FOR_STYLE[segment_style].value
+        ty = asgi_scope.get("type")
+
+        if segment_style == "endpoint":
+            endpoint = asgi_scope.get("endpoint")
+            # Webframeworks like Starlette mutate the ASGI env once routing is
+            # done, which is sometime after the request has started. If we have
+            # an endpoint, overwrite our generic transaction name.
+            if endpoint:
+                name = qualname_from_function(endpoint) or ""
+            else:
+                name = _get_url(asgi_scope, "http" if ty == "http" else "ws", host=None)
+                source = SegmentSource.URL.value
+
+        elif segment_style == "url":
+            # FastAPI includes the route object in the scope to let Sentry extract the
+            # path from it for the transaction name
+            route = asgi_scope.get("route")
+            if route:
+                path = getattr(route, "path", None)
+                if path is not None:
+                    name = path
+            else:
+                name = _get_url(asgi_scope, "http" if ty == "http" else "ws", host=None)
+                source = SegmentSource.URL.value
+
+        if name is None:
+            name = _DEFAULT_TRANSACTION_NAME
+            source = SegmentSource.ROUTE.value
+            return name, source
+
+        return name, source
diff --git a/sentry_sdk/integrations/asyncio.py b/sentry_sdk/integrations/asyncio.py
index b7aa0a7202..91fd54bf3a 100644
--- a/sentry_sdk/integrations/asyncio.py
+++ b/sentry_sdk/integrations/asyncio.py
@@ -5,7 +5,13 @@
 from sentry_sdk.consts import OP
 from sentry_sdk.integrations import Integration, DidNotEnable
 from sentry_sdk.integrations._wsgi_common import nullcontext
-from sentry_sdk.utils import event_from_exception, logger, reraise
+from sentry_sdk.utils import (
+    event_from_exception,
+    logger,
+    reraise,
+    is_internal_task,
+)
+from sentry_sdk.transport import AsyncHttpTransport
 
 try:
     import asyncio
@@ -13,7 +19,7 @@
 except ImportError:
     raise DidNotEnable("asyncio not available")
 
-from typing import cast, TYPE_CHECKING
+from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from typing import Any, Callable, TypeVar
@@ -42,6 +48,76 @@ def _wrap_coroutine(wrapped: "Coroutine[Any, Any, Any]") -> "Callable[[T], T]":
     )
 
 
+def patch_loop_close() -> None:
+    """Patch loop.close to flush pending events before shutdown."""
+    # Atexit shutdown hook happens after the event loop is closed.
+    # Therefore, it is necessary to patch the loop.close method to ensure
+    # that pending events are flushed before the interpreter shuts down.
+    try:
+        loop = asyncio.get_running_loop()
+    except RuntimeError:
+        # No running loop → cannot patch now
+        return
+
+    if getattr(loop, "_sentry_flush_patched", False):
+        return
+
+    async def _flush() -> None:
+        client = sentry_sdk.get_client()
+        if not client.is_active():
+            return
+
+        try:
+            if not isinstance(client.transport, AsyncHttpTransport):
+                return
+
+            await client.close_async()
+        except Exception:
+            logger.warning("Sentry flush failed during loop shutdown", exc_info=True)
+
+    orig_close = loop.close
+
+    def _patched_close() -> None:
+        try:
+            loop.run_until_complete(_flush())
+        except Exception:
+            logger.debug(
+                "Could not flush Sentry events during loop close", exc_info=True
+            )
+        finally:
+            orig_close()
+
+    loop.close = _patched_close  # type: ignore
+    loop._sentry_flush_patched = True  # type: ignore
+
+
+def _create_task_with_factory(
+    orig_task_factory: "Any",
+    loop: "asyncio.AbstractEventLoop",
+    coro: "Coroutine[Any, Any, Any]",
+    **kwargs: "Any",
+) -> "asyncio.Task[Any]":
+    task = None
+
+    # Trying to use user set task factory (if there is one)
+    if orig_task_factory:
+        task = orig_task_factory(loop, coro, **kwargs)
+
+    if task is None:
+        # The default task factory in `asyncio` does not have its own function
+        # but is just a couple of lines in `asyncio.base_events.create_task()`
+        # Those lines are copied here.
+
+        # WARNING:
+        # If the default behavior of the task creation in asyncio changes,
+        # this will break!
+        task = Task(coro, loop=loop, **kwargs)
+        if task._source_traceback:  # type: ignore
+            del task._source_traceback[-1]  # type: ignore
+
+    return task
+
+
 def patch_asyncio() -> None:
     orig_task_factory = None
     try:
@@ -57,6 +133,12 @@ def _sentry_task_factory(
             coro: "Coroutine[Any, Any, Any]",
             **kwargs: "Any",
         ) -> "asyncio.Future[Any]":
+            # Check if this is an internal Sentry task
+            if is_internal_task():
+                return _create_task_with_factory(
+                    orig_task_factory, loop, coro, **kwargs
+                )
+
             @_wrap_coroutine(coro)
             async def _task_with_sentry_span_creation() -> "Any":
                 result = None
@@ -85,31 +167,13 @@ async def _task_with_sentry_span_creation() -> "Any":
 
                 return result
 
-            task = None
-
-            # Trying to use user set task factory (if there is one)
-            if orig_task_factory:
-                task = orig_task_factory(
-                    loop, _task_with_sentry_span_creation(), **kwargs
-                )
-
-            if task is None:
-                # The default task factory in `asyncio` does not have its own function
-                # but is just a couple of lines in `asyncio.base_events.create_task()`
-                # Those lines are copied here.
-
-                # WARNING:
-                # If the default behavior of the task creation in asyncio changes,
-                # this will break!
-                task = Task(_task_with_sentry_span_creation(), loop=loop, **kwargs)
-                if task._source_traceback:  # type: ignore
-                    del task._source_traceback[-1]  # type: ignore
+            task = _create_task_with_factory(
+                orig_task_factory, loop, _task_with_sentry_span_creation(), **kwargs
+            )
 
             # Set the task name to include the original coroutine's name
             try:
-                cast("asyncio.Task[Any]", task).set_name(
-                    f"{get_name(coro)} (Sentry-wrapped)"
-                )
+                task.set_name(f"{get_name(coro)} (Sentry-wrapped)")
             except AttributeError:
                 # set_name might not be available in all Python versions
                 pass
@@ -156,6 +220,7 @@ def __init__(self, task_spans: bool = True) -> None:
     @staticmethod
     def setup_once() -> None:
         patch_asyncio()
+        patch_loop_close()
 
 
 def enable_asyncio_integration(*args: "Any", **kwargs: "Any") -> None:
diff --git a/sentry_sdk/integrations/asyncpg.py b/sentry_sdk/integrations/asyncpg.py
index 7f3591154a..29f3bad152 100644
--- a/sentry_sdk/integrations/asyncpg.py
+++ b/sentry_sdk/integrations/asyncpg.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 import contextlib
+import re
 from typing import Any, TypeVar, Callable, Awaitable, Iterator
 
 import sentry_sdk
@@ -55,6 +56,10 @@ def setup_once() -> None:
 T = TypeVar("T")
 
 
+def _normalize_query(query: str) -> str:
+    return re.sub(r"\s+", " ", query).strip()
+
+
 def _wrap_execute(f: "Callable[..., Awaitable[T]]") -> "Callable[..., Awaitable[T]]":
     async def _inner(*args: "Any", **kwargs: "Any") -> "T":
         if sentry_sdk.get_client().get_integration(AsyncPGIntegration) is None:
@@ -67,7 +72,7 @@ async def _inner(*args: "Any", **kwargs: "Any") -> "T":
         if len(args) > 2:
             return await f(*args, **kwargs)
 
-        query = args[1]
+        query = _normalize_query(args[1])
         with record_sql_queries(
             cursor=None,
             query=query,
@@ -103,6 +108,7 @@ def _record(
 
     param_style = "pyformat" if params_list else None
 
+    query = _normalize_query(query)
     with record_sql_queries(
         cursor=cursor,
         query=query,
@@ -178,6 +184,7 @@ async def _inner(*args: "Any", **kwargs: "Any") -> "T":
                     pass
             span.set_data(SPANDATA.DB_NAME, database)
             span.set_data(SPANDATA.DB_USER, user)
+            span.set_data(SPANDATA.DB_DRIVER_NAME, "asyncpg")
 
             with capture_internal_exceptions():
                 sentry_sdk.add_breadcrumb(
@@ -192,6 +199,7 @@ async def _inner(*args: "Any", **kwargs: "Any") -> "T":
 
 def _set_db_data(span: "Span", conn: "Any") -> None:
     span.set_data(SPANDATA.DB_SYSTEM, "postgresql")
+    span.set_data(SPANDATA.DB_DRIVER_NAME, "asyncpg")
 
     addr = conn._addr
     if addr:
diff --git a/sentry_sdk/integrations/celery/__init__.py b/sentry_sdk/integrations/celery/__init__.py
index fe832f159e..b8b1691979 100644
--- a/sentry_sdk/integrations/celery/__init__.py
+++ b/sentry_sdk/integrations/celery/__init__.py
@@ -14,7 +14,7 @@
 )
 from sentry_sdk.integrations.celery.utils import _now_seconds_since_epoch
 from sentry_sdk.integrations.logging import ignore_logger
-from sentry_sdk.tracing import BAGGAGE_HEADER_NAME, TransactionSource
+from sentry_sdk.tracing import BAGGAGE_HEADER_NAME, Span, TransactionSource
 from sentry_sdk.tracing_utils import Baggage
 from sentry_sdk.utils import (
     capture_internal_exceptions,
@@ -34,7 +34,6 @@
     from typing import Union
 
     from sentry_sdk._types import EventProcessor, Event, Hint, ExcInfo
-    from sentry_sdk.tracing import Span
 
     F = TypeVar("F", bound=Callable[..., Any])
 
@@ -100,7 +99,10 @@ def _set_status(status: str) -> None:
     with capture_internal_exceptions():
         scope = sentry_sdk.get_current_scope()
         if scope.span is not None:
-            scope.span.set_status(status)
+            if isinstance(scope.span, Span):
+                scope.span.set_status(status)
+            else:
+                scope.span.status = "ok" if status == "ok" else "error"
 
 
 def _capture_exception(task: "Any", exc_info: "ExcInfo") -> None:
diff --git a/sentry_sdk/integrations/celery/utils.py b/sentry_sdk/integrations/celery/utils.py
index f9378558c1..3a526ccdfa 100644
--- a/sentry_sdk/integrations/celery/utils.py
+++ b/sentry_sdk/integrations/celery/utils.py
@@ -2,7 +2,7 @@
 from typing import TYPE_CHECKING, cast
 
 if TYPE_CHECKING:
-    from typing import Any, Tuple
+    from typing import Tuple
     from sentry_sdk._types import MonitorConfigScheduleUnit
 
 
@@ -29,11 +29,3 @@ def _get_humanized_interval(seconds: float) -> "Tuple[int, MonitorConfigSchedule
             return (interval, cast("MonitorConfigScheduleUnit", unit))
 
     return (int(seconds), "second")
-
-
-class NoOpMgr:
-    def __enter__(self) -> None:
-        return None
-
-    def __exit__(self, exc_type: "Any", exc_value: "Any", traceback: "Any") -> None:
-        return None
diff --git a/sentry_sdk/integrations/clickhouse_driver.py b/sentry_sdk/integrations/clickhouse_driver.py
index 7bbea94210..3b7ec9891e 100644
--- a/sentry_sdk/integrations/clickhouse_driver.py
+++ b/sentry_sdk/integrations/clickhouse_driver.py
@@ -165,6 +165,7 @@ def wrapped_generator() -> "Iterator[Any]":
 
 def _set_db_data(span: "Span", connection: "Connection") -> None:
     span.set_data(SPANDATA.DB_SYSTEM, "clickhouse")
+    span.set_data(SPANDATA.DB_DRIVER_NAME, "clickhouse-driver")
     span.set_data(SPANDATA.SERVER_ADDRESS, connection.host)
     span.set_data(SPANDATA.SERVER_PORT, connection.port)
     span.set_data(SPANDATA.DB_NAME, connection.database)
diff --git a/sentry_sdk/integrations/django/tasks.py b/sentry_sdk/integrations/django/tasks.py
index 84bc4d2396..e6adb914e8 100644
--- a/sentry_sdk/integrations/django/tasks.py
+++ b/sentry_sdk/integrations/django/tasks.py
@@ -2,12 +2,11 @@
 
 import sentry_sdk
 from sentry_sdk.consts import OP
-from sentry_sdk.tracing import SPANSTATUS
 from sentry_sdk.utils import qualname_from_function
 
 try:
     # django.tasks were added in Django 6.0
-    from django.tasks.base import Task, TaskResultStatus
+    from django.tasks.base import Task
 except ImportError:
     Task = None
 
diff --git a/sentry_sdk/integrations/google_genai/streaming.py b/sentry_sdk/integrations/google_genai/streaming.py
index 8649ce2ac0..3405fe2b2a 100644
--- a/sentry_sdk/integrations/google_genai/streaming.py
+++ b/sentry_sdk/integrations/google_genai/streaming.py
@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, Any, List, TypedDict, Optional, Union
+from typing import TYPE_CHECKING, Any, List, TypedDict, Optional
 
 from sentry_sdk.ai.utils import set_data_normalized
 from sentry_sdk.consts import SPANDATA
diff --git a/sentry_sdk/integrations/google_genai/utils.py b/sentry_sdk/integrations/google_genai/utils.py
index b2d6499843..25763ebe07 100644
--- a/sentry_sdk/integrations/google_genai/utils.py
+++ b/sentry_sdk/integrations/google_genai/utils.py
@@ -5,7 +5,6 @@
 from .consts import ORIGIN, TOOL_ATTRIBUTES_MAP, GEN_AI_SYSTEM
 from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
 from typing import (
-    cast,
     TYPE_CHECKING,
     Iterable,
     Any,
@@ -22,7 +21,6 @@
     set_data_normalized,
     truncate_and_annotate_messages,
     normalize_message_roles,
-    redact_blob_message_parts,
     transform_google_content_part,
     get_modality_from_mime_type,
 )
@@ -33,7 +31,7 @@
     event_from_exception,
     safe_serialize,
 )
-from google.genai.types import GenerateContentConfig, Part, Content
+from google.genai.types import GenerateContentConfig, Part, Content, PartDict
 from itertools import chain
 
 if TYPE_CHECKING:
@@ -49,6 +47,18 @@
         ContentUnion,
     )
 
+_is_PIL_available = False
+try:
+    from PIL import Image as PILImage  # type: ignore[import-not-found]
+
+    _is_PIL_available = True
+except ImportError:
+    pass
+
+# Keys to use when checking to see if a dict provided by the user
+# is Part-like (as opposed to a Content or multi-turn conversation entry).
+_PART_DICT_KEYS = PartDict.__optional_keys__
+
 
 class UsageData(TypedDict):
     """Structure for token usage data."""
@@ -171,12 +181,23 @@ def extract_contents_messages(contents: "ContentListUnion") -> "List[Dict[str, A
     if isinstance(contents, str):
         return [{"role": "user", "content": contents}]
 
-    # Handle list case - process each item (non-recursive, flatten at top level)
+    # Handle list case
     if isinstance(contents, list):
-        for item in contents:
-            item_messages = extract_contents_messages(item)
-            messages.extend(item_messages)
-        return messages
+        if contents and all(_is_part_like(item) for item in contents):
+            # All items are parts — merge into a single multi-part user message
+            content_parts = []
+            for item in contents:
+                part = _extract_part_from_item(item)
+                if part is not None:
+                    content_parts.append(part)
+
+            return [{"role": "user", "content": content_parts}]
+        else:
+            # Multi-turn conversation or mixed content types
+            for item in contents:
+                item_messages = extract_contents_messages(item)
+                messages.extend(item_messages)
+            return messages
 
     # Handle dictionary case (ContentDict)
     if isinstance(contents, dict):
@@ -208,13 +229,23 @@ def extract_contents_messages(contents: "ContentListUnion") -> "List[Dict[str, A
             # Add tool messages
             messages.extend(tool_messages)
         elif "text" in contents:
-            # Simple text in dict
             messages.append(
                 {
-                    "role": role or "user",
+                    "role": role,
                     "content": [{"text": contents["text"], "type": "text"}],
                 }
             )
+        elif "inline_data" in contents:
+            # The "data" will always be bytes (or bytes within a string),
+            # so if this is present, it's safe to automatically substitute with the placeholder
+            messages.append(
+                {
+                    "inline_data": {
+                        "mime_type": contents["inline_data"].get("mime_type", ""),
+                        "data": BLOB_DATA_SUBSTITUTE,
+                    }
+                }
+            )
 
         return messages
 
@@ -250,15 +281,10 @@ def extract_contents_messages(contents: "ContentListUnion") -> "List[Dict[str, A
             return [{"role": "user", "content": [part_result]}]
 
     # Handle PIL.Image.Image
-    try:
-        from PIL import Image as PILImage  # type: ignore[import-not-found]
-
-        if isinstance(contents, PILImage.Image):
-            blob_part = _extract_pil_image(contents)
-            if blob_part:
-                return [{"role": "user", "content": [blob_part]}]
-    except ImportError:
-        pass
+    if _is_PIL_available and isinstance(contents, PILImage.Image):
+        blob_part = _extract_pil_image(contents)
+        if blob_part:
+            return [{"role": "user", "content": [blob_part]}]
 
     # Handle File object
     if hasattr(contents, "uri") and hasattr(contents, "mime_type"):
@@ -312,11 +338,9 @@ def _extract_part_content(part: "Any") -> "Optional[dict[str, Any]]":
         if result is not None:
             # For inline_data with bytes data, substitute the content
             if "inline_data" in part:
-                inline_data = part["inline_data"]
-                if isinstance(inline_data, dict) and isinstance(
-                    inline_data.get("data"), bytes
-                ):
-                    result["content"] = BLOB_DATA_SUBSTITUTE
+                # inline_data.data will always be bytes, or a string containing base64-encoded bytes,
+                # so can automatically substitute without further checks
+                result["content"] = BLOB_DATA_SUBSTITUTE
             return result
 
         return None
@@ -359,18 +383,11 @@ def _extract_part_content(part: "Any") -> "Optional[dict[str, Any]]":
             if mime_type is None:
                 mime_type = ""
 
-            # Handle both bytes (binary data) and str (base64-encoded data)
-            if isinstance(data, bytes):
-                content = BLOB_DATA_SUBSTITUTE
-            else:
-                # For non-bytes data (e.g., base64 strings), use as-is
-                content = data
-
             return {
                 "type": "blob",
                 "modality": get_modality_from_mime_type(mime_type),
                 "mime_type": mime_type,
-                "content": content,
+                "content": BLOB_DATA_SUBSTITUTE,
             }
 
     return None
@@ -431,25 +448,78 @@ def _extract_tool_message_from_part(part: "Any") -> "Optional[dict[str, Any]]":
 
 def _extract_pil_image(image: "Any") -> "Optional[dict[str, Any]]":
     """Extract blob part from PIL.Image.Image."""
-    try:
-        from PIL import Image as PILImage
+    if not _is_PIL_available or not isinstance(image, PILImage.Image):
+        return None
+
+    # Get format, default to JPEG
+    format_str = image.format or "JPEG"
+    suffix = format_str.lower()
+    mime_type = f"image/{suffix}"
 
-        if not isinstance(image, PILImage.Image):
-            return None
+    return {
+        "type": "blob",
+        "modality": get_modality_from_mime_type(mime_type),
+        "mime_type": mime_type,
+        "content": BLOB_DATA_SUBSTITUTE,
+    }
 
-        # Get format, default to JPEG
-        format_str = image.format or "JPEG"
-        suffix = format_str.lower()
-        mime_type = f"image/{suffix}"
 
+def _is_part_like(item: "Any") -> bool:
+    """Check if item is a part-like value (PartUnionDict) rather than a Content/multi-turn entry."""
+    if isinstance(item, (str, Part)):
+        return True
+    if isinstance(item, (list, Content)):
+        return False
+    if isinstance(item, dict):
+        if "role" in item or "parts" in item:
+            return False
+        # Part objects that came in as plain dicts
+        return bool(_PART_DICT_KEYS & item.keys())
+    # File objects
+    if hasattr(item, "uri"):
+        return True
+    # PIL.Image
+    if _is_PIL_available and isinstance(item, PILImage.Image):
+        return True
+    return False
+
+
+def _extract_part_from_item(item: "Any") -> "Optional[dict[str, Any]]":
+    """Convert a single part-like item to a content part dict."""
+    if isinstance(item, str):
+        return {"text": item, "type": "text"}
+
+    # Handle bare inline_data dicts directly to preserve the raw format
+    if isinstance(item, dict) and "inline_data" in item:
         return {
-            "type": "blob",
-            "modality": get_modality_from_mime_type(mime_type),
-            "mime_type": mime_type,
-            "content": BLOB_DATA_SUBSTITUTE,
+            "inline_data": {
+                "mime_type": item["inline_data"].get("mime_type", ""),
+                "data": BLOB_DATA_SUBSTITUTE,
+            }
         }
-    except Exception:
-        return None
+
+    # For other dicts and Part objects, use existing _extract_part_content
+    result = _extract_part_content(item)
+    if result is not None:
+        return result
+
+    # PIL.Image
+    if _is_PIL_available and isinstance(item, PILImage.Image):
+        return _extract_pil_image(item)
+
+    # File objects
+    if hasattr(item, "uri") and hasattr(item, "mime_type"):
+        file_uri = getattr(item, "uri", None)
+        mime_type = getattr(item, "mime_type", None) or ""
+        if file_uri is not None:
+            return {
+                "type": "uri",
+                "modality": get_modality_from_mime_type(mime_type),
+                "mime_type": mime_type,
+                "uri": file_uri,
+            }
+
+    return None
 
 
 def extract_contents_text(contents: "ContentListUnion") -> "Optional[str]":
@@ -599,7 +669,6 @@ def _create_tool_span(tool_name: str, tool_doc: "Optional[str]") -> "Span":
         origin=ORIGIN,
     )
     span.set_data(SPANDATA.GEN_AI_TOOL_NAME, tool_name)
-    span.set_data(SPANDATA.GEN_AI_TOOL_TYPE, "function")
     if tool_doc:
         span.set_data(SPANDATA.GEN_AI_TOOL_DESCRIPTION, tool_doc)
     return span
@@ -698,6 +767,9 @@ def _extract_response_text(
         if not hasattr(candidate, "content") or not hasattr(candidate.content, "parts"):
             continue
 
+        if candidate.content is None or candidate.content.parts is None:
+            continue
+
         for part in candidate.content.parts:
             if getattr(part, "text", None):
                 texts.append(part.text)
diff --git a/sentry_sdk/integrations/graphene.py b/sentry_sdk/integrations/graphene.py
index 5a61ca5c78..c2df9e7907 100644
--- a/sentry_sdk/integrations/graphene.py
+++ b/sentry_sdk/integrations/graphene.py
@@ -141,17 +141,15 @@ def graphql_span(
         },
     )
 
-    scope = sentry_sdk.get_current_scope()
-    if scope.span:
-        _graphql_span = scope.span.start_child(op=op, name=operation_name)
-    else:
-        _graphql_span = sentry_sdk.start_span(op=op, name=operation_name)
+    _graphql_span = sentry_sdk.start_span(op=op, name=operation_name)
 
     _graphql_span.set_data("graphql.document", source)
     _graphql_span.set_data("graphql.operation.name", operation_name)
     _graphql_span.set_data("graphql.operation.type", operation_type)
 
+    _graphql_span.__enter__()
+
     try:
         yield
     finally:
-        _graphql_span.finish()
+        _graphql_span.__exit__(None, None, None)
diff --git a/sentry_sdk/integrations/grpc/aio/server.py b/sentry_sdk/integrations/grpc/aio/server.py
index 3ed15c2de6..084c76ecc0 100644
--- a/sentry_sdk/integrations/grpc/aio/server.py
+++ b/sentry_sdk/integrations/grpc/aio/server.py
@@ -2,7 +2,7 @@
 from sentry_sdk.consts import OP
 from sentry_sdk.integrations import DidNotEnable
 from sentry_sdk.integrations.grpc.consts import SPAN_ORIGIN
-from sentry_sdk.tracing import Transaction, TransactionSource
+from sentry_sdk.tracing import TransactionSource
 from sentry_sdk.utils import event_from_exception
 
 from typing import TYPE_CHECKING
@@ -43,31 +43,32 @@ async def intercept_service(
             handler_factory = grpc.unary_unary_rpc_method_handler
 
             async def wrapped(request: "Any", context: "ServicerContext") -> "Any":
-                name = self._find_method_name(context)
-                if not name:
-                    return await handler(request, context)
-
-                # What if the headers are empty?
-                transaction = sentry_sdk.continue_trace(
-                    dict(context.invocation_metadata()),
-                    op=OP.GRPC_SERVER,
-                    name=name,
-                    source=TransactionSource.CUSTOM,
-                    origin=SPAN_ORIGIN,
-                )
-
-                with sentry_sdk.start_transaction(transaction=transaction):
-                    try:
-                        return await handler.unary_unary(request, context)
-                    except AbortError:
-                        raise
-                    except Exception as exc:
-                        event, hint = event_from_exception(
-                            exc,
-                            mechanism={"type": "grpc", "handled": False},
-                        )
-                        sentry_sdk.capture_event(event, hint=hint)
-                        raise
+                with sentry_sdk.isolation_scope():
+                    name = self._find_method_name(context)
+                    if not name:
+                        return await handler(request, context)
+
+                    # What if the headers are empty?
+                    transaction = sentry_sdk.continue_trace(
+                        dict(context.invocation_metadata()),
+                        op=OP.GRPC_SERVER,
+                        name=name,
+                        source=TransactionSource.CUSTOM,
+                        origin=SPAN_ORIGIN,
+                    )
+
+                    with sentry_sdk.start_transaction(transaction=transaction):
+                        try:
+                            return await handler.unary_unary(request, context)
+                        except AbortError:
+                            raise
+                        except Exception as exc:
+                            event, hint = event_from_exception(
+                                exc,
+                                mechanism={"type": "grpc", "handled": False},
+                            )
+                            sentry_sdk.capture_event(event, hint=hint)
+                            raise
 
         elif not handler.request_streaming and handler.response_streaming:
             handler_factory = grpc.unary_stream_rpc_method_handler
diff --git a/sentry_sdk/integrations/grpc/server.py b/sentry_sdk/integrations/grpc/server.py
index 7c06fd405a..af01f37fb2 100644
--- a/sentry_sdk/integrations/grpc/server.py
+++ b/sentry_sdk/integrations/grpc/server.py
@@ -2,7 +2,7 @@
 from sentry_sdk.consts import OP
 from sentry_sdk.integrations import DidNotEnable
 from sentry_sdk.integrations.grpc.consts import SPAN_ORIGIN
-from sentry_sdk.tracing import Transaction, TransactionSource
+from sentry_sdk.tracing import TransactionSource
 
 from typing import TYPE_CHECKING
 
diff --git a/sentry_sdk/integrations/httpx.py b/sentry_sdk/integrations/httpx.py
index 64fd8371e5..9e3de63ed1 100644
--- a/sentry_sdk/integrations/httpx.py
+++ b/sentry_sdk/integrations/httpx.py
@@ -23,7 +23,7 @@
 
 
 try:
-    from httpx import AsyncClient, Client, Request, Response  # type: ignore
+    from httpx import AsyncClient, Client, Request, Response
 except ImportError:
     raise DidNotEnable("httpx is not installed")
 
@@ -94,7 +94,7 @@ def send(self: "Client", request: "Request", **kwargs: "Any") -> "Response":
 
         return rv
 
-    Client.send = send
+    Client.send = send  # type: ignore
 
 
 def _install_httpx_async_client() -> None:
@@ -150,4 +150,4 @@ async def send(
 
         return rv
 
-    AsyncClient.send = send
+    AsyncClient.send = send  # type: ignore
diff --git a/sentry_sdk/integrations/huggingface_hub.py b/sentry_sdk/integrations/huggingface_hub.py
index 8509cadefa..d628ccf546 100644
--- a/sentry_sdk/integrations/huggingface_hub.py
+++ b/sentry_sdk/integrations/huggingface_hub.py
@@ -1,6 +1,7 @@
-import sys
 import inspect
+import sys
 from functools import wraps
+from typing import TYPE_CHECKING
 
 import sentry_sdk
 from sentry_sdk.ai.monitoring import record_token_usage
@@ -8,15 +9,12 @@
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations import DidNotEnable, Integration
 from sentry_sdk.scope import should_send_default_pii
-from sentry_sdk.tracing_utils import set_span_errored
 from sentry_sdk.utils import (
     capture_internal_exceptions,
     event_from_exception,
     reraise,
 )
 
-from typing import TYPE_CHECKING
-
 if TYPE_CHECKING:
     from typing import Any, Callable, Iterable
 
@@ -41,7 +39,7 @@ def setup_once() -> None:
         huggingface_hub.inference._client.InferenceClient.text_generation = (
             _wrap_huggingface_task(
                 huggingface_hub.inference._client.InferenceClient.text_generation,
-                OP.GEN_AI_GENERATE_TEXT,
+                OP.GEN_AI_TEXT_COMPLETION,
             )
         )
         huggingface_hub.inference._client.InferenceClient.chat_completion = (
@@ -53,8 +51,6 @@ def setup_once() -> None:
 
 
 def _capture_exception(exc: "Any") -> None:
-    set_span_errored()
-
     event, hint = event_from_exception(
         exc,
         client_options=sentry_sdk.get_client().options,
@@ -131,7 +127,7 @@ def new_huggingface_task(*args: "Any", **kwargs: "Any") -> "Any":
             exc_info = sys.exc_info()
             with capture_internal_exceptions():
                 _capture_exception(e)
-                span.__exit__(None, None, None)
+                span.__exit__(*exc_info)
             reraise(*exc_info)
 
         # Output attributes
diff --git a/sentry_sdk/integrations/langchain.py b/sentry_sdk/integrations/langchain.py
index 7a5e863e4d..49fa04c034 100644
--- a/sentry_sdk/integrations/langchain.py
+++ b/sentry_sdk/integrations/langchain.py
@@ -108,6 +108,15 @@
     OllamaEmbeddings = None
 
 
+def _get_ai_system(all_params: "Dict[str, Any]") -> "Optional[str]":
+    ai_type = all_params.get("_type")
+
+    if not ai_type or not isinstance(ai_type, str):
+        return None
+
+    return ai_type
+
+
 DATA_FIELDS = {
     "frequency_penalty": SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY,
     "function_call": SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS,
@@ -351,7 +360,6 @@ def on_llm_start(
         metadata: "Optional[Dict[str, Any]]" = None,
         **kwargs: "Any",
     ) -> "Any":
-        """Run when LLM starts running."""
         with capture_internal_exceptions():
             if not run_id:
                 return
@@ -369,23 +377,27 @@ def on_llm_start(
             watched_span = self._create_span(
                 run_id,
                 parent_run_id,
-                op=OP.GEN_AI_PIPELINE,
-                name=kwargs.get("name") or "Langchain LLM call",
+                op=OP.GEN_AI_TEXT_COMPLETION,
+                name=f"text_completion {model}".strip(),
                 origin=LangchainIntegration.origin,
             )
             span = watched_span.span
 
+            span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "text_completion")
+
+            pipeline_name = kwargs.get("name")
+            if pipeline_name:
+                span.set_data(SPANDATA.GEN_AI_PIPELINE_NAME, pipeline_name)
+
             if model:
                 span.set_data(
                     SPANDATA.GEN_AI_REQUEST_MODEL,
                     model,
                 )
 
-            ai_type = all_params.get("_type", "")
-            if "anthropic" in ai_type:
-                span.set_data(SPANDATA.GEN_AI_SYSTEM, "anthropic")
-            elif "openai" in ai_type:
-                span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")
+            ai_system = _get_ai_system(all_params)
+            if ai_system:
+                span.set_data(SPANDATA.GEN_AI_SYSTEM, ai_system)
 
             for key, attribute in DATA_FIELDS.items():
                 if key in all_params and all_params[key] is not None:
@@ -449,11 +461,9 @@ def on_chat_model_start(
             if model:
                 span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model)
 
-            ai_type = all_params.get("_type", "")
-            if "anthropic" in ai_type:
-                span.set_data(SPANDATA.GEN_AI_SYSTEM, "anthropic")
-            elif "openai" in ai_type:
-                span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")
+            ai_system = _get_ai_system(all_params)
+            if ai_system:
+                span.set_data(SPANDATA.GEN_AI_SYSTEM, ai_system)
 
             agent_name = _get_current_agent()
             if agent_name:
@@ -554,7 +564,8 @@ def on_llm_end(
                     finish_reason = generation.generation_info.get("finish_reason")
                     if finish_reason is not None:
                         span.set_data(
-                            SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS, finish_reason
+                            SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS,
+                            [finish_reason],
                         )
                 except AttributeError:
                     pass
diff --git a/sentry_sdk/integrations/litellm.py b/sentry_sdk/integrations/litellm.py
index 28bcc34d3e..3cff0fbc23 100644
--- a/sentry_sdk/integrations/litellm.py
+++ b/sentry_sdk/integrations/litellm.py
@@ -82,7 +82,7 @@ def _input_callback(kwargs: "Dict[str, Any]") -> None:
         provider = "unknown"
 
     call_type = kwargs.get("call_type", None)
-    if call_type == "embedding":
+    if call_type == "embedding" or call_type == "aembedding":
         operation = "embeddings"
     else:
         operation = "chat"
@@ -159,15 +159,9 @@ def _input_callback(kwargs: "Dict[str, Any]") -> None:
         if value is not None:
             set_data_normalized(span, attribute, value)
 
-    # Record LiteLLM-specific parameters
-    litellm_params = {
-        "api_base": kwargs.get("api_base"),
-        "api_version": kwargs.get("api_version"),
-        "custom_llm_provider": kwargs.get("custom_llm_provider"),
-    }
-    for key, value in litellm_params.items():
-        if value is not None:
-            set_data_normalized(span, f"gen_ai.litellm.{key}", value)
+
+async def _async_input_callback(kwargs: "Dict[str, Any]") -> None:
+    return _input_callback(kwargs)
 
 
 def _success_callback(
@@ -178,7 +172,8 @@ def _success_callback(
 ) -> None:
     """Handle successful completion."""
 
-    span = _get_metadata_dict(kwargs).get("_sentry_span")
+    metadata = _get_metadata_dict(kwargs)
+    span = metadata.get("_sentry_span")
     if span is None:
         return
 
@@ -230,8 +225,31 @@ def _success_callback(
             )
 
     finally:
-        # Always finish the span and clean up
-        span.__exit__(None, None, None)
+        is_streaming = kwargs.get("stream")
+        # Callback is fired multiple times when streaming a response.
+        # Streaming flag checked at https://github.com/BerriAI/litellm/blob/33c3f13443eaf990ac8c6e3da78bddbc2b7d0e7a/litellm/litellm_core_utils/litellm_logging.py#L1603
+        if (
+            is_streaming is not True
+            or "complete_streaming_response" in kwargs
+            or "async_complete_streaming_response" in kwargs
+        ):
+            span = metadata.pop("_sentry_span", None)
+            if span is not None:
+                span.__exit__(None, None, None)
+
+
+async def _async_success_callback(
+    kwargs: "Dict[str, Any]",
+    completion_response: "Any",
+    start_time: "datetime",
+    end_time: "datetime",
+) -> None:
+    return _success_callback(
+        kwargs,
+        completion_response,
+        start_time,
+        end_time,
+    )
 
 
 def _failure_callback(
@@ -315,10 +333,14 @@ def setup_once() -> None:
         litellm.input_callback = input_callback or []
         if _input_callback not in litellm.input_callback:
             litellm.input_callback.append(_input_callback)
+        if _async_input_callback not in litellm.input_callback:
+            litellm.input_callback.append(_async_input_callback)
 
         litellm.success_callback = success_callback or []
         if _success_callback not in litellm.success_callback:
             litellm.success_callback.append(_success_callback)
+        if _async_success_callback not in litellm.success_callback:
+            litellm.success_callback.append(_async_success_callback)
 
         litellm.failure_callback = failure_callback or []
         if _failure_callback not in litellm.failure_callback:
diff --git a/sentry_sdk/integrations/logging.py b/sentry_sdk/integrations/logging.py
index 42029c5a7a..ca13afc1e9 100644
--- a/sentry_sdk/integrations/logging.py
+++ b/sentry_sdk/integrations/logging.py
@@ -54,10 +54,18 @@
 #
 # Note: Ignoring by logger name here is better than mucking with thread-locals.
 # We do not necessarily know whether thread-locals work 100% correctly in the user's environment.
+#
+# Events/breadcrumbs and Sentry Logs have separate ignore lists so that
+# framework loggers silenced for events (e.g. django.server) can still be
+# captured as Sentry Logs.
 _IGNORED_LOGGERS = set(
     ["sentry_sdk.errors", "urllib3.connectionpool", "urllib3.connection"]
 )
 
+_IGNORED_LOGGERS_SENTRY_LOGS = set(
+    ["sentry_sdk.errors", "urllib3.connectionpool", "urllib3.connection"]
+)
+
 
 def ignore_logger(
     name: str,
@@ -67,11 +75,47 @@ def ignore_logger(
     use this to prevent their actions being recorded as breadcrumbs. Exposed
     to users as a way to quiet spammy loggers.
 
+    This does **not** affect Sentry Logs — use
+    :py:func:`ignore_logger_for_sentry_logs` for that.
+
     :param name: The name of the logger to ignore (same string you would pass to ``logging.getLogger``).
     """
     _IGNORED_LOGGERS.add(name)
 
 
+def ignore_logger_for_sentry_logs(
+    name: str,
+) -> None:
+    """This disables recording as Sentry Logs calls to a logger of a
+    specific name.
+
+    :param name: The name of the logger to ignore (same string you would pass to ``logging.getLogger``).
+    """
+    _IGNORED_LOGGERS_SENTRY_LOGS.add(name)
+
+
+def unignore_logger(
+    name: str,
+) -> None:
+    """Reverts a previous :py:func:`ignore_logger` call, re-enabling
+    recording of breadcrumbs and events for the named logger.
+
+    :param name: The name of the logger to unignore.
+    """
+    _IGNORED_LOGGERS.discard(name)
+
+
+def unignore_logger_for_sentry_logs(
+    name: str,
+) -> None:
+    """Reverts a previous :py:func:`ignore_logger_for_sentry_logs` call,
+    re-enabling recording of Sentry Logs for the named logger.
+
+    :param name: The name of the logger to unignore.
+    """
+    _IGNORED_LOGGERS_SENTRY_LOGS.discard(name)
+
+
 class LoggingIntegration(Integration):
     identifier = "logging"
 
@@ -104,6 +148,7 @@ def _handle_record(self, record: "LogRecord") -> None:
         ):
             self._breadcrumb_handler.handle(record)
 
+    def _handle_sentry_logs_record(self, record: "LogRecord") -> None:
         if (
             self._sentry_logs_handler is not None
             and record.levelno >= self._sentry_logs_handler.level
@@ -118,6 +163,7 @@ def sentry_patched_callhandlers(self: "Any", record: "LogRecord") -> "Any":
             # keeping a local reference because the
             # global might be discarded on shutdown
             ignored_loggers = _IGNORED_LOGGERS
+            ignored_loggers_sentry_logs = _IGNORED_LOGGERS_SENTRY_LOGS
 
             try:
                 return old_callhandlers(self, record)
@@ -126,15 +172,25 @@ def sentry_patched_callhandlers(self: "Any", record: "LogRecord") -> "Any":
                 # the integration.  Otherwise we have a high chance of getting
                 # into a recursion error when the integration is resolved
                 # (this also is slower).
-                if (
-                    ignored_loggers is not None
-                    and record.name.strip() not in ignored_loggers
-                ):
+                name = record.name.strip()
+
+                handle_events = (
+                    ignored_loggers is not None and name not in ignored_loggers
+                )
+                handle_sentry_logs = (
+                    ignored_loggers_sentry_logs is not None
+                    and name not in ignored_loggers_sentry_logs
+                )
+
+                if handle_events or handle_sentry_logs:
                     integration = sentry_sdk.get_client().get_integration(
                         LoggingIntegration
                     )
                     if integration is not None:
-                        integration._handle_record(record)
+                        if handle_events:
+                            integration._handle_record(record)
+                        if handle_sentry_logs:
+                            integration._handle_sentry_logs_record(record)
 
         logging.Logger.callHandlers = sentry_patched_callhandlers  # type: ignore
 
@@ -170,13 +226,6 @@ class _BaseHandler(logging.Handler):
         )
     )
 
-    def _can_record(self, record: "LogRecord") -> bool:
-        """Prevents ignored loggers from recording"""
-        for logger in _IGNORED_LOGGERS:
-            if fnmatch(record.name.strip(), logger):
-                return False
-        return True
-
     def _logging_to_event_level(self, record: "LogRecord") -> str:
         return LOGGING_TO_EVENT_LEVEL.get(
             record.levelno, record.levelname.lower() if record.levelname else ""
@@ -198,6 +247,13 @@ class EventHandler(_BaseHandler):
     Note that you do not have to use this class if the logging integration is enabled, which it is by default.
     """
 
+    def _can_record(self, record: "LogRecord") -> bool:
+        """Prevents ignored loggers from recording"""
+        for logger in _IGNORED_LOGGERS:
+            if fnmatch(record.name.strip(), logger):
+                return False
+        return True
+
     def emit(self, record: "LogRecord") -> "Any":
         with capture_internal_exceptions():
             self.format(record)
@@ -290,6 +346,13 @@ class BreadcrumbHandler(_BaseHandler):
     Note that you do not have to use this class if the logging integration is enabled, which it is by default.
     """
 
+    def _can_record(self, record: "LogRecord") -> bool:
+        """Prevents ignored loggers from recording"""
+        for logger in _IGNORED_LOGGERS:
+            if fnmatch(record.name.strip(), logger):
+                return False
+        return True
+
     def emit(self, record: "LogRecord") -> "Any":
         with capture_internal_exceptions():
             self.format(record)
@@ -321,6 +384,13 @@ class SentryLogsHandler(_BaseHandler):
     Note that you do not have to use this class if the logging integration is enabled, which it is by default.
     """
 
+    def _can_record(self, record: "LogRecord") -> bool:
+        """Prevents ignored loggers from recording"""
+        for logger in _IGNORED_LOGGERS_SENTRY_LOGS:
+            if fnmatch(record.name.strip(), logger):
+                return False
+        return True
+
     def emit(self, record: "LogRecord") -> "Any":
         with capture_internal_exceptions():
             self.format(record)
diff --git a/sentry_sdk/integrations/openai.py b/sentry_sdk/integrations/openai.py
index b1995a6287..480db9132d 100644
--- a/sentry_sdk/integrations/openai.py
+++ b/sentry_sdk/integrations/openai.py
@@ -50,7 +50,13 @@
     from sentry_sdk.tracing import Span
     from sentry_sdk._types import TextPart
 
-    from openai.types.responses import ResponseInputParam, SequenceNotStr
+    from openai.types.responses.response_usage import ResponseUsage
+    from openai.types.responses import (
+        ResponseInputParam,
+        SequenceNotStr,
+        ResponseStreamEvent,
+    )
+    from openai.types import CompletionUsage
     from openai import Omit
 
 try:
@@ -67,11 +73,12 @@
     from openai.resources.chat.completions import Completions, AsyncCompletions
     from openai.resources import Embeddings, AsyncEmbeddings
 
+    from openai import Stream, AsyncStream
+
     if TYPE_CHECKING:
         from openai.types.chat import (
             ChatCompletionMessageParam,
             ChatCompletionChunk,
-            ChatCompletionSystemMessageParam,
         )
 except ImportError:
     raise DidNotEnable("OpenAI not installed")
@@ -142,44 +149,56 @@ def _capture_exception(exc: "Any", manual_span_cleanup: bool = True) -> None:
     sentry_sdk.capture_event(event, hint=hint)
 
 
-def _get_usage(usage: "Any", names: "List[str]") -> int:
-    for name in names:
-        if hasattr(usage, name) and isinstance(getattr(usage, name), int):
-            return getattr(usage, name)
-    return 0
+def _has_attr_and_is_int(
+    token_usage: "Union[CompletionUsage, ResponseUsage]", attr_name: str
+) -> bool:
+    return hasattr(token_usage, attr_name) and isinstance(
+        getattr(token_usage, attr_name, None), int
+    )
 
 
-def _calculate_token_usage(
+def _calculate_completions_token_usage(
     messages: "Optional[Iterable[ChatCompletionMessageParam]]",
     response: "Any",
     span: "Span",
     streaming_message_responses: "Optional[List[str]]",
+    streaming_message_total_token_usage: "Optional[CompletionUsage]",
     count_tokens: "Callable[..., Any]",
 ) -> None:
+    """Extract and record token usage from a Chat Completions API response."""
     input_tokens: "Optional[int]" = 0
     input_tokens_cached: "Optional[int]" = 0
     output_tokens: "Optional[int]" = 0
     output_tokens_reasoning: "Optional[int]" = 0
     total_tokens: "Optional[int]" = 0
-
-    if hasattr(response, "usage"):
-        input_tokens = _get_usage(response.usage, ["input_tokens", "prompt_tokens"])
-        if hasattr(response.usage, "input_tokens_details"):
-            input_tokens_cached = _get_usage(
-                response.usage.input_tokens_details, ["cached_tokens"]
-            )
-
-        output_tokens = _get_usage(
-            response.usage, ["output_tokens", "completion_tokens"]
-        )
-        if hasattr(response.usage, "output_tokens_details"):
-            output_tokens_reasoning = _get_usage(
-                response.usage.output_tokens_details, ["reasoning_tokens"]
+    usage = None
+
+    if streaming_message_total_token_usage is not None:
+        usage = streaming_message_total_token_usage
+    elif hasattr(response, "usage"):
+        usage = response.usage
+
+    if usage is not None:
+        if _has_attr_and_is_int(usage, "prompt_tokens"):
+            input_tokens = usage.prompt_tokens
+        if _has_attr_and_is_int(usage, "completion_tokens"):
+            output_tokens = usage.completion_tokens
+        if _has_attr_and_is_int(usage, "total_tokens"):
+            total_tokens = usage.total_tokens
+
+        if hasattr(usage, "prompt_tokens_details"):
+            cached = getattr(usage.prompt_tokens_details, "cached_tokens", None)
+            if isinstance(cached, int):
+                input_tokens_cached = cached
+
+        if hasattr(usage, "completion_tokens_details"):
+            reasoning = getattr(
+                usage.completion_tokens_details, "reasoning_tokens", None
             )
+            if isinstance(reasoning, int):
+                output_tokens_reasoning = reasoning
 
-        total_tokens = _get_usage(response.usage, ["total_tokens"])
-
-    # Manually count tokens
+    # Manually count input tokens
     if input_tokens == 0:
         for message in messages or []:
             if isinstance(message, str):
@@ -189,11 +208,11 @@ def _calculate_token_usage(
                 message_content = message.get("content")
                 if message_content is None:
                     continue
-                # Deliberate use of Completions function for both Completions and Responses input format.
                 text_items = _get_text_items(message_content)
                 input_tokens += sum(count_tokens(text) for text in text_items)
                 continue
 
+    # Manually count output tokens
     if output_tokens == 0:
         if streaming_message_responses is not None:
             for message in streaming_message_responses:
@@ -220,35 +239,82 @@ def _calculate_token_usage(
     )
 
 
-def _commmon_set_input_data(
+def _calculate_responses_token_usage(
+    input: "Any",
+    response: "Any",
     span: "Span",
-    kwargs: "dict[str, Any]",
+    streaming_message_responses: "Optional[List[str]]",
+    count_tokens: "Callable[..., Any]",
 ) -> None:
-    # Input attributes: Common
-    set_data_normalized(span, SPANDATA.GEN_AI_SYSTEM, "openai")
-
-    # Input attributes: Optional
-    kwargs_keys_to_attributes = {
-        "model": SPANDATA.GEN_AI_REQUEST_MODEL,
-        "stream": SPANDATA.GEN_AI_RESPONSE_STREAMING,
-        "max_tokens": SPANDATA.GEN_AI_REQUEST_MAX_TOKENS,
-        "presence_penalty": SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY,
-        "frequency_penalty": SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY,
-        "temperature": SPANDATA.GEN_AI_REQUEST_TEMPERATURE,
-        "top_p": SPANDATA.GEN_AI_REQUEST_TOP_P,
-    }
-    for key, attribute in kwargs_keys_to_attributes.items():
-        value = kwargs.get(key)
-
-        if value is not None and _is_given(value):
-            set_data_normalized(span, attribute, value)
-
-    # Input attributes: Tools
-    tools = kwargs.get("tools")
-    if tools is not None and _is_given(tools) and len(tools) > 0:
-        set_data_normalized(
-            span, SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools)
-        )
+    """Extract and record token usage from a Responses API response."""
+    input_tokens: "Optional[int]" = 0
+    input_tokens_cached: "Optional[int]" = 0
+    output_tokens: "Optional[int]" = 0
+    output_tokens_reasoning: "Optional[int]" = 0
+    total_tokens: "Optional[int]" = 0
+
+    if hasattr(response, "usage"):
+        usage = response.usage
+
+        if _has_attr_and_is_int(usage, "input_tokens"):
+            input_tokens = usage.input_tokens
+        if _has_attr_and_is_int(usage, "output_tokens"):
+            output_tokens = usage.output_tokens
+        if _has_attr_and_is_int(usage, "total_tokens"):
+            total_tokens = usage.total_tokens
+
+        if hasattr(usage, "input_tokens_details"):
+            cached = getattr(usage.input_tokens_details, "cached_tokens", None)
+            if isinstance(cached, int):
+                input_tokens_cached = cached
+
+        if hasattr(usage, "output_tokens_details"):
+            reasoning = getattr(usage.output_tokens_details, "reasoning_tokens", None)
+            if isinstance(reasoning, int):
+                output_tokens_reasoning = reasoning
+
+    # Manually count input tokens
+    if input_tokens == 0:
+        for message in input or []:
+            if isinstance(message, str):
+                input_tokens += count_tokens(message)
+                continue
+            elif isinstance(message, dict):
+                message_content = message.get("content")
+                if message_content is None:
+                    continue
+                # Deliberate use of Completions function for both Completions and Responses input format.
+                text_items = _get_text_items(message_content)
+                input_tokens += sum(count_tokens(text) for text in text_items)
+                continue
+
+    # Manually count output tokens
+    if output_tokens == 0:
+        if streaming_message_responses is not None:
+            for message in streaming_message_responses:
+                output_tokens += count_tokens(message)
+        elif hasattr(response, "output"):
+            for output_item in response.output:
+                if hasattr(output_item, "content"):
+                    for content_item in output_item.content:
+                        if hasattr(content_item, "text"):
+                            output_tokens += count_tokens(content_item.text)
+
+    # Do not set token data if it is 0
+    input_tokens = input_tokens or None
+    input_tokens_cached = input_tokens_cached or None
+    output_tokens = output_tokens or None
+    output_tokens_reasoning = output_tokens_reasoning or None
+    total_tokens = total_tokens or None
+
+    record_token_usage(
+        span,
+        input_tokens=input_tokens,
+        input_tokens_cached=input_tokens_cached,
+        output_tokens=output_tokens,
+        output_tokens_reasoning=output_tokens_reasoning,
+        total_tokens=total_tokens,
+    )
 
 
 def _set_responses_api_input_data(
@@ -259,9 +325,30 @@ def _set_responses_api_input_data(
     explicit_instructions: "Union[Optional[str], Omit]" = kwargs.get("instructions")
     messages: "Optional[Union[str, ResponseInputParam]]" = kwargs.get("input")
 
+    tools = kwargs.get("tools")
+    if tools is not None and _is_given(tools) and len(tools) > 0:
+        set_data_normalized(
+            span, SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools)
+        )
+
+    model = kwargs.get("model")
+    if model is not None:
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model)
+
+    max_tokens = kwargs.get("max_output_tokens")
+    if max_tokens is not None and _is_given(max_tokens):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MAX_TOKENS, max_tokens)
+
+    temperature = kwargs.get("temperature")
+    if temperature is not None and _is_given(temperature):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TEMPERATURE, temperature)
+
+    top_p = kwargs.get("top_p")
+    if top_p is not None and _is_given(top_p):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TOP_P, top_p)
+
     if not should_send_default_pii() or not integration.include_prompts:
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "responses")
-        _commmon_set_input_data(span, kwargs)
         return
 
     if (
@@ -282,12 +369,10 @@ def _set_responses_api_input_data(
         )
 
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "responses")
-        _commmon_set_input_data(span, kwargs)
         return
 
     if messages is None:
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "responses")
-        _commmon_set_input_data(span, kwargs)
         return
 
     instructions_text_parts: "list[TextPart]" = []
@@ -320,7 +405,6 @@ def _set_responses_api_input_data(
             )
 
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "responses")
-        _commmon_set_input_data(span, kwargs)
         return
 
     non_system_messages = [
@@ -336,7 +420,6 @@ def _set_responses_api_input_data(
             )
 
     set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "responses")
-    _commmon_set_input_data(span, kwargs)
 
 
 def _set_completions_api_input_data(
@@ -348,13 +431,42 @@ def _set_completions_api_input_data(
         "messages"
     )
 
+    tools = kwargs.get("tools")
+    if tools is not None and _is_given(tools) and len(tools) > 0:
+        set_data_normalized(
+            span, SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools)
+        )
+
+    model = kwargs.get("model")
+    if model is not None:
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model)
+
+    max_tokens = kwargs.get("max_tokens")
+    if max_tokens is not None and _is_given(max_tokens):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MAX_TOKENS, max_tokens)
+
+    presence_penalty = kwargs.get("presence_penalty")
+    if presence_penalty is not None and _is_given(presence_penalty):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY, presence_penalty)
+
+    frequency_penalty = kwargs.get("frequency_penalty")
+    if frequency_penalty is not None and _is_given(frequency_penalty):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY, frequency_penalty)
+
+    temperature = kwargs.get("temperature")
+    if temperature is not None and _is_given(temperature):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TEMPERATURE, temperature)
+
+    top_p = kwargs.get("top_p")
+    if top_p is not None and _is_given(top_p):
+        span.set_data(SPANDATA.GEN_AI_REQUEST_TOP_P, top_p)
+
     if (
         not should_send_default_pii()
         or not integration.include_prompts
         or messages is None
     ):
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "chat")
-        _commmon_set_input_data(span, kwargs)
         return
 
     if isinstance(messages, str):
@@ -366,13 +478,11 @@ def _set_completions_api_input_data(
                 span, SPANDATA.GEN_AI_REQUEST_MESSAGES, messages_data, unpack=False
             )
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "chat")
-        _commmon_set_input_data(span, kwargs)
         return
 
     # dict special case following https://github.com/openai/openai-python/blob/3e0c05b84a2056870abf3bd6a5e7849020209cc3/src/openai/_utils/_transform.py#L194-L197
     if not isinstance(messages, Iterable) or isinstance(messages, dict):
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "chat")
-        _commmon_set_input_data(span, kwargs)
         return
 
     messages = list(messages)
@@ -400,7 +510,6 @@ def _set_completions_api_input_data(
             )
 
     set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "chat")
-    _commmon_set_input_data(span, kwargs)
 
 
 def _set_embeddings_input_data(
@@ -412,19 +521,21 @@ def _set_embeddings_input_data(
         "input"
     )
 
+    model = kwargs.get("model")
+    if model is not None:
+        span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model)
+
     if (
         not should_send_default_pii()
         or not integration.include_prompts
         or messages is None
     ):
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "embeddings")
-        _commmon_set_input_data(span, kwargs)
 
         return
 
     if isinstance(messages, str):
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "embeddings")
-        _commmon_set_input_data(span, kwargs)
 
         normalized_messages = normalize_message_roles([messages])  # type: ignore
         scope = sentry_sdk.get_current_scope()
@@ -441,7 +552,6 @@ def _set_embeddings_input_data(
     # dict special case following https://github.com/openai/openai-python/blob/3e0c05b84a2056870abf3bd6a5e7849020209cc3/src/openai/_utils/_transform.py#L194-L197
     if not isinstance(messages, Iterable) or isinstance(messages, dict):
         set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "embeddings")
-        _commmon_set_input_data(span, kwargs)
         return
 
     messages = list(messages)
@@ -459,7 +569,6 @@ def _set_embeddings_input_data(
             )
 
     set_data_normalized(span, SPANDATA.GEN_AI_OPERATION_NAME, "embeddings")
-    _commmon_set_input_data(span, kwargs)
 
 
 def _set_common_output_data(
@@ -472,6 +581,7 @@ def _set_common_output_data(
     if hasattr(response, "model"):
         set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_MODEL, response.model)
 
+    # Chat Completions API
     if hasattr(response, "choices"):
         if should_send_default_pii() and integration.include_prompts:
             response_text = [
@@ -482,11 +592,19 @@ def _set_common_output_data(
             if len(response_text) > 0:
                 set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, response_text)
 
-        _calculate_token_usage(input, response, span, None, integration.count_tokens)
+        _calculate_completions_token_usage(
+            messages=input,
+            response=response,
+            span=span,
+            streaming_message_responses=None,
+            streaming_message_total_token_usage=None,
+            count_tokens=integration.count_tokens,
+        )
 
         if finish_span:
             span.__exit__(None, None, None)
 
+    # Responses API
     elif hasattr(response, "output"):
         if should_send_default_pii() and integration.include_prompts:
             output_messages: "dict[str, list[Any]]" = {
@@ -518,12 +636,26 @@ def _set_common_output_data(
                     span, SPANDATA.GEN_AI_RESPONSE_TEXT, output_messages["response"]
                 )
 
-        _calculate_token_usage(input, response, span, None, integration.count_tokens)
+        _calculate_responses_token_usage(
+            input=input,
+            response=response,
+            span=span,
+            streaming_message_responses=None,
+            count_tokens=integration.count_tokens,
+        )
 
         if finish_span:
             span.__exit__(None, None, None)
+    # Embeddings API (fallback for responses with neither choices nor output)
     else:
-        _calculate_token_usage(input, response, span, None, integration.count_tokens)
+        _calculate_completions_token_usage(
+            messages=input,
+            response=response,
+            span=span,
+            streaming_message_responses=None,
+            streaming_message_total_token_usage=None,
+            count_tokens=integration.count_tokens,
+        )
         if finish_span:
             span.__exit__(None, None, None)
 
@@ -552,15 +684,49 @@ def _new_chat_completion_common(f: "Any", *args: "Any", **kwargs: "Any") -> "Any
     )
     span.__enter__()
 
+    span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")
+
+    # Same bool handling as in https://github.com/openai/openai-python/blob/acd0c54d8a68efeedde0e5b4e6c310eef1ce7867/src/openai/resources/completions.py#L585
+    is_streaming_response = kwargs.get("stream", False) or False
+    span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, is_streaming_response)
+
     _set_completions_api_input_data(span, kwargs, integration)
 
     start_time = time.perf_counter()
     response = yield f, args, kwargs
 
-    is_streaming_response = kwargs.get("stream", False)
-    if is_streaming_response:
-        _set_streaming_completions_api_output_data(
-            span, response, kwargs, integration, start_time, finish_span=True
+    # Attribute check to fail gracefully if the attribute is not present in future `openai` versions.
+    if isinstance(response, Stream) and hasattr(response, "_iterator"):
+        messages = kwargs.get("messages")
+
+        if messages is not None and isinstance(messages, str):
+            messages = [messages]
+
+        response._iterator = _wrap_synchronous_completions_chunk_iterator(
+            span=span,
+            integration=integration,
+            start_time=start_time,
+            messages=messages,
+            response=response,
+            old_iterator=response._iterator,
+            finish_span=True,
+        )
+
+    # Attribute check to fail gracefully if the attribute is not present in future `openai` versions.
+    elif isinstance(response, AsyncStream) and hasattr(response, "_iterator"):
+        messages = kwargs.get("messages")
+
+        if messages is not None and isinstance(messages, str):
+            messages = [messages]
+
+        response._iterator = _wrap_asynchronous_completions_chunk_iterator(
+            span=span,
+            integration=integration,
+            start_time=start_time,
+            messages=messages,
+            response=response,
+            old_iterator=response._iterator,
+            finish_span=True,
         )
     else:
         _set_completions_api_output_data(
@@ -591,116 +757,254 @@ def _set_completions_api_output_data(
     )
 
 
-def _set_streaming_completions_api_output_data(
+def _wrap_synchronous_completions_chunk_iterator(
     span: "Span",
-    response: "Any",
-    kwargs: "dict[str, Any]",
     integration: "OpenAIIntegration",
-    start_time: "Optional[float]" = None,
-    finish_span: bool = True,
-) -> None:
-    messages = kwargs.get("messages")
+    start_time: "Optional[float]",
+    messages: "Optional[Iterable[ChatCompletionMessageParam]]",
+    response: "Stream[ChatCompletionChunk]",
+    old_iterator: "Iterator[ChatCompletionChunk]",
+    finish_span: "bool",
+) -> "Iterator[ChatCompletionChunk]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Compute token count based on inputs and outputs using tiktoken if token counts are not in the model response.
+    Responsible for closing the AI Client Span if instructed to by the `finish_span` argument.
+    """
+    ttft = None
+    data_buf: "list[list[str]]" = []  # one for each choice
+    streaming_message_total_token_usage = None
 
-    if messages is not None and isinstance(messages, str):
-        messages = [messages]
+    for x in old_iterator:
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.model)
 
-    ttft: "Optional[float]" = None
+        with capture_internal_exceptions():
+            if hasattr(x, "choices"):
+                choice_index = 0
+                for choice in x.choices:
+                    if hasattr(choice, "delta") and hasattr(choice.delta, "content"):
+                        if start_time is not None and ttft is None:
+                            ttft = time.perf_counter() - start_time
+                        content = choice.delta.content
+                        if len(data_buf) <= choice_index:
+                            data_buf.append([])
+                        data_buf[choice_index].append(content or "")
+                    choice_index += 1
+            if hasattr(x, "usage"):
+                streaming_message_total_token_usage = x.usage
+
+        yield x
+
+    with capture_internal_exceptions():
+        if ttft is not None:
+            set_data_normalized(
+                span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
+            )
+        all_responses = None
+        if len(data_buf) > 0:
+            all_responses = ["".join(chunk) for chunk in data_buf]
+            if should_send_default_pii() and integration.include_prompts:
+                set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses)
+
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=all_responses,
+            streaming_message_total_token_usage=streaming_message_total_token_usage,
+            count_tokens=integration.count_tokens,
+        )
+
+    if finish_span:
+        span.__exit__(None, None, None)
+
+
+async def _wrap_asynchronous_completions_chunk_iterator(
+    span: "Span",
+    integration: "OpenAIIntegration",
+    start_time: "Optional[float]",
+    messages: "Optional[Iterable[ChatCompletionMessageParam]]",
+    response: "AsyncStream[ChatCompletionChunk]",
+    old_iterator: "AsyncIterator[ChatCompletionChunk]",
+    finish_span: "bool",
+) -> "AsyncIterator[ChatCompletionChunk]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Compute token count based on inputs and outputs using tiktoken if token counts are not in the model response.
+    Responsible for closing the AI Client Span if instructed to by the `finish_span` argument.
+    """
+    ttft = None
     data_buf: "list[list[str]]" = []  # one for each choice
+    streaming_message_total_token_usage = None
 
-    old_iterator = response._iterator
-
-    def new_iterator() -> "Iterator[ChatCompletionChunk]":
-        nonlocal ttft
-        for x in old_iterator:
-            span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.model)
-
-            with capture_internal_exceptions():
-                if hasattr(x, "choices"):
-                    choice_index = 0
-                    for choice in x.choices:
-                        if hasattr(choice, "delta") and hasattr(
-                            choice.delta, "content"
-                        ):
-                            if start_time is not None and ttft is None:
-                                ttft = time.perf_counter() - start_time
-                            content = choice.delta.content
-                            if len(data_buf) <= choice_index:
-                                data_buf.append([])
-                            data_buf[choice_index].append(content or "")
-                        choice_index += 1
-
-            yield x
+    async for x in old_iterator:
+        span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.model)
 
         with capture_internal_exceptions():
-            if ttft is not None:
-                set_data_normalized(
-                    span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
+            if hasattr(x, "choices"):
+                choice_index = 0
+                for choice in x.choices:
+                    if hasattr(choice, "delta") and hasattr(choice.delta, "content"):
+                        if start_time is not None and ttft is None:
+                            ttft = time.perf_counter() - start_time
+                        content = choice.delta.content
+                        if len(data_buf) <= choice_index:
+                            data_buf.append([])
+                        data_buf[choice_index].append(content or "")
+                    choice_index += 1
+            if hasattr(x, "usage"):
+                streaming_message_total_token_usage = x.usage
+
+        yield x
+
+    with capture_internal_exceptions():
+        if ttft is not None:
+            set_data_normalized(
+                span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
+            )
+        all_responses = None
+        if len(data_buf) > 0:
+            all_responses = ["".join(chunk) for chunk in data_buf]
+            if should_send_default_pii() and integration.include_prompts:
+                set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses)
+
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=all_responses,
+            streaming_message_total_token_usage=streaming_message_total_token_usage,
+            count_tokens=integration.count_tokens,
+        )
+
+    if finish_span:
+        span.__exit__(None, None, None)
+
+
+def _wrap_synchronous_responses_event_iterator(
+    span: "Span",
+    integration: "OpenAIIntegration",
+    start_time: "Optional[float]",
+    input: "Optional[Union[str, ResponseInputParam]]",
+    response: "Stream[ResponseStreamEvent]",
+    old_iterator: "Iterator[ResponseStreamEvent]",
+    finish_span: "bool",
+) -> "Iterator[ResponseStreamEvent]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Compute token count based on inputs and outputs using tiktoken if token counts are not in the model response.
+    Responsible for closing the AI Client Span if instructed to by the `finish_span` argument.
+    """
+    ttft = None
+    data_buf: "list[list[str]]" = []  # one for each choice
+
+    count_tokens_manually = True
+    for x in old_iterator:
+        with capture_internal_exceptions():
+            if hasattr(x, "delta"):
+                if start_time is not None and ttft is None:
+                    ttft = time.perf_counter() - start_time
+                if len(data_buf) == 0:
+                    data_buf.append([])
+                data_buf[0].append(x.delta or "")
+
+            if isinstance(x, ResponseCompletedEvent):
+                span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.response.model)
+
+                _calculate_responses_token_usage(
+                    input=input,
+                    response=x.response,
+                    span=span,
+                    streaming_message_responses=None,
+                    count_tokens=integration.count_tokens,
                 )
-            if len(data_buf) > 0:
-                all_responses = ["".join(chunk) for chunk in data_buf]
-                if should_send_default_pii() and integration.include_prompts:
-                    set_data_normalized(
-                        span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses
-                    )
-                _calculate_token_usage(
-                    messages,
-                    response,
-                    span,
-                    all_responses,
-                    integration.count_tokens,
+                count_tokens_manually = False
+
+        yield x
+
+    with capture_internal_exceptions():
+        if ttft is not None:
+            set_data_normalized(
+                span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
+            )
+        if len(data_buf) > 0:
+            all_responses = ["".join(chunk) for chunk in data_buf]
+            if should_send_default_pii() and integration.include_prompts:
+                set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses)
+
+            if count_tokens_manually:
+                _calculate_responses_token_usage(
+                    input=input,
+                    response=response,
+                    span=span,
+                    streaming_message_responses=all_responses,
+                    count_tokens=integration.count_tokens,
                 )
 
-        if finish_span:
-            span.__exit__(None, None, None)
+    if finish_span:
+        span.__exit__(None, None, None)
 
-    async def new_iterator_async() -> "AsyncIterator[ChatCompletionChunk]":
-        nonlocal ttft
-        async for x in old_iterator:
-            span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.model)
-
-            with capture_internal_exceptions():
-                if hasattr(x, "choices"):
-                    choice_index = 0
-                    for choice in x.choices:
-                        if hasattr(choice, "delta") and hasattr(
-                            choice.delta, "content"
-                        ):
-                            if start_time is not None and ttft is None:
-                                ttft = time.perf_counter() - start_time
-                            content = choice.delta.content
-                            if len(data_buf) <= choice_index:
-                                data_buf.append([])
-                            data_buf[choice_index].append(content or "")
-                        choice_index += 1
-
-            yield x
 
+async def _wrap_asynchronous_responses_event_iterator(
+    span: "Span",
+    integration: "OpenAIIntegration",
+    start_time: "Optional[float]",
+    input: "Optional[Union[str, ResponseInputParam]]",
+    response: "AsyncStream[ResponseStreamEvent]",
+    old_iterator: "AsyncIterator[ResponseStreamEvent]",
+    finish_span: "bool",
+) -> "AsyncIterator[ResponseStreamEvent]":
+    """
+    Sets information received while iterating the response stream on the AI Client Span.
+    Compute token count based on inputs and outputs using tiktoken if token counts are not in the model response.
+    Responsible for closing the AI Client Span if instructed to by the `finish_span` argument.
+    """
+    ttft: "Optional[float]" = None
+    data_buf: "list[list[str]]" = []  # one for each choice
+
+    count_tokens_manually = True
+    async for x in old_iterator:
         with capture_internal_exceptions():
-            if ttft is not None:
-                set_data_normalized(
-                    span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
-                )
-            if len(data_buf) > 0:
-                all_responses = ["".join(chunk) for chunk in data_buf]
-                if should_send_default_pii() and integration.include_prompts:
-                    set_data_normalized(
-                        span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses
-                    )
-                _calculate_token_usage(
-                    messages,
-                    response,
-                    span,
-                    all_responses,
-                    integration.count_tokens,
+            if hasattr(x, "delta"):
+                if start_time is not None and ttft is None:
+                    ttft = time.perf_counter() - start_time
+                if len(data_buf) == 0:
+                    data_buf.append([])
+                data_buf[0].append(x.delta or "")
+
+            if isinstance(x, ResponseCompletedEvent):
+                span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.response.model)
+
+                _calculate_responses_token_usage(
+                    input=input,
+                    response=x.response,
+                    span=span,
+                    streaming_message_responses=None,
+                    count_tokens=integration.count_tokens,
                 )
+                count_tokens_manually = False
 
-        if finish_span:
-            span.__exit__(None, None, None)
+        yield x
 
-    if str(type(response._iterator)) == "<class 'async_generator'>":
-        response._iterator = new_iterator_async()
-    else:
-        response._iterator = new_iterator()
+    with capture_internal_exceptions():
+        if ttft is not None:
+            set_data_normalized(
+                span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
+            )
+        if len(data_buf) > 0:
+            all_responses = ["".join(chunk) for chunk in data_buf]
+            if should_send_default_pii() and integration.include_prompts:
+                set_data_normalized(span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses)
+            if count_tokens_manually:
+                _calculate_responses_token_usage(
+                    input=input,
+                    response=response,
+                    span=span,
+                    streaming_message_responses=all_responses,
+                    count_tokens=integration.count_tokens,
+                )
+    if finish_span:
+        span.__exit__(None, None, None)
 
 
 def _set_responses_api_output_data(
@@ -724,127 +1028,6 @@ def _set_responses_api_output_data(
     )
 
 
-def _set_streaming_responses_api_output_data(
-    span: "Span",
-    response: "Any",
-    kwargs: "dict[str, Any]",
-    integration: "OpenAIIntegration",
-    start_time: "Optional[float]" = None,
-    finish_span: bool = True,
-) -> None:
-    input = kwargs.get("input")
-
-    if input is not None and isinstance(input, str):
-        input = [input]
-
-    ttft: "Optional[float]" = None
-    data_buf: "list[list[str]]" = []  # one for each choice
-
-    old_iterator = response._iterator
-
-    def new_iterator() -> "Iterator[ChatCompletionChunk]":
-        nonlocal ttft
-        count_tokens_manually = True
-        for x in old_iterator:
-            with capture_internal_exceptions():
-                if hasattr(x, "delta"):
-                    if start_time is not None and ttft is None:
-                        ttft = time.perf_counter() - start_time
-                    if len(data_buf) == 0:
-                        data_buf.append([])
-                    data_buf[0].append(x.delta or "")
-
-                if isinstance(x, ResponseCompletedEvent):
-                    span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.response.model)
-
-                    _calculate_token_usage(
-                        input,
-                        x.response,
-                        span,
-                        None,
-                        integration.count_tokens,
-                    )
-                    count_tokens_manually = False
-
-            yield x
-
-        with capture_internal_exceptions():
-            if ttft is not None:
-                set_data_normalized(
-                    span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
-                )
-            if len(data_buf) > 0:
-                all_responses = ["".join(chunk) for chunk in data_buf]
-                if should_send_default_pii() and integration.include_prompts:
-                    set_data_normalized(
-                        span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses
-                    )
-                if count_tokens_manually:
-                    _calculate_token_usage(
-                        input,
-                        response,
-                        span,
-                        all_responses,
-                        integration.count_tokens,
-                    )
-
-        if finish_span:
-            span.__exit__(None, None, None)
-
-    async def new_iterator_async() -> "AsyncIterator[ChatCompletionChunk]":
-        nonlocal ttft
-        count_tokens_manually = True
-        async for x in old_iterator:
-            with capture_internal_exceptions():
-                if hasattr(x, "delta"):
-                    if start_time is not None and ttft is None:
-                        ttft = time.perf_counter() - start_time
-                    if len(data_buf) == 0:
-                        data_buf.append([])
-                    data_buf[0].append(x.delta or "")
-
-                if isinstance(x, ResponseCompletedEvent):
-                    span.set_data(SPANDATA.GEN_AI_RESPONSE_MODEL, x.response.model)
-
-                    _calculate_token_usage(
-                        input,
-                        x.response,
-                        span,
-                        None,
-                        integration.count_tokens,
-                    )
-                    count_tokens_manually = False
-
-            yield x
-
-        with capture_internal_exceptions():
-            if ttft is not None:
-                set_data_normalized(
-                    span, SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN, ttft
-                )
-            if len(data_buf) > 0:
-                all_responses = ["".join(chunk) for chunk in data_buf]
-                if should_send_default_pii() and integration.include_prompts:
-                    set_data_normalized(
-                        span, SPANDATA.GEN_AI_RESPONSE_TEXT, all_responses
-                    )
-                if count_tokens_manually:
-                    _calculate_token_usage(
-                        input,
-                        response,
-                        span,
-                        all_responses,
-                        integration.count_tokens,
-                    )
-        if finish_span:
-            span.__exit__(None, None, None)
-
-    if str(type(response._iterator)) == "<class 'async_generator'>":
-        response._iterator = new_iterator_async()
-    else:
-        response._iterator = new_iterator()
-
-
 def _set_embeddings_output_data(
     span: "Span",
     response: "Any",
@@ -946,6 +1129,7 @@ def _new_embeddings_create_common(f: "Any", *args: "Any", **kwargs: "Any") -> "A
         name=f"embeddings {model}",
         origin=OpenAIIntegration.origin,
     ) as span:
+        span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")
         _set_embeddings_input_data(span, kwargs, integration)
 
         response = yield f, args, kwargs
@@ -1037,15 +1221,49 @@ def _new_responses_create_common(f: "Any", *args: "Any", **kwargs: "Any") -> "An
     )
     span.__enter__()
 
+    span.set_data(SPANDATA.GEN_AI_SYSTEM, "openai")
+
+    # Same bool handling as in https://github.com/openai/openai-python/blob/acd0c54d8a68efeedde0e5b4e6c310eef1ce7867/src/openai/resources/responses/responses.py#L940
+    is_streaming_response = kwargs.get("stream", False) or False
+    span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, is_streaming_response)
+
     _set_responses_api_input_data(span, kwargs, integration)
 
     start_time = time.perf_counter()
     response = yield f, args, kwargs
 
-    is_streaming_response = kwargs.get("stream", False)
-    if is_streaming_response:
-        _set_streaming_responses_api_output_data(
-            span, response, kwargs, integration, start_time, finish_span=True
+    # Attribute check to fail gracefully if the attribute is not present in future `openai` versions.
+    if isinstance(response, Stream) and hasattr(response, "_iterator"):
+        input = kwargs.get("input")
+
+        if input is not None and isinstance(input, str):
+            input = [input]
+
+        response._iterator = _wrap_synchronous_responses_event_iterator(
+            span=span,
+            integration=integration,
+            start_time=start_time,
+            input=input,
+            response=response,
+            old_iterator=response._iterator,
+            finish_span=True,
+        )
+
+    # Attribute check to fail gracefully if the attribute is not present in future `openai` versions.
+    elif isinstance(response, AsyncStream) and hasattr(response, "_iterator"):
+        input = kwargs.get("input")
+
+        if input is not None and isinstance(input, str):
+            input = [input]
+
+        response._iterator = _wrap_asynchronous_responses_event_iterator(
+            span=span,
+            integration=integration,
+            start_time=start_time,
+            input=input,
+            response=response,
+            old_iterator=response._iterator,
+            finish_span=True,
         )
     else:
         _set_responses_api_output_data(
diff --git a/sentry_sdk/integrations/openai_agents/__init__.py b/sentry_sdk/integrations/openai_agents/__init__.py
index 4d778676ac..1268ef3755 100644
--- a/sentry_sdk/integrations/openai_agents/__init__.py
+++ b/sentry_sdk/integrations/openai_agents/__init__.py
@@ -22,7 +22,6 @@
     # not installed. That's why we're adding the second, more specific import
     # after it, even if we don't use it.
     import agents
-    from agents.run import DEFAULT_AGENT_RUNNER
     from agents.run import AgentRunner
     from agents.version import __version__ as OPENAI_AGENTS_VERSION
 
diff --git a/sentry_sdk/integrations/openai_agents/patches/__init__.py b/sentry_sdk/integrations/openai_agents/patches/__init__.py
index e3be2776b3..9ab9e7fab6 100644
--- a/sentry_sdk/integrations/openai_agents/patches/__init__.py
+++ b/sentry_sdk/integrations/openai_agents/patches/__init__.py
@@ -2,9 +2,9 @@
 from .tools import _get_all_tools  # noqa: F401
 from .runner import _create_run_wrapper, _create_run_streamed_wrapper  # noqa: F401
 from .agent_run import (
-    _run_single_turn,
-    _run_single_turn_streamed,
-    _execute_handoffs,
-    _execute_final_output,
-)  # noqa: F401
+    _run_single_turn,  # noqa: F401
+    _run_single_turn_streamed,  # noqa: F401
+    _execute_handoffs,  # noqa: F401
+    _execute_final_output,  # noqa: F401
+)
 from .error_tracing import _patch_error_tracing  # noqa: F401
diff --git a/sentry_sdk/integrations/openai_agents/patches/agent_run.py b/sentry_sdk/integrations/openai_agents/patches/agent_run.py
index a828532ab3..1d085b2715 100644
--- a/sentry_sdk/integrations/openai_agents/patches/agent_run.py
+++ b/sentry_sdk/integrations/openai_agents/patches/agent_run.py
@@ -1,5 +1,4 @@
 import sys
-from functools import wraps
 
 from sentry_sdk.consts import SPANDATA
 from sentry_sdk.integrations import DidNotEnable
@@ -9,7 +8,7 @@
     end_invoke_agent_span,
     handoff_span,
 )
-from ..utils import _record_exception_on_span
+from sentry_sdk.tracing_utils import set_span_errored
 
 from typing import TYPE_CHECKING
 
@@ -90,7 +89,13 @@ async def _run_single_turn(
     - creates agent invocation spans if there is no already active agent invocation span.
     - ends the agent invocation span if and only if an exception is raised in `_run_single_turn()`.
     """
-    agent = kwargs.get("agent")
+    # openai-agents >= 0.14 passes `bindings: AgentBindings` instead of `agent`.
+    bindings = kwargs.get("bindings")
+    agent = (
+        getattr(bindings, "public_agent", None)
+        if bindings is not None
+        else kwargs.get("agent")
+    )
     context_wrapper = kwargs.get("context_wrapper")
     should_run_agent_start_hooks = kwargs.get("should_run_agent_start_hooks", False)
 
@@ -100,9 +105,9 @@ async def _run_single_turn(
 
     try:
         result = await original_run_single_turn(*args, **kwargs)
-    except Exception as exc:
+    except Exception:
         if span is not None and span.timestamp is None:
-            _record_exception_on_span(span, exc)
+            set_span_errored(span)
             end_invoke_agent_span(context_wrapper, agent)
         reraise(*sys.exc_info())
 
@@ -120,7 +125,7 @@ async def _run_single_turn_streamed(
     - ends the agent invocation span if and only if `_run_single_turn_streamed()` raises an exception.
 
     Note: Unlike _run_single_turn which uses keyword-only arguments (*,),
-    _run_single_turn_streamed uses positional arguments. The call signature is:
+    _run_single_turn_streamed uses positional arguments. The call signature <v0.14 is:
     _run_single_turn_streamed(
         streamed_result,              # args[0]
         agent,                        # args[1]
@@ -132,9 +137,26 @@ async def _run_single_turn_streamed(
         all_tools,                    # args[7]
         server_conversation_tracker,  # args[8] (optional)
     )
+
+    The call signature >=v0.14 is:
+    _run_single_turn_streamed(
+        streamed_result,              # args[0]
+        bindings,                     # args[1]
+        hooks,                        # args[2]
+        context_wrapper,              # args[3]
+        run_config,                   # args[4]
+        should_run_agent_start_hooks, # args[5]
+        tool_use_tracker,             # args[6]
+        all_tools,                    # args[7]
+        server_conversation_tracker,  # args[8] (optional)
+    )
     """
     streamed_result = args[0] if len(args) > 0 else kwargs.get("streamed_result")
-    agent = args[1] if len(args) > 1 else kwargs.get("agent")
+    # openai-agents >= 0.14 passes `bindings: AgentBindings` at args[1] instead of `agent`.
+    agent_or_bindings = (
+        args[1] if len(args) > 1 else kwargs.get("bindings", kwargs.get("agent"))
+    )
+    agent = getattr(agent_or_bindings, "public_agent", agent_or_bindings)
     context_wrapper = args[3] if len(args) > 3 else kwargs.get("context_wrapper")
     should_run_agent_start_hooks = bool(
         args[5] if len(args) > 5 else kwargs.get("should_run_agent_start_hooks", False)
@@ -154,11 +176,11 @@ async def _run_single_turn_streamed(
 
     try:
         result = await original_run_single_turn_streamed(*args, **kwargs)
-    except Exception as exc:
+    except Exception:
         exc_info = sys.exc_info()
         with capture_internal_exceptions():
             if span is not None and span.timestamp is None:
-                _record_exception_on_span(span, exc)
+                set_span_errored(span)
                 end_invoke_agent_span(context_wrapper, agent)
             _close_streaming_workflow_span(agent)
         reraise(*exc_info)
@@ -180,7 +202,8 @@ async def _execute_handoffs(
 
     context_wrapper = kwargs.get("context_wrapper")
     run_handoffs = kwargs.get("run_handoffs")
-    agent = kwargs.get("agent")
+    # openai-agents >= 0.14 renamed `agent` to `public_agent`.
+    agent = kwargs.get("public_agent", kwargs.get("agent"))
 
     # Create Sentry handoff span for the first handoff (agents library only processes the first one)
     if run_handoffs:
@@ -215,7 +238,8 @@ async def _execute_final_output(
     - ends the workflow span if the response is streamed.
     """
 
-    agent = kwargs.get("agent")
+    # openai-agents >= 0.14 renamed `agent` to `public_agent`.
+    agent = kwargs.get("public_agent", kwargs.get("agent"))
     context_wrapper = kwargs.get("context_wrapper")
     final_output = kwargs.get("final_output")
 
diff --git a/sentry_sdk/integrations/openai_agents/patches/error_tracing.py b/sentry_sdk/integrations/openai_agents/patches/error_tracing.py
index 8598d9c4fd..0921f25e48 100644
--- a/sentry_sdk/integrations/openai_agents/patches/error_tracing.py
+++ b/sentry_sdk/integrations/openai_agents/patches/error_tracing.py
@@ -1,14 +1,12 @@
 from functools import wraps
 
 import sentry_sdk
-from sentry_sdk.consts import SPANSTATUS
 from sentry_sdk.tracing_utils import set_span_errored
-from ..utils import _record_exception_on_span
 
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from typing import Any, Callable, Optional
+    from typing import Any
 
 
 def _patch_error_tracing() -> None:
@@ -59,7 +57,7 @@ def sentry_attach_error_to_current_span(
         # Set the current Sentry span to errored
         current_span = sentry_sdk.get_current_span()
         if current_span is not None:
-            _record_exception_on_span(current_span, error)
+            set_span_errored(current_span)
 
         # Call the original function
         return original_attach_error(error, *args, **kwargs)
diff --git a/sentry_sdk/integrations/openai_agents/patches/runner.py b/sentry_sdk/integrations/openai_agents/patches/runner.py
index 78c055890e..fb35424db5 100644
--- a/sentry_sdk/integrations/openai_agents/patches/runner.py
+++ b/sentry_sdk/integrations/openai_agents/patches/runner.py
@@ -5,9 +5,10 @@
 from sentry_sdk.consts import SPANDATA
 from sentry_sdk.integrations import DidNotEnable
 from sentry_sdk.utils import capture_internal_exceptions, reraise
+from sentry_sdk.tracing_utils import set_span_errored
 
 from ..spans import agent_workflow_span, end_invoke_agent_span
-from ..utils import _capture_exception, _record_exception_on_span
+from ..utils import _capture_exception
 
 try:
     from agents.exceptions import AgentsException
@@ -65,7 +66,7 @@ async def wrapper(*args: "Any", **kwargs: "Any") -> "Any":
                                 invoke_agent_span is not None
                                 and invoke_agent_span.timestamp is None
                             ):
-                                _record_exception_on_span(invoke_agent_span, exc)
+                                set_span_errored(invoke_agent_span)
                                 end_invoke_agent_span(context_wrapper, agent)
                     reraise(*exc_info)
                 except Exception as exc:
diff --git a/sentry_sdk/integrations/openai_agents/spans/__init__.py b/sentry_sdk/integrations/openai_agents/spans/__init__.py
index 64b979fc25..2187c4ee51 100644
--- a/sentry_sdk/integrations/openai_agents/spans/__init__.py
+++ b/sentry_sdk/integrations/openai_agents/spans/__init__.py
@@ -3,7 +3,7 @@
 from .execute_tool import execute_tool_span, update_execute_tool_span  # noqa: F401
 from .handoff import handoff_span  # noqa: F401
 from .invoke_agent import (
-    invoke_agent_span,
-    update_invoke_agent_span,
-    end_invoke_agent_span,
-)  # noqa: F401
+    invoke_agent_span,  # noqa: F401
+    update_invoke_agent_span,  # noqa: F401
+    end_invoke_agent_span,  # noqa: F401
+)
diff --git a/sentry_sdk/integrations/openai_agents/spans/execute_tool.py b/sentry_sdk/integrations/openai_agents/spans/execute_tool.py
index e12dce4e3e..26072cfdba 100644
--- a/sentry_sdk/integrations/openai_agents/spans/execute_tool.py
+++ b/sentry_sdk/integrations/openai_agents/spans/execute_tool.py
@@ -23,9 +23,6 @@ def execute_tool_span(
 
     span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "execute_tool")
 
-    if tool.__class__.__name__ == "FunctionTool":
-        span.set_data(SPANDATA.GEN_AI_TOOL_TYPE, "function")
-
     span.set_data(SPANDATA.GEN_AI_TOOL_NAME, tool.name)
     span.set_data(SPANDATA.GEN_AI_TOOL_DESCRIPTION, tool.description)
 
diff --git a/sentry_sdk/integrations/openai_agents/utils.py b/sentry_sdk/integrations/openai_agents/utils.py
index 15119a393c..ee504b3496 100644
--- a/sentry_sdk/integrations/openai_agents/utils.py
+++ b/sentry_sdk/integrations/openai_agents/utils.py
@@ -25,7 +25,6 @@
     from typing import Any
     from agents import Usage, TResponseInputItem
 
-    from sentry_sdk.tracing import Span
     from sentry_sdk._types import TextPart
 
 try:
@@ -46,19 +45,6 @@ def _capture_exception(exc: "Any") -> None:
     sentry_sdk.capture_event(event, hint=hint)
 
 
-def _record_exception_on_span(span: "Span", error: Exception) -> "Any":
-    set_span_errored(span)
-    span.set_data("span.status", "error")
-
-    # Optionally capture the error details if we have them
-    if hasattr(error, "__class__"):
-        span.set_data("error.type", error.__class__.__name__)
-    if hasattr(error, "__str__"):
-        error_message = str(error)
-        if error_message:
-            span.set_data("error.message", error_message)
-
-
 def _set_agent_data(span: "sentry_sdk.tracing.Span", agent: "agents.Agent") -> None:
     span.set_data(
         SPANDATA.GEN_AI_SYSTEM, "openai"
@@ -239,7 +225,6 @@ def _create_mcp_execute_tool_spans(
                 description=f"execute_tool {output.name}",
                 start_timestamp=span.start_timestamp,
             ) as execute_tool_span:
-                execute_tool_span.set_data(SPANDATA.GEN_AI_TOOL_TYPE, "mcp")
                 execute_tool_span.set_data(SPANDATA.GEN_AI_TOOL_NAME, output.name)
                 if should_send_default_pii():
                     execute_tool_span.set_data(
diff --git a/sentry_sdk/integrations/opentelemetry/span_processor.py b/sentry_sdk/integrations/opentelemetry/span_processor.py
index 407baef61c..8a589af308 100644
--- a/sentry_sdk/integrations/opentelemetry/span_processor.py
+++ b/sentry_sdk/integrations/opentelemetry/span_processor.py
@@ -34,6 +34,7 @@
 if TYPE_CHECKING:
     from typing import Any, Optional, Union
     from opentelemetry import context as context_api
+    from opentelemetry.trace import SpanContext
     from sentry_sdk._types import Event, Hint
 
 OPEN_TELEMETRY_CONTEXT = "otel"
@@ -86,7 +87,8 @@ def __new__(cls) -> "SentrySpanProcessor":
         if not hasattr(cls, "instance"):
             cls.instance = super().__new__(cls)
 
-        return cls.instance
+        # "instance" class attribute is guaranteed to be set above (mypy believes instance is an instance-only attribute).
+        return cls.instance  # type: ignore[misc]
 
     def __init__(self) -> None:
         @add_global_event_processor
@@ -123,13 +125,16 @@ def on_start(
         if client.options["instrumenter"] != INSTRUMENTER.OTEL:
             return
 
-        if not otel_span.get_span_context().is_valid:
+        span_context = otel_span.get_span_context()
+        if span_context is None or not span_context.is_valid:
             return
 
         if self._is_sentry_span(otel_span):
             return
 
-        trace_data = self._get_trace_data(otel_span, parent_context)
+        trace_data = self._get_trace_data(
+            span_context, otel_span.parent, parent_context
+        )
 
         parent_span_id = trace_data["parent_span_id"]
         sentry_parent_span = (
@@ -182,7 +187,7 @@ def on_end(self, otel_span: "OTelSpan") -> None:
             return
 
         span_context = otel_span.get_span_context()
-        if not span_context.is_valid:
+        if span_context is None or not span_context.is_valid:
             return
 
         span_id = format_span_id(span_context.span_id)
@@ -254,13 +259,15 @@ def _get_otel_context(self, otel_span: "OTelSpan") -> "dict[str, Any]":
         return ctx
 
     def _get_trace_data(
-        self, otel_span: "OTelSpan", parent_context: "Optional[context_api.Context]"
+        self,
+        span_context: "SpanContext",
+        parent_span_context: "Optional[SpanContext]",
+        parent_context: "Optional[context_api.Context]",
     ) -> "dict[str, Any]":
         """
-        Extracts tracing information from one OTel span and its parent OTel context.
+        Extracts tracing information from one OTel span's context and its parent OTel context.
         """
         trace_data: "dict[str, Any]" = {}
-        span_context = otel_span.get_span_context()
 
         span_id = format_span_id(span_context.span_id)
         trace_data["span_id"] = span_id
@@ -269,7 +276,7 @@ def _get_trace_data(
         trace_data["trace_id"] = trace_id
 
         parent_span_id = (
-            format_span_id(otel_span.parent.span_id) if otel_span.parent else None
+            format_span_id(parent_span_context.span_id) if parent_span_context else None
         )
         trace_data["parent_span_id"] = parent_span_id
 
diff --git a/sentry_sdk/integrations/otlp.py b/sentry_sdk/integrations/otlp.py
index 19c6099970..47556f9b80 100644
--- a/sentry_sdk/integrations/otlp.py
+++ b/sentry_sdk/integrations/otlp.py
@@ -66,7 +66,9 @@ def otel_propagation_context() -> "Optional[Tuple[str, str]]":
     return (format_trace_id(ctx.trace_id), format_span_id(ctx.span_id))
 
 
-def setup_otlp_traces_exporter(dsn: "Optional[str]" = None) -> None:
+def setup_otlp_traces_exporter(
+    dsn: "Optional[str]" = None, collector_url: "Optional[str]" = None
+) -> None:
     tracer_provider = get_tracer_provider()
 
     if not isinstance(tracer_provider, TracerProvider):
@@ -76,7 +78,10 @@ def setup_otlp_traces_exporter(dsn: "Optional[str]" = None) -> None:
 
     endpoint = None
     headers = None
-    if dsn:
+    if collector_url:
+        endpoint = collector_url
+        logger.debug(f"[OTLP] Sending traces to collector at {endpoint}")
+    elif dsn:
         auth = Dsn(dsn).to_auth(f"sentry.python/{VERSION}")
         endpoint = auth.get_api_url(EndpointType.OTLP_TRACES)
         headers = {"X-Sentry-Auth": auth.to_header()}
@@ -177,7 +182,9 @@ class OTLPIntegration(Integration):
     Automatically setup OTLP ingestion from the DSN.
 
     :param setup_otlp_traces_exporter: Automatically configure an Exporter to send OTLP traces from the DSN, defaults to True.
-        Set to False if using a custom collector or to setup the TracerProvider manually.
+        Set to False to setup the TracerProvider manually.
+    :param collector_url: URL of your own OpenTelemetry collector, defaults to None.
+        When set, the exporter will send traces to this URL instead of the Sentry OTLP endpoint derived from the DSN.
     :param setup_propagator: Automatically configure the Sentry Propagator for Distributed Tracing, defaults to True.
         Set to False to configure propagators manually or to disable propagation.
     :param capture_exceptions: Intercept and capture exceptions on the OpenTelemetry Span in Sentry as well, defaults to False.
@@ -189,10 +196,12 @@ class OTLPIntegration(Integration):
     def __init__(
         self,
         setup_otlp_traces_exporter: bool = True,
+        collector_url: "Optional[str]" = None,
         setup_propagator: bool = True,
         capture_exceptions: bool = False,
     ) -> None:
         self.setup_otlp_traces_exporter = setup_otlp_traces_exporter
+        self.collector_url = collector_url
         self.setup_propagator = setup_propagator
         self.capture_exceptions = capture_exceptions
 
@@ -207,7 +216,7 @@ def setup_once_with_options(
         if self.setup_otlp_traces_exporter:
             logger.debug("[OTLP] Setting up OTLP exporter")
             dsn: "Optional[str]" = options.get("dsn") if options else None
-            setup_otlp_traces_exporter(dsn)
+            setup_otlp_traces_exporter(dsn, collector_url=self.collector_url)
 
         if self.setup_propagator:
             logger.debug("[OTLP] Setting up propagator for distributed tracing")
diff --git a/sentry_sdk/integrations/pydantic_ai/__init__.py b/sentry_sdk/integrations/pydantic_ai/__init__.py
index 2f1808d14f..5868ccf07d 100644
--- a/sentry_sdk/integrations/pydantic_ai/__init__.py
+++ b/sentry_sdk/integrations/pydantic_ai/__init__.py
@@ -1,8 +1,11 @@
-from sentry_sdk.integrations import DidNotEnable, Integration
+import functools
 
+from sentry_sdk.integrations import DidNotEnable, Integration
+from sentry_sdk.utils import capture_internal_exceptions
 
 try:
-    import pydantic_ai  # type: ignore
+    import pydantic_ai  # type: ignore # noqa: F401
+    from pydantic_ai import Agent
 except ImportError:
     raise DidNotEnable("pydantic-ai not installed")
 
@@ -10,14 +13,122 @@
 from .patches import (
     _patch_agent_run,
     _patch_graph_nodes,
-    _patch_model_request,
     _patch_tool_execution,
 )
 
+from .spans.ai_client import ai_client_span, update_ai_client_span
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from typing import Any
+    from pydantic_ai import ModelRequestContext, RunContext
+    from pydantic_ai.messages import ModelResponse  # type: ignore
+    from pydantic_ai.capabilities import Hooks  # type: ignore
+
+
+def register_hooks(hooks: "Hooks") -> None:
+    """
+    Creates hooks for chat model calls and register the hooks by adding the hooks to the `capabilities` argument passed to `Agent.__init__()`.
+    """
+
+    @hooks.on.before_model_request  # type: ignore
+    async def on_request(
+        ctx: "RunContext[None]", request_context: "ModelRequestContext"
+    ) -> "ModelRequestContext":
+        run_context_metadata = ctx.metadata
+        if not isinstance(run_context_metadata, dict):
+            return request_context
+
+        span = ai_client_span(
+            messages=request_context.messages,
+            agent=None,
+            model=request_context.model,
+            model_settings=request_context.model_settings,
+        )
+
+        run_context_metadata["_sentry_span"] = span
+        span.__enter__()
+
+        return request_context
+
+    @hooks.on.after_model_request  # type: ignore
+    async def on_response(
+        ctx: "RunContext[None]",
+        *,
+        request_context: "ModelRequestContext",
+        response: "ModelResponse",
+    ) -> "ModelResponse":
+        run_context_metadata = ctx.metadata
+        if not isinstance(run_context_metadata, dict):
+            return response
+
+        span = run_context_metadata.pop("_sentry_span", None)
+        if span is None:
+            return response
+
+        update_ai_client_span(span, response)
+        span.__exit__(None, None, None)
+
+        return response
+
+    @hooks.on.model_request_error  # type: ignore
+    async def on_error(
+        ctx: "RunContext[None]",
+        *,
+        request_context: "ModelRequestContext",
+        error: "Exception",
+    ) -> "ModelResponse":
+        run_context_metadata = ctx.metadata
+
+        if not isinstance(run_context_metadata, dict):
+            raise error
+
+        span = run_context_metadata.pop("_sentry_span", None)
+        if span is None:
+            raise error
+
+        with capture_internal_exceptions():
+            span.__exit__(type(error), error, error.__traceback__)
+
+        raise error
+
+    original_init = Agent.__init__
+
+    @functools.wraps(original_init)
+    def patched_init(self: "Agent[Any, Any]", *args: "Any", **kwargs: "Any") -> None:
+        caps = list(kwargs.get("capabilities") or [])
+        caps.append(hooks)
+        kwargs["capabilities"] = caps
+
+        metadata = kwargs.get("metadata")
+        if metadata is None:
+            kwargs["metadata"] = {}  # Used as shared reference between hooks
+
+        return original_init(self, *args, **kwargs)
+
+    Agent.__init__ = patched_init
+
 
 class PydanticAIIntegration(Integration):
+    """
+    Typical interaction with the library:
+    1. The user creates an Agent instance with configuration, including system instructions sent to every model call.
+    2. The user calls `Agent.run()` or `Agent.run_stream()` to start an agent run. The latter can be used to incrementally receive progress.
+    - Each run invocation has `RunContext` objects that are passed to the library hooks.
+    3. In a loop, the agent repeatedly calls the model, maintaining a conversation history that includes previous messages and tool results, which is passed to each call.
+
+    Internally, Pydantic AI maintains an execution graph in which ModelRequestNode are responsible for model calls, including retries.
+    Hooks using the decorators provided by `pydantic_ai.capabilities` create and manage spans for model calls when these hooks are available (newer library versions).
+    The span is created in `on_request` and stored in the metadata of the `RunContext` object shared with `on_response` and `on_error`.
+
+    The metadata dictionary on the RunContext instance is initialized with `{"_sentry_span": None}` in the `_create_run_wrapper()` and `_create_streaming_wrapper()` wrappers that
+    instrument `Agent.run()` and `Agent.run_stream()`, respectively. A non-empty dictionary is required for the metadata object to be a shared reference between hooks.
+    """
+
     identifier = "pydantic_ai"
     origin = f"auto.ai.{identifier}"
+    are_request_hooks_available = True
 
     def __init__(
         self, include_prompts: bool = True, handled_tool_call_exceptions: bool = True
@@ -45,6 +156,17 @@ def setup_once() -> None:
         - Tool executions
         """
         _patch_agent_run()
-        _patch_graph_nodes()
-        _patch_model_request()
         _patch_tool_execution()
+
+        try:
+            from pydantic_ai.capabilities import Hooks
+        except ImportError:
+            Hooks = None
+            PydanticAIIntegration.are_request_hooks_available = False
+
+        if Hooks is None:
+            _patch_graph_nodes()
+            return
+
+        hooks = Hooks()
+        register_hooks(hooks)
diff --git a/sentry_sdk/integrations/pydantic_ai/patches/__init__.py b/sentry_sdk/integrations/pydantic_ai/patches/__init__.py
index de28780728..d0ea6242b4 100644
--- a/sentry_sdk/integrations/pydantic_ai/patches/__init__.py
+++ b/sentry_sdk/integrations/pydantic_ai/patches/__init__.py
@@ -1,4 +1,3 @@
 from .agent_run import _patch_agent_run  # noqa: F401
 from .graph_nodes import _patch_graph_nodes  # noqa: F401
-from .model_request import _patch_model_request  # noqa: F401
 from .tools import _patch_tool_execution  # noqa: F401
diff --git a/sentry_sdk/integrations/pydantic_ai/patches/agent_run.py b/sentry_sdk/integrations/pydantic_ai/patches/agent_run.py
index eaa4385834..15f2b1994c 100644
--- a/sentry_sdk/integrations/pydantic_ai/patches/agent_run.py
+++ b/sentry_sdk/integrations/pydantic_ai/patches/agent_run.py
@@ -96,6 +96,9 @@ def _create_run_wrapper(
         original_func: The original run method
         is_streaming: Whether this is a streaming method (for future use)
     """
+    from sentry_sdk.integrations.pydantic_ai import (
+        PydanticAIIntegration,
+    )  # Required to avoid circular import
 
     @wraps(original_func)
     async def wrapper(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
@@ -107,6 +110,11 @@ async def wrapper(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
             model = kwargs.get("model")
             model_settings = kwargs.get("model_settings")
 
+            if PydanticAIIntegration.are_request_hooks_available:
+                metadata = kwargs.get("metadata")
+                if metadata is None:
+                    kwargs["metadata"] = {"_sentry_span": None}
+
             # Create invoke_agent span
             with invoke_agent_span(
                 user_prompt, self, model, model_settings, is_streaming
@@ -140,6 +148,9 @@ def _create_streaming_wrapper(
     """
     Wraps run_stream method that returns an async context manager.
     """
+    from sentry_sdk.integrations.pydantic_ai import (
+        PydanticAIIntegration,
+    )  # Required to avoid circular import
 
     @wraps(original_func)
     def wrapper(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
@@ -148,6 +159,11 @@ def wrapper(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
         model = kwargs.get("model")
         model_settings = kwargs.get("model_settings")
 
+        if PydanticAIIntegration.are_request_hooks_available:
+            metadata = kwargs.get("metadata")
+            if metadata is None:
+                kwargs["metadata"] = {"_sentry_span": None}
+
         # Call original function to get the context manager
         original_ctx_manager = original_func(self, *args, **kwargs)
 
diff --git a/sentry_sdk/integrations/pydantic_ai/patches/graph_nodes.py b/sentry_sdk/integrations/pydantic_ai/patches/graph_nodes.py
index 56e46d869f..afb10395f4 100644
--- a/sentry_sdk/integrations/pydantic_ai/patches/graph_nodes.py
+++ b/sentry_sdk/integrations/pydantic_ai/patches/graph_nodes.py
@@ -1,7 +1,6 @@
 from contextlib import asynccontextmanager
 from functools import wraps
 
-import sentry_sdk
 from sentry_sdk.integrations import DidNotEnable
 
 from ..spans import (
diff --git a/sentry_sdk/integrations/pydantic_ai/patches/model_request.py b/sentry_sdk/integrations/pydantic_ai/patches/model_request.py
deleted file mode 100644
index 94a96161f3..0000000000
--- a/sentry_sdk/integrations/pydantic_ai/patches/model_request.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from functools import wraps
-from typing import TYPE_CHECKING
-
-from sentry_sdk.integrations import DidNotEnable
-
-try:
-    from pydantic_ai import models  # type: ignore
-except ImportError:
-    raise DidNotEnable("pydantic-ai not installed")
-
-from ..spans import ai_client_span, update_ai_client_span
-
-
-if TYPE_CHECKING:
-    from typing import Any
-
-
-def _patch_model_request() -> None:
-    """
-    Patches model request execution to create AI client spans.
-
-    In pydantic-ai, model requests are handled through the Model interface.
-    We need to patch the request method on models to create spans.
-    """
-
-    # Patch the base Model class's request method
-    if hasattr(models, "Model"):
-        original_request = models.Model.request
-
-        @wraps(original_request)
-        async def wrapped_request(
-            self: "Any", messages: "Any", *args: "Any", **kwargs: "Any"
-        ) -> "Any":
-            # Pass all messages (full conversation history)
-            with ai_client_span(messages, None, self, None) as span:
-                result = await original_request(self, messages, *args, **kwargs)
-                update_ai_client_span(span, result)
-                return result
-
-        models.Model.request = wrapped_request
diff --git a/sentry_sdk/integrations/pydantic_ai/patches/tools.py b/sentry_sdk/integrations/pydantic_ai/patches/tools.py
index e318b1322f..e719c7be78 100644
--- a/sentry_sdk/integrations/pydantic_ai/patches/tools.py
+++ b/sentry_sdk/integrations/pydantic_ai/patches/tools.py
@@ -14,14 +14,11 @@
     from typing import Any
 
 try:
-    from pydantic_ai.mcp import MCPServer  # type: ignore
+    try:
+        from pydantic_ai.tool_manager import ToolManager  # type: ignore
+    except ImportError:
+        from pydantic_ai._tool_manager import ToolManager  # type: ignore
 
-    HAS_MCP = True
-except ImportError:
-    HAS_MCP = False
-
-try:
-    from pydantic_ai._tool_manager import ToolManager  # type: ignore
     from pydantic_ai.exceptions import ToolRetryError  # type: ignore
 except ImportError:
     raise DidNotEnable("pydantic-ai not installed")
@@ -50,11 +47,7 @@ async def wrapped_execute_tool_call(
         call = validated.call
         name = call.tool_name
         tool = self.tools.get(name) if self.tools else None
-
-        # Determine tool type by checking tool.toolset
-        tool_type = "function"
-        if tool and HAS_MCP and isinstance(tool.toolset, MCPServer):
-            tool_type = "mcp"
+        selected_tool_definition = getattr(tool, "tool_def", None)
 
         # Get agent from contextvar
         agent = get_current_agent()
@@ -72,7 +65,7 @@ async def wrapped_execute_tool_call(
                     name,
                     args_dict,
                     agent,
-                    tool_type=tool_type,
+                    tool_definition=selected_tool_definition,
                 ) as span:
                     try:
                         result = await original_execute_tool_call(
@@ -127,11 +120,7 @@ async def wrapped_call_tool(
         # Extract tool info before calling original
         name = call.tool_name
         tool = self.tools.get(name) if self.tools else None
-
-        # Determine tool type by checking tool.toolset
-        tool_type = "function"  # default
-        if tool and HAS_MCP and isinstance(tool.toolset, MCPServer):
-            tool_type = "mcp"
+        selected_tool_definition = getattr(tool, "tool_def", None)
 
         # Get agent from contextvar
         agent = get_current_agent()
@@ -149,7 +138,7 @@ async def wrapped_call_tool(
                     name,
                     args_dict,
                     agent,
-                    tool_type=tool_type,
+                    tool_definition=selected_tool_definition,
                 ) as span:
                     try:
                         result = await original_call_tool(
diff --git a/sentry_sdk/integrations/pydantic_ai/spans/ai_client.py b/sentry_sdk/integrations/pydantic_ai/spans/ai_client.py
index b5ce15e99e..dc95acad45 100644
--- a/sentry_sdk/integrations/pydantic_ai/spans/ai_client.py
+++ b/sentry_sdk/integrations/pydantic_ai/spans/ai_client.py
@@ -1,12 +1,10 @@
 import json
 
 import sentry_sdk
-from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
 from sentry_sdk.ai.utils import (
     normalize_message_roles,
     set_data_normalized,
     truncate_and_annotate_messages,
-    get_modality_from_mime_type,
 )
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.utils import safe_serialize
@@ -21,13 +19,16 @@
     get_current_agent,
     get_is_streaming,
 )
-from .utils import _set_usage_data
+from .utils import (
+    _serialize_binary_content_item,
+    _serialize_image_url_item,
+    _set_usage_data,
+)
 
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from typing import Any, List, Dict
-    from pydantic_ai.usage import RequestUsage  # type: ignore
     from pydantic_ai.messages import ModelMessage, SystemPromptPart  # type: ignore
     from sentry_sdk._types import TextPart as SentryTextPart
 
@@ -40,6 +41,7 @@
         TextPart,
         ThinkingPart,
         BinaryContent,
+        ImageUrl,
     )
 except ImportError:
     # Fallback if these classes are not available
@@ -50,6 +52,7 @@
     TextPart = None
     ThinkingPart = None
     BinaryContent = None
+    ImageUrl = None
 
 
 def _transform_system_instructions(
@@ -158,22 +161,14 @@ def _set_input_messages(span: "sentry_sdk.tracing.Span", messages: "Any") -> Non
                             for item in part.content:
                                 if isinstance(item, str):
                                     content.append({"type": "text", "text": item})
+                                elif ImageUrl and isinstance(item, ImageUrl):
+                                    content.append(_serialize_image_url_item(item))
                                 elif BinaryContent and isinstance(item, BinaryContent):
-                                    content.append(
-                                        {
-                                            "type": "blob",
-                                            "modality": get_modality_from_mime_type(
-                                                item.media_type
-                                            ),
-                                            "mime_type": item.media_type,
-                                            "content": BLOB_DATA_SUBSTITUTE,
-                                        }
-                                    )
+                                    content.append(_serialize_binary_content_item(item))
                                 else:
                                     content.append(safe_serialize(item))
                         else:
                             content.append({"type": "text", "text": str(part.content)})
-
                     # Add message if we have content or tool calls
                     if content or tool_calls:
                         message: "Dict[str, Any]" = {"role": role}
diff --git a/sentry_sdk/integrations/pydantic_ai/spans/execute_tool.py b/sentry_sdk/integrations/pydantic_ai/spans/execute_tool.py
index cc18302f87..00b9cd4f57 100644
--- a/sentry_sdk/integrations/pydantic_ai/spans/execute_tool.py
+++ b/sentry_sdk/integrations/pydantic_ai/spans/execute_tool.py
@@ -9,10 +9,14 @@
 
 if TYPE_CHECKING:
     from typing import Any, Optional
+    from pydantic_ai._tool_manager import ToolDefinition  # type: ignore
 
 
 def execute_tool_span(
-    tool_name: str, tool_args: "Any", agent: "Any", tool_type: str = "function"
+    tool_name: str,
+    tool_args: "Any",
+    agent: "Any",
+    tool_definition: "Optional[ToolDefinition]" = None,
 ) -> "sentry_sdk.tracing.Span":
     """Create a span for tool execution.
 
@@ -20,7 +24,7 @@ def execute_tool_span(
         tool_name: The name of the tool being executed
         tool_args: The arguments passed to the tool
         agent: The agent executing the tool
-        tool_type: The type of tool ("function" for regular tools, "mcp" for MCP services)
+        tool_definition: The definition of the tool, if available
     """
     span = sentry_sdk.start_span(
         op=OP.GEN_AI_EXECUTE_TOOL,
@@ -29,9 +33,14 @@ def execute_tool_span(
     )
 
     span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "execute_tool")
-    span.set_data(SPANDATA.GEN_AI_TOOL_TYPE, tool_type)
     span.set_data(SPANDATA.GEN_AI_TOOL_NAME, tool_name)
 
+    if tool_definition is not None and hasattr(tool_definition, "description"):
+        span.set_data(
+            SPANDATA.GEN_AI_TOOL_DESCRIPTION,
+            tool_definition.description,
+        )
+
     _set_agent_data(span, agent)
 
     if _should_send_prompts() and tool_args is not None:
diff --git a/sentry_sdk/integrations/pydantic_ai/spans/invoke_agent.py b/sentry_sdk/integrations/pydantic_ai/spans/invoke_agent.py
index b4f8307170..ee08ca7036 100644
--- a/sentry_sdk/integrations/pydantic_ai/spans/invoke_agent.py
+++ b/sentry_sdk/integrations/pydantic_ai/spans/invoke_agent.py
@@ -1,7 +1,5 @@
 import sentry_sdk
-from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
 from sentry_sdk.ai.utils import (
-    get_modality_from_mime_type,
     get_start_span_function,
     normalize_message_roles,
     set_data_normalized,
@@ -16,7 +14,11 @@
     _set_model_data,
     _should_send_prompts,
 )
-from .utils import _set_usage_data
+from .utils import (
+    _serialize_binary_content_item,
+    _serialize_image_url_item,
+    _set_usage_data,
+)
 
 from typing import TYPE_CHECKING
 
@@ -24,9 +26,10 @@
     from typing import Any
 
 try:
-    from pydantic_ai.messages import BinaryContent  # type: ignore
+    from pydantic_ai.messages import BinaryContent, ImageUrl  # type: ignore
 except ImportError:
     BinaryContent = None
+    ImageUrl = None
 
 
 def invoke_agent_span(
@@ -105,17 +108,10 @@ def invoke_agent_span(
                 for item in user_prompt:
                     if isinstance(item, str):
                         content.append({"text": item, "type": "text"})
+                    elif ImageUrl and isinstance(item, ImageUrl):
+                        content.append(_serialize_image_url_item(item))
                     elif BinaryContent and isinstance(item, BinaryContent):
-                        content.append(
-                            {
-                                "type": "blob",
-                                "modality": get_modality_from_mime_type(
-                                    item.media_type
-                                ),
-                                "mime_type": item.media_type,
-                                "content": BLOB_DATA_SUBSTITUTE,
-                            }
-                        )
+                        content.append(_serialize_binary_content_item(item))
                 if content:
                     messages.append(
                         {
diff --git a/sentry_sdk/integrations/pydantic_ai/spans/utils.py b/sentry_sdk/integrations/pydantic_ai/spans/utils.py
index 4a8ad4c68c..8f158b6da2 100644
--- a/sentry_sdk/integrations/pydantic_ai/spans/utils.py
+++ b/sentry_sdk/integrations/pydantic_ai/spans/utils.py
@@ -1,15 +1,50 @@
 """Utility functions for PydanticAI span instrumentation."""
 
 import sentry_sdk
+from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
+from sentry_sdk.ai.utils import get_modality_from_mime_type
 from sentry_sdk.consts import SPANDATA
 
+from sentry_sdk.ai.consts import DATA_URL_BASE64_REGEX
+
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from typing import Union, Dict, Any, List
+    from typing import Union, Dict, Any
     from pydantic_ai.usage import RequestUsage, RunUsage  # type: ignore
 
 
+def _serialize_image_url_item(item: "Any") -> "Dict[str, Any]":
+    """Serialize an ImageUrl content item for span data.
+
+    For data URLs containing base64-encoded images, the content is redacted.
+    For regular HTTP URLs, the URL string is preserved.
+    """
+    url = str(item.url)
+    data_url_match = DATA_URL_BASE64_REGEX.match(url)
+
+    if data_url_match:
+        return {
+            "type": "image",
+            "content": BLOB_DATA_SUBSTITUTE,
+        }
+
+    return {
+        "type": "image",
+        "content": url,
+    }
+
+
+def _serialize_binary_content_item(item: "Any") -> "Dict[str, Any]":
+    """Serialize a BinaryContent item for span data, redacting the blob data."""
+    return {
+        "type": "blob",
+        "modality": get_modality_from_mime_type(item.media_type),
+        "mime_type": item.media_type,
+        "content": BLOB_DATA_SUBSTITUTE,
+    }
+
+
 def _set_usage_data(
     span: "sentry_sdk.tracing.Span", usage: "Union[RequestUsage, RunUsage]"
 ) -> None:
diff --git a/sentry_sdk/integrations/pymongo.py b/sentry_sdk/integrations/pymongo.py
index 86399b54d1..59daab34da 100644
--- a/sentry_sdk/integrations/pymongo.py
+++ b/sentry_sdk/integrations/pymongo.py
@@ -88,6 +88,7 @@ def _get_db_data(event: "Any") -> "Dict[str, Any]":
     data = {}
 
     data[SPANDATA.DB_SYSTEM] = "mongodb"
+    data[SPANDATA.DB_DRIVER_NAME] = "pymongo"
 
     db_name = event.database_name
     if db_name is not None:
@@ -128,6 +129,7 @@ def started(self, event: "CommandStartedEvent") -> None:
             tags = {
                 "db.name": event.database_name,
                 SPANDATA.DB_SYSTEM: "mongodb",
+                SPANDATA.DB_DRIVER_NAME: "pymongo",
                 SPANDATA.DB_OPERATION: event.command_name,
                 SPANDATA.DB_MONGODB_COLLECTION: command.get(event.command_name),
             }
diff --git a/sentry_sdk/integrations/pyreqwest.py b/sentry_sdk/integrations/pyreqwest.py
new file mode 100644
index 0000000000..9861a83bf1
--- /dev/null
+++ b/sentry_sdk/integrations/pyreqwest.py
@@ -0,0 +1,136 @@
+import sentry_sdk
+from sentry_sdk import start_span
+from sentry_sdk.consts import OP, SPANDATA
+from sentry_sdk.integrations import Integration, DidNotEnable
+from sentry_sdk.tracing import BAGGAGE_HEADER_NAME
+from sentry_sdk.tracing_utils import (
+    should_propagate_trace,
+    add_http_request_source,
+    add_sentry_baggage_to_headers,
+)
+from sentry_sdk.utils import (
+    SENSITIVE_DATA_SUBSTITUTE,
+    capture_internal_exceptions,
+    logger,
+    parse_url,
+)
+
+from contextlib import contextmanager
+from typing import Any, Generator
+
+try:
+    from pyreqwest.client import ClientBuilder, SyncClientBuilder  # type: ignore[import-not-found]
+    from pyreqwest.request import (  # type: ignore[import-not-found]
+        Request,
+        OneOffRequestBuilder,
+        SyncOneOffRequestBuilder,
+    )
+    from pyreqwest.middleware import Next, SyncNext  # type: ignore[import-not-found]
+    from pyreqwest.response import Response, SyncResponse  # type: ignore[import-not-found]
+except ImportError:
+    raise DidNotEnable("pyreqwest not installed or incompatible version installed")
+
+
+class PyreqwestIntegration(Integration):
+    identifier = "pyreqwest"
+    origin = f"auto.http.{identifier}"
+
+    @staticmethod
+    def setup_once() -> None:
+        _patch_pyreqwest()
+
+
+def _patch_pyreqwest() -> None:
+    # Patch Client Builders
+    _patch_builder_method(ClientBuilder, "build", sentry_async_middleware)
+    _patch_builder_method(SyncClientBuilder, "build", sentry_sync_middleware)
+
+    # Patch Request Builders
+    _patch_builder_method(OneOffRequestBuilder, "send", sentry_async_middleware)
+    _patch_builder_method(SyncOneOffRequestBuilder, "send", sentry_sync_middleware)
+
+
+def _patch_builder_method(cls: type, method_name: str, middleware: "Any") -> None:
+    if not hasattr(cls, method_name):
+        return
+
+    original_method = getattr(cls, method_name)
+
+    def sentry_patched_method(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
+        if not getattr(self, "_sentry_instrumented", False):
+            integration = sentry_sdk.get_client().get_integration(PyreqwestIntegration)
+            if integration is not None:
+                self.with_middleware(middleware)
+                try:
+                    self._sentry_instrumented = True
+                except (TypeError, AttributeError):
+                    # In case the instance itself is immutable or doesn't allow extra attributes
+                    pass
+        return original_method(self, *args, **kwargs)
+
+    setattr(cls, method_name, sentry_patched_method)
+
+
+@contextmanager
+def _sentry_pyreqwest_span(request: "Request") -> "Generator[Any, None, None]":
+    parsed_url = None
+    with capture_internal_exceptions():
+        parsed_url = parse_url(str(request.url), sanitize=False)
+
+    with start_span(
+        op=OP.HTTP_CLIENT,
+        name=f"{request.method} {parsed_url.url if parsed_url else SENSITIVE_DATA_SUBSTITUTE}",
+        origin=PyreqwestIntegration.origin,
+    ) as span:
+        span.set_data(SPANDATA.HTTP_METHOD, request.method)
+        if parsed_url is not None:
+            span.set_data("url", parsed_url.url)
+            span.set_data(SPANDATA.HTTP_QUERY, parsed_url.query)
+            span.set_data(SPANDATA.HTTP_FRAGMENT, parsed_url.fragment)
+
+        if should_propagate_trace(sentry_sdk.get_client(), str(request.url)):
+            for (
+                key,
+                value,
+            ) in sentry_sdk.get_current_scope().iter_trace_propagation_headers():
+                logger.debug(
+                    "[Tracing] Adding `{key}` header {value} to outgoing request to {url}.".format(
+                        key=key, value=value, url=request.url
+                    )
+                )
+
+                if key == BAGGAGE_HEADER_NAME:
+                    add_sentry_baggage_to_headers(request.headers, value)
+                else:
+                    request.headers[key] = value
+
+        yield span
+
+    with capture_internal_exceptions():
+        add_http_request_source(span)
+
+
+async def sentry_async_middleware(
+    request: "Request", next_handler: "Next"
+) -> "Response":
+    if sentry_sdk.get_client().get_integration(PyreqwestIntegration) is None:
+        return await next_handler.run(request)
+
+    with _sentry_pyreqwest_span(request) as span:
+        response = await next_handler.run(request)
+        span.set_http_status(response.status)
+
+    return response
+
+
+def sentry_sync_middleware(
+    request: "Request", next_handler: "SyncNext"
+) -> "SyncResponse":
+    if sentry_sdk.get_client().get_integration(PyreqwestIntegration) is None:
+        return next_handler.run(request)
+
+    with _sentry_pyreqwest_span(request) as span:
+        response = next_handler.run(request)
+        span.set_http_status(response.status)
+
+    return response
diff --git a/sentry_sdk/integrations/redis/modules/queries.py b/sentry_sdk/integrations/redis/modules/queries.py
index 3e8a820f44..c7780099c3 100644
--- a/sentry_sdk/integrations/redis/modules/queries.py
+++ b/sentry_sdk/integrations/redis/modules/queries.py
@@ -44,6 +44,7 @@ def _get_db_span_description(
 
 def _set_db_data_on_span(span: "Span", connection_params: "dict[str, Any]") -> None:
     span.set_data(SPANDATA.DB_SYSTEM, "redis")
+    span.set_data(SPANDATA.DB_DRIVER_NAME, "redis-py")
 
     db = connection_params.get("db")
     if db is not None:
diff --git a/sentry_sdk/integrations/rust_tracing.py b/sentry_sdk/integrations/rust_tracing.py
index e2b203a286..697cf7db60 100644
--- a/sentry_sdk/integrations/rust_tracing.py
+++ b/sentry_sdk/integrations/rust_tracing.py
@@ -32,7 +32,7 @@
 
 import json
 from enum import Enum, auto
-from typing import Any, Callable, Dict, Tuple, Optional
+from typing import Any, Callable, Dict, Optional
 
 import sentry_sdk
 from sentry_sdk.integrations import Integration
@@ -40,8 +40,6 @@
 from sentry_sdk.tracing import Span as SentrySpan
 from sentry_sdk.utils import SENSITIVE_DATA_SUBSTITUTE
 
-TraceState = Optional[Tuple[Optional[SentrySpan], SentrySpan]]
-
 
 class RustTracingLevel(Enum):
     Trace = "TRACE"
@@ -170,7 +168,7 @@ def _include_tracing_fields(self) -> bool:
             else self.include_tracing_fields
         )
 
-    def on_event(self, event: str, _span_state: "TraceState") -> None:
+    def on_event(self, event: str, sentry_span: "SentrySpan") -> None:
         deserialized_event = json.loads(event)
         metadata = deserialized_event.get("metadata", {})
 
@@ -184,7 +182,7 @@ def on_event(self, event: str, _span_state: "TraceState") -> None:
         elif event_type == EventTypeMapping.Event:
             process_event(deserialized_event)
 
-    def on_new_span(self, attrs: str, span_id: str) -> "TraceState":
+    def on_new_span(self, attrs: str, span_id: str) -> "Optional[SentrySpan]":
         attrs = json.loads(attrs)
         metadata = attrs.get("metadata", {})
 
@@ -210,13 +208,7 @@ def on_new_span(self, attrs: str, span_id: str) -> "TraceState":
             "origin": self.origin,
         }
 
-        scope = sentry_sdk.get_current_scope()
-        parent_sentry_span = scope.span
-        if parent_sentry_span:
-            sentry_span = parent_sentry_span.start_child(**kwargs)
-        else:
-            sentry_span = scope.start_span(**kwargs)
-
+        sentry_span = sentry_sdk.start_span(**kwargs)
         fields = metadata.get("fields", [])
         for field in fields:
             if self._include_tracing_fields():
@@ -224,21 +216,18 @@ def on_new_span(self, attrs: str, span_id: str) -> "TraceState":
             else:
                 sentry_span.set_data(field, SENSITIVE_DATA_SUBSTITUTE)
 
-        scope.span = sentry_span
-        return (parent_sentry_span, sentry_span)
+        sentry_span.__enter__()
+        return sentry_span
 
-    def on_close(self, span_id: str, span_state: "TraceState") -> None:
-        if span_state is None:
+    def on_close(self, span_id: str, sentry_span: "SentrySpan") -> None:
+        if sentry_span is None:
             return
 
-        parent_sentry_span, sentry_span = span_state
-        sentry_span.finish()
-        sentry_sdk.get_current_scope().span = parent_sentry_span
+        sentry_span.__exit__(None, None, None)
 
-    def on_record(self, span_id: str, values: str, span_state: "TraceState") -> None:
-        if span_state is None:
+    def on_record(self, span_id: str, values: str, sentry_span: "SentrySpan") -> None:
+        if sentry_span is None:
             return
-        _parent_sentry_span, sentry_span = span_state
 
         deserialized_values = json.loads(values)
         for key, value in deserialized_values.items():
diff --git a/sentry_sdk/integrations/sqlalchemy.py b/sentry_sdk/integrations/sqlalchemy.py
index 7d3ed95373..a4354f4228 100644
--- a/sentry_sdk/integrations/sqlalchemy.py
+++ b/sentry_sdk/integrations/sqlalchemy.py
@@ -137,6 +137,13 @@ def _set_db_data(span: "Span", conn: "Any") -> None:
     if db_system is not None:
         span.set_data(SPANDATA.DB_SYSTEM, db_system)
 
+    try:
+        driver = conn.dialect.driver
+        if driver:
+            span.set_data(SPANDATA.DB_DRIVER_NAME, driver)
+    except Exception:
+        pass
+
     if conn.engine.url is None:
         return
 
diff --git a/sentry_sdk/integrations/starlette.py b/sentry_sdk/integrations/starlette.py
index 0b797ebcde..dac9887e2f 100644
--- a/sentry_sdk/integrations/starlette.py
+++ b/sentry_sdk/integrations/starlette.py
@@ -552,7 +552,11 @@ def patch_templates() -> None:
     except ImportError:
         return  # Nothing to do
 
-    from starlette.templating import Jinja2Templates  # type: ignore
+    # https://github.com/Kludex/starlette/commit/96479daca2e4bd8157f68d914fd162aa94eff73a
+    try:
+        from starlette.templating import Jinja2Templates  # type: ignore
+    except ImportError:
+        return
 
     old_jinja2templates_init = Jinja2Templates.__init__
 
diff --git a/sentry_sdk/integrations/strawberry.py b/sentry_sdk/integrations/strawberry.py
index da3c31a967..a12ee63e2a 100644
--- a/sentry_sdk/integrations/strawberry.py
+++ b/sentry_sdk/integrations/strawberry.py
@@ -13,9 +13,7 @@
     capture_internal_exceptions,
     ensure_integration_enabled,
     event_from_exception,
-    logger,
     package_version,
-    _get_installed_modules,
 )
 
 try:
@@ -181,19 +179,12 @@ def on_operation(self) -> "Generator[None, None, None]":
         event_processor = _make_request_event_processor(self.execution_context)
         scope.add_event_processor(event_processor)
 
-        span = sentry_sdk.get_current_span()
-        if span:
-            self.graphql_span = span.start_child(
-                op=op,
-                name=description,
-                origin=StrawberryIntegration.origin,
-            )
-        else:
-            self.graphql_span = sentry_sdk.start_span(
-                op=op,
-                name=description,
-                origin=StrawberryIntegration.origin,
-            )
+        self.graphql_span = sentry_sdk.start_span(
+            op=op,
+            name=description,
+            origin=StrawberryIntegration.origin,
+        )
+        self.graphql_span.__enter__()
 
         self.graphql_span.set_data("graphql.operation.type", operation_type)
         self.graphql_span.set_data("graphql.operation.name", self._operation_name)
@@ -208,7 +199,7 @@ def on_operation(self) -> "Generator[None, None, None]":
             transaction.source = TransactionSource.COMPONENT
             transaction.op = op
 
-        self.graphql_span.finish()
+        self.graphql_span.__exit__(None, None, None)
 
     def on_validate(self) -> "Generator[None, None, None]":
         self.validation_span = self.graphql_span.start_child(
diff --git a/sentry_sdk/integrations/wsgi.py b/sentry_sdk/integrations/wsgi.py
index ea7ebbea4d..8814a82858 100644
--- a/sentry_sdk/integrations/wsgi.py
+++ b/sentry_sdk/integrations/wsgi.py
@@ -13,7 +13,9 @@
 )
 from sentry_sdk.scope import should_send_default_pii, use_isolation_scope
 from sentry_sdk.sessions import track_session
-from sentry_sdk.tracing import Transaction, TransactionSource
+from sentry_sdk.traces import StreamedSpan, SegmentSource
+from sentry_sdk.tracing import Span, TransactionSource
+from sentry_sdk.tracing_utils import has_span_streaming_enabled
 from sentry_sdk.utils import (
     ContextVar,
     capture_internal_exceptions,
@@ -22,7 +24,18 @@
 )
 
 if TYPE_CHECKING:
-    from typing import Any, Callable, Dict, Iterator, Optional, Protocol, Tuple, TypeVar
+    from typing import (
+        Any,
+        Callable,
+        ContextManager,
+        Dict,
+        Iterator,
+        Optional,
+        Protocol,
+        Tuple,
+        TypeVar,
+        Union,
+    )
 
     from sentry_sdk._types import Event, EventProcessor
     from sentry_sdk.utils import ExcInfo
@@ -42,6 +55,7 @@ def __call__(
 
 
 _wsgi_middleware_applied = ContextVar("sentry_wsgi_middleware_applied")
+_DEFAULT_TRANSACTION_NAME = "generic WSGI request"
 
 
 def wsgi_decoding_dance(s: str, charset: str = "utf-8", errors: str = "replace") -> str:
@@ -57,8 +71,12 @@ def get_request_url(
     path_info = environ.get("PATH_INFO", "").lstrip("/")
     path = f"{script_name}/{path_info}"
 
+    scheme = environ.get("wsgi.url_scheme")
+    if use_x_forwarded_for:
+        scheme = environ.get("HTTP_X_FORWARDED_PROTO", scheme)
+
     return "%s://%s/%s" % (
-        environ.get("wsgi.url_scheme"),
+        scheme,
         get_host(environ, use_x_forwarded_for),
         wsgi_decoding_dance(path).lstrip("/"),
     )
@@ -90,6 +108,9 @@ def __call__(
         if _wsgi_middleware_applied.get(False):
             return self.app(environ, start_response)
 
+        client = sentry_sdk.get_client()
+        span_streaming = has_span_streaming_enabled(client.options)
+
         _wsgi_middleware_applied.set(True)
         try:
             with sentry_sdk.isolation_scope() as scope:
@@ -104,34 +125,72 @@ def __call__(
                         )
 
                     method = environ.get("REQUEST_METHOD", "").upper()
-                    transaction = None
+
+                    span_ctx: "Optional[ContextManager[Union[Span, StreamedSpan, None]]]" = None
                     if method in self.http_methods_to_capture:
-                        transaction = continue_trace(
-                            environ,
-                            op=OP.HTTP_SERVER,
-                            name="generic WSGI request",
-                            source=TransactionSource.ROUTE,
-                            origin=self.span_origin,
-                        )
+                        if span_streaming:
+                            sentry_sdk.traces.continue_trace(
+                                dict(_get_headers(environ))
+                            )
+                            scope.set_custom_sampling_context({"wsgi_environ": environ})
+
+                            span_ctx = sentry_sdk.traces.start_span(
+                                name=_DEFAULT_TRANSACTION_NAME,
+                                attributes={
+                                    "sentry.span.source": SegmentSource.ROUTE,
+                                    "sentry.origin": self.span_origin,
+                                    "sentry.op": OP.HTTP_SERVER,
+                                },
+                            )
+                        else:
+                            transaction = continue_trace(
+                                environ,
+                                op=OP.HTTP_SERVER,
+                                name=_DEFAULT_TRANSACTION_NAME,
+                                source=TransactionSource.ROUTE,
+                                origin=self.span_origin,
+                            )
+
+                            span_ctx = sentry_sdk.start_transaction(
+                                transaction,
+                                custom_sampling_context={"wsgi_environ": environ},
+                            )
+
+                    span_ctx = span_ctx or nullcontext()
+
+                    with span_ctx as span:
+                        if isinstance(span, StreamedSpan):
+                            with capture_internal_exceptions():
+                                for attr, value in _get_request_attributes(
+                                    environ, self.use_x_forwarded_for
+                                ).items():
+                                    span.set_attribute(attr, value)
 
-                    transaction_context = (
-                        sentry_sdk.start_transaction(
-                            transaction,
-                            custom_sampling_context={"wsgi_environ": environ},
-                        )
-                        if transaction is not None
-                        else nullcontext()
-                    )
-                    with transaction_context:
                         try:
                             response = self.app(
                                 environ,
-                                partial(
-                                    _sentry_start_response, start_response, transaction
-                                ),
+                                partial(_sentry_start_response, start_response, span),
                             )
                         except BaseException:
                             reraise(*_capture_exception())
+                        finally:
+                            if isinstance(span, StreamedSpan):
+                                already_set = (
+                                    span.name != _DEFAULT_TRANSACTION_NAME
+                                    and span.get_attributes().get("sentry.span.source")
+                                    in [
+                                        SegmentSource.COMPONENT.value,
+                                        SegmentSource.ROUTE.value,
+                                        SegmentSource.CUSTOM.value,
+                                    ]
+                                )
+                                if not already_set:
+                                    with capture_internal_exceptions():
+                                        span.name = _DEFAULT_TRANSACTION_NAME
+                                        span.set_attribute(
+                                            "sentry.span.source",
+                                            SegmentSource.ROUTE.value,
+                                        )
         finally:
             _wsgi_middleware_applied.set(False)
 
@@ -163,15 +222,19 @@ def __call__(
 
 def _sentry_start_response(
     old_start_response: "StartResponse",
-    transaction: "Optional[Transaction]",
+    span: "Optional[Union[Span, StreamedSpan]]",
     status: str,
     response_headers: "WsgiResponseHeaders",
     exc_info: "Optional[WsgiExcInfo]" = None,
 ) -> "WsgiResponseIter":  # type: ignore[type-var]
     with capture_internal_exceptions():
         status_int = int(status.split(" ", 1)[0])
-        if transaction is not None:
-            transaction.set_http_status(status_int)
+        if span is not None:
+            if isinstance(span, StreamedSpan):
+                span.status = "error" if status_int >= 400 else "ok"
+                span.set_attribute("http.response.status_code", status_int)
+            else:
+                span.set_http_status(status_int)
 
     if exc_info is None:
         # The Django Rest Framework WSGI test client, and likely other
@@ -322,3 +385,50 @@ def event_processor(event: "Event", hint: "Dict[str, Any]") -> "Event":
         return event
 
     return event_processor
+
+
+def _get_request_attributes(
+    environ: "Dict[str, str]",
+    use_x_forwarded_for: bool = False,
+) -> "Dict[str, Any]":
+    """
+    Return span attributes related to the HTTP request from the WSGI environ.
+    """
+    attributes: "dict[str, Any]" = {}
+
+    method = environ.get("REQUEST_METHOD")
+    if method:
+        attributes["http.request.method"] = method.upper()
+
+    headers = _filter_headers(dict(_get_headers(environ)), use_annotated_value=False)
+    for header, value in headers.items():
+        attributes[f"http.request.header.{header.lower()}"] = value
+
+    query_string = environ.get("QUERY_STRING")
+    if query_string:
+        attributes["http.query"] = query_string
+
+    attributes["url.full"] = get_request_url(environ, use_x_forwarded_for)
+
+    url_scheme = environ.get("wsgi.url_scheme")
+    if url_scheme:
+        attributes["network.protocol.name"] = url_scheme
+
+    server_name = environ.get("SERVER_NAME")
+    if server_name:
+        attributes["server.address"] = server_name
+
+    server_port = environ.get("SERVER_PORT")
+    if server_port:
+        try:
+            attributes["server.port"] = int(server_port)
+        except ValueError:
+            pass
+
+    if should_send_default_pii():
+        client_ip = get_client_ip(environ)
+        if client_ip:
+            attributes["client.address"] = client_ip
+            attributes["user.ip_address"] = client_ip
+
+    return attributes
diff --git a/sentry_sdk/logger.py b/sentry_sdk/logger.py
index 4a90fef70b..ee6184105a 100644
--- a/sentry_sdk/logger.py
+++ b/sentry_sdk/logger.py
@@ -4,10 +4,10 @@
 from typing import Any, TYPE_CHECKING
 
 import sentry_sdk
-from sentry_sdk.utils import format_attribute, safe_repr, capture_internal_exceptions
+from sentry_sdk.utils import format_attribute, capture_internal_exceptions
 
 if TYPE_CHECKING:
-    from sentry_sdk._types import Attributes, Log
+    from sentry_sdk._types import Attributes
 
 
 OTEL_RANGES = [
diff --git a/sentry_sdk/metrics.py b/sentry_sdk/metrics.py
index 167e49da05..fb5f21ec4e 100644
--- a/sentry_sdk/metrics.py
+++ b/sentry_sdk/metrics.py
@@ -1,8 +1,8 @@
 import time
-from typing import Any, Optional, TYPE_CHECKING, Union
+from typing import Any, Optional, TYPE_CHECKING
 
 import sentry_sdk
-from sentry_sdk.utils import format_attribute, safe_repr
+from sentry_sdk.utils import format_attribute
 
 if TYPE_CHECKING:
     from sentry_sdk._types import Attributes, Metric, MetricType
diff --git a/sentry_sdk/profiler/continuous_profiler.py b/sentry_sdk/profiler/continuous_profiler.py
index a4c16a63d5..5a42785fdf 100644
--- a/sentry_sdk/profiler/continuous_profiler.py
+++ b/sentry_sdk/profiler/continuous_profiler.py
@@ -308,7 +308,7 @@ def reset_buffer(self) -> None:
 
     @property
     def profiler_id(self) -> "Union[str, None]":
-        if self.buffer is None:
+        if not self.running or self.buffer is None:
             return None
         return self.buffer.profiler_id
 
@@ -436,9 +436,9 @@ def run(self) -> None:
             # timestamp so we can use it next iteration
             last = time.perf_counter()
 
-        if self.buffer is not None:
-            self.buffer.flush()
-            self.buffer = None
+        buffer = self.buffer
+        if buffer is not None:
+            buffer.flush()
 
 
 class ThreadContinuousScheduler(ContinuousScheduler):
@@ -506,8 +506,6 @@ def teardown(self) -> None:
             self.thread.join()
             self.thread = None
 
-        self.buffer = None
-
 
 class GeventContinuousScheduler(ContinuousScheduler):
     """
@@ -580,8 +578,6 @@ def teardown(self) -> None:
             self.thread.join()
             self.thread = None
 
-        self.buffer = None
-
 
 PROFILE_BUFFER_SECONDS = 60
 
diff --git a/sentry_sdk/scope.py b/sentry_sdk/scope.py
index 3bc51c1af0..750e602127 100644
--- a/sentry_sdk/scope.py
+++ b/sentry_sdk/scope.py
@@ -30,10 +30,11 @@
     Baggage,
     has_tracing_enabled,
     has_span_streaming_enabled,
-    normalize_incoming_data,
+    is_ignored_span,
+    _make_sampling_decision,
     PropagationContext,
 )
-from sentry_sdk.traces import StreamedSpan
+from sentry_sdk.traces import _DEFAULT_PARENT_SPAN, StreamedSpan, NoOpStreamedSpan
 from sentry_sdk.tracing import (
     BAGGAGE_HEADER_NAME,
     SENTRY_TRACE_HEADER_NAME,
@@ -55,7 +56,6 @@
     has_metrics_enabled,
 )
 
-import typing
 from typing import TYPE_CHECKING, cast
 
 if TYPE_CHECKING:
@@ -581,8 +581,12 @@ def get_traceparent(self, *args: "Any", **kwargs: "Any") -> "Optional[str]":
         client = self.get_client()
 
         # If we have an active span, return traceparent from there
-        if has_tracing_enabled(client.options) and self.span is not None:
-            return self.span.to_traceparent()
+        if (
+            has_tracing_enabled(client.options)
+            and self.span is not None
+            and not isinstance(self.span, NoOpStreamedSpan)
+        ):
+            return self.span._to_traceparent()
 
         # else return traceparent from the propagation context
         return self.get_active_propagation_context().to_traceparent()
@@ -595,8 +599,12 @@ def get_baggage(self, *args: "Any", **kwargs: "Any") -> "Optional[Baggage]":
         client = self.get_client()
 
         # If we have an active span, return baggage from there
-        if has_tracing_enabled(client.options) and self.span is not None:
-            return self.span.to_baggage()
+        if (
+            has_tracing_enabled(client.options)
+            and self.span is not None
+            and not isinstance(self.span, NoOpStreamedSpan)
+        ):
+            return self.span._to_baggage()
 
         # else return baggage from the propagation context
         return self.get_active_propagation_context().get_baggage()
@@ -605,8 +613,12 @@ def get_trace_context(self) -> "Dict[str, Any]":
         """
         Returns the Sentry "trace" context from the Propagation Context.
         """
-        if has_tracing_enabled(self.get_client().options) and self._span is not None:
-            return self._span.get_trace_context()
+        if (
+            has_tracing_enabled(self.get_client().options)
+            and self._span is not None
+            and not isinstance(self._span, NoOpStreamedSpan)
+        ):
+            return self._span._get_trace_context()
 
         # if we are tracing externally (otel), those values take precedence
         external_propagation_context = get_external_propagation_context()
@@ -670,8 +682,12 @@ def iter_trace_propagation_headers(
         span = kwargs.pop("span", None)
         span = span or self.span
 
-        if has_tracing_enabled(client.options) and span is not None:
-            for header in span.iter_headers():
+        if (
+            has_tracing_enabled(client.options)
+            and span is not None
+            and not isinstance(span, NoOpStreamedSpan)
+        ):
+            for header in span._iter_headers():
                 yield header
         elif has_external_propagation_context():
             # when we have an external_propagation_context (otlp)
@@ -695,6 +711,13 @@ def get_active_propagation_context(self) -> "PropagationContext":
             isolation_scope._propagation_context = PropagationContext()
         return isolation_scope._propagation_context
 
+    def set_custom_sampling_context(
+        self, custom_sampling_context: "dict[str, Any]"
+    ) -> None:
+        self.get_current_scope().get_active_propagation_context()._set_custom_sampling_context(
+            custom_sampling_context
+        )
+
     def clear(self) -> None:
         """Clears the entire scope."""
         self._level: "Optional[LogLevelStr]" = None
@@ -711,7 +734,7 @@ def clear(self) -> None:
         self.clear_breadcrumbs()
         self._should_capture: bool = True
 
-        self._span: "Optional[Span]" = None
+        self._span: "Optional[Union[Span, StreamedSpan]]" = None
         self._session: "Optional[Session]" = None
         self._force_auto_session_tracking: "Optional[bool]" = None
 
@@ -765,6 +788,14 @@ def transaction(self) -> "Any":
         if self._span is None:
             return None
 
+        if isinstance(self._span, StreamedSpan):
+            warnings.warn(
+                "Scope.transaction is not available in streaming mode.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            return None
+
         # there is an orphan span on the scope
         if self._span.containing_transaction is None:
             return None
@@ -794,17 +825,36 @@ def transaction(self, value: "Any") -> None:
             "Assigning to scope.transaction directly is deprecated: use scope.set_transaction_name() instead."
         )
         self._transaction = value
-        if self._span and self._span.containing_transaction:
-            self._span.containing_transaction.name = value
+        if self._span:
+            if isinstance(self._span, StreamedSpan):
+                warnings.warn(
+                    "Scope.transaction is not available in streaming mode.",
+                    DeprecationWarning,
+                    stacklevel=2,
+                )
+                return None
+
+            if self._span.containing_transaction:
+                self._span.containing_transaction.name = value
 
     def set_transaction_name(self, name: str, source: "Optional[str]" = None) -> None:
         """Set the transaction name and optionally the transaction source."""
         self._transaction = name
-
-        if self._span and self._span.containing_transaction:
-            self._span.containing_transaction.name = name
-            if source:
-                self._span.containing_transaction.source = source
+        if self._span:
+            if isinstance(self._span, NoOpStreamedSpan):
+                return
+
+            elif isinstance(self._span, StreamedSpan):
+                self._span._segment.name = name
+                if source:
+                    self._span._segment.set_attribute(
+                        "sentry.span.source", getattr(source, "value", source)
+                    )
+
+            elif self._span.containing_transaction:
+                self._span.containing_transaction.name = name
+                if source:
+                    self._span.containing_transaction.source = source
 
         if source:
             self._transaction_info["source"] = source
@@ -827,12 +877,12 @@ def set_user(self, value: "Optional[Dict[str, Any]]") -> None:
             session.update(user=value)
 
     @property
-    def span(self) -> "Optional[Span]":
+    def span(self) -> "Optional[Union[Span, StreamedSpan]]":
         """Get/set current tracing span or transaction."""
         return self._span
 
     @span.setter
-    def span(self, span: "Optional[Span]") -> None:
+    def span(self, span: "Optional[Union[Span, StreamedSpan]]") -> None:
         self._span = span
         # XXX: this differs from the implementation in JS, there Scope.setSpan
         # does not set Scope._transactionName.
@@ -1141,6 +1191,15 @@ def start_span(
         be removed in the next major version. Going forward, it should only
         be used by the SDK itself.
         """
+        client = sentry_sdk.get_client()
+        if has_span_streaming_enabled(client.options):
+            warnings.warn(
+                "Scope.start_span is not available in streaming mode.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            return NoOpSpan()
+
         if kwargs.get("description") is not None:
             warnings.warn(
                 "The `description` parameter is deprecated. Please use `name` instead.",
@@ -1160,6 +1219,9 @@ def start_span(
 
             # get current span or transaction
             span = self.span or self.get_isolation_scope().span
+            if isinstance(span, StreamedSpan):
+                # make mypy happy
+                return NoOpSpan()
 
             if span is None:
                 # New spans get the `trace_id` from the scope
@@ -1174,6 +1236,96 @@ def start_span(
 
             return span
 
+    def start_streamed_span(
+        self,
+        name: str,
+        attributes: "Optional[Attributes]",
+        parent_span: "Optional[StreamedSpan]",
+        active: bool,
+    ) -> "StreamedSpan":
+        # TODO: rename to start_span once we drop the old API
+        if isinstance(parent_span, NoOpStreamedSpan):
+            # parent_span is only set if the user explicitly set it
+            logger.debug(
+                "Ignored parent span provided. Span will be parented to the "
+                "currently active span instead."
+            )
+
+        if parent_span is _DEFAULT_PARENT_SPAN or isinstance(
+            parent_span, NoOpStreamedSpan
+        ):
+            parent_span = self.span  # type: ignore
+
+        # If no eligible parent_span was provided and there is no currently
+        # active span, this is a segment
+        if parent_span is None:
+            propagation_context = self.get_active_propagation_context()
+
+            if is_ignored_span(name, attributes):
+                return NoOpStreamedSpan(
+                    scope=self,
+                    unsampled_reason="ignored",
+                )
+
+            sampled, sample_rate, sample_rand, outcome = _make_sampling_decision(
+                name,
+                attributes,
+                self,
+            )
+
+            if sample_rate is not None:
+                self._update_sample_rate(sample_rate)
+
+            if sampled is False:
+                return NoOpStreamedSpan(
+                    scope=self,
+                    unsampled_reason=outcome,
+                )
+
+            return StreamedSpan(
+                name=name,
+                attributes=attributes,
+                active=active,
+                scope=self,
+                segment=None,
+                trace_id=propagation_context.trace_id,
+                parent_span_id=propagation_context.parent_span_id,
+                parent_sampled=propagation_context.parent_sampled,
+                baggage=propagation_context.baggage,
+                sample_rand=sample_rand,
+                sample_rate=sample_rate,
+            )
+
+        # This is a child span; take propagation context from the parent span
+        with new_scope():
+            if is_ignored_span(name, attributes):
+                return NoOpStreamedSpan(
+                    unsampled_reason="ignored",
+                )
+
+            if isinstance(parent_span, NoOpStreamedSpan):
+                return NoOpStreamedSpan(unsampled_reason=parent_span._unsampled_reason)
+
+            return StreamedSpan(
+                name=name,
+                attributes=attributes,
+                active=active,
+                scope=self,
+                segment=parent_span._segment,
+                trace_id=parent_span.trace_id,
+                parent_span_id=parent_span.span_id,
+                parent_sampled=parent_span.sampled,
+            )
+
+    def _update_sample_rate(self, sample_rate: float) -> None:
+        # If we had to adjust the sample rate when setting the sampling decision
+        # for a span, it needs to be updated in the propagation context too
+        propagation_context = self.get_active_propagation_context()
+        baggage = propagation_context.baggage
+
+        if baggage is not None:
+            baggage.sentry_items["sample_rate"] = str(sample_rate)
+
     def continue_trace(
         self,
         environ_or_headers: "Dict[str, Any]",
diff --git a/sentry_sdk/traces.py b/sentry_sdk/traces.py
index e09d7191c3..f44ef71f5b 100644
--- a/sentry_sdk/traces.py
+++ b/sentry_sdk/traces.py
@@ -1,4 +1,6 @@
 """
+EXPERIMENTAL. Do not use in production.
+
 The API in this file is only meant to be used in span streaming mode.
 
 You can enable span streaming mode via
@@ -6,14 +8,39 @@
 """
 
 import uuid
+import warnings
+from datetime import datetime, timedelta, timezone
 from enum import Enum
 from typing import TYPE_CHECKING
 
-from sentry_sdk.utils import format_attribute, logger
+import sentry_sdk
+from sentry_sdk.consts import SPANDATA
+from sentry_sdk.profiler.continuous_profiler import (
+    get_profiler_id,
+    try_autostart_continuous_profiler,
+    try_profile_lifecycle_trace_start,
+)
+from sentry_sdk.tracing_utils import Baggage
+from sentry_sdk.utils import (
+    capture_internal_exceptions,
+    format_attribute,
+    get_current_thread_meta,
+    logger,
+    nanosecond_time,
+    should_be_treated_as_error,
+)
 
 if TYPE_CHECKING:
-    from typing import Optional, Union
+    from typing import Any, Callable, Iterator, Optional, ParamSpec, TypeVar, Union
     from sentry_sdk._types import Attributes, AttributeValue
+    from sentry_sdk.profiler.continuous_profiler import ContinuousProfile
+
+    P = ParamSpec("P")
+    R = TypeVar("R")
+
+
+BAGGAGE_HEADER_NAME = "baggage"
+SENTRY_TRACE_HEADER_NAME = "sentry-trace"
 
 
 class SpanStatus(str, Enum):
@@ -57,6 +84,132 @@ def __str__(self) -> str:
 }
 
 
+# Sentinel value for an unset parent_span to be able to distinguish it from
+# a None set by the user
+_DEFAULT_PARENT_SPAN = object()
+
+
+def start_span(
+    name: str,
+    attributes: "Optional[Attributes]" = None,
+    parent_span: "Optional[StreamedSpan]" = _DEFAULT_PARENT_SPAN,  # type: ignore[assignment]
+    active: bool = True,
+) -> "StreamedSpan":
+    """
+    Start a span.
+
+    EXPERIMENTAL. Use sentry_sdk.start_transaction() and sentry_sdk.start_span()
+    instead.
+
+    The span's parent, unless provided explicitly via the `parent_span` argument,
+    will be the current active span, if any. If there is none, this span will
+    become the root of a new span tree. If you explicitly want this span to be
+    top-level without a parent, set `parent_span=None`.
+
+    `start_span()` can either be used as context manager or you can use the span
+    object it returns and explicitly end it via `span.end()`. The following is
+    equivalent:
+
+    ```python
+    import sentry_sdk
+
+    with sentry_sdk.traces.start_span(name="My Span"):
+        # do something
+
+    # The span automatically finishes once the `with` block is exited
+    ```
+
+    ```python
+    import sentry_sdk
+
+    span = sentry_sdk.traces.start_span(name="My Span")
+    # do something
+    span.end()
+    ```
+
+    To continue a trace from another service, call
+    `sentry_sdk.traces.continue_trace()` prior to creating a top-level span.
+
+    :param name: The name to identify this span by.
+    :type name: str
+
+    :param attributes: Key-value attributes to set on the span from the start.
+        These will also be accessible in the traces sampler.
+    :type attributes: "Optional[Attributes]"
+
+    :param parent_span: A span instance that the new span should consider its
+        parent. If not provided, the parent will be set to the currently active
+        span, if any. If set to `None`, this span will become a new root-level
+        span.
+    :type parent_span: "Optional[StreamedSpan]"
+
+    :param active: Controls whether spans started while this span is running
+        will automatically become its children. That's the default behavior. If
+        you want to create a span that shouldn't have any children (unless
+        provided explicitly via the `parent_span` argument), set this to `False`.
+    :type active: bool
+
+    :return: The span that has been started.
+    :rtype: StreamedSpan
+    """
+    from sentry_sdk.tracing_utils import has_span_streaming_enabled
+
+    if not has_span_streaming_enabled(sentry_sdk.get_client().options):
+        warnings.warn(
+            "Using span streaming API in non-span-streaming mode. Use "
+            "sentry_sdk.start_transaction() and sentry_sdk.start_span() "
+            "instead.",
+            stacklevel=2,
+        )
+        return NoOpStreamedSpan()
+
+    return sentry_sdk.get_current_scope().start_streamed_span(
+        name, attributes, parent_span, active
+    )
+
+
+def continue_trace(incoming: "dict[str, Any]") -> None:
+    """
+    Continue a trace from headers or environment variables.
+
+    EXPERIMENTAL. Use sentry_sdk.continue_trace() instead.
+
+    This function sets the propagation context on the scope. Any span started
+    in the updated scope will belong under the trace extracted from the
+    provided propagation headers or environment variables.
+
+    continue_trace() doesn't start any spans on its own. Use the start_span()
+    API for that.
+    """
+    # This is set both on the isolation and the current scope for compatibility
+    # reasons. Conceptually, it belongs on the isolation scope, and it also
+    # used to be set there in non-span-first mode. But in span first mode, we
+    # start spans on the current scope, regardless of type, like JS does, so we
+    # need to set the propagation context there.
+    sentry_sdk.get_isolation_scope().generate_propagation_context(
+        incoming,
+    )
+    sentry_sdk.get_current_scope().generate_propagation_context(
+        incoming,
+    )
+
+
+def new_trace() -> None:
+    """
+    Resets the propagation context, forcing a new trace.
+
+    EXPERIMENTAL.
+
+    This function sets the propagation context on the scope. Any span started
+    in the updated scope will start its own trace.
+
+    new_trace() doesn't start any spans on its own. Use the start_span() API
+    for that.
+    """
+    sentry_sdk.get_isolation_scope().set_new_propagation_context()
+    sentry_sdk.get_current_scope().set_new_propagation_context()
+
+
 class StreamedSpan:
     """
     A span holds timing information of a block of code.
@@ -73,7 +226,19 @@ class StreamedSpan:
         "_active",
         "_span_id",
         "_trace_id",
+        "_parent_span_id",
+        "_segment",
+        "_parent_sampled",
+        "_start_timestamp",
+        "_start_timestamp_monotonic_ns",
+        "_timestamp",
         "_status",
+        "_scope",
+        "_previous_span_on_scope",
+        "_baggage",
+        "_sample_rand",
+        "_sample_rate",
+        "_continuous_profile",
     )
 
     def __init__(
@@ -82,20 +247,55 @@ def __init__(
         name: str,
         attributes: "Optional[Attributes]" = None,
         active: bool = True,
+        scope: "sentry_sdk.Scope",
+        segment: "Optional[StreamedSpan]" = None,
         trace_id: "Optional[str]" = None,
+        parent_span_id: "Optional[str]" = None,
+        parent_sampled: "Optional[bool]" = None,
+        baggage: "Optional[Baggage]" = None,
+        sample_rate: "Optional[float]" = None,
+        sample_rand: "Optional[float]" = None,
     ):
         self._name: str = name
         self._active: bool = active
         self._attributes: "Attributes" = {}
+
         if attributes:
             for attribute, value in attributes.items():
                 self.set_attribute(attribute, value)
 
-        self._span_id: "Optional[str]" = None
+        self._scope = scope
+
+        self._segment = segment or self
+
         self._trace_id: "Optional[str]" = trace_id
+        self._parent_span_id = parent_span_id
+        self._parent_sampled = parent_sampled
+        self._baggage = baggage
+        self._sample_rand = sample_rand
+        self._sample_rate = sample_rate
+
+        self._start_timestamp = datetime.now(timezone.utc)
+        self._timestamp: "Optional[datetime]" = None
+
+        try:
+            # profiling depends on this value and requires that
+            # it is measured in nanoseconds
+            self._start_timestamp_monotonic_ns = nanosecond_time()
+        except AttributeError:
+            pass
+
+        self._span_id: "Optional[str]" = None
 
         self._status = SpanStatus.OK.value
-        self.set_attribute("sentry.span.source", SegmentSource.CUSTOM.value)
+
+        self._update_active_thread()
+
+        self._continuous_profile: "Optional[ContinuousProfile]" = None
+        self._start_profile()
+        self._set_profile_id(get_profiler_id())
+
+        self._start()
 
     def __repr__(self) -> str:
         return (
@@ -103,9 +303,103 @@ def __repr__(self) -> str:
             f"name={self._name}, "
             f"trace_id={self.trace_id}, "
             f"span_id={self.span_id}, "
+            f"parent_span_id={self._parent_span_id}, "
             f"active={self._active})>"
         )
 
+    def __enter__(self) -> "StreamedSpan":
+        return self
+
+    def __exit__(
+        self, ty: "Optional[Any]", value: "Optional[Any]", tb: "Optional[Any]"
+    ) -> None:
+        if self._timestamp is not None:
+            # This span is already finished, ignore
+            return
+
+        if value is not None and should_be_treated_as_error(ty, value):
+            self.status = SpanStatus.ERROR.value
+
+        self._end()
+
+    def end(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        """
+        Finish this span and queue it for sending.
+
+        :param end_timestamp: End timestamp to use instead of current time.
+        :type end_timestamp: "Optional[Union[float, datetime]]"
+        """
+        self._end(end_timestamp)
+
+    def finish(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        warnings.warn(
+            "span.finish() is deprecated. Use span.end() instead.",
+            stacklevel=2,
+            category=DeprecationWarning,
+        )
+
+        self.end(end_timestamp)
+
+    def _start(self) -> None:
+        if self._active:
+            old_span = self._scope.span
+            self._scope.span = self
+            self._previous_span_on_scope = old_span
+
+    def _end(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        if self._timestamp is not None:
+            # This span is already finished, ignore.
+            return
+
+        # Stop the profiler
+        if self._is_segment() and self._continuous_profile is not None:
+            with capture_internal_exceptions():
+                self._continuous_profile.stop()
+
+        # Detach from scope
+        if self._active:
+            with capture_internal_exceptions():
+                old_span = self._previous_span_on_scope
+                del self._previous_span_on_scope
+                self._scope.span = old_span
+
+        # Set attributes from the segment. These are set on span end on purpose
+        # so that we have the best chance to capture the segment's final name
+        # (since it might change during its lifetime)
+        self.set_attribute("sentry.segment.id", self._segment.span_id)
+        self.set_attribute("sentry.segment.name", self._segment.name)
+
+        # Set the end timestamp
+        if end_timestamp is not None:
+            if isinstance(end_timestamp, (float, int)):
+                try:
+                    end_timestamp = datetime.fromtimestamp(end_timestamp, timezone.utc)
+                except Exception:
+                    pass
+
+            if isinstance(end_timestamp, datetime):
+                self._timestamp = end_timestamp
+            else:
+                logger.debug(
+                    "[Tracing] Failed to set end_timestamp. Using current time instead."
+                )
+
+        if self._timestamp is None:
+            try:
+                elapsed = nanosecond_time() - self._start_timestamp_monotonic_ns
+                self._timestamp = self._start_timestamp + timedelta(
+                    microseconds=elapsed / 1000
+                )
+            except AttributeError:
+                self._timestamp = datetime.now(timezone.utc)
+
+        client = sentry_sdk.get_client()
+        if not client.is_active():
+            return
+
+        # Finally, queue the span for sending to Sentry
+        self._scope._capture_span(self)
+
     def get_attributes(self) -> "Attributes":
         return self._attributes
 
@@ -133,7 +427,7 @@ def status(self, status: "Union[SpanStatus, str]") -> None:
 
         if status not in {e.value for e in SpanStatus}:
             logger.debug(
-                f'Unsupported span status {status}. Expected one of: "ok", "error"'
+                f'[Tracing] Unsupported span status {status}. Expected one of: "ok", "error"'
             )
             return
 
@@ -165,8 +459,177 @@ def trace_id(self) -> str:
 
         return self._trace_id
 
+    @property
+    def sampled(self) -> "Optional[bool]":
+        return True
+
+    @property
+    def start_timestamp(self) -> "Optional[datetime]":
+        return self._start_timestamp
+
+    @property
+    def timestamp(self) -> "Optional[datetime]":
+        return self._timestamp
+
+    def _is_segment(self) -> bool:
+        return self._segment is self
+
+    def _update_active_thread(self) -> None:
+        thread_id, thread_name = get_current_thread_meta()
+
+        if thread_id is not None:
+            self.set_attribute(SPANDATA.THREAD_ID, str(thread_id))
+
+            if thread_name is not None:
+                self.set_attribute(SPANDATA.THREAD_NAME, thread_name)
+
+    def _dynamic_sampling_context(self) -> "dict[str, str]":
+        return self._segment._get_baggage().dynamic_sampling_context()
+
+    def _to_traceparent(self) -> str:
+        if self.sampled is True:
+            sampled = "1"
+        elif self.sampled is False:
+            sampled = "0"
+        else:
+            sampled = None
+
+        traceparent = "%s-%s" % (self.trace_id, self.span_id)
+        if sampled is not None:
+            traceparent += "-%s" % (sampled,)
+
+        return traceparent
+
+    def _to_baggage(self) -> "Optional[Baggage]":
+        if self._segment:
+            return self._segment._get_baggage()
+        return None
+
+    def _get_baggage(self) -> "Baggage":
+        """
+        Return the :py:class:`~sentry_sdk.tracing_utils.Baggage` associated with
+        the segment.
+
+        The first time a new baggage with Sentry items is made, it will be frozen.
+        """
+        if not self._baggage or self._baggage.mutable:
+            self._baggage = Baggage.populate_from_segment(self)
+
+        return self._baggage
+
+    def _iter_headers(self) -> "Iterator[tuple[str, str]]":
+        if not self._segment:
+            return
+
+        yield SENTRY_TRACE_HEADER_NAME, self._to_traceparent()
+
+        baggage = self._segment._get_baggage().serialize()
+        if baggage:
+            yield BAGGAGE_HEADER_NAME, baggage
+
+    def _get_trace_context(self) -> "dict[str, Any]":
+        # Even if spans themselves are not event-based anymore, we need this
+        # to populate trace context on events
+        context: "dict[str, Any]" = {
+            "trace_id": self.trace_id,
+            "span_id": self.span_id,
+            "parent_span_id": self._parent_span_id,
+            "dynamic_sampling_context": self._dynamic_sampling_context(),
+        }
+
+        if "sentry.op" in self._attributes:
+            context["op"] = self._attributes["sentry.op"]
+        if "sentry.origin" in self._attributes:
+            context["origin"] = self._attributes["sentry.origin"]
+
+        return context
+
+    def _set_profile_id(self, profiler_id: "Optional[str]") -> None:
+        if profiler_id is not None:
+            self.set_attribute("sentry.profiler_id", profiler_id)
+
+    def _start_profile(self) -> None:
+        if not self._is_segment():
+            return
+
+        try_autostart_continuous_profiler()
+
+        self._continuous_profile = try_profile_lifecycle_trace_start()
+
 
 class NoOpStreamedSpan(StreamedSpan):
+    __slots__ = (
+        "_finished",
+        "_unsampled_reason",
+    )
+
+    def __init__(
+        self,
+        unsampled_reason: "Optional[str]" = None,
+        scope: "Optional[sentry_sdk.Scope]" = None,
+    ) -> None:
+        self._scope = scope  # type: ignore[assignment]
+        self._unsampled_reason = unsampled_reason
+
+        self._finished = False
+
+        self._start()
+
+    def __repr__(self) -> str:
+        return f"<{self.__class__.__name__}(sampled={self.sampled})>"
+
+    def __enter__(self) -> "NoOpStreamedSpan":
+        return self
+
+    def __exit__(
+        self, ty: "Optional[Any]", value: "Optional[Any]", tb: "Optional[Any]"
+    ) -> None:
+        self._end()
+
+    def _start(self) -> None:
+        if self._scope is None:
+            return
+
+        old_span = self._scope.span
+        self._scope.span = self
+        self._previous_span_on_scope = old_span
+
+    def _end(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        if self._finished:
+            return
+
+        if self._unsampled_reason is not None:
+            client = sentry_sdk.get_client()
+            if client.is_active() and client.transport:
+                logger.debug(
+                    f"[Tracing] Discarding span because sampled=False (reason: {self._unsampled_reason})"
+                )
+                client.transport.record_lost_event(
+                    reason=self._unsampled_reason,
+                    data_category="span",
+                    quantity=1,
+                )
+
+        if self._scope and hasattr(self, "_previous_span_on_scope"):
+            with capture_internal_exceptions():
+                old_span = self._previous_span_on_scope
+                del self._previous_span_on_scope
+                self._scope.span = old_span
+
+        self._finished = True
+
+    def end(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        self._end()
+
+    def finish(self, end_timestamp: "Optional[Union[float, datetime]]" = None) -> None:
+        warnings.warn(
+            "span.finish() is deprecated. Use span.end() instead.",
+            stacklevel=2,
+            category=DeprecationWarning,
+        )
+
+        self._end()
+
     def get_attributes(self) -> "Attributes":
         return {}
 
@@ -179,6 +642,9 @@ def set_attributes(self, attributes: "Attributes") -> None:
     def remove_attribute(self, key: str) -> None:
         pass
 
+    def _is_segment(self) -> bool:
+        return self._scope is not None
+
     @property
     def status(self) -> "str":
         return SpanStatus.OK.value
@@ -206,3 +672,90 @@ def span_id(self) -> str:
     @property
     def trace_id(self) -> str:
         return "00000000000000000000000000000000"
+
+    @property
+    def sampled(self) -> "Optional[bool]":
+        return False
+
+    @property
+    def start_timestamp(self) -> "Optional[datetime]":
+        return None
+
+    @property
+    def timestamp(self) -> "Optional[datetime]":
+        return None
+
+
+def trace(
+    func: "Optional[Callable[P, R]]" = None,
+    *,
+    name: "Optional[str]" = None,
+    attributes: "Optional[dict[str, Any]]" = None,
+    active: bool = True,
+) -> "Union[Callable[P, R], Callable[[Callable[P, R]], Callable[P, R]]]":
+    """
+    Decorator to start a span around a function call.
+
+    EXPERIMENTAL. Use @sentry_sdk.trace instead.
+
+    This decorator automatically creates a new span when the decorated function
+    is called, and finishes the span when the function returns or raises an exception.
+
+    :param func: The function to trace. When used as a decorator without parentheses,
+        this is the function being decorated. When used with parameters (e.g.,
+        ``@trace(op="custom")``, this should be None.
+    :type func: Callable or None
+
+    :param name: The human-readable name/description for the span. If not provided,
+        defaults to the function name. This provides more specific details about
+        what the span represents (e.g., "GET /api/users", "process_user_data").
+    :type name: str or None
+
+    :param attributes: A dictionary of key-value pairs to add as attributes to the span.
+        Attribute values must be strings, integers, floats, or booleans. These
+        attributes provide additional context about the span's execution.
+    :type attributes: dict[str, Any] or None
+
+    :param active: Controls whether spans started while this span is running
+        will automatically become its children. That's the default behavior. If
+        you want to create a span that shouldn't have any children (unless
+        provided explicitly via the `parent_span` argument), set this to False.
+    :type active: bool
+
+    :returns: When used as ``@trace``, returns the decorated function. When used as
+        ``@trace(...)`` with parameters, returns a decorator function.
+    :rtype: Callable or decorator function
+
+    Example::
+
+        import sentry_sdk
+
+        # Simple usage with default values
+        @sentry_sdk.trace
+        def process_data():
+            # Function implementation
+            pass
+
+        # With custom parameters
+        @sentry_sdk.trace(
+            name="Get user data",
+            attributes={"postgres": True}
+        )
+        def make_db_query(sql):
+            # Function implementation
+            pass
+    """
+    from sentry_sdk.tracing_utils import (
+        create_streaming_span_decorator,
+    )
+
+    decorator = create_streaming_span_decorator(
+        name=name,
+        attributes=attributes,
+        active=active,
+    )
+
+    if func:
+        return decorator(func)
+    else:
+        return decorator
diff --git a/sentry_sdk/tracing.py b/sentry_sdk/tracing.py
index a778da7361..7f2baba0c9 100644
--- a/sentry_sdk/tracing.py
+++ b/sentry_sdk/tracing.py
@@ -25,7 +25,6 @@
         List,
         Optional,
         ParamSpec,
-        Set,
         Tuple,
         TypeVar,
         Union,
@@ -771,6 +770,12 @@ def update_active_thread(self) -> None:
         thread_id, thread_name = get_current_thread_meta()
         self.set_thread(thread_id, thread_name)
 
+    # Private aliases matching StreamedSpan's private API
+    _to_traceparent = to_traceparent
+    _to_baggage = to_baggage
+    _iter_headers = iter_headers
+    _get_trace_context = get_trace_context
+
 
 class Transaction(Span):
     """The Transaction is the root element that holds all the spans
@@ -1243,6 +1248,10 @@ def _set_initial_sampling_decision(
                 )
             )
 
+    # Private aliases matching StreamedSpan's private API
+    _get_baggage = get_baggage
+    _get_trace_context = get_trace_context
+
 
 class NoOpSpan(Span):
     def __repr__(self) -> str:
@@ -1324,6 +1333,13 @@ def _set_initial_sampling_decision(
     ) -> None:
         pass
 
+    # Private aliases matching StreamedSpan's private API
+    _to_traceparent = to_traceparent
+    _to_baggage = to_baggage
+    _get_baggage = get_baggage
+    _iter_headers = iter_headers
+    _get_trace_context = get_trace_context
+
 
 if TYPE_CHECKING:
 
diff --git a/sentry_sdk/tracing_utils.py b/sentry_sdk/tracing_utils.py
index c1d6c44535..9efb01000c 100644
--- a/sentry_sdk/tracing_utils.py
+++ b/sentry_sdk/tracing_utils.py
@@ -4,12 +4,19 @@
 import os
 import re
 import sys
+import warnings
 from collections.abc import Mapping, MutableMapping
 from datetime import timedelta
 from random import Random
 from urllib.parse import quote, unquote
 import uuid
 
+try:
+    from re import Pattern
+except ImportError:
+    # 3.6
+    from typing import Pattern
+
 import sentry_sdk
 from sentry_sdk.consts import OP, SPANDATA, SPANSTATUS, SPANTEMPLATE
 from sentry_sdk.utils import (
@@ -22,6 +29,7 @@
     to_string,
     try_convert,
     is_sentry_url,
+    is_valid_sample_rate,
     _is_external_source,
     _is_in_project_root,
     _module_in_list,
@@ -40,6 +48,8 @@
 
     from types import FrameType
 
+    from sentry_sdk._types import Attributes
+
 
 SENTRY_TRACE_REGEX = re.compile(
     "^[ \t]*"  # whitespace
@@ -413,6 +423,7 @@ class PropagationContext:
         "parent_span_id",
         "parent_sampled",
         "baggage",
+        "custom_sampling_context",
     )
 
     def __init__(
@@ -446,6 +457,8 @@ def __init__(
         if baggage is None and dynamic_sampling_context is not None:
             self.baggage = Baggage(dynamic_sampling_context)
 
+        self.custom_sampling_context: "Optional[dict[str, Any]]" = None
+
     @classmethod
     def from_incoming_data(
         cls, incoming_data: "Dict[str, Any]"
@@ -533,6 +546,11 @@ def update(self, other_dict: "Dict[str, Any]") -> None:
             except AttributeError:
                 pass
 
+    def _set_custom_sampling_context(
+        self, custom_sampling_context: "dict[str, Any]"
+    ) -> None:
+        self.custom_sampling_context = custom_sampling_context
+
     def __repr__(self) -> str:
         return "<PropagationContext _trace_id={} _span_id={} parent_span_id={} parent_sampled={} baggage={}>".format(
             self._trace_id,
@@ -749,6 +767,55 @@ def populate_from_transaction(
 
         return Baggage(sentry_items, mutable=False)
 
+    @classmethod
+    def populate_from_segment(cls, segment: "StreamedSpan") -> "Baggage":
+        """
+        Populate fresh baggage entry with sentry_items and make it immutable
+        if this is the head SDK which originates traces.
+        """
+        client = sentry_sdk.get_client()
+        sentry_items: "Dict[str, str]" = {}
+
+        if not client.is_active():
+            return Baggage(sentry_items)
+
+        options = client.options or {}
+
+        sentry_items["trace_id"] = segment.trace_id
+        sentry_items["sample_rand"] = f"{segment._sample_rand:.6f}"  # noqa: E231
+
+        if options.get("environment"):
+            sentry_items["environment"] = options["environment"]
+
+        if options.get("release"):
+            sentry_items["release"] = options["release"]
+
+        if client.parsed_dsn:
+            sentry_items["public_key"] = client.parsed_dsn.public_key
+            if client.parsed_dsn.org_id:
+                sentry_items["org_id"] = client.parsed_dsn.org_id
+
+        if (
+            segment.get_attributes().get("sentry.span.source")
+            not in LOW_QUALITY_SEGMENT_SOURCES
+        ) and segment._name:
+            sentry_items["transaction"] = segment._name
+
+        if segment._sample_rate is not None:
+            sentry_items["sample_rate"] = str(segment._sample_rate)
+
+        if segment.sampled is not None:
+            sentry_items["sampled"] = "true" if segment.sampled else "false"
+
+        # There's an existing baggage but it was mutable, which is why we are
+        # creating this new baggage.
+        # However, if by chance the user put some sentry items in there, give
+        # them precedence.
+        if segment._baggage and segment._baggage.sentry_items:
+            sentry_items.update(segment._baggage.sentry_items)
+
+        return Baggage(sentry_items, mutable=False)
+
     def freeze(self) -> None:
         self.mutable = False
 
@@ -872,6 +939,14 @@ async def async_wrapper(*args: "Any", **kwargs: "Any") -> "Any":
                 )
                 return await f(*args, **kwargs)
 
+            if isinstance(current_span, StreamedSpan):
+                warnings.warn(
+                    "Use the @sentry_sdk.traces.trace decorator in span streaming mode.",
+                    DeprecationWarning,
+                    stacklevel=2,
+                )
+                return await f(*args, **kwargs)
+
             span_op = op or _get_span_op(template)
             function_name = name or qualname_from_function(f) or ""
             span_name = _get_span_name(template, function_name, kwargs)
@@ -909,6 +984,14 @@ def sync_wrapper(*args: "Any", **kwargs: "Any") -> "Any":
                 )
                 return f(*args, **kwargs)
 
+            if isinstance(current_span, StreamedSpan):
+                warnings.warn(
+                    "Use the @sentry_sdk.traces.trace decorator in span streaming mode.",
+                    DeprecationWarning,
+                    stacklevel=2,
+                )
+                return f(*args, **kwargs)
+
             span_op = op or _get_span_op(template)
             function_name = name or qualname_from_function(f) or ""
             span_name = _get_span_name(template, function_name, kwargs)
@@ -942,7 +1025,76 @@ def sync_wrapper(*args: "Any", **kwargs: "Any") -> "Any":
     return span_decorator
 
 
-def get_current_span(scope: "Optional[sentry_sdk.Scope]" = None) -> "Optional[Span]":
+def create_streaming_span_decorator(
+    name: "Optional[str]" = None,
+    attributes: "Optional[dict[str, Any]]" = None,
+    active: bool = True,
+) -> "Any":
+    """
+    Create a span creating decorator that can wrap both sync and async functions.
+    """
+
+    def span_decorator(f: "Any") -> "Any":
+        """
+        Decorator to create a span for the given function.
+        """
+
+        @functools.wraps(f)
+        async def async_wrapper(*args: "Any", **kwargs: "Any") -> "Any":
+            client = sentry_sdk.get_client()
+            if not has_span_streaming_enabled(client.options):
+                warnings.warn(
+                    "Using span streaming API in non-span-streaming mode. Use "
+                    "@sentry_sdk.trace instead.",
+                    stacklevel=2,
+                )
+
+            span_name = name or qualname_from_function(f) or ""
+
+            with start_streaming_span(
+                name=span_name, attributes=attributes, active=active
+            ):
+                result = await f(*args, **kwargs)
+                return result
+
+        try:
+            async_wrapper.__signature__ = inspect.signature(f)  # type: ignore[attr-defined]
+        except Exception:
+            pass
+
+        @functools.wraps(f)
+        def sync_wrapper(*args: "Any", **kwargs: "Any") -> "Any":
+            client = sentry_sdk.get_client()
+            if not has_span_streaming_enabled(client.options):
+                warnings.warn(
+                    "Using span streaming API in non-span-streaming mode. Use "
+                    "@sentry_sdk.trace instead.",
+                    stacklevel=2,
+                )
+
+            span_name = name or qualname_from_function(f) or ""
+
+            with start_streaming_span(
+                name=span_name, attributes=attributes, active=active
+            ):
+                return f(*args, **kwargs)
+
+        try:
+            sync_wrapper.__signature__ = inspect.signature(f)  # type: ignore[attr-defined]
+        except Exception:
+            pass
+
+        if inspect.iscoroutinefunction(f):
+            return async_wrapper
+        else:
+            return sync_wrapper
+
+    return span_decorator
+
+
+def get_current_span(
+    scope: "Optional[sentry_sdk.Scope]" = None,
+) -> "Optional[Union[Span, StreamedSpan]]":
     """
     Returns the currently active span if there is one running, otherwise `None`
     """
@@ -951,16 +1103,24 @@ def get_current_span(scope: "Optional[sentry_sdk.Scope]" = None) -> "Optional[Sp
     return current_span
 
 
-def set_span_errored(span: "Optional[Span]" = None) -> None:
+def set_span_errored(span: "Optional[Union[Span, StreamedSpan]]" = None) -> None:
     """
     Set the status of the current or given span to INTERNAL_ERROR.
     Also sets the status of the transaction (root span) to INTERNAL_ERROR.
     """
+    from sentry_sdk.traces import StreamedSpan, SpanStatus
+
     span = span or get_current_span()
+
     if span is not None:
-        span.set_status(SPANSTATUS.INTERNAL_ERROR)
-        if span.containing_transaction is not None:
-            span.containing_transaction.set_status(SPANSTATUS.INTERNAL_ERROR)
+        if isinstance(span, Span):
+            span.set_status(SPANSTATUS.INTERNAL_ERROR)
+            if span.containing_transaction is not None:
+                span.containing_transaction.set_status(SPANSTATUS.INTERNAL_ERROR)
+        elif isinstance(span, StreamedSpan):
+            span.status = SpanStatus.ERROR
+            if span._segment is not None:
+                span._segment.status = SpanStatus.ERROR
 
 
 def _generate_sample_rand(
@@ -1311,11 +1471,150 @@ def add_sentry_baggage_to_headers(
     )
 
 
+def _make_sampling_decision(
+    name: str,
+    attributes: "Optional[Attributes]",
+    scope: "sentry_sdk.Scope",
+) -> "tuple[bool, Optional[float], Optional[float], Optional[str]]":
+    """
+    Decide whether a span should be sampled.
+
+    Returns a tuple with:
+    1. the sampling decision
+    2. the effective sample rate
+    3. the sample rand
+    4. the reason for not sampling the span, if unsampled
+    """
+    client = sentry_sdk.get_client()
+
+    if not has_tracing_enabled(client.options):
+        return False, None, None, None
+
+    propagation_context = scope.get_active_propagation_context()
+
+    sample_rand = None
+    if propagation_context.baggage is not None:
+        sample_rand = propagation_context.baggage._sample_rand()
+    if sample_rand is None:
+        sample_rand = _generate_sample_rand(propagation_context.trace_id)
+
+    # If there's a traces_sampler, use that; otherwise use traces_sample_rate
+    traces_sampler_defined = callable(client.options.get("traces_sampler"))
+    if traces_sampler_defined:
+        sampling_context = {
+            "span_context": {
+                "name": name,
+                "trace_id": propagation_context.trace_id,
+                "parent_span_id": propagation_context.parent_span_id,
+                "parent_sampled": propagation_context.parent_sampled,
+                "attributes": dict(attributes) if attributes else {},
+            },
+        }
+
+        if propagation_context.custom_sampling_context:
+            sampling_context.update(propagation_context.custom_sampling_context)
+
+        sample_rate = client.options["traces_sampler"](sampling_context)
+    else:
+        if propagation_context.parent_sampled is not None:
+            sample_rate = propagation_context.parent_sampled
+        else:
+            sample_rate = client.options["traces_sample_rate"]
+
+    # Validate whether the sample_rate we got is actually valid. Since
+    # traces_sampler is user-provided, it could return anything.
+    if not is_valid_sample_rate(sample_rate, source="Tracing"):
+        logger.warning(f"[Tracing] Discarding {name} because of invalid sample rate.")
+        return False, None, None, "sample_rate"
+
+    sample_rate = float(sample_rate)
+    if not sample_rate:
+        if traces_sampler_defined:
+            reason = "traces_sampler returned 0 or False"
+        else:
+            reason = "traces_sample_rate is set to 0"
+
+        logger.debug(f"[Tracing] Discarding {name} because {reason}")
+        return False, 0.0, None, "sample_rate"
+
+    # Adjust sample rate if we're under backpressure
+    if client.monitor:
+        sample_rate /= 2**client.monitor.downsample_factor
+
+        if not sample_rate:
+            logger.debug(f"[Tracing] Discarding {name} because backpressure")
+            return False, 0.0, None, "backpressure"
+
+    sampled = sample_rand < sample_rate
+
+    if sampled:
+        logger.debug(f"[Tracing] Starting {name}")
+        outcome = None
+    else:
+        logger.debug(
+            f"[Tracing] Discarding {name} because it's not included in the random sample (sampling rate = {sample_rate})"
+        )
+        outcome = "sample_rate"
+
+    return sampled, sample_rate, sample_rand, outcome
+
+
+def is_ignored_span(name: str, attributes: "Optional[Attributes]") -> bool:
+    """Determine if a span fits one of the rules in ignore_spans."""
+    client = sentry_sdk.get_client()
+    ignore_spans = (client.options.get("_experiments") or {}).get("ignore_spans")
+
+    if not ignore_spans:
+        return False
+
+    def _matches(rule: "Any", value: "Any") -> bool:
+        if isinstance(rule, Pattern):
+            if isinstance(value, str):
+                return bool(rule.fullmatch(value))
+            else:
+                return False
+
+        return rule == value
+
+    for rule in ignore_spans:
+        if isinstance(rule, (str, Pattern)):
+            if _matches(rule, name):
+                return True
+
+        elif isinstance(rule, dict) and ("name" in rule or "attributes" in rule):
+            name_matches = True
+            attributes_match = True
+
+            attributes = attributes or {}
+
+            if "name" in rule:
+                name_matches = _matches(rule["name"], name)
+
+            if "attributes" in rule:
+                for attribute, value in rule["attributes"].items():
+                    if attribute not in attributes or not _matches(
+                        value, attributes[attribute]
+                    ):
+                        attributes_match = False
+                        break
+
+            if name_matches and attributes_match:
+                return True
+
+    return False
+
+
 # Circular imports
 from sentry_sdk.tracing import (
     BAGGAGE_HEADER_NAME,
     LOW_QUALITY_TRANSACTION_SOURCES,
     SENTRY_TRACE_HEADER_NAME,
+    Span,
+)
+from sentry_sdk.traces import (
+    LOW_QUALITY_SEGMENT_SOURCES,
+    StreamedSpan,
+    start_span as start_streaming_span,
 )
 
 if TYPE_CHECKING:
diff --git a/sentry_sdk/transport.py b/sentry_sdk/transport.py
index dcfe55406b..c9fb596c44 100644
--- a/sentry_sdk/transport.py
+++ b/sentry_sdk/transport.py
@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+import asyncio
 import io
 import os
 import gzip
@@ -15,13 +16,37 @@
 except ImportError:
     brotli = None
 
+try:
+    import httpcore
+except ImportError:
+    httpcore = None  # type: ignore[assignment,unused-ignore]
+
+try:
+    import h2  # noqa: F401
+
+    HTTP2_ENABLED = httpcore is not None
+except ImportError:
+    HTTP2_ENABLED = False
+
+try:
+    import anyio  # noqa: F401
+
+    ASYNC_TRANSPORT_AVAILABLE = httpcore is not None
+except ImportError:
+    ASYNC_TRANSPORT_AVAILABLE = False
+
 import urllib3
 import certifi
 
 import sentry_sdk
 from sentry_sdk.consts import EndpointType
-from sentry_sdk.utils import Dsn, logger, capture_internal_exceptions
-from sentry_sdk.worker import BackgroundWorker
+from sentry_sdk.utils import (
+    Dsn,
+    logger,
+    capture_internal_exceptions,
+    mark_sentry_task_internal,
+)
+from sentry_sdk.worker import BackgroundWorker, Worker, AsyncWorker
 from sentry_sdk.envelope import Envelope, Item, PayloadRef
 
 from typing import TYPE_CHECKING, cast, List, Dict
@@ -58,6 +83,19 @@
         pass
 
 
+def _get_httpcore_header_value(response: "Any", header: str) -> "Optional[str]":
+    """Case-insensitive header lookup for httpcore-style responses."""
+    header_lower = header.lower()
+    return next(
+        (
+            val.decode("ascii")
+            for key, val in response.headers
+            if key.decode("ascii").lower() == header_lower
+        ),
+        None,
+    )
+
+
 class Transport(ABC):
     """Baseclass for all transports.
 
@@ -170,8 +208,8 @@ def _parse_rate_limits(
             continue
 
 
-class BaseHttpTransport(Transport):
-    """The base HTTP transport."""
+class HttpTransportCore(Transport):
+    """Shared base class for sync and async transports."""
 
     TIMEOUT = 30  # seconds
 
@@ -181,7 +219,7 @@ def __init__(self: "Self", options: "Dict[str, Any]") -> None:
         Transport.__init__(self, options)
         assert self.parsed_dsn is not None
         self.options: "Dict[str, Any]" = options
-        self._worker = BackgroundWorker(queue_size=options["transport_queue_size"])
+        self._worker = self._create_worker(options)
         self._auth = self.parsed_dsn.to_auth("sentry.python/%s" % VERSION)
         self._disabled_until: "Dict[Optional[EventDataCategory], datetime]" = {}
         # We only use this Retry() class for the `get_retry_after` method it exposes
@@ -235,6 +273,9 @@ def __init__(self: "Self", options: "Dict[str, Any]") -> None:
         elif self._compression_algo == "br":
             self._compression_level = 4
 
+    def _create_worker(self: "Self", options: "Dict[str, Any]") -> "Worker":
+        raise NotImplementedError()
+
     def record_lost_event(
         self,
         reason: str,
@@ -305,12 +346,11 @@ def _update_rate_limits(
                 seconds=retry_after
             )
 
-    def _send_request(
+    def _handle_request_error(
         self: "Self",
-        body: bytes,
-        headers: "Dict[str, str]",
-        endpoint_type: "EndpointType" = EndpointType.ENVELOPE,
-        envelope: "Optional[Envelope]" = None,
+        envelope: "Optional[Envelope]",
+        loss_reason: str = "network",
+        record_reason: str = "network_error",
     ) -> None:
         def record_loss(reason: str) -> None:
             if envelope is None:
@@ -319,59 +359,59 @@ def record_loss(reason: str) -> None:
                 for item in envelope.items:
                     self.record_lost_event(reason, item=item)
 
+        self.on_dropped_event(loss_reason)
+        record_loss(record_reason)
+
+    def _handle_response(
+        self: "Self",
+        response: "Union[urllib3.BaseHTTPResponse, httpcore.Response]",
+        envelope: "Optional[Envelope]",
+    ) -> None:
+        self._update_rate_limits(response)
+
+        if response.status == 413:
+            size_exceeded_message = (
+                "HTTP 413: Event dropped due to exceeded envelope size limit"
+            )
+            response_message = getattr(
+                response, "data", getattr(response, "content", None)
+            )
+            if response_message is not None:
+                size_exceeded_message += f" (body: {response_message})"
+
+            logger.error(size_exceeded_message)
+            self._handle_request_error(
+                envelope=envelope, loss_reason="status_413", record_reason="send_error"
+            )
+
+        elif response.status == 429:
+            # if we hit a 429.  Something was rate limited but we already
+            # acted on this in `self._update_rate_limits`.  Note that we
+            # do not want to record event loss here as we will have recorded
+            # an outcome in relay already.
+            self.on_dropped_event("status_429")
+            pass
+
+        elif response.status >= 300 or response.status < 200:
+            logger.error(
+                "Unexpected status code: %s (body: %s)",
+                response.status,
+                getattr(response, "data", getattr(response, "content", None)),
+            )
+            self._handle_request_error(
+                envelope=envelope, loss_reason="status_{}".format(response.status)
+            )
+
+    def _update_headers(
+        self: "Self",
+        headers: "Dict[str, str]",
+    ) -> None:
         headers.update(
             {
                 "User-Agent": str(self._auth.client),
                 "X-Sentry-Auth": str(self._auth.to_header()),
             }
         )
-        try:
-            response = self._request(
-                "POST",
-                endpoint_type,
-                body,
-                headers,
-            )
-        except Exception:
-            self.on_dropped_event("network")
-            record_loss("network_error")
-            raise
-
-        try:
-            self._update_rate_limits(response)
-
-            if response.status == 413:
-                size_exceeded_message = (
-                    "HTTP 413: Event dropped due to exceeded envelope size limit"
-                )
-                response_message = getattr(
-                    response, "data", getattr(response, "content", None)
-                )
-                if response_message is not None:
-                    size_exceeded_message += f" (body: {response_message})"
-
-                logger.error(size_exceeded_message)
-                self.on_dropped_event("status_413")
-                record_loss("send_error")
-
-            elif response.status == 429:
-                # if we hit a 429.  Something was rate limited but we already
-                # acted on this in `self._update_rate_limits`.  Note that we
-                # do not want to record event loss here as we will have recorded
-                # an outcome in relay already.
-                self.on_dropped_event("status_429")
-                pass
-
-            elif response.status >= 300 or response.status < 200:
-                logger.error(
-                    "Unexpected status code: %s (body: %s)",
-                    response.status,
-                    getattr(response, "data", getattr(response, "content", None)),
-                )
-                self.on_dropped_event("status_{}".format(response.status))
-                record_loss("network_error")
-        finally:
-            response.close()
 
     def on_dropped_event(self: "Self", _reason: str) -> None:
         return None
@@ -408,11 +448,6 @@ def _fetch_pending_client_report(
             type="client_report",
         )
 
-    def _flush_client_reports(self: "Self", force: bool = False) -> None:
-        client_report = self._fetch_pending_client_report(force=force, interval=60)
-        if client_report is not None:
-            self.capture_envelope(Envelope(items=[client_report]))
-
     def _check_disabled(self, category: str) -> bool:
         def _disabled(bucket: "Any") -> bool:
             ts = self._disabled_until.get(bucket)
@@ -431,7 +466,9 @@ def _is_worker_full(self: "Self") -> bool:
     def is_healthy(self: "Self") -> bool:
         return not (self._is_worker_full() or self._is_rate_limited())
 
-    def _send_envelope(self: "Self", envelope: "Envelope") -> None:
+    def _prepare_envelope(
+        self: "Self", envelope: "Envelope"
+    ) -> "Optional[Tuple[Envelope, io.BytesIO, Dict[str, str]]]":
         # remove all items from the envelope which are over quota
         new_items = []
         for item in envelope.items:
@@ -468,19 +505,13 @@ def _send_envelope(self: "Self", envelope: "Envelope") -> None:
             self.parsed_dsn.host,
         )
 
-        headers = {
+        headers: "Dict[str, str]" = {
             "Content-Type": "application/x-sentry-envelope",
         }
         if content_encoding:
             headers["Content-Encoding"] = content_encoding
 
-        self._send_request(
-            body.getvalue(),
-            headers=headers,
-            endpoint_type=EndpointType.ENVELOPE,
-            envelope=envelope,
-        )
-        return None
+        return envelope, body, headers
 
     def _serialize_envelope(
         self: "Self", envelope: "Envelope"
@@ -505,6 +536,77 @@ def _serialize_envelope(
 
         return content_encoding, body
 
+    def _get_httpcore_pool_options(
+        self: "Self", http2: bool = False
+    ) -> "Dict[str, Any]":
+        """Shared pool options for httpcore-based transports (Http2 and Async)."""
+        options: "Dict[str, Any]" = {
+            "http2": http2,
+            "retries": 3,
+        }
+
+        socket_options: "Optional[List[Tuple[int, int, int | bytes]]]" = None
+
+        if self.options["socket_options"] is not None:
+            socket_options = self.options["socket_options"]
+
+        if socket_options is None:
+            socket_options = []
+
+        used_options = {(o[0], o[1]) for o in socket_options}
+        for default_option in KEEP_ALIVE_SOCKET_OPTIONS:
+            if (default_option[0], default_option[1]) not in used_options:
+                socket_options.append(default_option)
+
+        if socket_options is not None:
+            options["socket_options"] = socket_options
+
+        ssl_context = ssl.create_default_context()
+        ssl_context.load_verify_locations(
+            self.options["ca_certs"]
+            or os.environ.get("SSL_CERT_FILE")
+            or os.environ.get("REQUESTS_CA_BUNDLE")
+            or certifi.where()
+        )
+        cert_file = self.options["cert_file"] or os.environ.get("CLIENT_CERT_FILE")
+        key_file = self.options["key_file"] or os.environ.get("CLIENT_KEY_FILE")
+        if cert_file is not None:
+            ssl_context.load_cert_chain(cert_file, key_file)
+
+        options["ssl_context"] = ssl_context
+        return options
+
+    def _resolve_proxy(self: "Self") -> "Optional[str]":
+        """Resolve proxy URL from options and environment. Returns proxy URL or None."""
+        if self.parsed_dsn is None:
+            return None
+
+        no_proxy = self._in_no_proxy(self.parsed_dsn)
+        proxy = None
+
+        # try HTTPS first
+        https_proxy = self.options["https_proxy"]
+        if self.parsed_dsn.scheme == "https" and (https_proxy != ""):
+            proxy = https_proxy or (not no_proxy and getproxies().get("https"))
+
+        # maybe fallback to HTTP proxy
+        http_proxy = self.options["http_proxy"]
+        if not proxy and (http_proxy != ""):
+            proxy = http_proxy or (not no_proxy and getproxies().get("http"))
+
+        return proxy or None
+
+    @property
+    def _timeout_extensions(self: "Self") -> "Dict[str, Any]":
+        return {
+            "timeout": {
+                "pool": self.TIMEOUT,
+                "connect": self.TIMEOUT,
+                "write": self.TIMEOUT,
+                "read": self.TIMEOUT,
+            }
+        }
+
     def _get_pool_options(self: "Self") -> "Dict[str, Any]":
         raise NotImplementedError()
 
@@ -520,7 +622,7 @@ def _in_no_proxy(self: "Self", parsed_dsn: "Dsn") -> bool:
 
     def _make_pool(
         self: "Self",
-    ) -> "Union[PoolManager, ProxyManager, httpcore.SOCKSProxy, httpcore.HTTPProxy, httpcore.ConnectionPool]":
+    ) -> "Union[PoolManager, ProxyManager, httpcore.SOCKSProxy, httpcore.HTTPProxy, httpcore.ConnectionPool, httpcore.AsyncSOCKSProxy, httpcore.AsyncHTTPProxy, httpcore.AsyncConnectionPool]":
         raise NotImplementedError()
 
     def _request(
@@ -532,6 +634,59 @@ def _request(
     ) -> "Union[urllib3.BaseHTTPResponse, httpcore.Response]":
         raise NotImplementedError()
 
+    def kill(self: "Self") -> None:
+        logger.debug("Killing HTTP transport")
+        self._worker.kill()
+
+
+# Keep BaseHttpTransport as an alias for backwards compatibility
+# and for the sync transport implementation
+class BaseHttpTransport(HttpTransportCore):
+    """The base HTTP transport (synchronous)."""
+
+    def _send_envelope(self: "Self", envelope: "Envelope") -> None:
+        _prepared_envelope = self._prepare_envelope(envelope)
+        if _prepared_envelope is not None:
+            envelope, body, headers = _prepared_envelope
+            self._send_request(
+                body.getvalue(),
+                headers=headers,
+                endpoint_type=EndpointType.ENVELOPE,
+                envelope=envelope,
+            )
+        return None
+
+    def _send_request(
+        self: "Self",
+        body: bytes,
+        headers: "Dict[str, str]",
+        endpoint_type: "EndpointType",
+        envelope: "Optional[Envelope]" = None,
+    ) -> None:
+        self._update_headers(headers)
+        try:
+            response = self._request(
+                "POST",
+                endpoint_type,
+                body,
+                headers,
+            )
+        except Exception:
+            self._handle_request_error(envelope=envelope, loss_reason="network")
+            raise
+        try:
+            self._handle_response(response=response, envelope=envelope)
+        finally:
+            response.close()
+
+    def _create_worker(self: "Self", options: "Dict[str, Any]") -> "Worker":
+        return BackgroundWorker(queue_size=options["transport_queue_size"])
+
+    def _flush_client_reports(self: "Self", force: bool = False) -> None:
+        client_report = self._fetch_pending_client_report(force=force, interval=60)
+        if client_report is not None:
+            self.capture_envelope(Envelope(items=[client_report]))
+
     def capture_envelope(
         self,
         envelope: "Envelope",
@@ -557,10 +712,6 @@ def flush(
             self._worker.submit(lambda: self._flush_client_reports(force=True))
             self._worker.flush(timeout, callback)
 
-    def kill(self: "Self") -> None:
-        logger.debug("Killing HTTP transport")
-        self._worker.kill()
-
     @staticmethod
     def _warn_hub_cls() -> None:
         """Convenience method to warn users about the deprecation of the `hub_cls` attribute."""
@@ -688,10 +839,168 @@ def _request(
         )
 
 
-try:
-    import httpcore
-    import h2  # noqa: F401
-except ImportError:
+class AsyncHttpTransport(HttpTransportCore):
+    def __init__(self: "Self", options: "Dict[str, Any]") -> None:
+        if not ASYNC_TRANSPORT_AVAILABLE:
+            raise RuntimeError(
+                "AsyncHttpTransport requires httpcore[asyncio]. "
+                "Install it with: pip install sentry-sdk[asyncio]"
+            )
+        super().__init__(options)
+        # Requires event loop at init time
+        self.loop = asyncio.get_running_loop()
+
+    def _create_worker(self: "Self", options: "Dict[str, Any]") -> "Worker":
+        return AsyncWorker(queue_size=options["transport_queue_size"])
+
+    def _get_header_value(
+        self: "Self", response: "Any", header: str
+    ) -> "Optional[str]":
+        return _get_httpcore_header_value(response, header)
+
+    async def _send_envelope(self: "Self", envelope: "Envelope") -> None:
+        _prepared_envelope = self._prepare_envelope(envelope)
+        if _prepared_envelope is not None:
+            envelope, body, headers = _prepared_envelope
+            await self._send_request(
+                body.getvalue(),
+                headers=headers,
+                endpoint_type=EndpointType.ENVELOPE,
+                envelope=envelope,
+            )
+        return None
+
+    async def _send_request(
+        self: "Self",
+        body: bytes,
+        headers: "Dict[str, str]",
+        endpoint_type: "EndpointType",
+        envelope: "Optional[Envelope]" = None,
+    ) -> None:
+        self._update_headers(headers)
+        try:
+            response = await self._request(
+                "POST",
+                endpoint_type,
+                body,
+                headers,
+            )
+        except Exception:
+            self._handle_request_error(envelope=envelope, loss_reason="network")
+            raise
+        try:
+            self._handle_response(response=response, envelope=envelope)
+        finally:
+            await response.aclose()
+
+    async def _request(  # type: ignore[override]
+        self: "Self",
+        method: str,
+        endpoint_type: "EndpointType",
+        body: "Any",
+        headers: "Mapping[str, str]",
+    ) -> "httpcore.Response":
+        return await self._pool.request(  # type: ignore[misc,unused-ignore]
+            method,
+            self._auth.get_api_url(endpoint_type),
+            content=body,
+            headers=headers,  # type: ignore[arg-type,unused-ignore]
+            extensions=self._timeout_extensions,
+        )
+
+    async def _flush_client_reports(self: "Self", force: bool = False) -> None:
+        client_report = self._fetch_pending_client_report(force=force, interval=60)
+        if client_report is not None:
+            self.capture_envelope(Envelope(items=[client_report]))
+
+    def _capture_envelope(self: "Self", envelope: "Envelope") -> None:
+        async def send_envelope_wrapper() -> None:
+            with capture_internal_exceptions():
+                await self._send_envelope(envelope)
+                await self._flush_client_reports()
+
+        if not self._worker.submit(send_envelope_wrapper):
+            self.on_dropped_event("full_queue")
+            for item in envelope.items:
+                self.record_lost_event("queue_overflow", item=item)
+
+    def capture_envelope(self: "Self", envelope: "Envelope") -> None:
+        # Synchronous entry point
+        if self.loop and self.loop.is_running():
+            self.loop.call_soon_threadsafe(self._capture_envelope, envelope)
+        else:
+            # The event loop is no longer running
+            logger.warning("Async Transport is not running in an event loop.")
+            self.on_dropped_event("internal_sdk_error")
+            for item in envelope.items:
+                self.record_lost_event("internal_sdk_error", item=item)
+
+    def flush(  # type: ignore[override]
+        self: "Self",
+        timeout: float,
+        callback: "Optional[Callable[[int, float], None]]" = None,
+    ) -> "Optional[asyncio.Task[None]]":
+        logger.debug("Flushing HTTP transport")
+
+        if timeout > 0:
+            self._worker.submit(lambda: self._flush_client_reports(force=True))
+            return self._worker.flush(timeout, callback)  # type: ignore[func-returns-value]
+        return None
+
+    def _get_pool_options(self: "Self") -> "Dict[str, Any]":
+        return self._get_httpcore_pool_options(
+            http2=HTTP2_ENABLED
+            and self.parsed_dsn is not None
+            and self.parsed_dsn.scheme == "https"
+        )
+
+    def _make_pool(
+        self: "Self",
+    ) -> "Union[httpcore.AsyncSOCKSProxy, httpcore.AsyncHTTPProxy, httpcore.AsyncConnectionPool]":
+        if self.parsed_dsn is None:
+            raise ValueError("Cannot create HTTP-based transport without valid DSN")
+
+        proxy = self._resolve_proxy()
+        opts = self._get_pool_options()
+
+        if proxy:
+            proxy_headers = self.options["proxy_headers"]
+            if proxy_headers:
+                opts["proxy_headers"] = proxy_headers
+
+            if proxy.startswith("socks"):
+                try:
+                    socks_opts = opts.copy()
+                    if "socket_options" in socks_opts:
+                        socket_options = socks_opts.pop("socket_options")
+                        if socket_options:
+                            logger.warning(
+                                "You have defined socket_options but using a SOCKS proxy which doesn't support these. We'll ignore socket_options."
+                            )
+                    return httpcore.AsyncSOCKSProxy(proxy_url=proxy, **socks_opts)
+                except RuntimeError:
+                    logger.warning(
+                        "You have configured a SOCKS proxy (%s) but support for SOCKS proxies is not installed. Disabling proxy support.",
+                        proxy,
+                    )
+            else:
+                return httpcore.AsyncHTTPProxy(proxy_url=proxy, **opts)
+
+        return httpcore.AsyncConnectionPool(**opts)
+
+    def kill(self: "Self") -> "Optional[asyncio.Task[None]]":  # type: ignore[override]
+        logger.debug("Killing HTTP transport")
+        self._worker.kill()
+        try:
+            # Return the pool cleanup task so caller can await it if needed
+            with mark_sentry_task_internal():
+                return self.loop.create_task(self._pool.aclose())  # type: ignore[union-attr,unused-ignore]
+        except RuntimeError:
+            logger.warning("Event loop not running, aborting kill.")
+            return None
+
+
+if not HTTP2_ENABLED:
     # Sorry, no Http2Transport for you
     class Http2Transport(HttpTransport):
         def __init__(self: "Self", options: "Dict[str, Any]") -> None:
@@ -715,14 +1024,7 @@ class Http2Transport(BaseHttpTransport):  # type: ignore
         def _get_header_value(
             self: "Self", response: "httpcore.Response", header: str
         ) -> "Optional[str]":
-            return next(
-                (
-                    val.decode("ascii")
-                    for key, val in response.headers
-                    if key.decode("ascii").lower() == header
-                ),
-                None,
-            )
+            return _get_httpcore_header_value(response, header)
 
         def _request(
             self: "Self",
@@ -735,72 +1037,23 @@ def _request(
                 method,
                 self._auth.get_api_url(endpoint_type),
                 content=body,
-                headers=headers,  # type: ignore
-                extensions={
-                    "timeout": {
-                        "pool": self.TIMEOUT,
-                        "connect": self.TIMEOUT,
-                        "write": self.TIMEOUT,
-                        "read": self.TIMEOUT,
-                    }
-                },
+                headers=headers,  # type: ignore[arg-type,unused-ignore]
+                extensions=self._timeout_extensions,
             )
             return response
 
         def _get_pool_options(self: "Self") -> "Dict[str, Any]":
-            options: "Dict[str, Any]" = {
-                "http2": self.parsed_dsn is not None
-                and self.parsed_dsn.scheme == "https",
-                "retries": 3,
-            }
-
-            socket_options = (
-                self.options["socket_options"]
-                if self.options["socket_options"] is not None
-                else []
-            )
-
-            used_options = {(o[0], o[1]) for o in socket_options}
-            for default_option in KEEP_ALIVE_SOCKET_OPTIONS:
-                if (default_option[0], default_option[1]) not in used_options:
-                    socket_options.append(default_option)
-
-            options["socket_options"] = socket_options
-
-            ssl_context = ssl.create_default_context()
-            ssl_context.load_verify_locations(
-                self.options["ca_certs"]  # User-provided bundle from the SDK init
-                or os.environ.get("SSL_CERT_FILE")
-                or os.environ.get("REQUESTS_CA_BUNDLE")
-                or certifi.where()
+            return self._get_httpcore_pool_options(
+                http2=self.parsed_dsn is not None and self.parsed_dsn.scheme == "https"
             )
-            cert_file = self.options["cert_file"] or os.environ.get("CLIENT_CERT_FILE")
-            key_file = self.options["key_file"] or os.environ.get("CLIENT_KEY_FILE")
-            if cert_file is not None:
-                ssl_context.load_cert_chain(cert_file, key_file)
-
-            options["ssl_context"] = ssl_context
-
-            return options
 
         def _make_pool(
             self: "Self",
         ) -> "Union[httpcore.SOCKSProxy, httpcore.HTTPProxy, httpcore.ConnectionPool]":
             if self.parsed_dsn is None:
                 raise ValueError("Cannot create HTTP-based transport without valid DSN")
-            proxy = None
-            no_proxy = self._in_no_proxy(self.parsed_dsn)
-
-            # try HTTPS first
-            https_proxy = self.options["https_proxy"]
-            if self.parsed_dsn.scheme == "https" and (https_proxy != ""):
-                proxy = https_proxy or (not no_proxy and getproxies().get("https"))
-
-            # maybe fallback to HTTP proxy
-            http_proxy = self.options["http_proxy"]
-            if not proxy and (http_proxy != ""):
-                proxy = http_proxy or (not no_proxy and getproxies().get("http"))
 
+            proxy = self._resolve_proxy()
             opts = self._get_pool_options()
 
             if proxy:
@@ -861,12 +1114,39 @@ def make_transport(options: "Dict[str, Any]") -> "Optional[Transport]":
     ref_transport = options["transport"]
 
     use_http2_transport = options.get("_experiments", {}).get("transport_http2", False)
+    use_async_transport = options.get("_experiments", {}).get("transport_async", False)
+    async_integration = any(
+        integration.__class__.__name__ == "AsyncioIntegration"
+        for integration in options.get("integrations") or []
+    )
 
     # By default, we use the http transport class
     transport_cls: "Type[Transport]" = (
         Http2Transport if use_http2_transport else HttpTransport
     )
 
+    if use_async_transport and ASYNC_TRANSPORT_AVAILABLE:
+        try:
+            asyncio.get_running_loop()
+            if async_integration:
+                if use_http2_transport:
+                    logger.warning(
+                        "HTTP/2 transport is not supported with async transport. "
+                        "Ignoring transport_http2 experiment."
+                    )
+                transport_cls = AsyncHttpTransport
+            else:
+                logger.warning(
+                    "You tried to use AsyncHttpTransport but the AsyncioIntegration is not enabled. Falling back to sync transport."
+                )
+        except RuntimeError:
+            # No event loop running, fall back to sync transport
+            logger.warning("No event loop running, falling back to sync transport.")
+    elif use_async_transport:
+        logger.warning(
+            "You tried to use AsyncHttpTransport but don't have httpcore[asyncio] installed. Falling back to sync transport."
+        )
+
     if isinstance(ref_transport, Transport):
         return ref_transport
     elif isinstance(ref_transport, type) and issubclass(ref_transport, Transport):
diff --git a/sentry_sdk/utils.py b/sentry_sdk/utils.py
index a333467ae9..be238e5142 100644
--- a/sentry_sdk/utils.py
+++ b/sentry_sdk/utils.py
@@ -1,4 +1,5 @@
 import base64
+import contextvars
 import json
 import linecache
 import logging
@@ -12,6 +13,7 @@
 import threading
 import time
 from collections import namedtuple
+from contextlib import contextmanager
 from datetime import datetime, timezone
 from decimal import Decimal
 from functools import partial, partialmethod, wraps
@@ -44,9 +46,9 @@
         Callable,
         ContextManager,
         Dict,
+        Generator,
         Iterator,
         List,
-        Literal,
         NoReturn,
         Optional,
         ParamSpec,
@@ -82,6 +84,25 @@
 
 _installed_modules = None
 
+_is_sentry_internal_task = contextvars.ContextVar(
+    "is_sentry_internal_task", default=False
+)
+
+
+def is_internal_task() -> bool:
+    return _is_sentry_internal_task.get()
+
+
+@contextmanager
+def mark_sentry_task_internal() -> "Generator[None, None, None]":
+    """Context manager to mark a task as Sentry internal."""
+    token = _is_sentry_internal_task.set(True)
+    try:
+        yield
+    finally:
+        _is_sentry_internal_task.reset(token)
+
+
 BASE64_ALPHABET = re.compile(r"^[a-zA-Z0-9/+=]*$")
 
 FALSY_ENV_VALUES = frozenset(("false", "f", "n", "no", "off", "0"))
@@ -820,6 +841,8 @@ def exceptions_from_error(
     parent_id: int = 0,
     source: "Optional[str]" = None,
     full_stack: "Optional[list[dict[str, Any]]]" = None,
+    seen_exceptions: "Optional[list[BaseException]]" = None,
+    seen_exception_ids: "Optional[Set[int]]" = None,
 ) -> "Tuple[int, List[Dict[str, Any]]]":
     """
     Creates the list of exceptions.
@@ -827,8 +850,37 @@ def exceptions_from_error(
 
     See the Exception Interface documentation for more details:
     https://develop.sentry.dev/sdk/event-payloads/exception/
+
+    Args:
+        exception_id (int):
+
+            Sequential counter for assigning ``mechanism.exception_id``
+            to each processed exception. Is NOT the result of calling `id()` on the exception itself.
+
+        parent_id (int):
+
+            The ``mechanism.exception_id`` of the parent exception.
+
+            Written into ``mechanism.parent_id`` in the event payload so Sentry can
+            reconstruct the exception tree.
+
+            Not to be confused with ``seen_exception_ids``, which tracks Python ``id()``
+            values for cycle detection.
     """
 
+    if seen_exception_ids is None:
+        seen_exception_ids = set()
+
+    if seen_exceptions is None:
+        seen_exceptions = []
+
+    if exc_value is not None and id(exc_value) in seen_exception_ids:
+        return (exception_id, [])
+
+    if exc_value is not None:
+        seen_exceptions.append(exc_value)
+        seen_exception_ids.add(id(exc_value))
+
     parent = single_exception_from_error_tuple(
         exc_type=exc_type,
         exc_value=exc_value,
@@ -867,6 +919,8 @@ def exceptions_from_error(
                 exception_id=exception_id,
                 source="__cause__",
                 full_stack=full_stack,
+                seen_exceptions=seen_exceptions,
+                seen_exception_ids=seen_exception_ids,
             )
             exceptions.extend(child_exceptions)
 
@@ -889,6 +943,8 @@ def exceptions_from_error(
                 exception_id=exception_id,
                 source="__context__",
                 full_stack=full_stack,
+                seen_exceptions=seen_exceptions,
+                seen_exception_ids=seen_exception_ids,
             )
             exceptions.extend(child_exceptions)
 
@@ -906,6 +962,8 @@ def exceptions_from_error(
                 parent_id=parent_id,
                 source="exceptions[%s]" % idx,
                 full_stack=full_stack,
+                seen_exceptions=seen_exceptions,
+                seen_exception_ids=seen_exception_ids,
             )
             exceptions.extend(child_exceptions)
 
diff --git a/sentry_sdk/worker.py b/sentry_sdk/worker.py
index 3d85a653d6..7931f9c027 100644
--- a/sentry_sdk/worker.py
+++ b/sentry_sdk/worker.py
@@ -1,9 +1,11 @@
+from abc import ABC, abstractmethod
+import asyncio
 import os
 import threading
 
 from time import sleep, time
 from sentry_sdk._queue import Queue, FullError
-from sentry_sdk.utils import logger
+from sentry_sdk.utils import logger, mark_sentry_task_internal
 from sentry_sdk.consts import DEFAULT_QUEUE_SIZE
 
 from typing import TYPE_CHECKING
@@ -17,7 +19,38 @@
 _TERMINATOR = object()
 
 
-class BackgroundWorker:
+class Worker(ABC):
+    """Base class for all workers."""
+
+    @property
+    @abstractmethod
+    def is_alive(self) -> bool:
+        """Whether the worker is alive and running."""
+        pass
+
+    @abstractmethod
+    def kill(self) -> None:
+        """Kill the worker. It will not process any more events."""
+        pass
+
+    def flush(
+        self, timeout: float, callback: "Optional[Callable[[int, float], Any]]" = None
+    ) -> None:
+        """Flush the worker, blocking until done or timeout is reached."""
+        return None
+
+    @abstractmethod
+    def full(self) -> bool:
+        """Whether the worker's queue is full."""
+        pass
+
+    @abstractmethod
+    def submit(self, callback: "Callable[[], Any]") -> bool:
+        """Schedule a callback. Returns True if queued, False if full."""
+        pass
+
+
+class BackgroundWorker(Worker):
     def __init__(self, queue_size: int = DEFAULT_QUEUE_SIZE) -> None:
         self._queue: "Queue" = Queue(queue_size)
         self._lock = threading.Lock()
@@ -107,7 +140,7 @@ def _wait_flush(self, timeout: float, callback: "Optional[Any]") -> None:
                 pending = self._queue.qsize() + 1
                 logger.error("flush timed out, dropped %s events", pending)
 
-    def submit(self, callback: "Callable[[], None]") -> bool:
+    def submit(self, callback: "Callable[[], Any]") -> bool:
         self._ensure_thread()
         try:
             self._queue.put_nowait(callback)
@@ -128,3 +161,151 @@ def _target(self) -> None:
             finally:
                 self._queue.task_done()
             sleep(0)
+
+
+class AsyncWorker(Worker):
+    def __init__(self, queue_size: int = DEFAULT_QUEUE_SIZE) -> None:
+        self._queue: "Optional[asyncio.Queue[Any]]" = None
+        self._queue_size = queue_size
+        self._task: "Optional[asyncio.Task[None]]" = None
+        # Event loop needs to remain in the same process
+        self._task_for_pid: "Optional[int]" = None
+        self._loop: "Optional[asyncio.AbstractEventLoop]" = None
+        # Track active callback tasks so they have a strong reference and can be cancelled on kill
+        self._active_tasks: "set[asyncio.Task[None]]" = set()
+
+    @property
+    def is_alive(self) -> bool:
+        if self._task_for_pid != os.getpid():
+            return False
+        if not self._task or not self._loop:
+            return False
+        return self._loop.is_running() and not self._task.done()
+
+    def kill(self) -> None:
+        if self._task:
+            # Cancel the main consumer task to prevent duplicate consumers
+            self._task.cancel()
+            # Also cancel any active callback tasks
+            # Avoid modifying the set while cancelling tasks
+            tasks_to_cancel = set(self._active_tasks)
+            for task in tasks_to_cancel:
+                task.cancel()
+            self._active_tasks.clear()
+            self._loop = None
+            self._task = None
+            self._task_for_pid = None
+
+    def start(self) -> None:
+        if not self.is_alive:
+            try:
+                self._loop = asyncio.get_running_loop()
+                # Always create a fresh queue on start to avoid stale items
+                self._queue = asyncio.Queue(maxsize=self._queue_size)
+                with mark_sentry_task_internal():
+                    self._task = self._loop.create_task(self._target())
+                self._task_for_pid = os.getpid()
+            except RuntimeError:
+                # There is no event loop running
+                logger.warning("No event loop running, async worker not started")
+                self._loop = None
+                self._task = None
+                self._task_for_pid = None
+
+    def full(self) -> bool:
+        if self._queue is None:
+            return True
+        return self._queue.full()
+
+    def _ensure_task(self) -> None:
+        if not self.is_alive:
+            self.start()
+
+    async def _wait_flush(
+        self, timeout: float, callback: "Optional[Any]" = None
+    ) -> None:
+        if not self._loop or not self._loop.is_running() or self._queue is None:
+            return
+
+        initial_timeout = min(0.1, timeout)
+
+        # Timeout on the join
+        try:
+            await asyncio.wait_for(self._queue.join(), timeout=initial_timeout)
+        except asyncio.TimeoutError:
+            pending = self._queue.qsize() + len(self._active_tasks)
+            logger.debug("%d event(s) pending on flush", pending)
+            if callback is not None:
+                callback(pending, timeout)
+
+            try:
+                remaining_timeout = timeout - initial_timeout
+                await asyncio.wait_for(self._queue.join(), timeout=remaining_timeout)
+            except asyncio.TimeoutError:
+                pending = self._queue.qsize() + len(self._active_tasks)
+                logger.error("flush timed out, dropped %s events", pending)
+
+    def flush(  # type: ignore[override]
+        self, timeout: float, callback: "Optional[Any]" = None
+    ) -> "Optional[asyncio.Task[None]]":
+        if self.is_alive and timeout > 0.0 and self._loop and self._loop.is_running():
+            with mark_sentry_task_internal():
+                return self._loop.create_task(self._wait_flush(timeout, callback))
+        return None
+
+    def submit(self, callback: "Callable[[], Any]") -> bool:
+        self._ensure_task()
+        if self._queue is None:
+            return False
+        try:
+            self._queue.put_nowait(callback)
+            return True
+        except asyncio.QueueFull:
+            return False
+
+    async def _target(self) -> None:
+        if self._queue is None:
+            return
+        try:
+            while True:
+                callback = await self._queue.get()
+                if callback is _TERMINATOR:
+                    self._queue.task_done()
+                    break
+                # Firing tasks instead of awaiting them allows for concurrent requests
+                with mark_sentry_task_internal():
+                    task = asyncio.create_task(self._process_callback(callback))
+                # Create a strong reference to the task so it can be cancelled on kill
+                # and does not get garbage collected while running
+                self._active_tasks.add(task)
+                # Capture queue ref at dispatch time so done callbacks use the
+                # correct queue even if kill()/start() replace self._queue.
+                queue_ref = self._queue
+                task.add_done_callback(lambda t: self._on_task_complete(t, queue_ref))
+                # Yield to let the event loop run other tasks
+                await asyncio.sleep(0)
+        except asyncio.CancelledError:
+            pass  # Expected during kill()
+
+    async def _process_callback(self, callback: "Callable[[], Any]") -> None:
+        # Callback is an async coroutine, need to await it
+        await callback()
+
+    def _on_task_complete(
+        self,
+        task: "asyncio.Task[None]",
+        queue: "Optional[asyncio.Queue[Any]]" = None,
+    ) -> None:
+        try:
+            task.result()
+        except asyncio.CancelledError:
+            pass  # Task was cancelled, expected during shutdown
+        except Exception:
+            logger.error("Failed processing job", exc_info=True)
+        finally:
+            # Mark the task as done and remove it from the active tasks set
+            # Use the queue reference captured at dispatch time, not self._queue,
+            # to avoid calling task_done() on a different queue after kill()/start().
+            if queue is not None:
+                queue.task_done()
+            self._active_tasks.discard(task)
diff --git a/setup.py b/setup.py
index eb8ee4bd4a..3942ee630e 100644
--- a/setup.py
+++ b/setup.py
@@ -21,7 +21,7 @@ def get_file_text(file_name):
 
 setup(
     name="sentry-sdk",
-    version="2.54.0",
+    version="2.58.0",
     author="Sentry Team and Contributors",
     author_email="hello@sentry.io",
     url="https://github.com/getsentry/sentry-python",
@@ -36,7 +36,7 @@ def get_file_text(file_name):
     # PEP 561
     package_data={"sentry_sdk": ["py.typed"]},
     zip_safe=False,
-    license="MIT",
+    license_expression="MIT",
     python_requires=">=3.6",
     install_requires=[
         "urllib3>=1.26.11",
@@ -59,13 +59,14 @@ def get_file_text(file_name):
         "flask": ["flask>=0.11", "blinker>=1.1", "markupsafe"],
         "grpcio": ["grpcio>=1.21.1", "protobuf>=3.8.0"],
         "http2": ["httpcore[http2]==1.*"],
+        "asyncio": ["httpcore[asyncio]==1.*"],
         "httpx": ["httpx>=0.16.0"],
         "huey": ["huey>=2"],
         "huggingface_hub": ["huggingface_hub>=0.22"],
         "langchain": ["langchain>=0.0.210"],
         "langgraph": ["langgraph>=0.6.6"],
         "launchdarkly": ["launchdarkly-server-sdk>=9.8.0"],
-        "litellm": ["litellm>=1.77.5"],
+        "litellm": ["litellm>=1.77.5,!=1.82.7,!=1.82.8"],
         "litestar": ["litestar>=2.0.0"],
         "loguru": ["loguru>=0.5"],
         "mcp": ["mcp>=1.15.0"],
@@ -98,7 +99,6 @@ def get_file_text(file_name):
         "Development Status :: 5 - Production/Stable",
         "Environment :: Web Environment",
         "Intended Audience :: Developers",
-        "License :: OSI Approved :: BSD License",
         "Operating System :: OS Independent",
         "Programming Language :: Python",
         "Programming Language :: Python :: 3",
diff --git a/tests/conftest.py b/tests/conftest.py
index d6240e17eb..4e4943ba85 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -7,6 +7,7 @@
 import brotli
 import gzip
 import io
+from dataclasses import dataclass
 from threading import Thread
 from contextlib import contextmanager
 from http.server import BaseHTTPRequestHandler, HTTPServer
@@ -48,6 +49,24 @@
 from sentry_sdk.transport import Transport
 from sentry_sdk.utils import reraise
 
+try:
+    import openai
+except ImportError:
+    openai = None
+
+
+try:
+    import anthropic
+except ImportError:
+    anthropic = None
+
+
+try:
+    import google
+except ImportError:
+    google = None
+
+
 from tests import _warning_recorder, _warning_recorder_mgr
 
 from typing import TYPE_CHECKING
@@ -57,13 +76,6 @@
     from collections.abc import Iterator
 
 try:
-    from anyio import create_memory_object_stream, create_task_group, EndOfStream
-    from mcp.types import (
-        JSONRPCMessage,
-        JSONRPCNotification,
-        JSONRPCRequest,
-    )
-    from mcp.shared.message import SessionMessage
     from httpx import (
         ASGITransport,
         Request as HttpxRequest,
@@ -71,6 +83,22 @@
         AsyncByteStream,
         AsyncClient,
     )
+except ImportError:
+    ASGITransport = None
+    HttpxRequest = None
+    HttpxResponse = None
+    AsyncByteStream = None
+    AsyncClient = None
+
+
+try:
+    from anyio import create_memory_object_stream, create_task_group, EndOfStream
+    from mcp.types import (
+        JSONRPCMessage,
+        JSONRPCNotification,
+        JSONRPCRequest,
+    )
+    from mcp.shared.message import SessionMessage
 except ImportError:
     create_memory_object_stream = None
     create_task_group = None
@@ -81,12 +109,6 @@
     JSONRPCRequest = None
     SessionMessage = None
 
-    ASGITransport = None
-    HttpxRequest = None
-    HttpxResponse = None
-    AsyncByteStream = None
-    AsyncClient = None
-
 
 SENTRY_EVENT_SCHEMA = "./checkouts/data-schemas/relay/event.schema.json"
 
@@ -311,6 +333,52 @@ def append_envelope(envelope):
     return inner
 
 
+@dataclass
+class UnwrappedItem:
+    type: str
+    payload: dict
+
+
+@pytest.fixture
+def capture_items(monkeypatch):
+    """
+    Capture envelope payload, unfurling individual items.
+
+    Makes it easier to work with both events and attribute-based telemetry in
+    one test.
+    """
+
+    def inner(*types):
+        telemetry = []
+        test_client = sentry_sdk.get_client()
+        old_capture_envelope = test_client.transport.capture_envelope
+
+        def append_envelope(envelope):
+            for item in envelope:
+                if types and item.type not in types:
+                    continue
+
+                if item.type in ("metric", "log", "span"):
+                    for i in item.payload.json["items"]:
+                        t = {k: v for k, v in i.items() if k != "attributes"}
+                        t["attributes"] = {
+                            k: v["value"] for k, v in i["attributes"].items()
+                        }
+                        telemetry.append(UnwrappedItem(type=item.type, payload=t))
+                else:
+                    telemetry.append(
+                        UnwrappedItem(type=item.type, payload=item.payload.json)
+                    )
+
+            return old_capture_envelope(envelope)
+
+        monkeypatch.setattr(test_client.transport, "capture_envelope", append_envelope)
+
+        return telemetry
+
+    return inner
+
+
 @pytest.fixture
 def capture_record_lost_event_calls(monkeypatch):
     def inner():
@@ -1004,6 +1072,386 @@ async def parse_stream():
     return inner
 
 
+@pytest.fixture()
+def async_iterator():
+    async def inner(values):
+        for value in values:
+            yield value
+
+    return inner
+
+
+@pytest.fixture
+def server_side_event_chunks():
+    def inner(events, include_event_type=True):
+        for event in events:
+            payload = event.model_dump()
+            chunk = (
+                f"event: {payload['type']}\ndata: {json.dumps(payload)}\n\n"
+                if include_event_type
+                else f"data: {json.dumps(payload)}\n\n"
+            )
+            yield chunk.encode("utf-8")
+
+    return inner
+
+
+@pytest.fixture
+def get_model_response():
+    def inner(response_content, serialize_pydantic=False, request_headers=None):
+        if request_headers is None:
+            request_headers = {}
+
+        model_request = HttpxRequest(
+            "POST",
+            "/responses",
+            headers=request_headers,
+        )
+
+        if serialize_pydantic:
+            response_content = json.dumps(
+                response_content.model_dump(
+                    by_alias=True,
+                    exclude_none=True,
+                )
+            ).encode("utf-8")
+
+        response = HttpxResponse(
+            200,
+            request=model_request,
+            content=response_content,
+        )
+
+        return response
+
+    return inner
+
+
+@pytest.fixture
+def get_rate_limit_model_response():
+    def inner(request_headers=None):
+        if request_headers is None:
+            request_headers = {}
+
+        model_request = HttpxRequest(
+            "POST",
+            "/responses",
+            headers=request_headers,
+        )
+
+        response = HttpxResponse(
+            429,
+            request=model_request,
+        )
+
+        return response
+
+    return inner
+
+
+@pytest.fixture
+def streaming_chat_completions_model_response():
+    return [
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        role="assistant"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        content="Tes"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        content="t r"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        content="esp"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        content="ons"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(
+                        content="e"
+                    ),
+                    finish_reason=None,
+                ),
+            ],
+        ),
+        openai.types.chat.ChatCompletionChunk(
+            id="chatcmpl-test",
+            object="chat.completion.chunk",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                openai.types.chat.chat_completion_chunk.Choice(
+                    index=0,
+                    delta=openai.types.chat.chat_completion_chunk.ChoiceDelta(),
+                    finish_reason="stop",
+                ),
+            ],
+            usage=openai.types.CompletionUsage(
+                prompt_tokens=10,
+                completion_tokens=20,
+                total_tokens=30,
+            ),
+        ),
+    ]
+
+
+@pytest.fixture
+def nonstreaming_chat_completions_model_response():
+    return openai.types.chat.ChatCompletion(
+        id="chatcmpl-test",
+        choices=[
+            openai.types.chat.chat_completion.Choice(
+                index=0,
+                finish_reason="stop",
+                message=openai.types.chat.ChatCompletionMessage(
+                    role="assistant", content="Test response"
+                ),
+            )
+        ],
+        created=1234567890,
+        model="gpt-3.5-turbo",
+        object="chat.completion",
+        usage=openai.types.CompletionUsage(
+            prompt_tokens=10,
+            completion_tokens=20,
+            total_tokens=30,
+        ),
+    )
+
+
+@pytest.fixture
+def openai_embedding_model_response():
+    return openai.types.CreateEmbeddingResponse(
+        data=[
+            openai.types.Embedding(
+                embedding=[0.1, 0.2, 0.3],
+                index=0,
+                object="embedding",
+            )
+        ],
+        model="text-embedding-ada-002",
+        object="list",
+        usage=openai.types.create_embedding_response.Usage(
+            prompt_tokens=5,
+            total_tokens=5,
+        ),
+    )
+
+
+@pytest.fixture
+def nonstreaming_responses_model_response():
+    return openai.types.responses.Response(
+        id="resp_123",
+        output=[
+            openai.types.responses.ResponseOutputMessage(
+                id="msg_123",
+                type="message",
+                status="completed",
+                content=[
+                    openai.types.responses.ResponseOutputText(
+                        text="Hello, how can I help you?",
+                        type="output_text",
+                        annotations=[],
+                    )
+                ],
+                role="assistant",
+            )
+        ],
+        parallel_tool_calls=False,
+        tool_choice="none",
+        tools=[],
+        created_at=10000000,
+        model="gpt-4",
+        object="response",
+        usage=openai.types.responses.ResponseUsage(
+            input_tokens=10,
+            input_tokens_details=openai.types.responses.response_usage.InputTokensDetails(
+                cached_tokens=0,
+            ),
+            output_tokens=20,
+            output_tokens_details=openai.types.responses.response_usage.OutputTokensDetails(
+                reasoning_tokens=5,
+            ),
+            total_tokens=30,
+        ),
+    )
+
+
+@pytest.fixture
+def nonstreaming_anthropic_model_response():
+    return anthropic.types.Message(
+        id="msg_123",
+        type="message",
+        role="assistant",
+        model="claude-3-opus-20240229",
+        content=[
+            anthropic.types.TextBlock(
+                type="text",
+                text="Hello, how can I help you?",
+            )
+        ],
+        stop_reason="end_turn",
+        stop_sequence=None,
+        usage=anthropic.types.Usage(
+            input_tokens=10,
+            output_tokens=20,
+        ),
+    )
+
+
+@pytest.fixture
+def nonstreaming_google_genai_model_response():
+    return google.genai.types.GenerateContentResponse(
+        response_id="resp_123",
+        candidates=[
+            google.genai.types.Candidate(
+                content=google.genai.types.Content(
+                    role="model",
+                    parts=[
+                        google.genai.types.Part(
+                            text="Hello, how can I help you?",
+                        )
+                    ],
+                ),
+                finish_reason="STOP",
+            )
+        ],
+        model_version="gemini/gemini-pro",
+        usage_metadata=google.genai.types.GenerateContentResponseUsageMetadata(
+            prompt_token_count=10,
+            candidates_token_count=20,
+            total_token_count=30,
+        ),
+    )
+
+
+@pytest.fixture
+def responses_tool_call_model_responses():
+    def inner(
+        tool_name: str,
+        arguments: str,
+        response_model: str,
+        response_text: str,
+        response_ids: "Iterator[str]",
+        usages: "Iterator[openai.types.responses.ResponseUsage]",
+    ):
+        yield openai.types.responses.Response(
+            id=next(response_ids),
+            output=[
+                openai.types.responses.ResponseFunctionToolCall(
+                    id="call_123",
+                    call_id="call_123",
+                    name=tool_name,
+                    type="function_call",
+                    arguments=arguments,
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model=response_model,
+            object="response",
+            usage=next(usages),
+        )
+
+        yield openai.types.responses.Response(
+            id=next(response_ids),
+            output=[
+                openai.types.responses.ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        openai.types.responses.ResponseOutputText(
+                            text=response_text,
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model=response_model,
+            object="response",
+            usage=next(usages),
+        )
+
+    return inner
+
+
 class MockServerRequestHandler(BaseHTTPRequestHandler):
     def do_GET(self):  # noqa: N802
         # Process an HTTP GET request and return a response.
diff --git a/tests/integrations/anthropic/test_anthropic.py b/tests/integrations/anthropic/test_anthropic.py
index 4361ba9629..e86f7e1fa9 100644
--- a/tests/integrations/anthropic/test_anthropic.py
+++ b/tests/integrations/anthropic/test_anthropic.py
@@ -11,7 +11,7 @@ async def __call__(self, *args, **kwargs):
             return super(AsyncMock, self).__call__(*args, **kwargs)
 
 
-from anthropic import Anthropic, AnthropicError, AsyncAnthropic, AsyncStream, Stream
+from anthropic import Anthropic, AnthropicError, AsyncAnthropic
 from anthropic.types import MessageDeltaUsage, TextDelta, Usage
 from anthropic.types.content_block_delta_event import ContentBlockDeltaEvent
 from anthropic.types.content_block_start_event import ContentBlockStartEvent
@@ -20,6 +20,14 @@ async def __call__(self, *args, **kwargs):
 from anthropic.types.message_delta_event import MessageDeltaEvent
 from anthropic.types.message_start_event import MessageStartEvent
 
+try:
+    from anthropic.types import ErrorResponse, OverloadedError
+    from anthropic import APIStatusError
+except ImportError:
+    ErrorResponse = None
+    OverloadedError = None
+    APIStatusError = None
+
 try:
     from anthropic.types import InputJSONDelta
 except ImportError:
@@ -28,6 +36,11 @@ async def __call__(self, *args, **kwargs):
     except ImportError:
         pass
 
+try:
+    from anthropic.lib.streaming import TextEvent
+except ImportError:
+    TextEvent = None
+
 try:
     # 0.27+
     from anthropic.types.raw_message_delta_event import Delta
@@ -58,20 +71,16 @@ async def __call__(self, *args, **kwargs):
 ANTHROPIC_VERSION = package_version("anthropic")
 
 EXAMPLE_MESSAGE = Message(
-    id="id",
+    id="msg_01XFDUDYJgAACzvnptvVoYEL",
     model="model",
     role="assistant",
     content=[TextBlock(type="text", text="Hi, I'm Claude.")],
     type="message",
+    stop_reason="end_turn",
     usage=Usage(input_tokens=10, output_tokens=20),
 )
 
 
-async def async_iterator(values):
-    for value in values:
-        yield value
-
-
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -122,6 +131,7 @@ def test_nonstreaming_create_message(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -139,6 +149,8 @@ def test_nonstreaming_create_message(
     assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
     assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["end_turn"]
 
 
 @pytest.mark.asyncio
@@ -155,13 +167,1324 @@ async def test_nonstreaming_create_message_async(
     sentry_init, capture_events, send_default_pii, include_prompts
 ):
     sentry_init(
-        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+    client = AsyncAnthropic(api_key="z")
+    client.messages._post = AsyncMock(return_value=EXAMPLE_MESSAGE)
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with start_transaction(name="anthropic"):
+        response = await client.messages.create(
+            max_tokens=1024, messages=messages, model="model"
+        )
+
+    assert response == EXAMPLE_MESSAGE
+    usage = response.usage
+
+    assert usage.input_tokens == 10
+    assert usage.output_tokens == 20
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    assert len(event["spans"]) == 1
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert (
+            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+            == '[{"role": "user", "content": "Hello, Claude"}]'
+        )
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi, I'm Claude."
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_streaming_create_message(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="max_tokens"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            for _ in message:
+                pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert (
+            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+            == '[{"role": "user", "content": "Hello, Claude"}]'
+        )
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["max_tokens"]
+
+
+def test_streaming_create_message_close(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="max_tokens"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            messages = client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            for _ in range(4):
+                next(messages)
+
+            messages.close()
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 41),
+    reason="Error classes moved in https://github.com/anthropics/anthropic-sdk-python/commit/4e0b15e22fe40e9aa513459564f641bf97c90954.",
+)
+def test_streaming_create_message_api_error(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ErrorResponse(
+                    type="error",
+                    error=OverloadedError(
+                        message="Overloaded", type="overloaded_error"
+                    ),
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with pytest.raises(APIStatusError), mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            for _ in message:
+                pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+    assert span["status"] == "internal_error"
+    assert span["tags"]["status"] == "internal_error"
+    assert event["contexts"]["trace"]["status"] == "internal_error"
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_stream_messages(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="max_tokens"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                for event in stream:
+                    pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert (
+            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+            == '[{"role": "user", "content": "Hello, Claude"}]'
+        )
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["max_tokens"]
+
+
+def test_stream_messages_close(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="max_tokens"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                for _ in range(4):
+                    next(stream)
+
+                # New versions add TextEvent, so consume one more event.
+                if TextEvent is not None and isinstance(next(stream), TextEvent):
+                    next(stream)
+
+                stream.close()
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 41),
+    reason="Error classes moved in https://github.com/anthropics/anthropic-sdk-python/commit/4e0b15e22fe40e9aa513459564f641bf97c90954.",
+)
+def test_stream_messages_api_error(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ErrorResponse(
+                    type="error",
+                    error=OverloadedError(
+                        message="Overloaded", type="overloaded_error"
+                    ),
+                ),
+            ]
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with pytest.raises(APIStatusError), mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                for event in stream:
+                    pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+    assert span["status"] == "internal_error"
+    assert span["tags"]["status"] == "internal_error"
+    assert event["contexts"]["trace"]["status"] == "internal_error"
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+async def test_streaming_create_message_async(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(stop_reason="max_tokens"),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        ),
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        default_integrations=False,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = await client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            async for _ in message:
+                pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    assert len(event["spans"]) == 1
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert (
+            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+            == '[{"role": "user", "content": "Hello, Claude"}]'
+        )
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["max_tokens"]
+
+
+@pytest.mark.asyncio
+async def test_streaming_create_message_async_close(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(stop_reason="max_tokens"),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            messages = await client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            for _ in range(4):
+                await messages.__anext__()
+            await messages.close()
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 41),
+    reason="Error classes moved in https://github.com/anthropics/anthropic-sdk-python/commit/4e0b15e22fe40e9aa513459564f641bf97c90954.",
+)
+@pytest.mark.asyncio
+async def test_streaming_create_message_async_api_error(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ErrorResponse(
+                        type="error",
+                        error=OverloadedError(
+                            message="Overloaded", type="overloaded_error"
+                        ),
+                    ),
+                ]
+            )
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with pytest.raises(APIStatusError), mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = await client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
+
+            async for _ in message:
+                pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+    assert span["status"] == "internal_error"
+    assert span["tags"]["status"] == "internal_error"
+    assert event["contexts"]["trace"]["status"] == "internal_error"
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+async def test_stream_message_async(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        ),
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            async with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                async for event in stream:
+                    pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    assert len(event["spans"]) == 1
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert (
+            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+            == '[{"role": "user", "content": "Hello, Claude"}]'
+        )
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 41),
+    reason="Error classes moved in https://github.com/anthropics/anthropic-sdk-python/commit/4e0b15e22fe40e9aa513459564f641bf97c90954.",
+)
+@pytest.mark.asyncio
+async def test_stream_messages_async_api_error(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ErrorResponse(
+                        type="error",
+                        error=OverloadedError(
+                            message="Overloaded", type="overloaded_error"
+                        ),
+                    ),
+                ]
+            )
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with pytest.raises(APIStatusError), mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            async with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                async for event in stream:
+                    pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
+
+    assert span["status"] == "internal_error"
+    assert span["tags"]["status"] == "internal_error"
+    assert event["contexts"]["trace"]["status"] == "internal_error"
+
+
+@pytest.mark.asyncio
+async def test_stream_messages_async_close(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(stop_reason="max_tokens"),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        )
+    )
+
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
-        send_default_pii=send_default_pii,
+        send_default_pii=True,
     )
     events = capture_events()
-    client = AsyncAnthropic(api_key="z")
-    client.messages._post = AsyncMock(return_value=EXAMPLE_MESSAGE)
 
     messages = [
         {
@@ -170,16 +1493,27 @@ async def test_nonstreaming_create_message_async(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        response = await client.messages.create(
-            max_tokens=1024, messages=messages, model="model"
-        )
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            async with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                for _ in range(4):
+                    await stream.__anext__()
 
-    assert response == EXAMPLE_MESSAGE
-    usage = response.usage
+                # New versions add TextEvent, so consume one more event.
+                if TextEvent is not None and isinstance(
+                    await stream.__anext__(), TextEvent
+                ):
+                    await stream.__anext__()
 
-    assert usage.input_tokens == 10
-    assert usage.output_tokens == 20
+                await stream.close()
 
     assert len(events) == 1
     (event,) = events
@@ -187,30 +1521,31 @@ async def test_nonstreaming_create_message_async(
     assert event["type"] == "transaction"
     assert event["transaction"] == "anthropic"
 
-    assert len(event["spans"]) == 1
-    (span,) = event["spans"]
+    span = next(span for span in event["spans"] if span["op"] == OP.GEN_AI_CHAT)
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
-    if send_default_pii and include_prompts:
-        assert (
-            span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
-            == '[{"role": "user", "content": "Hello, Claude"}]'
-        )
-        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi, I'm Claude."
-    else:
-        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
-        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+    assert (
+        span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
+        == '[{"role": "user", "content": "Hello, Claude"}]'
+    )
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi!"
 
     assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
     assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
     assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
-    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_ID] == "msg_01XFDUDYJgAACzvnptvVoYEL"
 
 
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 27),
+    reason="Versions <0.27.0 do not include InputJSONDelta, which was introduced in >=0.27.0 along with a new message delta type for tool calling.",
+)
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -220,43 +1555,82 @@ async def test_nonstreaming_create_message_async(
         (False, False),
     ],
 )
-def test_streaming_create_message(
-    sentry_init, capture_events, send_default_pii, include_prompts
+def test_streaming_create_message_with_input_json_delta(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
     client = Anthropic(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        MessageStartEvent(
-            message=EXAMPLE_MESSAGE,
-            type="message_start",
-        ),
-        ContentBlockStartEvent(
-            type="content_block_start",
-            index=0,
-            content_block=TextBlock(type="text", text=""),
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text="Hi", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text="!", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text=" I'm Claude!", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockStopEvent(type="content_block_stop", index=0),
-        MessageDeltaEvent(
-            delta=Delta(),
-            usage=MessageDeltaUsage(output_tokens=10),
-            type="message_delta",
-        ),
-    ]
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=Message(
+                        id="msg_0",
+                        content=[],
+                        model="claude-3-5-sonnet-20240620",
+                        role="assistant",
+                        stop_reason=None,
+                        stop_sequence=None,
+                        type="message",
+                        usage=Usage(input_tokens=366, output_tokens=10),
+                    ),
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=ToolUseBlock(
+                        id="toolu_0", input={}, name="get_weather", type="tool_use"
+                    ),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(
+                        partial_json='{"location": "', type="input_json_delta"
+                    ),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="S", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="an ", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(
+                        partial_json="Francisco, C", type="input_json_delta"
+                    ),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json='A"}', type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="tool_use", stop_sequence=None),
+                    usage=MessageDeltaUsage(output_tokens=41),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
 
     sentry_init(
         integrations=[AnthropicIntegration(include_prompts=include_prompts)],
@@ -264,24 +1638,27 @@ def test_streaming_create_message(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = mock.Mock(return_value=returned_stream)
 
     messages = [
         {
             "role": "user",
-            "content": "Hello, Claude",
+            "content": "What is the weather like in San Francisco?",
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = client.messages.create(
-            max_tokens=1024, messages=messages, model="model", stream=True
-        )
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
 
-        for _ in message:
-            pass
+            for _ in message:
+                pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -293,27 +1670,33 @@ def test_streaming_create_message(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
     if send_default_pii and include_prompts:
         assert (
             span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
-            == '[{"role": "user", "content": "Hello, Claude"}]'
+            == '[{"role": "user", "content": "What is the weather like in San Francisco?"}]'
+        )
+        assert (
+            span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
+            == '{"location": "San Francisco, CA"}'
         )
-        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
-
     else:
         assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
         assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
 
-    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
-    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
-    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 366
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 41
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 407
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
 
 
-@pytest.mark.asyncio
+@pytest.mark.skipif(
+    ANTHROPIC_VERSION < (0, 27),
+    reason="Versions <0.27.0 do not include InputJSONDelta, which was introduced in >=0.27.0 along with a new message delta type for tool calling.",
+)
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -323,44 +1706,81 @@ def test_streaming_create_message(
         (False, False),
     ],
 )
-async def test_streaming_create_message_async(
-    sentry_init, capture_events, send_default_pii, include_prompts
+def test_stream_messages_with_input_json_delta(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
-    client = AsyncAnthropic(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            MessageStartEvent(
-                message=EXAMPLE_MESSAGE,
-                type="message_start",
-            ),
-            ContentBlockStartEvent(
-                type="content_block_start",
-                index=0,
-                content_block=TextBlock(type="text", text=""),
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text="Hi", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text="!", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text=" I'm Claude!", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockStopEvent(type="content_block_stop", index=0),
-            MessageDeltaEvent(
-                delta=Delta(),
-                usage=MessageDeltaUsage(output_tokens=10),
-                type="message_delta",
-            ),
-        ]
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=Message(
+                        id="msg_0",
+                        content=[],
+                        model="claude-3-5-sonnet-20240620",
+                        role="assistant",
+                        stop_reason=None,
+                        stop_sequence=None,
+                        type="message",
+                        usage=Usage(input_tokens=366, output_tokens=10),
+                    ),
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=ToolUseBlock(
+                        id="toolu_0", input={}, name="get_weather", type="tool_use"
+                    ),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(
+                        partial_json='{"location": "', type="input_json_delta"
+                    ),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="S", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json="an ", type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(
+                        partial_json="Francisco, C", type="input_json_delta"
+                    ),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=InputJSONDelta(partial_json='A"}', type="input_json_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(stop_reason="tool_use", stop_sequence=None),
+                    usage=MessageDeltaUsage(output_tokens=41),
+                    type="message_delta",
+                ),
+            ]
+        )
     )
 
     sentry_init(
@@ -369,24 +1789,28 @@ async def test_streaming_create_message_async(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = AsyncMock(return_value=returned_stream)
 
     messages = [
         {
             "role": "user",
-            "content": "Hello, Claude",
+            "content": "What is the weather like in San Francisco?",
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = await client.messages.create(
-            max_tokens=1024, messages=messages, model="model", stream=True
-        )
-
-        async for _ in message:
-            pass
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                for event in stream:
+                    pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -398,26 +1822,30 @@ async def test_streaming_create_message_async(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
     if send_default_pii and include_prompts:
         assert (
             span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
-            == '[{"role": "user", "content": "Hello, Claude"}]'
+            == '[{"role": "user", "content": "What is the weather like in San Francisco?"}]'
+        )
+        assert (
+            span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
+            == '{"location": "San Francisco, CA"}'
         )
-        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
-
     else:
         assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
         assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
 
-    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
-    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
-    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 366
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 41
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 407
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
 
 
+@pytest.mark.asyncio
 @pytest.mark.skipif(
     ANTHROPIC_VERSION < (0, 27),
     reason="Versions <0.27.0 do not include InputJSONDelta, which was introduced in >=0.27.0 along with a new message delta type for tool calling.",
@@ -431,69 +1859,88 @@ async def test_streaming_create_message_async(
         (False, False),
     ],
 )
-def test_streaming_create_message_with_input_json_delta(
-    sentry_init, capture_events, send_default_pii, include_prompts
+async def test_streaming_create_message_with_input_json_delta_async(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
-    client = Anthropic(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        MessageStartEvent(
-            message=Message(
-                id="msg_0",
-                content=[],
-                model="claude-3-5-sonnet-20240620",
-                role="assistant",
-                stop_reason=None,
-                stop_sequence=None,
-                type="message",
-                usage=Usage(input_tokens=366, output_tokens=10),
-            ),
-            type="message_start",
-        ),
-        ContentBlockStartEvent(
-            type="content_block_start",
-            index=0,
-            content_block=ToolUseBlock(
-                id="toolu_0", input={}, name="get_weather", type="tool_use"
-            ),
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json="", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json="{'location':", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json=" 'S", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json="an ", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json="Francisco, C", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=InputJSONDelta(partial_json="A'}", type="input_json_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockStopEvent(type="content_block_stop", index=0),
-        MessageDeltaEvent(
-            delta=Delta(stop_reason="tool_use", stop_sequence=None),
-            usage=MessageDeltaUsage(output_tokens=41),
-            type="message_delta",
-        ),
-    ]
+    client = AsyncAnthropic(api_key="z")
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=Message(
+                            id="msg_0",
+                            content=[],
+                            model="claude-3-5-sonnet-20240620",
+                            role="assistant",
+                            stop_reason=None,
+                            stop_sequence=None,
+                            type="message",
+                            usage=Usage(input_tokens=366, output_tokens=10),
+                        ),
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=ToolUseBlock(
+                            id="toolu_0", input={}, name="get_weather", type="tool_use"
+                        ),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(partial_json="", type="input_json_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json='{"location": "', type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(partial_json="S", type="input_json_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json="an ", type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json="Francisco, C", type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json='A"}', type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(stop_reason="tool_use", stop_sequence=None),
+                        usage=MessageDeltaUsage(output_tokens=41),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        )
+    )
 
     sentry_init(
         integrations=[AnthropicIntegration(include_prompts=include_prompts)],
@@ -501,7 +1948,6 @@ def test_streaming_create_message_with_input_json_delta(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = mock.Mock(return_value=returned_stream)
 
     messages = [
         {
@@ -510,15 +1956,19 @@ def test_streaming_create_message_with_input_json_delta(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = client.messages.create(
-            max_tokens=1024, messages=messages, model="model", stream=True
-        )
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = await client.messages.create(
+                max_tokens=1024, messages=messages, model="model", stream=True
+            )
 
-        for _ in message:
-            pass
+            async for _ in message:
+                pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -530,6 +1980,7 @@ def test_streaming_create_message_with_input_json_delta(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -540,8 +1991,9 @@ def test_streaming_create_message_with_input_json_delta(
         )
         assert (
             span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
-            == "{'location': 'San Francisco, CA'}"
+            == '{"location": "San Francisco, CA"}'
         )
+
     else:
         assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
         assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
@@ -566,74 +2018,87 @@ def test_streaming_create_message_with_input_json_delta(
         (False, False),
     ],
 )
-async def test_streaming_create_message_with_input_json_delta_async(
-    sentry_init, capture_events, send_default_pii, include_prompts
+async def test_stream_message_with_input_json_delta_async(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     client = AsyncAnthropic(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            MessageStartEvent(
-                message=Message(
-                    id="msg_0",
-                    content=[],
-                    model="claude-3-5-sonnet-20240620",
-                    role="assistant",
-                    stop_reason=None,
-                    stop_sequence=None,
-                    type="message",
-                    usage=Usage(input_tokens=366, output_tokens=10),
-                ),
-                type="message_start",
-            ),
-            ContentBlockStartEvent(
-                type="content_block_start",
-                index=0,
-                content_block=ToolUseBlock(
-                    id="toolu_0", input={}, name="get_weather", type="tool_use"
-                ),
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(partial_json="", type="input_json_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(
-                    partial_json="{'location':", type="input_json_delta"
-                ),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(partial_json=" 'S", type="input_json_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(partial_json="an ", type="input_json_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(
-                    partial_json="Francisco, C", type="input_json_delta"
-                ),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=InputJSONDelta(partial_json="A'}", type="input_json_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockStopEvent(type="content_block_stop", index=0),
-            MessageDeltaEvent(
-                delta=Delta(stop_reason="tool_use", stop_sequence=None),
-                usage=MessageDeltaUsage(output_tokens=41),
-                type="message_delta",
-            ),
-        ]
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=Message(
+                            id="msg_0",
+                            content=[],
+                            model="claude-3-5-sonnet-20240620",
+                            role="assistant",
+                            stop_reason=None,
+                            stop_sequence=None,
+                            type="message",
+                            usage=Usage(input_tokens=366, output_tokens=10),
+                        ),
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=ToolUseBlock(
+                            id="toolu_0", input={}, name="get_weather", type="tool_use"
+                        ),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(partial_json="", type="input_json_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json='{"location": "', type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(partial_json="S", type="input_json_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json="an ", type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json="Francisco, C", type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=InputJSONDelta(
+                            partial_json='A"}', type="input_json_delta"
+                        ),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(stop_reason="tool_use", stop_sequence=None),
+                        usage=MessageDeltaUsage(output_tokens=41),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        )
     )
 
     sentry_init(
@@ -642,7 +2107,6 @@ async def test_streaming_create_message_with_input_json_delta_async(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = AsyncMock(return_value=returned_stream)
 
     messages = [
         {
@@ -651,15 +2115,20 @@ async def test_streaming_create_message_with_input_json_delta_async(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = await client.messages.create(
-            max_tokens=1024, messages=messages, model="model", stream=True
-        )
-
-        async for _ in message:
-            pass
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            async with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+            ) as stream:
+                async for event in stream:
+                    pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -671,6 +2140,7 @@ async def test_streaming_create_message_with_input_json_delta_async(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -681,7 +2151,7 @@ async def test_streaming_create_message_with_input_json_delta_async(
         )
         assert (
             span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
-            == "{'location': 'San Francisco, CA'}"
+            == '{"location": "San Francisco, CA"}'
         )
 
     else:
@@ -734,7 +2204,7 @@ def test_span_status_error(sentry_init, capture_events):
     assert error["level"] == "error"
     assert transaction["spans"][0]["status"] == "internal_error"
     assert transaction["spans"][0]["tags"]["status"] == "internal_error"
-    assert transaction["contexts"]["trace"]["status"] == "internal_error"
+    assert transaction["spans"][0]["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert transaction["spans"][0]["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
 
 
@@ -759,7 +2229,7 @@ async def test_span_status_error_async(sentry_init, capture_events):
     assert error["level"] == "error"
     assert transaction["spans"][0]["status"] == "internal_error"
     assert transaction["spans"][0]["tags"]["status"] == "internal_error"
-    assert transaction["contexts"]["trace"]["status"] == "internal_error"
+    assert transaction["spans"][0]["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert transaction["spans"][0]["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
 
 
@@ -808,6 +2278,7 @@ def test_span_origin(sentry_init, capture_events):
 
     assert event["contexts"]["trace"]["origin"] == "manual"
     assert event["spans"][0]["origin"] == "auto.ai.anthropic"
+    assert event["spans"][0]["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert event["spans"][0]["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
 
 
@@ -836,6 +2307,7 @@ async def test_span_origin_async(sentry_init, capture_events):
 
     assert event["contexts"]["trace"]["origin"] == "manual"
     assert event["spans"][0]["origin"] == "auto.ai.anthropic"
+    assert event["spans"][0]["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert event["spans"][0]["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
 
 
@@ -857,13 +2329,15 @@ def test_collect_ai_data_with_input_json_delta():
 
     content_blocks = []
 
-    model, new_usage, new_content_blocks = _collect_ai_data(
+    model, new_usage, new_content_blocks, response_id, finish_reason = _collect_ai_data(
         event, model, usage, content_blocks
     )
     assert model is None
     assert new_usage.input_tokens == usage.input_tokens
     assert new_usage.output_tokens == usage.output_tokens
     assert new_content_blocks == ["test"]
+    assert response_id is None
+    assert finish_reason is None
 
 
 @pytest.mark.skipif(
@@ -956,6 +2430,7 @@ def mock_messages_create(*args, **kwargs):
 
     # Verify that the span was created correctly
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert SPANDATA.GEN_AI_REQUEST_MESSAGES in span["data"]
 
@@ -1001,6 +2476,7 @@ def test_anthropic_message_truncation(sentry_init, capture_events):
     assert len(chat_spans) > 0
 
     chat_span = chat_spans[0]
+    assert chat_span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert chat_span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert SPANDATA.GEN_AI_REQUEST_MESSAGES in chat_span["data"]
 
@@ -1052,6 +2528,7 @@ async def test_anthropic_message_truncation_async(sentry_init, capture_events):
     assert len(chat_spans) > 0
 
     chat_span = chat_spans[0]
+    assert chat_span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert chat_span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert SPANDATA.GEN_AI_REQUEST_MESSAGES in chat_span["data"]
 
@@ -1063,9 +2540,95 @@ async def test_anthropic_message_truncation_async(sentry_init, capture_events):
     assert len(parsed_messages) == 1
     assert "small message 5" in str(parsed_messages[0])
 
-    assert tx["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 5
+    assert tx["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 5
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_nonstreaming_create_message_with_system_prompt(
+    sentry_init, capture_events, send_default_pii, include_prompts
+):
+    """Test that system prompts are properly captured in GEN_AI_REQUEST_MESSAGES."""
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+    client = Anthropic(api_key="z")
+    client.messages._post = mock.Mock(return_value=EXAMPLE_MESSAGE)
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with start_transaction(name="anthropic"):
+        response = client.messages.create(
+            max_tokens=1024,
+            messages=messages,
+            model="model",
+            system="You are a helpful assistant.",
+        )
+
+    assert response == EXAMPLE_MESSAGE
+    usage = response.usage
+
+    assert usage.input_tokens == 10
+    assert usage.output_tokens == 20
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    assert len(event["spans"]) == 1
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS in span["data"]
+        system_instructions = json.loads(
+            span["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS]
+        )
+        assert system_instructions == [
+            {"type": "text", "content": "You are a helpful assistant."}
+        ]
+
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES in span["data"]
+        stored_messages = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+        assert len(stored_messages) == 1
+        assert stored_messages[0]["role"] == "user"
+        assert stored_messages[0]["content"] == "Hello, Claude"
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi, I'm Claude."
+    else:
+        assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in span["data"]
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["end_turn"]
 
 
+@pytest.mark.asyncio
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -1075,18 +2638,18 @@ async def test_anthropic_message_truncation_async(sentry_init, capture_events):
         (False, False),
     ],
 )
-def test_nonstreaming_create_message_with_system_prompt(
+async def test_nonstreaming_create_message_with_system_prompt_async(
     sentry_init, capture_events, send_default_pii, include_prompts
 ):
-    """Test that system prompts are properly captured in GEN_AI_REQUEST_MESSAGES."""
+    """Test that system prompts are properly captured in GEN_AI_REQUEST_MESSAGES (async)."""
     sentry_init(
         integrations=[AnthropicIntegration(include_prompts=include_prompts)],
         traces_sample_rate=1.0,
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client = Anthropic(api_key="z")
-    client.messages._post = mock.Mock(return_value=EXAMPLE_MESSAGE)
+    client = AsyncAnthropic(api_key="z")
+    client.messages._post = AsyncMock(return_value=EXAMPLE_MESSAGE)
 
     messages = [
         {
@@ -1096,7 +2659,7 @@ def test_nonstreaming_create_message_with_system_prompt(
     ]
 
     with start_transaction(name="anthropic"):
-        response = client.messages.create(
+        response = await client.messages.create(
             max_tokens=1024,
             messages=messages,
             model="model",
@@ -1120,6 +2683,7 @@ def test_nonstreaming_create_message_with_system_prompt(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -1147,9 +2711,9 @@ def test_nonstreaming_create_message_with_system_prompt(
     assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
     assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["end_turn"]
 
 
-@pytest.mark.asyncio
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -1159,18 +2723,60 @@ def test_nonstreaming_create_message_with_system_prompt(
         (False, False),
     ],
 )
-async def test_nonstreaming_create_message_with_system_prompt_async(
-    sentry_init, capture_events, send_default_pii, include_prompts
+def test_streaming_create_message_with_system_prompt(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
-    """Test that system prompts are properly captured in GEN_AI_REQUEST_MESSAGES (async)."""
+    """Test that system prompts are properly captured in streaming mode."""
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
+
     sentry_init(
         integrations=[AnthropicIntegration(include_prompts=include_prompts)],
         traces_sample_rate=1.0,
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client = AsyncAnthropic(api_key="z")
-    client.messages._post = AsyncMock(return_value=EXAMPLE_MESSAGE)
 
     messages = [
         {
@@ -1179,19 +2785,22 @@ async def test_nonstreaming_create_message_with_system_prompt_async(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        response = await client.messages.create(
-            max_tokens=1024,
-            messages=messages,
-            model="model",
-            system="You are a helpful assistant.",
-        )
-
-    assert response == EXAMPLE_MESSAGE
-    usage = response.usage
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = client.messages.create(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+                stream=True,
+                system="You are a helpful assistant.",
+            )
 
-    assert usage.input_tokens == 10
-    assert usage.output_tokens == 20
+            for _ in message:
+                pass
 
     assert len(events) == 1
     (event,) = events
@@ -1204,6 +2813,7 @@ async def test_nonstreaming_create_message_with_system_prompt_async(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -1221,16 +2831,17 @@ async def test_nonstreaming_create_message_with_system_prompt_async(
         assert len(stored_messages) == 1
         assert stored_messages[0]["role"] == "user"
         assert stored_messages[0]["content"] == "Hello, Claude"
-        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi, I'm Claude."
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
     else:
         assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in span["data"]
         assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
         assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
 
     assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
-    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
-    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
-    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
 
 
 @pytest.mark.parametrize(
@@ -1242,44 +2853,53 @@ async def test_nonstreaming_create_message_with_system_prompt_async(
         (False, False),
     ],
 )
-def test_streaming_create_message_with_system_prompt(
-    sentry_init, capture_events, send_default_pii, include_prompts
+def test_stream_messages_with_system_prompt(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
     """Test that system prompts are properly captured in streaming mode."""
     client = Anthropic(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        MessageStartEvent(
-            message=EXAMPLE_MESSAGE,
-            type="message_start",
-        ),
-        ContentBlockStartEvent(
-            type="content_block_start",
-            index=0,
-            content_block=TextBlock(type="text", text=""),
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text="Hi", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text="!", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockDeltaEvent(
-            delta=TextDelta(text=" I'm Claude!", type="text_delta"),
-            index=0,
-            type="content_block_delta",
-        ),
-        ContentBlockStopEvent(type="content_block_stop", index=0),
-        MessageDeltaEvent(
-            delta=Delta(),
-            usage=MessageDeltaUsage(output_tokens=10),
-            type="message_delta",
-        ),
-    ]
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    message=EXAMPLE_MESSAGE,
+                    type="message_start",
+                ),
+                ContentBlockStartEvent(
+                    type="content_block_start",
+                    index=0,
+                    content_block=TextBlock(type="text", text=""),
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="Hi", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text="!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockDeltaEvent(
+                    delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                    index=0,
+                    type="content_block_delta",
+                ),
+                ContentBlockStopEvent(type="content_block_stop", index=0),
+                MessageDeltaEvent(
+                    delta=Delta(),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                    type="message_delta",
+                ),
+            ]
+        )
+    )
 
     sentry_init(
         integrations=[AnthropicIntegration(include_prompts=include_prompts)],
@@ -1287,7 +2907,6 @@ def test_streaming_create_message_with_system_prompt(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = mock.Mock(return_value=returned_stream)
 
     messages = [
         {
@@ -1296,19 +2915,153 @@ def test_streaming_create_message_with_system_prompt(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = client.messages.create(
-            max_tokens=1024,
-            messages=messages,
-            model="model",
-            stream=True,
-            system="You are a helpful assistant.",
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+                system="You are a helpful assistant.",
+            ) as stream:
+                for event in stream:
+                    pass
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "anthropic"
+
+    assert len(event["spans"]) == 1
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
+
+    if send_default_pii and include_prompts:
+        assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS in span["data"]
+        system_instructions = json.loads(
+            span["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS]
+        )
+        assert system_instructions == [
+            {"type": "text", "content": "You are a helpful assistant."}
+        ]
+
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES in span["data"]
+        stored_messages = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+        assert len(stored_messages) == 1
+        assert stored_messages[0]["role"] == "user"
+        assert stored_messages[0]["content"] == "Hello, Claude"
+        assert span["data"][SPANDATA.GEN_AI_RESPONSE_TEXT] == "Hi! I'm Claude!"
+
+    else:
+        assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in span["data"]
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+async def test_stream_message_with_system_prompt_async(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    """Test that system prompts are properly captured in streaming mode (async)."""
+    client = AsyncAnthropic(api_key="z")
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
         )
+    )
 
-        for _ in message:
-            pass
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, Claude",
+        }
+    ]
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            async with client.messages.stream(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+                system="You are a helpful assistant.",
+            ) as stream:
+                async for event in stream:
+                    pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -1320,6 +3073,7 @@ def test_streaming_create_message_with_system_prompt(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -1361,44 +3115,54 @@ def test_streaming_create_message_with_system_prompt(
     ],
 )
 async def test_streaming_create_message_with_system_prompt_async(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     """Test that system prompts are properly captured in streaming mode (async)."""
     client = AsyncAnthropic(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            MessageStartEvent(
-                message=EXAMPLE_MESSAGE,
-                type="message_start",
-            ),
-            ContentBlockStartEvent(
-                type="content_block_start",
-                index=0,
-                content_block=TextBlock(type="text", text=""),
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text="Hi", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text="!", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockDeltaEvent(
-                delta=TextDelta(text=" I'm Claude!", type="text_delta"),
-                index=0,
-                type="content_block_delta",
-            ),
-            ContentBlockStopEvent(type="content_block_stop", index=0),
-            MessageDeltaEvent(
-                delta=Delta(),
-                usage=MessageDeltaUsage(output_tokens=10),
-                type="message_delta",
-            ),
-        ]
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    MessageStartEvent(
+                        message=EXAMPLE_MESSAGE,
+                        type="message_start",
+                    ),
+                    ContentBlockStartEvent(
+                        type="content_block_start",
+                        index=0,
+                        content_block=TextBlock(type="text", text=""),
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="Hi", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text="!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockDeltaEvent(
+                        delta=TextDelta(text=" I'm Claude!", type="text_delta"),
+                        index=0,
+                        type="content_block_delta",
+                    ),
+                    ContentBlockStopEvent(type="content_block_stop", index=0),
+                    MessageDeltaEvent(
+                        delta=Delta(),
+                        usage=MessageDeltaUsage(output_tokens=10),
+                        type="message_delta",
+                    ),
+                ]
+            )
+        )
     )
 
     sentry_init(
@@ -1407,7 +3171,6 @@ async def test_streaming_create_message_with_system_prompt_async(
         send_default_pii=send_default_pii,
     )
     events = capture_events()
-    client.messages._post = AsyncMock(return_value=returned_stream)
 
     messages = [
         {
@@ -1416,19 +3179,23 @@ async def test_streaming_create_message_with_system_prompt_async(
         }
     ]
 
-    with start_transaction(name="anthropic"):
-        message = await client.messages.create(
-            max_tokens=1024,
-            messages=messages,
-            model="model",
-            stream=True,
-            system="You are a helpful assistant.",
-        )
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            message = await client.messages.create(
+                max_tokens=1024,
+                messages=messages,
+                model="model",
+                stream=True,
+                system="You are a helpful assistant.",
+            )
 
-        async for _ in message:
-            pass
+            async for _ in message:
+                pass
 
-    assert message == returned_stream
     assert len(events) == 1
     (event,) = events
 
@@ -1440,6 +3207,7 @@ async def test_streaming_create_message_with_system_prompt_async(
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat model"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "model"
 
@@ -1506,6 +3274,7 @@ def test_system_prompt_with_complex_structure(sentry_init, capture_events):
     assert len(event["spans"]) == 1
     (span,) = event["spans"]
 
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
     assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
 
     assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS in span["data"]
@@ -2365,50 +4134,129 @@ def test_input_tokens_include_cache_read_nonstreaming(sentry_init, capture_event
     assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE] == 0
 
 
-def test_input_tokens_include_cache_read_streaming(sentry_init, capture_events):
+def test_input_tokens_include_cache_read_streaming(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
     """
     Test that gen_ai.usage.input_tokens includes cache_read tokens (streaming).
 
     Same cache-hit scenario as non-streaming, using realistic streaming events.
     """
     client = Anthropic(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        MessageStartEvent(
-            type="message_start",
-            message=Message(
-                id="id",
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    type="message_start",
+                    message=Message(
+                        id="id",
+                        model="claude-sonnet-4-20250514",
+                        role="assistant",
+                        content=[],
+                        type="message",
+                        usage=Usage(
+                            input_tokens=19,
+                            output_tokens=0,
+                            cache_read_input_tokens=2846,
+                            cache_creation_input_tokens=0,
+                        ),
+                    ),
+                ),
+                MessageDeltaEvent(
+                    type="message_delta",
+                    delta=Delta(stop_reason="end_turn"),
+                    usage=MessageDeltaUsage(output_tokens=14),
+                ),
+            ]
+        )
+    )
+
+    sentry_init(integrations=[AnthropicIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            for _ in client.messages.create(
+                max_tokens=1024,
+                messages=[{"role": "user", "content": "What is 5+5?"}],
                 model="claude-sonnet-4-20250514",
-                role="assistant",
-                content=[],
-                type="message",
-                usage=Usage(
-                    input_tokens=19,
-                    output_tokens=0,
-                    cache_read_input_tokens=2846,
-                    cache_creation_input_tokens=0,
+                stream=True,
+            ):
+                pass
+
+    (span,) = events[0]["spans"]
+
+    # input_tokens should be total: 19 + 2846 = test_stream_messages_input_tokens_include_cache_read_streaming
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 2865
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 2879  # 2865 + 14
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHED] == 2846
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE] == 0
+
+
+def test_stream_messages_input_tokens_include_cache_read_streaming(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    """
+    Test that gen_ai.usage.input_tokens includes cache_read tokens (streaming).
+
+    Same cache-hit scenario as non-streaming, using realistic streaming events.
+    """
+    client = Anthropic(api_key="z")
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    type="message_start",
+                    message=Message(
+                        id="id",
+                        model="claude-sonnet-4-20250514",
+                        role="assistant",
+                        content=[],
+                        type="message",
+                        usage=Usage(
+                            input_tokens=19,
+                            output_tokens=0,
+                            cache_read_input_tokens=2846,
+                            cache_creation_input_tokens=0,
+                        ),
+                    ),
                 ),
-            ),
-        ),
-        MessageDeltaEvent(
-            type="message_delta",
-            delta=Delta(stop_reason="end_turn"),
-            usage=MessageDeltaUsage(output_tokens=14),
-        ),
-    ]
+                MessageDeltaEvent(
+                    type="message_delta",
+                    delta=Delta(stop_reason="end_turn"),
+                    usage=MessageDeltaUsage(output_tokens=14),
+                ),
+            ]
+        )
+    )
 
     sentry_init(integrations=[AnthropicIntegration()], traces_sample_rate=1.0)
     events = capture_events()
-    client.messages._post = mock.Mock(return_value=returned_stream)
 
-    with start_transaction(name="anthropic"):
-        for _ in client.messages.create(
-            max_tokens=1024,
-            messages=[{"role": "user", "content": "What is 5+5?"}],
-            model="claude-sonnet-4-20250514",
-            stream=True,
-        ):
-            pass
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=[{"role": "user", "content": "What is 5+5?"}],
+                model="claude-sonnet-4-20250514",
+            ) as stream:
+                for event in stream:
+                    pass
 
     (span,) = events[0]["spans"]
 
@@ -2457,46 +4305,119 @@ def test_input_tokens_unchanged_without_caching(sentry_init, capture_events):
     assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 32  # 20 + 12
 
 
-def test_cache_tokens_streaming(sentry_init, capture_events):
+def test_cache_tokens_streaming(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
     """Test cache tokens are tracked for streaming responses."""
     client = Anthropic(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        MessageStartEvent(
-            type="message_start",
-            message=Message(
-                id="id",
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    type="message_start",
+                    message=Message(
+                        id="id",
+                        model="claude-3-5-sonnet-20241022",
+                        role="assistant",
+                        content=[],
+                        type="message",
+                        usage=Usage(
+                            input_tokens=100,
+                            output_tokens=0,
+                            cache_read_input_tokens=80,
+                            cache_creation_input_tokens=20,
+                        ),
+                    ),
+                ),
+                MessageDeltaEvent(
+                    type="message_delta",
+                    delta=Delta(stop_reason="end_turn"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                ),
+            ]
+        )
+    )
+
+    sentry_init(integrations=[AnthropicIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            for _ in client.messages.create(
+                max_tokens=1024,
+                messages=[{"role": "user", "content": "Hello"}],
                 model="claude-3-5-sonnet-20241022",
-                role="assistant",
-                content=[],
-                type="message",
-                usage=Usage(
-                    input_tokens=100,
-                    output_tokens=0,
-                    cache_read_input_tokens=80,
-                    cache_creation_input_tokens=20,
+                stream=True,
+            ):
+                pass
+
+    (span,) = events[0]["spans"]
+    # input_tokens normalized: 100 + 80 (cache_read) + 20 (cache_write) = 200
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 200
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 210
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHED] == 80
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE] == 20
+
+
+def test_stream_messages_cache_tokens(
+    sentry_init, capture_events, get_model_response, server_side_event_chunks
+):
+    """Test cache tokens are tracked for streaming responses."""
+    client = Anthropic(api_key="z")
+
+    response = get_model_response(
+        server_side_event_chunks(
+            [
+                MessageStartEvent(
+                    type="message_start",
+                    message=Message(
+                        id="id",
+                        model="claude-3-5-sonnet-20241022",
+                        role="assistant",
+                        content=[],
+                        type="message",
+                        usage=Usage(
+                            input_tokens=100,
+                            output_tokens=0,
+                            cache_read_input_tokens=80,
+                            cache_creation_input_tokens=20,
+                        ),
+                    ),
                 ),
-            ),
-        ),
-        MessageDeltaEvent(
-            type="message_delta",
-            delta=Delta(stop_reason="end_turn"),
-            usage=MessageDeltaUsage(output_tokens=10),
-        ),
-    ]
+                MessageDeltaEvent(
+                    type="message_delta",
+                    delta=Delta(stop_reason="end_turn"),
+                    usage=MessageDeltaUsage(output_tokens=10),
+                ),
+            ]
+        )
+    )
 
     sentry_init(integrations=[AnthropicIntegration()], traces_sample_rate=1.0)
     events = capture_events()
-    client.messages._post = mock.Mock(return_value=returned_stream)
 
-    with start_transaction(name="anthropic"):
-        for _ in client.messages.create(
-            max_tokens=1024,
-            messages=[{"role": "user", "content": "Hello"}],
-            model="claude-3-5-sonnet-20241022",
-            stream=True,
-        ):
-            pass
+    with mock.patch.object(
+        client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        with start_transaction(name="anthropic"):
+            with client.messages.stream(
+                max_tokens=1024,
+                messages=[{"role": "user", "content": "Hello"}],
+                model="claude-3-5-sonnet-20241022",
+            ) as stream:
+                for event in stream:
+                    pass
 
     (span,) = events[0]["spans"]
     # input_tokens normalized: 100 + 80 (cache_read) + 20 (cache_write) = 200
diff --git a/tests/integrations/asgi/test_asgi.py b/tests/integrations/asgi/test_asgi.py
index ec2796c140..7f44c9d00a 100644
--- a/tests/integrations/asgi/test_asgi.py
+++ b/tests/integrations/asgi/test_asgi.py
@@ -164,55 +164,117 @@ def test_invalid_transaction_style(asgi3_app):
 
 
 @pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_capture_transaction(
     sentry_init,
     asgi3_app,
     capture_events,
+    capture_items,
+    span_streaming,
 ):
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryAsgiMiddleware(asgi3_app)
 
     async with TestClient(app) as client:
-        events = capture_events()
+        if span_streaming:
+            items = capture_items("span")
+        else:
+            events = capture_events()
         await client.get("/some_url?somevalue=123")
 
-    (transaction_event,) = events
-
-    assert transaction_event["type"] == "transaction"
-    assert transaction_event["transaction"] == "/some_url"
-    assert transaction_event["transaction_info"] == {"source": "url"}
-    assert transaction_event["contexts"]["trace"]["op"] == "http.server"
-    assert transaction_event["request"] == {
-        "headers": {
-            "host": "localhost",
-            "remote-addr": "127.0.0.1",
-            "user-agent": "ASGI-Test-Client",
-        },
-        "method": "GET",
-        "query_string": "somevalue=123",
-        "url": "http://localhost/some_url",
-    }
+    sentry_sdk.flush()
+
+    if span_streaming:
+        assert len(items) == 1
+        span = items[0].payload
+
+        assert span["is_segment"] is True
+        assert span["name"] == "/some_url"
+
+        assert span["attributes"]["sentry.span.source"] == "url"
+        assert span["attributes"]["sentry.op"] == "http.server"
+
+        assert span["attributes"]["url.full"] == "http://localhost/some_url"
+        assert span["attributes"]["network.protocol.name"] == "http"
+        assert span["attributes"]["http.request.method"] == "GET"
+        assert span["attributes"]["http.query"] == "somevalue=123"
+        assert span["attributes"]["http.request.header.host"] == "localhost"
+        assert span["attributes"]["http.request.header.remote-addr"] == "127.0.0.1"
+        assert (
+            span["attributes"]["http.request.header.user-agent"] == "ASGI-Test-Client"
+        )
+
+    else:
+        (transaction_event,) = events
+
+        assert transaction_event["type"] == "transaction"
+        assert transaction_event["transaction"] == "/some_url"
+        assert transaction_event["transaction_info"] == {"source": "url"}
+        assert transaction_event["contexts"]["trace"]["op"] == "http.server"
+        assert transaction_event["request"] == {
+            "headers": {
+                "host": "localhost",
+                "remote-addr": "127.0.0.1",
+                "user-agent": "ASGI-Test-Client",
+            },
+            "method": "GET",
+            "query_string": "somevalue=123",
+            "url": "http://localhost/some_url",
+        }
 
 
 @pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_capture_transaction_with_error(
     sentry_init,
     asgi3_app_with_error,
     capture_events,
+    capture_items,
     DictionaryContaining,  # noqa: N803
+    span_streaming,
 ):
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
+
     app = SentryAsgiMiddleware(asgi3_app_with_error)
 
-    events = capture_events()
+    if span_streaming:
+        items = capture_items("event", "span")
+    else:
+        events = capture_events()
+
     with pytest.raises(ZeroDivisionError):
         async with TestClient(app) as client:
             await client.get("/some_url")
 
-    (
-        error_event,
-        transaction_event,
-    ) = events
+    sentry_sdk.flush()
+
+    if span_streaming:
+        assert len(items) == 2
+        assert items[0].type == "event"
+        assert items[1].type == "span"
+
+        error_event = items[0].payload
+        span_item = items[1].payload
+    else:
+        (error_event, transaction_event) = events
 
     assert error_event["transaction"] == "/some_url"
     assert error_event["transaction_info"] == {"source": "url"}
@@ -222,45 +284,94 @@ async def test_capture_transaction_with_error(
     assert error_event["exception"]["values"][0]["mechanism"]["handled"] is False
     assert error_event["exception"]["values"][0]["mechanism"]["type"] == "asgi"
 
-    assert transaction_event["type"] == "transaction"
-    assert transaction_event["contexts"]["trace"] == DictionaryContaining(
-        error_event["contexts"]["trace"]
-    )
-    assert transaction_event["contexts"]["trace"]["status"] == "internal_error"
-    assert transaction_event["transaction"] == error_event["transaction"]
-    assert transaction_event["request"] == error_event["request"]
+    if span_streaming:
+        assert span_item["trace_id"] == error_event["contexts"]["trace"]["trace_id"]
+        assert span_item["span_id"] == error_event["contexts"]["trace"]["span_id"]
+        assert span_item.get("parent_span_id") == error_event["contexts"]["trace"].get(
+            "parent_span_id"
+        )
+        assert span_item["status"] == "error"
+
+    else:
+        assert transaction_event["type"] == "transaction"
+        assert transaction_event["contexts"]["trace"] == DictionaryContaining(
+            error_event["contexts"]["trace"]
+        )
+        assert transaction_event["contexts"]["trace"]["status"] == "internal_error"
+        assert transaction_event["transaction"] == error_event["transaction"]
+        assert transaction_event["request"] == error_event["request"]
 
 
 @pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_has_trace_if_performance_enabled(
     sentry_init,
     asgi3_app_with_error_and_msg,
     capture_events,
+    capture_items,
+    span_streaming,
 ):
-    sentry_init(traces_sample_rate=1.0)
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryAsgiMiddleware(asgi3_app_with_error_and_msg)
 
     with pytest.raises(ZeroDivisionError):
         async with TestClient(app) as client:
-            events = capture_events()
+            if span_streaming:
+                items = capture_items("event", "span")
+            else:
+                events = capture_events()
             await client.get("/")
 
-    msg_event, error_event, transaction_event = events
+    sentry_sdk.flush()
 
-    assert msg_event["contexts"]["trace"]
-    assert "trace_id" in msg_event["contexts"]["trace"]
+    if span_streaming:
+        msg_event, error_event, span = items
 
-    assert error_event["contexts"]["trace"]
-    assert "trace_id" in error_event["contexts"]["trace"]
+        assert msg_event.type == "event"
+        msg_event = msg_event.payload
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
 
-    assert transaction_event["contexts"]["trace"]
-    assert "trace_id" in transaction_event["contexts"]["trace"]
+        assert error_event.type == "event"
+        error_event = error_event.payload
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
 
-    assert (
-        error_event["contexts"]["trace"]["trace_id"]
-        == transaction_event["contexts"]["trace"]["trace_id"]
-        == msg_event["contexts"]["trace"]["trace_id"]
-    )
+        assert span.type == "span"
+        span = span.payload
+        assert span["trace_id"] is not None
+
+        assert (
+            error_event["contexts"]["trace"]["trace_id"]
+            == msg_event["contexts"]["trace"]["trace_id"]
+            == span["trace_id"]
+        )
+
+    else:
+        msg_event, error_event, transaction_event = events
+
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
+
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
+
+        assert transaction_event["contexts"]["trace"]
+        assert "trace_id" in transaction_event["contexts"]["trace"]
+
+        assert (
+            error_event["contexts"]["trace"]["trace_id"]
+            == transaction_event["contexts"]["trace"]["trace_id"]
+            == msg_event["contexts"]["trace"]["trace_id"]
+        )
 
 
 @pytest.mark.asyncio
@@ -286,13 +397,24 @@ async def test_has_trace_if_performance_disabled(
     assert "trace_id" in error_event["contexts"]["trace"]
 
 
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 @pytest.mark.asyncio
 async def test_trace_from_headers_if_performance_enabled(
     sentry_init,
     asgi3_app_with_error_and_msg,
     capture_events,
+    capture_items,
+    span_streaming,
 ):
-    sentry_init(traces_sample_rate=1.0)
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryAsgiMiddleware(asgi3_app_with_error_and_msg)
 
     trace_id = "582b43a4192642f0b136d5159a501701"
@@ -300,23 +422,50 @@ async def test_trace_from_headers_if_performance_enabled(
 
     with pytest.raises(ZeroDivisionError):
         async with TestClient(app) as client:
-            events = capture_events()
+            if span_streaming:
+                items = capture_items("event", "span")
+            else:
+                events = capture_events()
             await client.get("/", headers={"sentry-trace": sentry_trace_header})
 
-    msg_event, error_event, transaction_event = events
+    sentry_sdk.flush()
 
-    assert msg_event["contexts"]["trace"]
-    assert "trace_id" in msg_event["contexts"]["trace"]
+    if span_streaming:
+        msg_event, error_event, span = items
 
-    assert error_event["contexts"]["trace"]
-    assert "trace_id" in error_event["contexts"]["trace"]
+        assert msg_event.type == "event"
+        msg_event = msg_event.payload
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
 
-    assert transaction_event["contexts"]["trace"]
-    assert "trace_id" in transaction_event["contexts"]["trace"]
+        assert error_event.type == "event"
+        error_event = error_event.payload
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
 
-    assert msg_event["contexts"]["trace"]["trace_id"] == trace_id
-    assert error_event["contexts"]["trace"]["trace_id"] == trace_id
-    assert transaction_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert span.type == "span"
+        span = span.payload
+        assert span["trace_id"] is not None
+
+        assert msg_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert error_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert span["trace_id"] == trace_id
+
+    else:
+        msg_event, error_event, transaction_event = events
+
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
+
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
+
+        assert transaction_event["contexts"]["trace"]
+        assert "trace_id" in transaction_event["contexts"]["trace"]
+
+        assert msg_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert error_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert transaction_event["contexts"]["trace"]["trace_id"] == trace_id
 
 
 @pytest.mark.asyncio
@@ -348,10 +497,25 @@ async def test_trace_from_headers_if_performance_disabled(
 
 
 @pytest.mark.asyncio
-async def test_websocket(sentry_init, asgi3_ws_app, capture_events, request):
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
-
-    events = capture_events()
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
+async def test_websocket(
+    sentry_init,
+    asgi3_ws_app,
+    capture_events,
+    capture_items,
+    request,
+    span_streaming,
+):
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
 
     asgi3_ws_app = SentryAsgiMiddleware(asgi3_ws_app)
 
@@ -359,21 +523,48 @@ async def test_websocket(sentry_init, asgi3_ws_app, capture_events, request):
 
     with pytest.raises(ValueError):
         client = TestClient(asgi3_ws_app)
+        if span_streaming:
+            items = capture_items("event", "span")
+        else:
+            events = capture_events()
         async with client.websocket_connect(request_url) as ws:
             await ws.receive_text()
 
-    msg_event, error_event, transaction_event = events
+    sentry_sdk.flush()
+
+    if span_streaming:
+        msg_event, error_event, span = items
+
+        assert msg_event.type == "event"
+        msg_event = msg_event.payload
+        assert msg_event["transaction"] == request_url
+        assert msg_event["transaction_info"] == {"source": "url"}
+        assert msg_event["message"] == "Some message to the world!"
+
+        assert error_event.type == "event"
+        error_event = error_event.payload
+        (exc,) = error_event["exception"]["values"]
+        assert exc["type"] == "ValueError"
+        assert exc["value"] == "Oh no"
+
+        assert span.type == "span"
+        span = span.payload
+        assert span["name"] == request_url
+        assert span["attributes"]["sentry.span.source"] == "url"
+
+    else:
+        msg_event, error_event, transaction_event = events
 
-    assert msg_event["transaction"] == request_url
-    assert msg_event["transaction_info"] == {"source": "url"}
-    assert msg_event["message"] == "Some message to the world!"
+        assert msg_event["transaction"] == request_url
+        assert msg_event["transaction_info"] == {"source": "url"}
+        assert msg_event["message"] == "Some message to the world!"
 
-    (exc,) = error_event["exception"]["values"]
-    assert exc["type"] == "ValueError"
-    assert exc["value"] == "Oh no"
+        (exc,) = error_event["exception"]["values"]
+        assert exc["type"] == "ValueError"
+        assert exc["value"] == "Oh no"
 
-    assert transaction_event["transaction"] == request_url
-    assert transaction_event["transaction_info"] == {"source": "url"}
+        assert transaction_event["transaction"] == request_url
+        assert transaction_event["transaction_info"] == {"source": "url"}
 
 
 @pytest.mark.asyncio
@@ -431,17 +622,29 @@ async def test_auto_session_tracking_with_aggregates(
         ),
     ],
 )
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 @pytest.mark.asyncio
 async def test_transaction_style(
     sentry_init,
     asgi3_app,
     capture_events,
+    capture_items,
     url,
     transaction_style,
     expected_transaction,
     expected_source,
+    span_streaming,
 ):
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryAsgiMiddleware(asgi3_app, transaction_style=transaction_style)
 
     scope = {
@@ -451,13 +654,26 @@ async def test_transaction_style(
     }
 
     async with TestClient(app, scope=scope) as client:
-        events = capture_events()
+        if span_streaming:
+            items = capture_items("span")
+        else:
+            events = capture_events()
         await client.get(url)
 
-    (transaction_event,) = events
+    sentry_sdk.flush()
+
+    if span_streaming:
+        assert len(items) == 1
+        span = items[0].payload
+
+        assert span["name"] == expected_transaction
+        assert span["attributes"]["sentry.span.source"] == expected_source
+
+    else:
+        (transaction_event,) = events
 
-    assert transaction_event["transaction"] == expected_transaction
-    assert transaction_event["transaction_info"] == {"source": expected_source}
+        assert transaction_event["transaction"] == expected_transaction
+        assert transaction_event["transaction_info"] == {"source": expected_source}
 
 
 def mock_asgi2_app():
@@ -622,6 +838,10 @@ def test_get_headers():
         ),
     ],
 )
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_transaction_name(
     sentry_init,
     request_url,
@@ -630,28 +850,47 @@ async def test_transaction_name(
     expected_transaction_source,
     asgi3_app,
     capture_envelopes,
+    capture_items,
+    span_streaming,
 ):
     """
     Tests that the transaction name is something meaningful.
     """
     sentry_init(
         traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
     )
 
-    envelopes = capture_envelopes()
+    if span_streaming:
+        items = capture_items("span")
+    else:
+        envelopes = capture_envelopes()
 
     app = SentryAsgiMiddleware(asgi3_app, transaction_style=transaction_style)
 
     async with TestClient(app) as client:
         await client.get(request_url)
 
-    (transaction_envelope,) = envelopes
-    transaction_event = transaction_envelope.get_transaction_event()
+    if span_streaming:
+        sentry_sdk.flush()
 
-    assert transaction_event["transaction"] == expected_transaction_name
-    assert (
-        transaction_event["transaction_info"]["source"] == expected_transaction_source
-    )
+        assert len(items) == 1
+        span = items[0].payload
+
+        assert span["name"] == expected_transaction_name
+        assert span["attributes"]["sentry.span.source"] == expected_transaction_source
+
+    else:
+        (transaction_envelope,) = envelopes
+        transaction_event = transaction_envelope.get_transaction_event()
+
+        assert transaction_event["transaction"] == expected_transaction_name
+        assert (
+            transaction_event["transaction_info"]["source"]
+            == expected_transaction_source
+        )
 
 
 @pytest.mark.asyncio
@@ -672,6 +911,10 @@ async def test_transaction_name(
         ),
     ],
 )
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_transaction_name_in_traces_sampler(
     sentry_init,
     request_url,
@@ -679,6 +922,7 @@ async def test_transaction_name_in_traces_sampler(
     expected_transaction_name,
     expected_transaction_source,
     asgi3_app,
+    span_streaming,
 ):
     """
     Tests that a custom traces_sampler has a meaningful transaction name.
@@ -686,17 +930,28 @@ async def test_transaction_name_in_traces_sampler(
     """
 
     def dummy_traces_sampler(sampling_context):
-        assert (
-            sampling_context["transaction_context"]["name"] == expected_transaction_name
-        )
-        assert (
-            sampling_context["transaction_context"]["source"]
-            == expected_transaction_source
-        )
+        if span_streaming:
+            assert sampling_context["span_context"]["name"] == expected_transaction_name
+            assert (
+                sampling_context["span_context"]["attributes"]["sentry.span.source"]
+                == expected_transaction_source
+            )
+        else:
+            assert (
+                sampling_context["transaction_context"]["name"]
+                == expected_transaction_name
+            )
+            assert (
+                sampling_context["transaction_context"]["source"]
+                == expected_transaction_source
+            )
 
     sentry_init(
         traces_sampler=dummy_traces_sampler,
         traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
     )
 
     app = SentryAsgiMiddleware(asgi3_app, transaction_style=transaction_style)
@@ -706,17 +961,44 @@ def dummy_traces_sampler(sampling_context):
 
 
 @pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "span_streaming",
+    [True, False],
+)
 async def test_custom_transaction_name(
-    sentry_init, asgi3_custom_transaction_app, capture_events
+    sentry_init,
+    asgi3_custom_transaction_app,
+    capture_events,
+    capture_items,
+    span_streaming,
 ):
-    sentry_init(traces_sample_rate=1.0)
-    events = capture_events()
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryAsgiMiddleware(asgi3_custom_transaction_app)
 
     async with TestClient(app) as client:
+        if span_streaming:
+            items = capture_items("span")
+        else:
+            events = capture_events()
         await client.get("/test")
 
-    (transaction_event,) = events
-    assert transaction_event["type"] == "transaction"
-    assert transaction_event["transaction"] == "foobar"
-    assert transaction_event["transaction_info"] == {"source": "custom"}
+    sentry_sdk.flush()
+
+    if span_streaming:
+        assert len(items) == 1
+        span = items[0].payload
+
+        assert span["is_segment"] is True
+        assert span["name"] == "foobar"
+        assert span["attributes"]["sentry.span.source"] == "custom"
+
+    else:
+        (transaction_event,) = events
+        assert transaction_event["type"] == "transaction"
+        assert transaction_event["transaction"] == "foobar"
+        assert transaction_event["transaction_info"] == {"source": "custom"}
diff --git a/tests/integrations/asyncio/test_asyncio.py b/tests/integrations/asyncio/test_asyncio.py
index b41aa244cb..d32849c7b5 100644
--- a/tests/integrations/asyncio/test_asyncio.py
+++ b/tests/integrations/asyncio/test_asyncio.py
@@ -1,7 +1,10 @@
 import asyncio
 import inspect
 import sys
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock, Mock, patch
+
+if sys.version_info >= (3, 8):
+    from unittest.mock import AsyncMock
 
 import pytest
 
@@ -24,6 +27,11 @@
 )
 
 
+minimum_python_39 = pytest.mark.skipif(
+    sys.version_info < (3, 9), reason="Test requires Python >= 3.9"
+)
+
+
 minimum_python_311 = pytest.mark.skipif(
     sys.version_info < (3, 11),
     reason="Asyncio task context parameter was introduced in Python 3.11",
@@ -564,3 +572,112 @@ async def test_delayed_enable_integration_after_disabling(sentry_init, capture_e
     (transaction,) = events
     assert transaction["spans"]
     assert transaction["spans"][0]["origin"] == "auto.function.asyncio"
+
+
+@minimum_python_39
+@pytest.mark.asyncio(loop_scope="module")
+async def test_internal_tasks_not_wrapped(sentry_init, capture_events):
+    from sentry_sdk.utils import mark_sentry_task_internal
+
+    sentry_init(integrations=[AsyncioIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    # Create a user task that should be wrapped
+    async def user_task():
+        await asyncio.sleep(0.01)
+        return "user_result"
+
+    # Create an internal task that should NOT be wrapped
+    async def internal_task():
+        await asyncio.sleep(0.01)
+        return "internal_result"
+
+    with sentry_sdk.start_transaction(name="test_transaction"):
+        user_task_obj = asyncio.create_task(user_task())
+
+        with mark_sentry_task_internal():
+            internal_task_obj = asyncio.create_task(internal_task())
+
+        user_result = await user_task_obj
+        internal_result = await internal_task_obj
+
+    assert user_result == "user_result"
+    assert internal_result == "internal_result"
+
+    assert len(events) == 1
+    transaction = events[0]
+
+    user_spans = []
+    internal_spans = []
+
+    for span in transaction.get("spans", []):
+        if "user_task" in span.get("description", ""):
+            user_spans.append(span)
+        elif "internal_task" in span.get("description", ""):
+            internal_spans.append(span)
+
+    assert len(user_spans) > 0, (
+        f"User task should have been traced. All spans: {[s.get('description') for s in transaction.get('spans', [])]}"
+    )
+    assert len(internal_spans) == 0, (
+        f"Internal task should NOT have been traced. All spans: {[s.get('description') for s in transaction.get('spans', [])]}"
+    )
+
+
+@minimum_python_38
+def test_loop_close_patching(sentry_init):
+    sentry_init(integrations=[AsyncioIntegration()])
+
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+
+    try:
+        with patch("asyncio.get_running_loop", return_value=loop):
+            assert not hasattr(loop, "_sentry_flush_patched")
+            AsyncioIntegration.setup_once()
+            assert hasattr(loop, "_sentry_flush_patched")
+            assert loop._sentry_flush_patched is True
+
+    finally:
+        if not loop.is_closed():
+            loop.close()
+
+
+@minimum_python_38
+def test_loop_close_flushes_async_transport(sentry_init):
+    from sentry_sdk.transport import ASYNC_TRANSPORT_AVAILABLE, AsyncHttpTransport
+
+    if not ASYNC_TRANSPORT_AVAILABLE:
+        pytest.skip("httpcore[asyncio] not installed")
+
+    sentry_init(integrations=[AsyncioIntegration()])
+
+    # Save the current event loop to restore it later
+    try:
+        original_loop = asyncio.get_event_loop()
+    except RuntimeError:
+        original_loop = None
+
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+
+    try:
+        with patch("asyncio.get_running_loop", return_value=loop):
+            AsyncioIntegration.setup_once()
+
+        mock_client = Mock()
+        mock_transport = Mock(spec=AsyncHttpTransport)
+        mock_client.transport = mock_transport
+        mock_client.close_async = AsyncMock(return_value=None)
+
+        with patch("sentry_sdk.get_client", return_value=mock_client):
+            loop.close()
+
+        mock_client.close_async.assert_called_once()
+        mock_client.close_async.assert_awaited_once()
+
+    finally:
+        if not loop.is_closed():
+            loop.close()
+        if original_loop:
+            asyncio.set_event_loop(original_loop)
diff --git a/tests/integrations/asyncpg/test_asyncpg.py b/tests/integrations/asyncpg/test_asyncpg.py
index e23612c055..2dcce52070 100644
--- a/tests/integrations/asyncpg/test_asyncpg.py
+++ b/tests/integrations/asyncpg/test_asyncpg.py
@@ -49,6 +49,7 @@ def _get_db_name():
             "db.name": PG_NAME,
             "db.system": "postgresql",
             "db.user": PG_USER,
+            "db.driver.name": "asyncpg",
             "server.address": PG_HOST,
             "server.port": PG_PORT,
         }
@@ -463,10 +464,7 @@ async def test_connection_pool(sentry_init, capture_events) -> None:
         {
             "category": "query",
             "data": {},
-            "message": "SELECT pg_advisory_unlock_all();\n"
-            "CLOSE ALL;\n"
-            "UNLISTEN *;\n"
-            "RESET ALL;",
+            "message": "SELECT pg_advisory_unlock_all(); CLOSE ALL; UNLISTEN *; RESET ALL;",
             "type": "default",
         },
         {
@@ -478,10 +476,7 @@ async def test_connection_pool(sentry_init, capture_events) -> None:
         {
             "category": "query",
             "data": {},
-            "message": "SELECT pg_advisory_unlock_all();\n"
-            "CLOSE ALL;\n"
-            "UNLISTEN *;\n"
-            "RESET ALL;",
+            "message": "SELECT pg_advisory_unlock_all(); CLOSE ALL; UNLISTEN *; RESET ALL;",
             "type": "default",
         },
     ]
@@ -491,7 +486,7 @@ async def test_connection_pool(sentry_init, capture_events) -> None:
 async def test_query_source_disabled(sentry_init, capture_events):
     sentry_options = {
         "integrations": [AsyncPGIntegration()],
-        "enable_tracing": True,
+        "traces_sample_rate": 1.0,
         "enable_db_query_source": False,
         "db_query_source_threshold_ms": 0,
     }
@@ -529,7 +524,7 @@ async def test_query_source_enabled(
 ):
     sentry_options = {
         "integrations": [AsyncPGIntegration()],
-        "enable_tracing": True,
+        "traces_sample_rate": 1.0,
         "db_query_source_threshold_ms": 0,
     }
     if enable_db_query_source is not None:
@@ -565,7 +560,7 @@ async def test_query_source_enabled(
 async def test_query_source(sentry_init, capture_events):
     sentry_init(
         integrations=[AsyncPGIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=0,
     )
@@ -615,7 +610,7 @@ async def test_query_source_with_module_in_search_path(sentry_init, capture_even
     """
     sentry_init(
         integrations=[AsyncPGIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=0,
     )
@@ -661,7 +656,7 @@ async def test_query_source_with_module_in_search_path(sentry_init, capture_even
 async def test_no_query_source_if_duration_too_short(sentry_init, capture_events):
     sentry_init(
         integrations=[AsyncPGIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=100,
     )
@@ -706,7 +701,7 @@ def fake_record_sql_queries(*args, **kwargs):
 async def test_query_source_if_duration_over_threshold(sentry_init, capture_events):
     sentry_init(
         integrations=[AsyncPGIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=100,
     )
@@ -786,3 +781,79 @@ async def test_span_origin(sentry_init, capture_events):
 
     for span in event["spans"]:
         assert span["origin"] == "auto.db.asyncpg"
+
+
+@pytest.mark.asyncio
+async def test_multiline_query_description_normalized(sentry_init, capture_events):
+    sentry_init(
+        integrations=[AsyncPGIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    with start_transaction(name="test_transaction"):
+        conn: Connection = await connect(PG_CONNECTION_URI)
+        await conn.execute(
+            """
+            SELECT
+                id,
+                name
+            FROM
+                users
+            WHERE
+                name = 'Alice'
+            """
+        )
+        await conn.close()
+
+    (event,) = events
+
+    spans = [
+        s
+        for s in event["spans"]
+        if s["op"] == "db" and "SELECT" in s.get("description", "")
+    ]
+    assert len(spans) == 1
+    assert spans[0]["description"] == "SELECT id, name FROM users WHERE name = 'Alice'"
+
+
+@pytest.mark.asyncio
+async def test_before_send_transaction_sees_normalized_description(
+    sentry_init, capture_events
+):
+    def before_send_transaction(event, hint):
+        for span in event.get("spans", []):
+            desc = span.get("description", "")
+            if "SELECT id, name FROM users" in desc:
+                span["description"] = "filtered"
+        return event
+
+    sentry_init(
+        integrations=[AsyncPGIntegration()],
+        traces_sample_rate=1.0,
+        before_send_transaction=before_send_transaction,
+    )
+    events = capture_events()
+
+    with start_transaction(name="test_transaction"):
+        conn: Connection = await connect(PG_CONNECTION_URI)
+        await conn.execute(
+            """
+            SELECT
+                id,
+                name
+            FROM
+                users
+            """
+        )
+        await conn.close()
+
+    (event,) = events
+    spans = [
+        s
+        for s in event["spans"]
+        if s["op"] == "db" and "filtered" in s.get("description", "")
+    ]
+
+    assert len(spans) == 1
+    assert spans[0]["description"] == "filtered"
diff --git a/tests/integrations/celery/test_celery.py b/tests/integrations/celery/test_celery.py
index 42ae6ea14f..5d2d19c06a 100644
--- a/tests/integrations/celery/test_celery.py
+++ b/tests/integrations/celery/test_celery.py
@@ -606,7 +606,7 @@ def example_task():
 def test_messaging_destination_name_default_exchange(
     mock_request, routing_key, init_celery, capture_events
 ):
-    celery_app = init_celery(enable_tracing=True)
+    celery_app = init_celery(traces_sample_rate=1.0)
     events = capture_events()
     mock_request.delivery_info = {"routing_key": routing_key, "exchange": ""}
 
@@ -630,7 +630,7 @@ def test_messaging_destination_name_nondefault_exchange(
     that the routing key is the queue name. Other exchanges may not guarantee this
     behavior.
     """
-    celery_app = init_celery(enable_tracing=True)
+    celery_app = init_celery(traces_sample_rate=1.0)
     events = capture_events()
     mock_request.delivery_info = {"routing_key": "celery", "exchange": "custom"}
 
@@ -645,7 +645,7 @@ def task(): ...
 
 
 def test_messaging_id(init_celery, capture_events):
-    celery = init_celery(enable_tracing=True)
+    celery = init_celery(traces_sample_rate=1.0)
     events = capture_events()
 
     @celery.task
@@ -659,7 +659,7 @@ def example_task(): ...
 
 
 def test_retry_count_zero(init_celery, capture_events):
-    celery = init_celery(enable_tracing=True)
+    celery = init_celery(traces_sample_rate=1.0)
     events = capture_events()
 
     @celery.task()
@@ -676,7 +676,7 @@ def task(): ...
 def test_retry_count_nonzero(mock_request, init_celery, capture_events):
     mock_request.retries = 3
 
-    celery = init_celery(enable_tracing=True)
+    celery = init_celery(traces_sample_rate=1.0)
     events = capture_events()
 
     @celery.task()
@@ -691,7 +691,7 @@ def task(): ...
 
 @pytest.mark.parametrize("system", ("redis", "amqp"))
 def test_messaging_system(system, init_celery, capture_events):
-    celery = init_celery(enable_tracing=True)
+    celery = init_celery(traces_sample_rate=1.0)
     events = capture_events()
 
     # Does not need to be a real URL, since we use always eager
@@ -716,7 +716,7 @@ def publish(*args, **kwargs):
 
     monkeypatch.setattr(kombu.messaging.Producer, "_publish", publish)
 
-    sentry_init(integrations=[CeleryIntegration()], enable_tracing=True)
+    sentry_init(integrations=[CeleryIntegration()], traces_sample_rate=1.0)
     celery = Celery(__name__, broker=f"{system}://example.com")  # noqa: E231
     events = capture_events()
 
@@ -754,7 +754,7 @@ def task(): ...
 
 
 def tests_span_origin_consumer(init_celery, capture_events):
-    celery = init_celery(enable_tracing=True)
+    celery = init_celery(traces_sample_rate=1.0)
     celery.conf.broker_url = "redis://example.com"  # noqa: E231
 
     events = capture_events()
@@ -778,7 +778,7 @@ def publish(*args, **kwargs):
 
     monkeypatch.setattr(kombu.messaging.Producer, "_publish", publish)
 
-    sentry_init(integrations=[CeleryIntegration()], enable_tracing=True)
+    sentry_init(integrations=[CeleryIntegration()], traces_sample_rate=1.0)
     celery = Celery(__name__, broker="redis://example.com")  # noqa: E231
 
     events = capture_events()
@@ -807,7 +807,7 @@ def test_send_task_wrapped(
     capture_events,
     reset_integrations,
 ):
-    sentry_init(integrations=[CeleryIntegration()], enable_tracing=True)
+    sentry_init(integrations=[CeleryIntegration()], traces_sample_rate=1.0)
     celery = Celery(__name__, broker="redis://example.com")  # noqa: E231
 
     events = capture_events()
diff --git a/tests/integrations/celery/test_update_celery_task_headers.py b/tests/integrations/celery/test_update_celery_task_headers.py
index 705c00de58..950b13826c 100644
--- a/tests/integrations/celery/test_update_celery_task_headers.py
+++ b/tests/integrations/celery/test_update_celery_task_headers.py
@@ -71,7 +71,7 @@ def test_monitor_beat_tasks_with_headers(monitor_beat_tasks):
 
 
 def test_span_with_transaction(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
     headers = {}
     monitor_beat_tasks = False
 
@@ -91,7 +91,7 @@ def test_span_with_transaction(sentry_init):
 
 
 def test_span_with_transaction_custom_headers(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
     headers = {
         "baggage": BAGGAGE_VALUE,
         "sentry-trace": SENTRY_TRACE_VALUE,
diff --git a/tests/integrations/clickhouse_driver/test_clickhouse_driver.py b/tests/integrations/clickhouse_driver/test_clickhouse_driver.py
index 635f9334c4..b501aa3531 100644
--- a/tests/integrations/clickhouse_driver/test_clickhouse_driver.py
+++ b/tests/integrations/clickhouse_driver/test_clickhouse_driver.py
@@ -42,6 +42,7 @@ def test_clickhouse_client_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -54,6 +55,7 @@ def test_clickhouse_client_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -66,6 +68,7 @@ def test_clickhouse_client_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -78,6 +81,7 @@ def test_clickhouse_client_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -90,6 +94,7 @@ def test_clickhouse_client_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -257,6 +262,7 @@ def test_clickhouse_client_spans(
             "description": "DROP TABLE IF EXISTS test",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -272,6 +278,7 @@ def test_clickhouse_client_spans(
             "description": "CREATE TABLE test (x Int32) ENGINE = Memory",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -287,6 +294,7 @@ def test_clickhouse_client_spans(
             "description": "INSERT INTO test (x) VALUES",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -302,6 +310,7 @@ def test_clickhouse_client_spans(
             "description": "INSERT INTO test (x) VALUES",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -317,6 +326,7 @@ def test_clickhouse_client_spans(
             "description": "SELECT sum(x) FROM test WHERE x > 150",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -529,6 +539,7 @@ def test_clickhouse_dbapi_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -541,6 +552,7 @@ def test_clickhouse_dbapi_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -553,6 +565,7 @@ def test_clickhouse_dbapi_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -565,6 +578,7 @@ def test_clickhouse_dbapi_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -577,6 +591,7 @@ def test_clickhouse_dbapi_breadcrumbs(sentry_init, capture_events) -> None:
             "category": "query",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -737,6 +752,7 @@ def test_clickhouse_dbapi_spans(sentry_init, capture_events, capture_envelopes)
             "description": "DROP TABLE IF EXISTS test",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -752,6 +768,7 @@ def test_clickhouse_dbapi_spans(sentry_init, capture_events, capture_envelopes)
             "description": "CREATE TABLE test (x Int32) ENGINE = Memory",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -767,6 +784,7 @@ def test_clickhouse_dbapi_spans(sentry_init, capture_events, capture_envelopes)
             "description": "INSERT INTO test (x) VALUES",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -782,6 +800,7 @@ def test_clickhouse_dbapi_spans(sentry_init, capture_events, capture_envelopes)
             "description": "INSERT INTO test (x) VALUES",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
@@ -797,6 +816,7 @@ def test_clickhouse_dbapi_spans(sentry_init, capture_events, capture_envelopes)
             "description": "SELECT sum(x) FROM test WHERE x > 150",
             "data": {
                 "db.system": "clickhouse",
+                "db.driver.name": "clickhouse-driver",
                 "db.name": "",
                 "db.user": "default",
                 "server.address": "localhost",
diff --git a/tests/integrations/django/test_tasks.py b/tests/integrations/django/test_tasks.py
index 220d64b111..56c68b807f 100644
--- a/tests/integrations/django/test_tasks.py
+++ b/tests/integrations/django/test_tasks.py
@@ -1,7 +1,6 @@
 import pytest
 
 import sentry_sdk
-from sentry_sdk import start_span
 from sentry_sdk.integrations.django import DjangoIntegration
 from sentry_sdk.consts import OP
 
diff --git a/tests/integrations/google_genai/test_google_genai.py b/tests/integrations/google_genai/test_google_genai.py
index 68ae9d234f..6e91ba6634 100644
--- a/tests/integrations/google_genai/test_google_genai.py
+++ b/tests/integrations/google_genai/test_google_genai.py
@@ -373,7 +373,6 @@ def get_weather(location: str) -> str:
     assert tool_span["op"] == OP.GEN_AI_EXECUTE_TOOL
     assert tool_span["description"] == "execute_tool get_weather"
     assert tool_span["data"][SPANDATA.GEN_AI_TOOL_NAME] == "get_weather"
-    assert tool_span["data"][SPANDATA.GEN_AI_TOOL_TYPE] == "function"
     assert (
         tool_span["data"][SPANDATA.GEN_AI_TOOL_DESCRIPTION]
         == "Get the weather for a location"
@@ -942,11 +941,9 @@ def test_google_genai_message_truncation(
     assert isinstance(parsed_messages, list)
     assert len(parsed_messages) == 1
     assert parsed_messages[0]["role"] == "user"
-    assert small_content in parsed_messages[0]["content"]
 
-    assert (
-        event["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 2
-    )
+    # What "small content" becomes because the large message used the entire character limit
+    assert "..." in parsed_messages[0]["content"][1]["text"]
 
 
 # Sample embed content API response JSON
@@ -1595,6 +1592,12 @@ def test_generate_content_with_function_response(
 
     mock_http_response = create_mock_http_response(EXAMPLE_API_RESPONSE_JSON)
 
+    # Conversation with the function call from the model
+    function_call = genai_types.FunctionCall(
+        name="get_weather",
+        args={"location": "Paris"},
+    )
+
     # Conversation with function response (tool result)
     function_response = genai_types.FunctionResponse(
         id="call_123", name="get_weather", response={"output": "Sunny, 72F"}
@@ -1603,6 +1606,9 @@ def test_generate_content_with_function_response(
         genai_types.Content(
             role="user", parts=[genai_types.Part(text="What's the weather in Paris?")]
         ),
+        genai_types.Content(
+            role="model", parts=[genai_types.Part(function_call=function_call)]
+        ),
         genai_types.Content(
             role="user", parts=[genai_types.Part(function_response=function_response)]
         ),
@@ -1708,7 +1714,13 @@ def test_generate_content_with_part_object_directly(
 def test_generate_content_with_list_of_dicts(
     sentry_init, capture_events, mock_genai_client
 ):
-    """Test generate_content with list of dict format inputs."""
+    """
+    Test generate_content with list of dict format inputs.
+
+    We only keep (and assert) the last dict in `content` because we've made popping the last message a form of
+    message truncation to keep the span size within limits. If we were following OTEL conventions, all 3 dicts
+    would be present.
+    """
     sentry_init(
         integrations=[GoogleGenAIIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -1788,6 +1800,98 @@ def test_generate_content_with_dict_inline_data(
     assert messages[0]["content"][1]["content"] == BLOB_DATA_SUBSTITUTE
 
 
+def test_generate_content_without_parts_property_inline_data(
+    sentry_init, capture_events, mock_genai_client
+):
+    sentry_init(
+        integrations=[GoogleGenAIIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    mock_http_response = create_mock_http_response(EXAMPLE_API_RESPONSE_JSON)
+
+    contents = [
+        {"text": "What's in this image?"},
+        {"inline_data": {"data": b"fake_binary_data", "mime_type": "image/gif"}},
+    ]
+
+    with mock.patch.object(
+        mock_genai_client._api_client, "request", return_value=mock_http_response
+    ):
+        with start_transaction(name="google_genai"):
+            mock_genai_client.models.generate_content(
+                model="gemini-1.5-flash", contents=contents, config=create_test_config()
+            )
+
+    (event,) = events
+    invoke_span = event["spans"][0]
+
+    messages = json.loads(invoke_span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+
+    assert len(messages) == 1
+
+    assert len(messages[0]["content"]) == 2
+    assert messages[0]["role"] == "user"
+    assert messages[0]["content"][0] == {
+        "text": "What's in this image?",
+        "type": "text",
+    }
+    assert messages[0]["content"][1]["inline_data"]
+
+    assert messages[0]["content"][1]["inline_data"]["data"] == BLOB_DATA_SUBSTITUTE
+    assert messages[0]["content"][1]["inline_data"]["mime_type"] == "image/gif"
+
+
+def test_generate_content_without_parts_property_inline_data_and_binary_data_within_string(
+    sentry_init, capture_events, mock_genai_client
+):
+    sentry_init(
+        integrations=[GoogleGenAIIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    mock_http_response = create_mock_http_response(EXAMPLE_API_RESPONSE_JSON)
+
+    contents = [
+        {"text": "What's in this image?"},
+        {
+            "inline_data": {
+                "data": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8z8BQz0AEYBxVSF+FABJADveWkH6oAAAAAElFTkSuQmCC",
+                "mime_type": "image/png",
+            }
+        },
+    ]
+
+    with mock.patch.object(
+        mock_genai_client._api_client, "request", return_value=mock_http_response
+    ):
+        with start_transaction(name="google_genai"):
+            mock_genai_client.models.generate_content(
+                model="gemini-1.5-flash", contents=contents, config=create_test_config()
+            )
+
+    (event,) = events
+    invoke_span = event["spans"][0]
+
+    messages = json.loads(invoke_span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+    assert len(messages) == 1
+    assert messages[0]["role"] == "user"
+
+    assert len(messages[0]["content"]) == 2
+    assert messages[0]["content"][0] == {
+        "text": "What's in this image?",
+        "type": "text",
+    }
+    assert messages[0]["content"][1]["inline_data"]
+
+    assert messages[0]["content"][1]["inline_data"]["data"] == BLOB_DATA_SUBSTITUTE
+    assert messages[0]["content"][1]["inline_data"]["mime_type"] == "image/png"
+
+
 # Tests for extract_contents_messages function
 def test_extract_contents_messages_none():
     """Test extract_contents_messages with None input"""
diff --git a/tests/integrations/graphene/test_graphene.py b/tests/integrations/graphene/test_graphene.py
index 5d54bb49cb..63bc5de5d2 100644
--- a/tests/integrations/graphene/test_graphene.py
+++ b/tests/integrations/graphene/test_graphene.py
@@ -207,7 +207,7 @@ def graphql_server_sync():
 def test_graphql_span_holds_query_information(sentry_init, capture_events):
     sentry_init(
         integrations=[GrapheneIntegration(), FlaskIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         default_integrations=False,
     )
     events = capture_events()
diff --git a/tests/integrations/huggingface_hub/test_huggingface_hub.py b/tests/integrations/huggingface_hub/test_huggingface_hub.py
index 851c1f717a..9dd15ca4b5 100644
--- a/tests/integrations/huggingface_hub/test_huggingface_hub.py
+++ b/tests/integrations/huggingface_hub/test_huggingface_hub.py
@@ -1,16 +1,14 @@
+import re
+from typing import TYPE_CHECKING
 from unittest import mock
+
 import pytest
-import re
 import responses
-import httpx
-
 from huggingface_hub import InferenceClient
 
 import sentry_sdk
-from sentry_sdk.utils import package_version
 from sentry_sdk.integrations.huggingface_hub import HuggingfaceHubIntegration
-
-from typing import TYPE_CHECKING
+from sentry_sdk.utils import package_version
 
 try:
     from huggingface_hub.utils._errors import HfHubHTTPError
@@ -508,12 +506,12 @@ def test_text_generation(
 
     assert span is not None
 
-    assert span["op"] == "gen_ai.generate_text"
-    assert span["description"] == "generate_text test-model"
+    assert span["op"] == "gen_ai.text_completion"
+    assert span["description"] == "text_completion test-model"
     assert span["origin"] == "auto.ai.huggingface_hub"
 
     expected_data = {
-        "gen_ai.operation.name": "generate_text",
+        "gen_ai.operation.name": "text_completion",
         "gen_ai.request.model": "test-model",
         "gen_ai.response.finish_reasons": "length",
         "gen_ai.response.streaming": False,
@@ -577,12 +575,12 @@ def test_text_generation_streaming(
 
     assert span is not None
 
-    assert span["op"] == "gen_ai.generate_text"
-    assert span["description"] == "generate_text test-model"
+    assert span["op"] == "gen_ai.text_completion"
+    assert span["description"] == "text_completion test-model"
     assert span["origin"] == "auto.ai.huggingface_hub"
 
     expected_data = {
-        "gen_ai.operation.name": "generate_text",
+        "gen_ai.operation.name": "text_completion",
         "gen_ai.request.model": "test-model",
         "gen_ai.response.finish_reasons": "length",
         "gen_ai.response.streaming": True,
@@ -835,8 +833,6 @@ def test_span_status_error(
     assert span["status"] == "internal_error"
     assert span["tags"]["status"] == "internal_error"
 
-    assert transaction["contexts"]["trace"]["status"] == "internal_error"
-
 
 @pytest.mark.httpx_mock(assert_all_requests_were_expected=False)
 @pytest.mark.parametrize("send_default_pii", [True, False])
diff --git a/tests/integrations/langchain/test_langchain.py b/tests/integrations/langchain/test_langchain.py
index 8a8d646113..498a5d6f4a 100644
--- a/tests/integrations/langchain/test_langchain.py
+++ b/tests/integrations/langchain/test_langchain.py
@@ -9,9 +9,10 @@
 
 try:
     # Langchain >= 0.2
-    from langchain_openai import ChatOpenAI
+    from langchain_openai import ChatOpenAI, OpenAI
 except ImportError:
     # Langchain < 0.2
+    from langchain_community.llms import OpenAI
     from langchain_community.chat_models import ChatOpenAI
 
 from langchain_core.callbacks import BaseCallbackManager, CallbackManagerForLLMRun
@@ -22,6 +23,7 @@
 
 import sentry_sdk
 from sentry_sdk import start_transaction
+from sentry_sdk.utils import package_version
 from sentry_sdk.integrations.langchain import (
     LangchainIntegration,
     SentryLangchainCallback,
@@ -32,12 +34,39 @@
 try:
     # langchain v1+
     from langchain.tools import tool
+    from langchain.agents import create_agent
     from langchain_classic.agents import AgentExecutor, create_openai_tools_agent  # type: ignore[import-not-found]
 except ImportError:
     # langchain <v1
     from langchain.agents import tool, AgentExecutor, create_openai_tools_agent
 
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.messages import HumanMessage, SystemMessage
+
+from openai.types.chat.chat_completion_chunk import (
+    ChatCompletionChunk,
+    Choice,
+    ChoiceDelta,
+    ChoiceDeltaToolCall,
+    ChoiceDeltaToolCallFunction,
+)
+
+from openai.types.completion import Completion
+from openai.types.completion_choice import CompletionChoice
+
+from openai.types.completion_usage import (
+    CompletionUsage,
+)
+
+from openai.types.responses import (
+    ResponseUsage,
+)
+from openai.types.responses.response_usage import (
+    InputTokensDetails,
+    OutputTokensDetails,
+)
+
+LANGCHAIN_VERSION = package_version("langchain")
 
 
 @tool
@@ -66,13 +95,383 @@ def _llm_type(self) -> str:
         return llm_type
 
 
+def test_langchain_text_completion(
+    sentry_init,
+    capture_events,
+    get_model_response,
+):
+    sentry_init(
+        integrations=[
+            LangchainIntegration(
+                include_prompts=True,
+            )
+        ],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    model_response = get_model_response(
+        Completion(
+            id="completion-id",
+            object="text_completion",
+            created=10000000,
+            model="gpt-3.5-turbo",
+            choices=[
+                CompletionChoice(
+                    index=0,
+                    finish_reason="stop",
+                    text="The capital of France is Paris.",
+                )
+            ],
+            usage=CompletionUsage(
+                prompt_tokens=10,
+                completion_tokens=15,
+                total_tokens=25,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
+
+    model = OpenAI(
+        model_name="gpt-3.5-turbo",
+        temperature=0.7,
+        max_tokens=100,
+        openai_api_key="badkey",
+    )
+
+    with patch.object(
+        model.client._client._client,
+        "send",
+        return_value=model_response,
+    ) as _:
+        with start_transaction():
+            input_text = "What is the capital of France?"
+            model.invoke(input_text, config={"run_name": "my-snazzy-pipeline"})
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+
+    llm_spans = [
+        span
+        for span in tx.get("spans", [])
+        if span.get("op") == "gen_ai.text_completion"
+    ]
+    assert len(llm_spans) > 0
+
+    llm_span = llm_spans[0]
+    assert llm_span["description"] == "text_completion gpt-3.5-turbo"
+    assert llm_span["data"]["gen_ai.system"] == "openai"
+    assert llm_span["data"]["gen_ai.pipeline.name"] == "my-snazzy-pipeline"
+    assert llm_span["data"]["gen_ai.request.model"] == "gpt-3.5-turbo"
+    assert llm_span["data"]["gen_ai.response.text"] == "The capital of France is Paris."
+    assert llm_span["data"]["gen_ai.usage.total_tokens"] == 25
+    assert llm_span["data"]["gen_ai.usage.input_tokens"] == 10
+    assert llm_span["data"]["gen_ai.usage.output_tokens"] == 15
+
+
+@pytest.mark.skipif(
+    LANGCHAIN_VERSION < (1,),
+    reason="LangChain 1.0+ required (ONE AGENT refactor)",
+)
 @pytest.mark.parametrize(
-    "send_default_pii, include_prompts, use_unknown_llm_type",
+    "send_default_pii, include_prompts",
     [
-        (True, True, False),
-        (True, False, False),
-        (False, True, False),
-        (False, False, True),
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+@pytest.mark.parametrize(
+    "system_instructions_content",
+    [
+        "You are very powerful assistant, but don't know current events",
+        [
+            {"type": "text", "text": "You are a helpful assistant."},
+            {"type": "text", "text": "Be concise and clear."},
+        ],
+    ],
+    ids=["string", "blocks"],
+)
+def test_langchain_create_agent(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    system_instructions_content,
+    request,
+    get_model_response,
+    nonstreaming_responses_model_response,
+):
+    sentry_init(
+        integrations=[
+            LangchainIntegration(
+                include_prompts=include_prompts,
+            )
+        ],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    model_response = get_model_response(
+        nonstreaming_responses_model_response,
+        serialize_pydantic=True,
+        request_headers={
+            "X-Stainless-Raw-Response": "True",
+        },
+    )
+
+    llm = ChatOpenAI(
+        model_name="gpt-3.5-turbo",
+        temperature=0,
+        openai_api_key="badkey",
+        use_responses_api=True,
+    )
+    agent = create_agent(
+        model=llm,
+        tools=[get_word_length],
+        system_prompt=SystemMessage(content=system_instructions_content),
+        name="word_length_agent",
+    )
+
+    with patch.object(
+        llm.client._client._client,
+        "send",
+        return_value=model_response,
+    ) as _:
+        with start_transaction():
+            agent.invoke(
+                {
+                    "messages": [
+                        HumanMessage(content="How many letters in the word eudca"),
+                    ],
+                },
+            )
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    assert tx["contexts"]["trace"]["origin"] == "manual"
+
+    chat_spans = list(x for x in tx["spans"] if x["op"] == "gen_ai.chat")
+    assert len(chat_spans) == 1
+    assert chat_spans[0]["origin"] == "auto.ai.langchain"
+
+    assert chat_spans[0]["data"]["gen_ai.system"] == "openai-chat"
+    assert chat_spans[0]["data"]["gen_ai.usage.input_tokens"] == 10
+    assert chat_spans[0]["data"]["gen_ai.usage.output_tokens"] == 20
+    assert chat_spans[0]["data"]["gen_ai.usage.total_tokens"] == 30
+
+    if send_default_pii and include_prompts:
+        assert (
+            chat_spans[0]["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
+            == "Hello, how can I help you?"
+        )
+
+        param_id = request.node.callspec.id
+        if "string" in param_id:
+            assert [
+                {
+                    "type": "text",
+                    "content": "You are very powerful assistant, but don't know current events",
+                }
+            ] == json.loads(chat_spans[0]["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS])
+        else:
+            assert [
+                {
+                    "type": "text",
+                    "content": "You are a helpful assistant.",
+                },
+                {
+                    "type": "text",
+                    "content": "Be concise and clear.",
+                },
+            ] == json.loads(chat_spans[0]["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS])
+    else:
+        assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in chat_spans[0].get("data", {})
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in chat_spans[0].get("data", {})
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in chat_spans[0].get("data", {})
+
+
+@pytest.mark.skipif(
+    LANGCHAIN_VERSION < (1,),
+    reason="LangChain 1.0+ required (ONE AGENT refactor)",
+)
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_tool_execution_span(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    responses_tool_call_model_responses,
+):
+    sentry_init(
+        integrations=[
+            LangchainIntegration(
+                include_prompts=include_prompts,
+            )
+        ],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    responses = responses_tool_call_model_responses(
+        tool_name="get_word_length",
+        arguments='{"word": "eudca"}',
+        response_model="gpt-4-0613",
+        response_text="The word eudca has 5 letters.",
+        response_ids=iter(["resp_1", "resp_2"]),
+        usages=iter(
+            [
+                ResponseUsage(
+                    input_tokens=142,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=50,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=192,
+                ),
+                ResponseUsage(
+                    input_tokens=89,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=28,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=117,
+                ),
+            ]
+        ),
+    )
+    tool_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+        request_headers={
+            "X-Stainless-Raw-Response": "True",
+        },
+    )
+    final_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+        request_headers={
+            "X-Stainless-Raw-Response": "True",
+        },
+    )
+
+    llm = ChatOpenAI(
+        model_name="gpt-4",
+        temperature=0,
+        openai_api_key="badkey",
+        use_responses_api=True,
+    )
+    agent = create_agent(
+        model=llm,
+        tools=[get_word_length],
+        name="word_length_agent",
+    )
+
+    with patch.object(
+        llm.client._client._client,
+        "send",
+        side_effect=[tool_response, final_response],
+    ) as _:
+        with start_transaction():
+            agent.invoke(
+                {
+                    "messages": [
+                        HumanMessage(content="How many letters in the word eudca"),
+                    ],
+                },
+            )
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    assert tx["contexts"]["trace"]["origin"] == "manual"
+
+    chat_spans = list(x for x in tx["spans"] if x["op"] == "gen_ai.chat")
+    assert len(chat_spans) == 2
+
+    tool_exec_spans = list(x for x in tx["spans"] if x["op"] == "gen_ai.execute_tool")
+    assert len(tool_exec_spans) == 1
+    tool_exec_span = tool_exec_spans[0]
+
+    assert chat_spans[0]["origin"] == "auto.ai.langchain"
+    assert chat_spans[1]["origin"] == "auto.ai.langchain"
+    assert tool_exec_span["origin"] == "auto.ai.langchain"
+
+    assert chat_spans[0]["data"]["gen_ai.usage.input_tokens"] == 142
+    assert chat_spans[0]["data"]["gen_ai.usage.output_tokens"] == 50
+    assert chat_spans[0]["data"]["gen_ai.usage.total_tokens"] == 192
+    assert chat_spans[0]["data"]["gen_ai.system"] == "openai-chat"
+
+    assert chat_spans[1]["data"]["gen_ai.usage.input_tokens"] == 89
+    assert chat_spans[1]["data"]["gen_ai.usage.output_tokens"] == 28
+    assert chat_spans[1]["data"]["gen_ai.usage.total_tokens"] == 117
+    assert chat_spans[1]["data"]["gen_ai.system"] == "openai-chat"
+
+    if send_default_pii and include_prompts:
+        assert "word" in tool_exec_span["data"][SPANDATA.GEN_AI_TOOL_INPUT]
+
+        assert "5" in chat_spans[1]["data"][SPANDATA.GEN_AI_RESPONSE_TEXT]
+
+        # Verify tool calls are recorded when PII is enabled
+        assert SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS in chat_spans[0].get("data", {}), (
+            "Tool calls should be recorded when send_default_pii=True and include_prompts=True"
+        )
+        tool_calls_data = chat_spans[0]["data"][SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS]
+        assert isinstance(tool_calls_data, str)
+        assert "get_word_length" in tool_calls_data
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in chat_spans[0].get("data", {})
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in chat_spans[0].get("data", {})
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in chat_spans[1].get("data", {})
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in chat_spans[1].get("data", {})
+        assert SPANDATA.GEN_AI_TOOL_INPUT not in tool_exec_span.get("data", {})
+        assert SPANDATA.GEN_AI_TOOL_OUTPUT not in tool_exec_span.get("data", {})
+
+        # Verify tool calls are NOT recorded when PII is disabled
+        assert SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS not in chat_spans[0].get(
+            "data", {}
+        ), (
+            f"Tool calls should NOT be recorded when send_default_pii={send_default_pii} "
+            f"and include_prompts={include_prompts}"
+        )
+        assert SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS not in chat_spans[1].get(
+            "data", {}
+        ), (
+            f"Tool calls should NOT be recorded when send_default_pii={send_default_pii} "
+            f"and include_prompts={include_prompts}"
+        )
+
+    # Verify that available tools are always recorded regardless of PII settings
+    for chat_span in chat_spans:
+        tools_data = chat_span["data"][SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS]
+        assert "get_word_length" in tools_data
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
     ],
 )
 @pytest.mark.parametrize(
@@ -87,18 +486,16 @@ def _llm_type(self) -> str:
     ],
     ids=["string", "list", "blocks"],
 )
-def test_langchain_agent(
+def test_langchain_openai_tools_agent(
     sentry_init,
     capture_events,
     send_default_pii,
     include_prompts,
-    use_unknown_llm_type,
     system_instructions_content,
     request,
+    get_model_response,
+    server_side_event_chunks,
 ):
-    global llm_type
-    llm_type = "acme-llm" if use_unknown_llm_type else "openai-chat"
-
     sentry_init(
         integrations=[
             LangchainIntegration(
@@ -120,87 +517,173 @@ def test_langchain_agent(
             MessagesPlaceholder(variable_name="agent_scratchpad"),
         ]
     )
-    global stream_result_mock
-    stream_result_mock = Mock(
-        side_effect=[
+
+    tool_response = get_model_response(
+        server_side_event_chunks(
             [
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="",
-                        additional_kwargs={
-                            "tool_calls": [
-                                {
-                                    "index": 0,
-                                    "id": "call_BbeyNhCKa6kYLYzrD40NGm3b",
-                                    "function": {
-                                        "arguments": "",
-                                        "name": "get_word_length",
-                                    },
-                                    "type": "function",
-                                }
-                            ]
-                        },
-                    ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(role="assistant"),
+                            finish_reason=None,
+                        ),
+                    ],
                 ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="",
-                        additional_kwargs={
-                            "tool_calls": [
-                                {
-                                    "index": 0,
-                                    "id": None,
-                                    "function": {
-                                        "arguments": '{"word": "eudca"}',
-                                        "name": None,
-                                    },
-                                    "type": None,
-                                }
-                            ]
-                        },
-                    ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(
+                                tool_calls=[
+                                    ChoiceDeltaToolCall(
+                                        index=0,
+                                        id="call_BbeyNhCKa6kYLYzrD40NGm3b",
+                                        type="function",
+                                        function=ChoiceDeltaToolCallFunction(
+                                            name="get_word_length",
+                                            arguments="",
+                                        ),
+                                    ),
+                                ],
+                            ),
+                            finish_reason=None,
+                        ),
+                    ],
                 ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="5",
-                        usage_metadata={
-                            "input_tokens": 142,
-                            "output_tokens": 50,
-                            "total_tokens": 192,
-                            "input_token_details": {"audio": 0, "cache_read": 0},
-                            "output_token_details": {"audio": 0, "reasoning": 0},
-                        },
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(
+                                tool_calls=[
+                                    ChoiceDeltaToolCall(
+                                        index=0,
+                                        function=ChoiceDeltaToolCallFunction(
+                                            arguments='{"word": "eudca"}',
+                                        ),
+                                    ),
+                                ],
+                            ),
+                            finish_reason=None,
+                        ),
+                    ],
+                ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(content="5"),
+                            finish_reason=None,
+                        ),
+                    ],
+                ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(),
+                            finish_reason="function_call",
+                        ),
+                    ],
+                ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-1",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[],
+                    usage=CompletionUsage(
+                        prompt_tokens=142,
+                        completion_tokens=50,
+                        total_tokens=192,
                     ),
-                    generation_info={"finish_reason": "function_call"},
                 ),
             ],
+            include_event_type=False,
+        )
+    )
+
+    final_response = get_model_response(
+        server_side_event_chunks(
             [
-                ChatGenerationChunk(
-                    text="The word eudca has 5 letters.",
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="The word eudca has 5 letters.",
-                        usage_metadata={
-                            "input_tokens": 89,
-                            "output_tokens": 28,
-                            "total_tokens": 117,
-                            "input_token_details": {"audio": 0, "cache_read": 0},
-                            "output_token_details": {"audio": 0, "reasoning": 0},
-                        },
-                    ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-2",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(role="assistant"),
+                            finish_reason=None,
+                        ),
+                    ],
                 ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    generation_info={"finish_reason": "stop"},
-                    message=AIMessageChunk(content=""),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-2",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(content="The word eudca has 5 letters."),
+                            finish_reason=None,
+                        ),
+                    ],
+                ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-2",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[
+                        Choice(
+                            index=0,
+                            delta=ChoiceDelta(),
+                            finish_reason="stop",
+                        ),
+                    ],
+                ),
+                ChatCompletionChunk(
+                    id="chatcmpl-turn-2",
+                    object="chat.completion.chunk",
+                    created=10000000,
+                    model="gpt-3.5-turbo",
+                    choices=[],
+                    usage=CompletionUsage(
+                        prompt_tokens=89,
+                        completion_tokens=28,
+                        total_tokens=117,
+                    ),
                 ),
             ],
-        ]
+            include_event_type=False,
+        )
     )
-    llm = MockOpenAI(
+
+    llm = ChatOpenAI(
         model_name="gpt-3.5-turbo",
         temperature=0,
         openai_api_key="badkey",
@@ -209,16 +692,29 @@ def test_langchain_agent(
 
     agent_executor = AgentExecutor(agent=agent, tools=[get_word_length], verbose=True)
 
-    with start_transaction():
-        list(agent_executor.stream({"input": "How many letters in the word eudca"}))
+    with patch.object(
+        llm.client._client._client,
+        "send",
+        side_effect=[tool_response, final_response],
+    ) as _:
+        with start_transaction():
+            list(agent_executor.stream({"input": "How many letters in the word eudca"}))
 
     tx = events[0]
     assert tx["type"] == "transaction"
+    assert tx["contexts"]["trace"]["origin"] == "manual"
+
+    invoke_agent_span = next(x for x in tx["spans"] if x["op"] == "gen_ai.invoke_agent")
     chat_spans = list(x for x in tx["spans"] if x["op"] == "gen_ai.chat")
     tool_exec_span = next(x for x in tx["spans"] if x["op"] == "gen_ai.execute_tool")
 
     assert len(chat_spans) == 2
 
+    assert invoke_agent_span["origin"] == "auto.ai.langchain"
+    assert chat_spans[0]["origin"] == "auto.ai.langchain"
+    assert chat_spans[1]["origin"] == "auto.ai.langchain"
+    assert tool_exec_span["origin"] == "auto.ai.langchain"
+
     # We can't guarantee anything about the "shape" of the langchain execution graph
     assert len(list(x for x in tx["spans"] if x["op"] == "gen_ai.chat")) > 0
 
@@ -297,17 +793,25 @@ def test_langchain_agent(
             f"and include_prompts={include_prompts}"
         )
 
+    # Verify finish_reasons is always an array of strings
+    assert chat_spans[0]["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == [
+        "function_call"
+    ]
+    assert chat_spans[1]["data"][SPANDATA.GEN_AI_RESPONSE_FINISH_REASONS] == ["stop"]
+
     # Verify that available tools are always recorded regardless of PII settings
     for chat_span in chat_spans:
-        span_data = chat_span.get("data", {})
-        if SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS in span_data:
-            tools_data = span_data[SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS]
-            assert tools_data is not None, (
-                "Available tools should always be recorded regardless of PII settings"
-            )
+        tools_data = chat_span["data"][SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS]
+        assert tools_data is not None, (
+            "Available tools should always be recorded regardless of PII settings"
+        )
+        assert "get_word_length" in tools_data
 
 
 def test_langchain_error(sentry_init, capture_events):
+    global llm_type
+    llm_type = "acme-llm"
+
     sentry_init(
         integrations=[LangchainIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -387,122 +891,6 @@ def test_span_status_error(sentry_init, capture_events):
     assert transaction["contexts"]["trace"]["status"] == "internal_error"
 
 
-def test_span_origin(sentry_init, capture_events):
-    sentry_init(
-        integrations=[LangchainIntegration()],
-        traces_sample_rate=1.0,
-    )
-    events = capture_events()
-
-    prompt = ChatPromptTemplate.from_messages(
-        [
-            (
-                "system",
-                "You are very powerful assistant, but don't know current events",
-            ),
-            ("user", "{input}"),
-            MessagesPlaceholder(variable_name="agent_scratchpad"),
-        ]
-    )
-    global stream_result_mock
-    stream_result_mock = Mock(
-        side_effect=[
-            [
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="",
-                        additional_kwargs={
-                            "tool_calls": [
-                                {
-                                    "index": 0,
-                                    "id": "call_BbeyNhCKa6kYLYzrD40NGm3b",
-                                    "function": {
-                                        "arguments": "",
-                                        "name": "get_word_length",
-                                    },
-                                    "type": "function",
-                                }
-                            ]
-                        },
-                    ),
-                ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="",
-                        additional_kwargs={
-                            "tool_calls": [
-                                {
-                                    "index": 0,
-                                    "id": None,
-                                    "function": {
-                                        "arguments": '{"word": "eudca"}',
-                                        "name": None,
-                                    },
-                                    "type": None,
-                                }
-                            ]
-                        },
-                    ),
-                ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="5",
-                        usage_metadata={
-                            "input_tokens": 142,
-                            "output_tokens": 50,
-                            "total_tokens": 192,
-                            "input_token_details": {"audio": 0, "cache_read": 0},
-                            "output_token_details": {"audio": 0, "reasoning": 0},
-                        },
-                    ),
-                    generation_info={"finish_reason": "function_call"},
-                ),
-            ],
-            [
-                ChatGenerationChunk(
-                    text="The word eudca has 5 letters.",
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(
-                        content="The word eudca has 5 letters.",
-                        usage_metadata={
-                            "input_tokens": 89,
-                            "output_tokens": 28,
-                            "total_tokens": 117,
-                            "input_token_details": {"audio": 0, "cache_read": 0},
-                            "output_token_details": {"audio": 0, "reasoning": 0},
-                        },
-                    ),
-                ),
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    generation_info={"finish_reason": "stop"},
-                    message=AIMessageChunk(content=""),
-                ),
-            ],
-        ]
-    )
-    llm = MockOpenAI(
-        model_name="gpt-3.5-turbo",
-        temperature=0,
-        openai_api_key="badkey",
-    )
-    agent = create_openai_tools_agent(llm, [get_word_length], prompt)
-
-    agent_executor = AgentExecutor(agent=agent, tools=[get_word_length], verbose=True)
-
-    with start_transaction():
-        list(agent_executor.stream({"input": "How many letters in the word eudca"}))
-
-    (event,) = events
-
-    assert event["contexts"]["trace"]["origin"] == "manual"
-    for span in event["spans"]:
-        assert span["origin"] == "auto.ai.langchain"
-
-
 def test_manual_callback_no_duplication(sentry_init):
     """
     Test that when a user manually provides a SentryLangchainCallback,
@@ -712,155 +1100,6 @@ def test_langchain_callback_list_existing_callback(sentry_init):
         assert handler is sentry_callback
 
 
-def test_tools_integration_in_spans(sentry_init, capture_events):
-    """Test that tools are properly set on spans in actual LangChain integration."""
-    global llm_type
-    llm_type = "openai-chat"
-
-    sentry_init(
-        integrations=[LangchainIntegration(include_prompts=False)],
-        traces_sample_rate=1.0,
-    )
-    events = capture_events()
-
-    prompt = ChatPromptTemplate.from_messages(
-        [
-            ("system", "You are a helpful assistant"),
-            ("user", "{input}"),
-            MessagesPlaceholder(variable_name="agent_scratchpad"),
-        ]
-    )
-
-    global stream_result_mock
-    stream_result_mock = Mock(
-        side_effect=[
-            [
-                ChatGenerationChunk(
-                    type="ChatGenerationChunk",
-                    message=AIMessageChunk(content="Simple response"),
-                ),
-            ]
-        ]
-    )
-
-    llm = MockOpenAI(
-        model_name="gpt-3.5-turbo",
-        temperature=0,
-        openai_api_key="badkey",
-    )
-    agent = create_openai_tools_agent(llm, [get_word_length], prompt)
-    agent_executor = AgentExecutor(agent=agent, tools=[get_word_length], verbose=True)
-
-    with start_transaction():
-        list(agent_executor.stream({"input": "Hello"}))
-
-    # Check that events were captured and contain tools data
-    if events:
-        tx = events[0]
-        spans = tx.get("spans", [])
-
-        # Look for spans that should have tools data
-        tools_found = False
-        for span in spans:
-            span_data = span.get("data", {})
-            if SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS in span_data:
-                tools_found = True
-                tools_data = span_data[SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS]
-                # Verify tools are in the expected format
-                assert isinstance(tools_data, (str, list))  # Could be serialized
-                if isinstance(tools_data, str):
-                    # If serialized as string, should contain tool name
-                    assert "get_word_length" in tools_data
-                else:
-                    # If still a list, verify structure
-                    assert len(tools_data) >= 1
-                    names = [
-                        tool.get("name")
-                        for tool in tools_data
-                        if isinstance(tool, dict)
-                    ]
-                    assert "get_word_length" in names
-
-        # Ensure we found at least one span with tools data
-        assert tools_found, "No spans found with tools data"
-
-
-def test_langchain_integration_with_langchain_core_only(sentry_init, capture_events):
-    """Test that the langchain integration works when langchain.agents.AgentExecutor
-    is not available or langchain is not installed, but langchain-core is.
-    """
-
-    from langchain_core.outputs import LLMResult, Generation
-
-    with patch("sentry_sdk.integrations.langchain.AgentExecutor", None):
-        from sentry_sdk.integrations.langchain import (
-            LangchainIntegration,
-            SentryLangchainCallback,
-        )
-
-        sentry_init(
-            integrations=[LangchainIntegration(include_prompts=True)],
-            traces_sample_rate=1.0,
-            send_default_pii=True,
-        )
-        events = capture_events()
-
-        try:
-            LangchainIntegration.setup_once()
-        except Exception as e:
-            pytest.fail(f"setup_once() failed when AgentExecutor is None: {e}")
-
-        callback = SentryLangchainCallback(max_span_map_size=100, include_prompts=True)
-
-        run_id = "12345678-1234-1234-1234-123456789012"
-        serialized = {"_type": "openai-chat", "model_name": "gpt-3.5-turbo"}
-        prompts = ["What is the capital of France?"]
-
-        with start_transaction():
-            callback.on_llm_start(
-                serialized=serialized,
-                prompts=prompts,
-                run_id=run_id,
-                invocation_params={
-                    "temperature": 0.7,
-                    "max_tokens": 100,
-                    "model": "gpt-3.5-turbo",
-                },
-            )
-
-            response = LLMResult(
-                generations=[[Generation(text="The capital of France is Paris.")]],
-                llm_output={
-                    "token_usage": {
-                        "total_tokens": 25,
-                        "prompt_tokens": 10,
-                        "completion_tokens": 15,
-                    }
-                },
-            )
-            callback.on_llm_end(response=response, run_id=run_id)
-
-        assert len(events) > 0
-        tx = events[0]
-        assert tx["type"] == "transaction"
-
-        llm_spans = [
-            span for span in tx.get("spans", []) if span.get("op") == "gen_ai.pipeline"
-        ]
-        assert len(llm_spans) > 0
-
-        llm_span = llm_spans[0]
-        assert llm_span["description"] == "Langchain LLM call"
-        assert llm_span["data"]["gen_ai.request.model"] == "gpt-3.5-turbo"
-        assert (
-            llm_span["data"]["gen_ai.response.text"]
-            == "The capital of France is Paris."
-        )
-        assert llm_span["data"]["gen_ai.usage.total_tokens"] == 25
-        assert llm_span["data"]["gen_ai.usage.input_tokens"] == 10
-        assert llm_span["data"]["gen_ai.usage.output_tokens"] == 15
-
-
 def test_langchain_message_role_mapping(sentry_init, capture_events):
     """Test that message roles are properly normalized in langchain integration."""
     global llm_type
@@ -1032,6 +1271,7 @@ def test_langchain_message_truncation(sentry_init, capture_events):
             serialized=serialized,
             prompts=prompts,
             run_id=run_id,
+            name="my_pipeline",
             invocation_params={
                 "temperature": 0.7,
                 "max_tokens": 100,
@@ -1056,13 +1296,17 @@ def test_langchain_message_truncation(sentry_init, capture_events):
     assert tx["type"] == "transaction"
 
     llm_spans = [
-        span for span in tx.get("spans", []) if span.get("op") == "gen_ai.pipeline"
+        span
+        for span in tx.get("spans", [])
+        if span.get("op") == "gen_ai.text_completion"
     ]
     assert len(llm_spans) > 0
 
     llm_span = llm_spans[0]
-    assert SPANDATA.GEN_AI_REQUEST_MESSAGES in llm_span["data"]
+    assert llm_span["data"]["gen_ai.operation.name"] == "text_completion"
+    assert llm_span["data"][SPANDATA.GEN_AI_PIPELINE_NAME] == "my_pipeline"
 
+    assert SPANDATA.GEN_AI_REQUEST_MESSAGES in llm_span["data"]
     messages_data = llm_span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
     assert isinstance(messages_data, str)
 
@@ -1770,11 +2014,14 @@ def test_langchain_response_model_extraction(
     assert tx["type"] == "transaction"
 
     llm_spans = [
-        span for span in tx.get("spans", []) if span.get("op") == "gen_ai.pipeline"
+        span
+        for span in tx.get("spans", [])
+        if span.get("op") == "gen_ai.text_completion"
     ]
     assert len(llm_spans) > 0
 
     llm_span = llm_spans[0]
+    assert llm_span["data"]["gen_ai.operation.name"] == "text_completion"
 
     if expected_model is not None:
         assert SPANDATA.GEN_AI_RESPONSE_MODEL in llm_span["data"]
@@ -1994,6 +2241,96 @@ def test_transform_google_file_data(self):
         }
 
 
+@pytest.mark.parametrize(
+    "ai_type,expected_system",
+    [
+        # Real LangChain _type values (from _llm_type properties)
+        # OpenAI
+        ("openai-chat", "openai-chat"),
+        ("openai", "openai"),
+        # Azure OpenAI
+        ("azure-openai-chat", "azure-openai-chat"),
+        ("azure", "azure"),
+        # Anthropic
+        ("anthropic-chat", "anthropic-chat"),
+        # Google
+        ("vertexai", "vertexai"),
+        ("chat-google-generative-ai", "chat-google-generative-ai"),
+        ("google_gemini", "google_gemini"),
+        # AWS Bedrock
+        ("amazon_bedrock_chat", "amazon_bedrock_chat"),
+        ("amazon_bedrock", "amazon_bedrock"),
+        # Cohere
+        ("cohere-chat", "cohere-chat"),
+        # Ollama
+        ("chat-ollama", "chat-ollama"),
+        ("ollama-llm", "ollama-llm"),
+        # Mistral
+        ("mistralai-chat", "mistralai-chat"),
+        # Fireworks
+        ("fireworks-chat", "fireworks-chat"),
+        ("fireworks", "fireworks"),
+        # HuggingFace
+        ("huggingface-chat-wrapper", "huggingface-chat-wrapper"),
+        # Groq
+        ("groq-chat", "groq-chat"),
+        # NVIDIA
+        ("chat-nvidia-ai-playground", "chat-nvidia-ai-playground"),
+        # xAI
+        ("xai-chat", "xai-chat"),
+        # DeepSeek
+        ("chat-deepseek", "chat-deepseek"),
+        # Edge cases
+        ("", None),
+        (None, None),
+    ],
+)
+def test_langchain_ai_system_detection(
+    sentry_init, capture_events, ai_type, expected_system
+):
+    sentry_init(
+        integrations=[LangchainIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    callback = SentryLangchainCallback(max_span_map_size=100, include_prompts=True)
+
+    run_id = "test-ai-system-uuid"
+    serialized = {"_type": ai_type} if ai_type is not None else {}
+    prompts = ["Test prompt"]
+
+    with start_transaction():
+        callback.on_llm_start(
+            serialized=serialized,
+            prompts=prompts,
+            run_id=run_id,
+            invocation_params={"_type": ai_type, "model": "test-model"},
+        )
+
+        generation = Mock(text="Test response", message=None)
+        response = Mock(generations=[[generation]])
+        callback.on_llm_end(response=response, run_id=run_id)
+
+    assert len(events) > 0
+    tx = events[0]
+    assert tx["type"] == "transaction"
+
+    llm_spans = [
+        span
+        for span in tx.get("spans", [])
+        if span.get("op") == "gen_ai.text_completion"
+    ]
+    assert len(llm_spans) > 0
+
+    llm_span = llm_spans[0]
+
+    if expected_system is not None:
+        assert llm_span["data"][SPANDATA.GEN_AI_SYSTEM] == expected_system
+    else:
+        assert SPANDATA.GEN_AI_SYSTEM not in llm_span.get("data", {})
+
+
 class TestTransformLangchainMessageContent:
     """Tests for _transform_langchain_message_content function."""
 
diff --git a/tests/integrations/litellm/test_litellm.py b/tests/integrations/litellm/test_litellm.py
index ef129c6cfd..a8df5891ce 100644
--- a/tests/integrations/litellm/test_litellm.py
+++ b/tests/integrations/litellm/test_litellm.py
@@ -2,6 +2,7 @@
 import json
 import pytest
 import time
+import asyncio
 from unittest import mock
 from datetime import datetime
 
@@ -19,7 +20,6 @@ async def __call__(self, *args, **kwargs):
 except ImportError:
     pytest.skip("litellm not installed", allow_module_level=True)
 
-import sentry_sdk
 from sentry_sdk import start_transaction
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk._types import BLOB_DATA_SUBSTITUTE
@@ -32,10 +32,34 @@ async def __call__(self, *args, **kwargs):
 )
 from sentry_sdk.utils import package_version
 
+from openai import OpenAI, AsyncOpenAI
+
+from concurrent.futures import ThreadPoolExecutor
+
+import litellm.utils as litellm_utils
+from litellm.litellm_core_utils import streaming_handler
+from litellm.litellm_core_utils import thread_pool_executor
+from litellm.litellm_core_utils import litellm_logging
+from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
+from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler
+
 
 LITELLM_VERSION = package_version("litellm")
 
 
+def _reset_litellm_executor():
+    thread_pool_executor.executor = ThreadPoolExecutor(max_workers=100)
+    litellm_utils.executor = thread_pool_executor.executor
+    streaming_handler.executor = thread_pool_executor.executor
+    litellm_logging.executor = thread_pool_executor.executor
+
+
+@pytest.fixture()
+def reset_litellm_executor():
+    yield
+    _reset_litellm_executor()
+
+
 @pytest.fixture
 def clear_litellm_cache():
     """
@@ -106,38 +130,89 @@ def __init__(
         self.created = 1234567890
 
 
-class MockEmbeddingData:
-    def __init__(self, embedding=None):
-        self.embedding = embedding or [0.1, 0.2, 0.3]
-        self.index = 0
-        self.object = "embedding"
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_nonstreaming_chat_completion(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
 
+    messages = [{"role": "user", "content": "Hello!"}]
 
-class MockEmbeddingResponse:
-    def __init__(self, model="text-embedding-ada-002", data=None, usage=None):
-        self.model = model
-        self.data = data or [MockEmbeddingData()]
-        self.usage = usage or MockUsage(
-            prompt_tokens=5, completion_tokens=0, total_tokens=5
-        )
-        self.object = "list"
+    client = OpenAI(api_key="test-key")
 
-    def model_dump(self):
-        return {
-            "model": self.model,
-            "data": [
-                {"embedding": d.embedding, "index": d.index, "object": d.object}
-                for d in self.data
-            ],
-            "usage": {
-                "prompt_tokens": self.usage.prompt_tokens,
-                "completion_tokens": self.usage.completion_tokens,
-                "total_tokens": self.usage.total_tokens,
-            },
-            "object": self.object,
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    assert event["transaction"] == "litellm test"
+
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["description"] == "chat gpt-3.5-turbo"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "gpt-3.5-turbo"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "gpt-3.5-turbo"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
+
+    if send_default_pii and include_prompts:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT in span["data"]
+    else:
+        assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
+        assert SPANDATA.GEN_AI_RESPONSE_TEXT not in span["data"]
+
+    assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 10
+    assert span["data"][SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS] == 20
+    assert span["data"][SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS] == 30
 
 
+@pytest.mark.asyncio(loop_scope="session")
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -147,8 +222,13 @@ def model_dump(self):
         (False, False),
     ],
 )
-def test_nonstreaming_chat_completion(
-    sentry_init, capture_events, send_default_pii, include_prompts
+async def test_async_nonstreaming_chat_completion(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
 ):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=include_prompts)],
@@ -158,22 +238,29 @@ def test_nonstreaming_chat_completion(
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
 
-    with start_transaction(name="litellm test"):
-        # Simulate what litellm does: call input callback, then success callback
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    client = AsyncOpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
 
     assert len(events) == 1
     (event,) = events
@@ -181,8 +268,13 @@ def test_nonstreaming_chat_completion(
     assert event["type"] == "transaction"
     assert event["transaction"] == "litellm test"
 
-    assert len(event["spans"]) == 1
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["description"] == "chat gpt-3.5-turbo"
@@ -213,7 +305,14 @@ def test_nonstreaming_chat_completion(
     ],
 )
 def test_streaming_chat_completion(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
+    streaming_chat_completions_model_response,
 ):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=include_prompts)],
@@ -223,35 +322,132 @@ def test_streaming_chat_completion(
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-            "stream": True,
-        }
+    client = OpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_model_response(
+        server_side_event_chunks(
+            streaming_chat_completions_model_response,
+            include_event_type=False,
+        ),
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            response = litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+                stream=True,
+            )
+            for _ in response:
+                pass
+
+            streaming_handler.executor.shutdown(wait=True)
 
     assert len(events) == 1
     (event,) = events
 
     assert event["type"] == "transaction"
-    assert len(event["spans"]) == 1
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+
+@pytest.mark.asyncio(loop_scope="session")
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+async def test_async_streaming_chat_completion(
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+    streaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    messages = [{"role": "user", "content": "Hello!"}]
+
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                streaming_chat_completions_model_response,
+                include_event_type=False,
+            ),
+        ),
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            response = await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+                stream=True,
+            )
+            async for _ in response:
+                pass
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    assert len(events) == 1
+    (event,) = events
+
+    assert event["type"] == "transaction"
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
     assert span["op"] == OP.GEN_AI_CHAT
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
 
 
-def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
+def test_embeddings_create(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
+):
     """
     Test that litellm.embedding() calls are properly instrumented.
 
@@ -265,20 +461,24 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
     )
     events = capture_events()
 
-    mock_response = MockEmbeddingResponse()
+    client = OpenAI(api_key="test-key")
 
-    # Mock within the test to ensure proper ordering with cache clearing
-    with mock.patch(
-        "litellm.openai_chat_completions.make_sync_openai_embedding_request"
-    ) as mock_http:
-        # The function returns (headers, response)
-        mock_http.return_value = ({}, mock_response)
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
         with start_transaction(name="litellm test"):
             response = litellm.embedding(
                 model="text-embedding-ada-002",
                 input="Hello, world!",
-                api_key="test-key",  # Provide a fake API key to avoid authentication errors
+                client=client,
             )
             # Allow time for callbacks to complete (they may run in separate threads)
             time.sleep(0.1)
@@ -289,8 +489,81 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
         (event,) = events
 
         assert event["type"] == "transaction"
-        assert len(event["spans"]) == 1
-        (span,) = event["spans"]
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
+
+        assert span["op"] == OP.GEN_AI_EMBEDDINGS
+        assert span["description"] == "embeddings text-embedding-ada-002"
+        assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "embeddings"
+        assert span["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS] == 5
+        assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "text-embedding-ada-002"
+        # Check that embeddings input is captured (it's JSON serialized)
+        embeddings_input = span["data"][SPANDATA.GEN_AI_EMBEDDINGS_INPUT]
+        assert json.loads(embeddings_input) == ["Hello, world!"]
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_embeddings_create(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
+):
+    """
+    Test that litellm.embedding() calls are properly instrumented.
+
+    This test calls the actual litellm.embedding() function (not just callbacks)
+    to ensure proper integration testing.
+    """
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            response = await litellm.aembedding(
+                model="text-embedding-ada-002",
+                input="Hello, world!",
+                client=client,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+        # Response is processed by litellm, so just check it exists
+        assert response is not None
+        assert len(events) == 1
+        (event,) = events
+
+        assert event["type"] == "transaction"
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
 
         assert span["op"] == OP.GEN_AI_EMBEDDINGS
         assert span["description"] == "embeddings text-embedding-ada-002"
@@ -303,7 +576,11 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
 
 
 def test_embeddings_create_with_list_input(
-    sentry_init, capture_events, clear_litellm_cache
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
 ):
     """Test embedding with list input."""
     sentry_init(
@@ -313,20 +590,24 @@ def test_embeddings_create_with_list_input(
     )
     events = capture_events()
 
-    mock_response = MockEmbeddingResponse()
+    client = OpenAI(api_key="test-key")
 
-    # Mock within the test to ensure proper ordering with cache clearing
-    with mock.patch(
-        "litellm.openai_chat_completions.make_sync_openai_embedding_request"
-    ) as mock_http:
-        # The function returns (headers, response)
-        mock_http.return_value = ({}, mock_response)
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
         with start_transaction(name="litellm test"):
             response = litellm.embedding(
                 model="text-embedding-ada-002",
                 input=["First text", "Second text", "Third text"],
-                api_key="test-key",  # Provide a fake API key to avoid authentication errors
+                client=client,
             )
             # Allow time for callbacks to complete (they may run in separate threads)
             time.sleep(0.1)
@@ -337,8 +618,77 @@ def test_embeddings_create_with_list_input(
         (event,) = events
 
         assert event["type"] == "transaction"
-        assert len(event["spans"]) == 1
-        (span,) = event["spans"]
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
+
+        assert span["op"] == OP.GEN_AI_EMBEDDINGS
+        assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "embeddings"
+        # Check that list of embeddings input is captured (it's JSON serialized)
+        embeddings_input = span["data"][SPANDATA.GEN_AI_EMBEDDINGS_INPUT]
+        assert json.loads(embeddings_input) == [
+            "First text",
+            "Second text",
+            "Third text",
+        ]
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_embeddings_create_with_list_input(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
+):
+    """Test embedding with list input."""
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            response = await litellm.aembedding(
+                model="text-embedding-ada-002",
+                input=["First text", "Second text", "Third text"],
+                client=client,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+        # Response is processed by litellm, so just check it exists
+        assert response is not None
+        assert len(events) == 1
+        (event,) = events
+
+        assert event["type"] == "transaction"
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
 
         assert span["op"] == OP.GEN_AI_EMBEDDINGS
         assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "embeddings"
@@ -351,7 +701,13 @@ def test_embeddings_create_with_list_input(
         ]
 
 
-def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
+def test_embeddings_no_pii(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
+):
     """Test that PII is not captured when disabled."""
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
@@ -360,20 +716,24 @@ def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
     )
     events = capture_events()
 
-    mock_response = MockEmbeddingResponse()
+    client = OpenAI(api_key="test-key")
 
-    # Mock within the test to ensure proper ordering with cache clearing
-    with mock.patch(
-        "litellm.openai_chat_completions.make_sync_openai_embedding_request"
-    ) as mock_http:
-        # The function returns (headers, response)
-        mock_http.return_value = ({}, mock_response)
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
         with start_transaction(name="litellm test"):
             response = litellm.embedding(
                 model="text-embedding-ada-002",
                 input="Hello, world!",
-                api_key="test-key",  # Provide a fake API key to avoid authentication errors
+                client=client,
             )
             # Allow time for callbacks to complete (they may run in separate threads)
             time.sleep(0.1)
@@ -384,45 +744,116 @@ def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
         (event,) = events
 
         assert event["type"] == "transaction"
-        assert len(event["spans"]) == 1
-        (span,) = event["spans"]
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
 
         assert span["op"] == OP.GEN_AI_EMBEDDINGS
         # Check that embeddings input is NOT captured when PII is disabled
         assert SPANDATA.GEN_AI_EMBEDDINGS_INPUT not in span["data"]
 
 
-def test_exception_handling(sentry_init, capture_events):
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_embeddings_no_pii(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    openai_embedding_model_response,
+    clear_litellm_cache,
+):
+    """Test that PII is not captured when disabled."""
     sentry_init(
-        integrations=[LiteLLMIntegration()],
+        integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
+        send_default_pii=False,  # PII disabled
     )
     events = capture_events()
 
-    messages = [{"role": "user", "content": "Hello!"}]
-
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    client = AsyncOpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _failure_callback(
-            kwargs,
-            Exception("API rate limit reached"),
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_model_response(
+        openai_embedding_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-    # Should have error event and transaction
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            response = await litellm.aembedding(
+                model="text-embedding-ada-002",
+                input="Hello, world!",
+                client=client,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+        # Response is processed by litellm, so just check it exists
+        assert response is not None
+        assert len(events) == 1
+        (event,) = events
+
+        assert event["type"] == "transaction"
+        spans = list(
+            x
+            for x in event["spans"]
+            if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
+        )
+        assert len(spans) == 1
+        span = spans[0]
+
+        assert span["op"] == OP.GEN_AI_EMBEDDINGS
+        # Check that embeddings input is NOT captured when PII is disabled
+        assert SPANDATA.GEN_AI_EMBEDDINGS_INPUT not in span["data"]
+
+
+def test_exception_handling(
+    reset_litellm_executor, sentry_init, capture_events, get_rate_limit_model_response
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    messages = [{"role": "user", "content": "Hello!"}]
+
+    client = OpenAI(api_key="test-key")
+
+    model_response = get_rate_limit_model_response()
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            with pytest.raises(litellm.RateLimitError):
+                litellm.completion(
+                    model="gpt-3.5-turbo",
+                    messages=messages,
+                    client=client,
+                )
+
+    # Should have error event and transaction
     assert len(events) >= 1
     # Find the error event
     error_events = [e for e in events if e.get("level") == "error"]
     assert len(error_events) == 1
 
 
-def test_span_origin(sentry_init, capture_events):
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_exception_handling(
+    sentry_init, capture_events, get_rate_limit_model_response
+):
     sentry_init(
         integrations=[LiteLLMIntegration()],
         traces_sample_rate=1.0,
@@ -430,21 +861,67 @@ def test_span_origin(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    client = AsyncOpenAI(api_key="test-key")
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    model_response = get_rate_limit_model_response()
+
+    with mock.patch.object(
+        client.embeddings._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            with pytest.raises(litellm.RateLimitError):
+                await litellm.acompletion(
+                    model="gpt-3.5-turbo",
+                    messages=messages,
+                    client=client,
+                )
+
+    # Should have error event and transaction
+    assert len(events) >= 1
+    # Find the error event
+    error_events = [e for e in events if e.get("level") == "error"]
+    assert len(error_events) == 1
+
+
+def test_span_origin(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    messages = [{"role": "user", "content": "Hello!"}]
+
+    client = OpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
 
@@ -452,7 +929,15 @@ def test_span_origin(sentry_init, capture_events):
     assert event["spans"][0]["origin"] == "auto.ai.litellm"
 
 
-def test_multiple_providers(sentry_init, capture_events):
+def test_multiple_providers(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+    nonstreaming_anthropic_model_response,
+    nonstreaming_google_genai_model_response,
+):
     """Test that the integration correctly identifies different providers."""
     sentry_init(
         integrations=[LiteLLMIntegration()],
@@ -462,38 +947,186 @@ def test_multiple_providers(sentry_init, capture_events):
 
     messages = [{"role": "user", "content": "Hello!"}]
 
-    # Test with different model prefixes
-    test_cases = [
-        ("gpt-3.5-turbo", "openai"),
-        ("claude-3-opus-20240229", "anthropic"),
-        ("gemini/gemini-pro", "gemini"),
-    ]
+    openai_client = OpenAI(api_key="test-key")
+    openai_model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        openai_client.completions._client._client,
+        "send",
+        return_value=openai_model_response,
+    ):
+        with start_transaction(name="test gpt-3.5-turbo"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=openai_client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    _reset_litellm_executor()
+
+    anthropic_client = HTTPHandler()
+    anthropic_model_response = get_model_response(
+        nonstreaming_anthropic_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        anthropic_client,
+        "post",
+        return_value=anthropic_model_response,
+    ):
+        with start_transaction(name="test claude-3-opus-20240229"):
+            litellm.completion(
+                model="claude-3-opus-20240229",
+                messages=messages,
+                client=anthropic_client,
+                api_key="test-key",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    _reset_litellm_executor()
+
+    gemini_client = HTTPHandler()
+    gemini_model_response = get_model_response(
+        nonstreaming_google_genai_model_response,
+        serialize_pydantic=True,
+    )
+
+    with mock.patch.object(
+        gemini_client,
+        "post",
+        return_value=gemini_model_response,
+    ):
+        with start_transaction(name="test gemini/gemini-pro"):
+            litellm.completion(
+                model="gemini/gemini-pro",
+                messages=messages,
+                client=gemini_client,
+                api_key="test-key",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    assert len(events) == 3
+
+    for i in range(3):
+        span = events[i]["spans"][0]
+        # The provider should be detected by litellm.get_llm_provider
+        assert SPANDATA.GEN_AI_SYSTEM in span["data"]
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_multiple_providers(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+    nonstreaming_anthropic_model_response,
+    nonstreaming_google_genai_model_response,
+):
+    """Test that the integration correctly identifies different providers."""
+    sentry_init(
+        integrations=[LiteLLMIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    messages = [{"role": "user", "content": "Hello!"}]
 
-    for model, _ in test_cases:
-        mock_response = MockCompletionResponse(model=model)
-        with start_transaction(name=f"test {model}"):
-            kwargs = {
-                "model": model,
-                "messages": messages,
-            }
-
-            _input_callback(kwargs)
-            _success_callback(
-                kwargs,
-                mock_response,
-                datetime.now(),
-                datetime.now(),
+    openai_client = AsyncOpenAI(api_key="test-key")
+    openai_model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        openai_client.completions._client._client,
+        "send",
+        return_value=openai_model_response,
+    ):
+        with start_transaction(name="test gpt-3.5-turbo"):
+            await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=openai_client,
             )
 
-    assert len(events) == len(test_cases)
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    _reset_litellm_executor()
 
-    for i in range(len(test_cases)):
+    anthropic_client = AsyncHTTPHandler()
+    anthropic_model_response = get_model_response(
+        nonstreaming_anthropic_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "True"},
+    )
+
+    with mock.patch.object(
+        anthropic_client,
+        "post",
+        return_value=anthropic_model_response,
+    ):
+        with start_transaction(name="test claude-3-opus-20240229"):
+            await litellm.acompletion(
+                model="claude-3-opus-20240229",
+                messages=messages,
+                client=anthropic_client,
+                api_key="test-key",
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    _reset_litellm_executor()
+
+    gemini_client = AsyncHTTPHandler()
+    gemini_model_response = get_model_response(
+        nonstreaming_google_genai_model_response,
+        serialize_pydantic=True,
+    )
+
+    with mock.patch.object(
+        gemini_client,
+        "post",
+        return_value=gemini_model_response,
+    ):
+        with start_transaction(name="test gemini/gemini-pro"):
+            await litellm.acompletion(
+                model="gemini/gemini-pro",
+                messages=messages,
+                client=gemini_client,
+                api_key="test-key",
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    assert len(events) == 3
+
+    for i in range(3):
         span = events[i]["spans"][0]
         # The provider should be detected by litellm.get_llm_provider
         assert SPANDATA.GEN_AI_SYSTEM in span["data"]
 
 
-def test_additional_parameters(sentry_init, capture_events):
+def test_additional_parameters(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     """Test that additional parameters are captured."""
     sentry_init(
         integrations=[LiteLLMIntegration()],
@@ -502,29 +1135,41 @@ def test_additional_parameters(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-            "temperature": 0.7,
-            "max_tokens": 100,
-            "top_p": 0.9,
-            "frequency_penalty": 0.5,
-            "presence_penalty": 0.5,
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+                temperature=0.7,
+                max_tokens=100,
+                top_p=0.9,
+                frequency_penalty=0.5,
+                presence_penalty=0.5,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
     assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
     assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
@@ -533,8 +1178,14 @@ def test_additional_parameters(sentry_init, capture_events):
     assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.5
 
 
-def test_litellm_specific_parameters(sentry_init, capture_events):
-    """Test that LiteLLM-specific parameters are captured."""
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_additional_parameters(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    """Test that additional parameters are captured."""
     sentry_init(
         integrations=[LiteLLMIntegration()],
         traces_sample_rate=1.0,
@@ -542,34 +1193,57 @@ def test_litellm_specific_parameters(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
+    client = AsyncOpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-            "api_base": "https://custom-api.example.com",
-            "api_version": "2023-01-01",
-            "custom_llm_provider": "custom_provider",
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+                temperature=0.7,
+                max_tokens=100,
+                top_p=0.9,
+                frequency_penalty=0.5,
+                presence_penalty=0.5,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
 
-    assert span["data"]["gen_ai.litellm.api_base"] == "https://custom-api.example.com"
-    assert span["data"]["gen_ai.litellm.api_version"] == "2023-01-01"
-    assert span["data"]["gen_ai.litellm.custom_llm_provider"] == "custom_provider"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.5
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.5
 
 
-def test_no_integration(sentry_init, capture_events):
+def test_no_integration(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     """Test that when integration is not enabled, callbacks don't break."""
     sentry_init(
         traces_sample_rate=1.0,
@@ -577,28 +1251,85 @@ def test_no_integration(sentry_init, capture_events):
     events = capture_events()
 
     messages = [{"role": "user", "content": "Hello!"}]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        # When the integration isn't enabled, the callbacks should exit early
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
 
-        # These should not crash, just do nothing
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
+
+    (event,) = events
+    # Should still have the transaction, but no child spans since integration is off
+    assert event["type"] == "transaction"
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 0
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_no_integration(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    """Test that when integration is not enabled, callbacks don't break."""
+    sentry_init(
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    messages = [{"role": "user", "content": "Hello!"}]
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=messages,
+                client=client,
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
 
     (event,) = events
     # Should still have the transaction, but no child spans since integration is off
     assert event["type"] == "transaction"
-    assert len(event.get("spans", [])) == 0
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 0
 
 
 def test_response_without_usage(sentry_init, capture_events):
@@ -656,50 +1387,6 @@ def test_integration_setup(sentry_init):
     assert _failure_callback in (litellm.failure_callback or [])
 
 
-def test_message_dict_extraction(sentry_init, capture_events):
-    """Test that response messages are properly extracted with dict() fallback."""
-    sentry_init(
-        integrations=[LiteLLMIntegration(include_prompts=True)],
-        traces_sample_rate=1.0,
-        send_default_pii=True,
-    )
-    events = capture_events()
-
-    messages = [{"role": "user", "content": "Hello!"}]
-
-    # Create a message that has dict() method instead of model_dump()
-    class DictMessage:
-        def __init__(self):
-            self.role = "assistant"
-            self.content = "Response"
-            self.tool_calls = None
-
-        def dict(self):
-            return {"role": self.role, "content": self.content}
-
-    mock_response = MockCompletionResponse(choices=[MockChoice(message=DictMessage())])
-
-    with start_transaction(name="litellm test"):
-        kwargs = {
-            "model": "gpt-3.5-turbo",
-            "messages": messages,
-        }
-
-        _input_callback(kwargs)
-        _success_callback(
-            kwargs,
-            mock_response,
-            datetime.now(),
-            datetime.now(),
-        )
-
-    (event,) = events
-    (span,) = event["spans"]
-
-    # Should have extracted the response message
-    assert SPANDATA.GEN_AI_RESPONSE_TEXT in span["data"]
-
-
 def test_litellm_message_truncation(sentry_init, capture_events):
     """Test that large messages are truncated properly in LiteLLM integration."""
     sentry_init(
@@ -762,7 +1449,13 @@ def test_litellm_message_truncation(sentry_init, capture_events):
 IMAGE_DATA_URI = f"data:image/png;base64,{IMAGE_B64}"
 
 
-def test_binary_content_encoding_image_url(sentry_init, capture_events):
+def test_binary_content_encoding_image_url(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -782,15 +1475,116 @@ def test_binary_content_encoding_image_url(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
+    messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+
+    blob_item = next(
+        (
+            item
+            for msg in messages_data
+            if "content" in msg
+            for item in msg["content"]
+            if item.get("type") == "blob"
+        ),
+        None,
+    )
+    assert blob_item is not None
+    assert blob_item["modality"] == "image"
+    assert blob_item["mime_type"] == "image/png"
+    assert (
+        IMAGE_B64 in blob_item["content"]
+        or blob_item["content"] == BLOB_DATA_SUBSTITUTE
+    )
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_binary_content_encoding_image_url(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Look at this image:"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": IMAGE_DATA_URI, "detail": "high"},
+                },
+            ],
+        }
+    ]
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    (event,) = events
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     blob_item = next(
@@ -812,7 +1606,13 @@ def test_binary_content_encoding_image_url(sentry_init, capture_events):
     )
 
 
-def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
+def test_binary_content_encoding_mixed_content(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -833,15 +1633,37 @@ def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     content_items = [
@@ -851,7 +1673,81 @@ def test_binary_content_encoding_mixed_content(sentry_init, capture_events):
     assert any(item.get("type") == "blob" for item in content_items)
 
 
-def test_binary_content_encoding_uri_type(sentry_init, capture_events):
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_binary_content_encoding_mixed_content(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Here is an image:"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": IMAGE_DATA_URI},
+                },
+                {"type": "text", "text": "What do you see?"},
+            ],
+        }
+    ]
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    (event,) = events
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
+    messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+
+    content_items = [
+        item for msg in messages_data if "content" in msg for item in msg["content"]
+    ]
+    assert any(item.get("type") == "text" for item in content_items)
+    assert any(item.get("type") == "blob" for item in content_items)
+
+
+def test_binary_content_encoding_uri_type(
+    reset_litellm_executor,
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
     sentry_init(
         integrations=[LiteLLMIntegration(include_prompts=True)],
         traces_sample_rate=1.0,
@@ -870,15 +1766,110 @@ def test_binary_content_encoding_uri_type(sentry_init, capture_events):
             ],
         }
     ]
-    mock_response = MockCompletionResponse()
+    client = OpenAI(api_key="test-key")
 
-    with start_transaction(name="litellm test"):
-        kwargs = {"model": "gpt-4-vision-preview", "messages": messages}
-        _input_callback(kwargs)
-        _success_callback(kwargs, mock_response, datetime.now(), datetime.now())
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            litellm.completion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            litellm_utils.executor.shutdown(wait=True)
 
     (event,) = events
-    (span,) = event["spans"]
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
+    messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
+
+    uri_item = next(
+        (
+            item
+            for msg in messages_data
+            if "content" in msg
+            for item in msg["content"]
+            if item.get("type") == "uri"
+        ),
+        None,
+    )
+    assert uri_item is not None
+    assert uri_item["uri"] == "https://example.com/image.jpg"
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_async_binary_content_encoding_uri_type(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    nonstreaming_chat_completions_model_response,
+):
+    sentry_init(
+        integrations=[LiteLLMIntegration(include_prompts=True)],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+    events = capture_events()
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {"url": "https://example.com/image.jpg"},
+                }
+            ],
+        }
+    ]
+    client = AsyncOpenAI(api_key="test-key")
+
+    model_response = get_model_response(
+        nonstreaming_chat_completions_model_response,
+        serialize_pydantic=True,
+        request_headers={"X-Stainless-Raw-Response": "true"},
+    )
+
+    with mock.patch.object(
+        client.completions._client._client,
+        "send",
+        return_value=model_response,
+    ):
+        with start_transaction(name="litellm test"):
+            await litellm.acompletion(
+                model="gpt-4-vision-preview",
+                messages=messages,
+                client=client,
+                custom_llm_provider="openai",
+            )
+
+            await GLOBAL_LOGGING_WORKER.flush()
+            await asyncio.sleep(0.5)
+
+    (event,) = events
+    chat_spans = list(
+        x
+        for x in event["spans"]
+        if x["op"] == OP.GEN_AI_CHAT and x["origin"] == "auto.ai.litellm"
+    )
+    assert len(chat_spans) == 1
+    span = chat_spans[0]
     messages_data = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_MESSAGES])
 
     uri_item = next(
diff --git a/tests/integrations/logging/test_logging.py b/tests/integrations/logging/test_logging.py
index 7b144f4b55..5e384bd3db 100644
--- a/tests/integrations/logging/test_logging.py
+++ b/tests/integrations/logging/test_logging.py
@@ -5,7 +5,13 @@
 
 from sentry_sdk import get_client
 from sentry_sdk.consts import VERSION
-from sentry_sdk.integrations.logging import LoggingIntegration, ignore_logger
+from sentry_sdk.integrations.logging import (
+    LoggingIntegration,
+    ignore_logger,
+    ignore_logger_for_sentry_logs,
+    unignore_logger,
+    unignore_logger_for_sentry_logs,
+)
 from tests.test_logs import envelopes_to_logs
 
 other_logger = logging.getLogger("testfoo")
@@ -222,34 +228,37 @@ def test_logging_captured_warnings(sentry_init, capture_events, recwarn):
     assert str(recwarn[0].message) == "third"
 
 
-def test_ignore_logger(sentry_init, capture_events):
+def test_ignore_logger(sentry_init, capture_events, request):
     sentry_init(integrations=[LoggingIntegration()], default_integrations=False)
     events = capture_events()
 
     ignore_logger("testfoo")
+    request.addfinalizer(lambda: unignore_logger("testfoo"))
 
     other_logger.error("hi")
 
     assert not events
 
 
-def test_ignore_logger_whitespace_padding(sentry_init, capture_events):
+def test_ignore_logger_whitespace_padding(sentry_init, capture_events, request):
     """Here we test insensitivity to whitespace padding of ignored loggers"""
     sentry_init(integrations=[LoggingIntegration()], default_integrations=False)
     events = capture_events()
 
     ignore_logger("testfoo")
+    request.addfinalizer(lambda: unignore_logger("testfoo"))
 
     padded_logger = logging.getLogger("       testfoo   ")
     padded_logger.error("hi")
     assert not events
 
 
-def test_ignore_logger_wildcard(sentry_init, capture_events):
+def test_ignore_logger_wildcard(sentry_init, capture_events, request):
     sentry_init(integrations=[LoggingIntegration()], default_integrations=False)
     events = capture_events()
 
     ignore_logger("testfoo.*")
+    request.addfinalizer(lambda: unignore_logger("testfoo.*"))
 
     nested_logger = logging.getLogger("testfoo.submodule")
 
@@ -262,6 +271,44 @@ def test_ignore_logger_wildcard(sentry_init, capture_events):
     assert event["logentry"]["formatted"] == "hi"
 
 
+def test_ignore_logger_does_not_affect_sentry_logs(
+    sentry_init, capture_envelopes, request
+):
+    """ignore_logger should suppress events/breadcrumbs but not Sentry Logs."""
+    sentry_init(enable_logs=True)
+    envelopes = capture_envelopes()
+
+    ignore_logger("testfoo")
+    request.addfinalizer(lambda: unignore_logger("testfoo"))
+
+    other_logger.error("hi")
+    get_client().flush()
+
+    logs = envelopes_to_logs(envelopes)
+    assert len(logs) == 1
+    assert logs[0]["body"] == "hi"
+
+
+def test_ignore_logger_for_sentry_logs(sentry_init, capture_envelopes, request):
+    """ignore_logger_for_sentry_logs should suppress Sentry Logs but not events."""
+    sentry_init(enable_logs=True)
+    envelopes = capture_envelopes()
+
+    ignore_logger_for_sentry_logs("testfoo")
+    request.addfinalizer(lambda: unignore_logger_for_sentry_logs("testfoo"))
+
+    other_logger.error("hi")
+    get_client().flush()
+
+    # Event should still be captured
+    event_envelopes = [e for e in envelopes if e.items[0].type == "event"]
+    assert len(event_envelopes) == 1
+
+    # But no Sentry Logs
+    logs = envelopes_to_logs(envelopes)
+    assert len(logs) == 0
+
+
 def test_logging_dictionary_interpolation(sentry_init, capture_events):
     """Here we test an entire dictionary being interpolated into the log message."""
     sentry_init(integrations=[LoggingIntegration()], default_integrations=False)
diff --git a/tests/integrations/openai/test_openai.py b/tests/integrations/openai/test_openai.py
index b8701a65c0..ada2e633de 100644
--- a/tests/integrations/openai/test_openai.py
+++ b/tests/integrations/openai/test_openai.py
@@ -41,13 +41,12 @@
     SKIP_RESPONSES_TESTS = True
 
 from sentry_sdk import start_transaction
-from sentry_sdk.consts import SPANDATA
+from sentry_sdk.consts import SPANDATA, OP
 from sentry_sdk.integrations.openai import (
     OpenAIIntegration,
-    _calculate_token_usage,
+    _calculate_completions_token_usage,
+    _calculate_responses_token_usage,
 )
-from sentry_sdk._types import AnnotatedValue
-from sentry_sdk.serializer import serialize
 from sentry_sdk.utils import safe_serialize
 
 from unittest import mock  # python 3.3 and above
@@ -124,11 +123,6 @@ async def __call__(self, *args, **kwargs):
     )
 
 
-async def async_iterator(values):
-    for value in values:
-        yield value
-
-
 @pytest.mark.parametrize(
     "send_default_pii, include_prompts",
     [
@@ -158,6 +152,11 @@ def test_nonstreaming_chat_completion_no_prompts(
                     {"role": "system", "content": "You are a helpful assistant."},
                     {"role": "user", "content": "hello"},
                 ],
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
             )
             .choices[0]
             .message.content
@@ -168,6 +167,15 @@ def test_nonstreaming_chat_completion_no_prompts(
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in span["data"]
     assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
@@ -237,6 +245,11 @@ def test_nonstreaming_chat_completion(sentry_init, capture_events, messages, req
             client.chat.completions.create(
                 model="some-model",
                 messages=messages,
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
             )
             .choices[0]
             .message.content
@@ -247,6 +260,15 @@ def test_nonstreaming_chat_completion(sentry_init, capture_events, messages, req
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     param_id = request.node.callspec.id
     if "blocks" in param_id:
@@ -305,6 +327,11 @@ async def test_nonstreaming_chat_completion_async_no_prompts(
                 {"role": "system", "content": "You are a helpful assistant."},
                 {"role": "user", "content": "hello"},
             ],
+            max_tokens=100,
+            presence_penalty=0.1,
+            frequency_penalty=0.2,
+            temperature=0.7,
+            top_p=0.9,
         )
         response = response.choices[0].message.content
 
@@ -313,6 +340,15 @@ async def test_nonstreaming_chat_completion_async_no_prompts(
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in span["data"]
     assert SPANDATA.GEN_AI_REQUEST_MESSAGES not in span["data"]
@@ -384,6 +420,11 @@ async def test_nonstreaming_chat_completion_async(
         response = await client.chat.completions.create(
             model="some-model",
             messages=messages,
+            max_tokens=100,
+            presence_penalty=0.1,
+            frequency_penalty=0.2,
+            temperature=0.7,
+            top_p=0.9,
         )
         response = response.choices[0].message.content
 
@@ -392,6 +433,15 @@ async def test_nonstreaming_chat_completion_async(
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is False
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     param_id = request.node.callspec.id
     if "blocks" in param_id:
@@ -440,7 +490,12 @@ def tiktoken_encoding_if_installed():
     ],
 )
 def test_streaming_chat_completion_no_prompts(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[
@@ -455,61 +510,90 @@ def test_streaming_chat_completion_no_prompts(
     events = capture_events()
 
     client = OpenAI(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=0, delta=ChoiceDelta(content="hel"), finish_reason=None
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=1, delta=ChoiceDelta(content="lo "), finish_reason=None
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=2, delta=ChoiceDelta(content="world"), finish_reason="stop"
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-    ]
-
-    client.chat.completions._post = mock.Mock(return_value=returned_stream)
-    with start_transaction(name="openai tx"):
-        response_stream = client.chat.completions.create(
-            model="some-model",
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": "hello"},
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            [
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content="hel"),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=1,
+                            delta=ChoiceDelta(content="lo "),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=2,
+                            delta=ChoiceDelta(content="world"),
+                            finish_reason="stop",
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
             ],
-            stream=True,
-        )
-        response_string = "".join(
-            map(lambda x: x.choices[0].delta.content, response_stream)
+            include_event_type=False,
         )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.chat.completions.create(
+                model="some-model",
+                messages=[
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": "hello"},
+                ],
+                stream=True,
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
+            )
+            response_string = "".join(
+                map(lambda x: x.choices[0].delta.content, response_stream)
+            )
+
     assert response_string == "hello world"
     tx = events[0]
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "model-id"
 
@@ -527,6 +611,304 @@ def test_streaming_chat_completion_no_prompts(
         pass  # if tiktoken is not installed, we can't guarantee token usage will be calculated properly
 
 
+@pytest.mark.skipif(
+    OPENAI_VERSION <= (1, 1, 0),
+    reason="OpenAI versions <=1.1.0 do not support the stream_options parameter.",
+)
+def test_streaming_chat_completion_with_usage_in_stream(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    """When stream_options=include_usage is set, token usage comes from the final chunk's usage field."""
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=False)],
+        traces_sample_rate=1.0,
+        send_default_pii=False,
+    )
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            [
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content="hel"),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content="lo"),
+                            finish_reason="stop",
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                    usage=CompletionUsage(
+                        prompt_tokens=20,
+                        completion_tokens=10,
+                        total_tokens=30,
+                    ),
+                ),
+            ],
+            include_event_type=False,
+        )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "hello"}],
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            for _ in response_stream:
+                pass
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "gen_ai.chat"
+    assert span["data"]["gen_ai.usage.input_tokens"] == 20
+    assert span["data"]["gen_ai.usage.output_tokens"] == 10
+    assert span["data"]["gen_ai.usage.total_tokens"] == 30
+
+
+@pytest.mark.skipif(
+    OPENAI_VERSION <= (1, 1, 0),
+    reason="OpenAI versions <=1.1.0 do not support the stream_options parameter.",
+)
+def test_streaming_chat_completion_empty_content_preserves_token_usage(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    server_side_event_chunks,
+):
+    """Token usage from the stream is recorded even when no content is produced (e.g. content filter)."""
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=False)],
+        traces_sample_rate=1.0,
+        send_default_pii=False,
+    )
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            [
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                    usage=CompletionUsage(
+                        prompt_tokens=20,
+                        completion_tokens=0,
+                        total_tokens=20,
+                    ),
+                ),
+            ],
+            include_event_type=False,
+        )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "hello"}],
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            for _ in response_stream:
+                pass
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "gen_ai.chat"
+    assert span["data"]["gen_ai.usage.input_tokens"] == 20
+    assert "gen_ai.usage.output_tokens" not in span["data"]
+    assert span["data"]["gen_ai.usage.total_tokens"] == 20
+
+
+@pytest.mark.skipif(
+    OPENAI_VERSION <= (1, 1, 0),
+    reason="OpenAI versions <=1.1.0 do not support the stream_options parameter.",
+)
+@pytest.mark.asyncio
+async def test_streaming_chat_completion_empty_content_preserves_token_usage_async(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    """Token usage from the stream is recorded even when no content is produced - async variant."""
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=False)],
+        traces_sample_rate=1.0,
+        send_default_pii=False,
+    )
+    events = capture_events()
+
+    client = AsyncOpenAI(api_key="z")
+    returned_stream = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                        usage=CompletionUsage(
+                            prompt_tokens=20,
+                            completion_tokens=0,
+                            total_tokens=20,
+                        ),
+                    ),
+                ],
+                include_event_type=False,
+            )
+        )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "hello"}],
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            async for _ in response_stream:
+                pass
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "gen_ai.chat"
+    assert span["data"]["gen_ai.usage.input_tokens"] == 20
+    assert "gen_ai.usage.output_tokens" not in span["data"]
+    assert span["data"]["gen_ai.usage.total_tokens"] == 20
+
+
+@pytest.mark.skipif(
+    OPENAI_VERSION <= (1, 1, 0),
+    reason="OpenAI versions <=1.1.0 do not support the stream_options parameter.",
+)
+@pytest.mark.asyncio
+async def test_streaming_chat_completion_async_with_usage_in_stream(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
+    """When stream_options=include_usage is set, token usage comes from the final chunk's usage field (async)."""
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=False)],
+        traces_sample_rate=1.0,
+        send_default_pii=False,
+    )
+    events = capture_events()
+
+    client = AsyncOpenAI(api_key="z")
+    returned_stream = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content="hel"),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content="lo"),
+                                finish_reason="stop",
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                        usage=CompletionUsage(
+                            prompt_tokens=20,
+                            completion_tokens=10,
+                            total_tokens=30,
+                        ),
+                    ),
+                ],
+                include_event_type=False,
+            )
+        )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "hello"}],
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            async for _ in response_stream:
+                pass
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "gen_ai.chat"
+    assert span["data"]["gen_ai.usage.input_tokens"] == 20
+    assert span["data"]["gen_ai.usage.output_tokens"] == 10
+    assert span["data"]["gen_ai.usage.total_tokens"] == 30
+
+
 # noinspection PyTypeChecker
 @pytest.mark.parametrize(
     "messages",
@@ -571,7 +953,14 @@ def test_streaming_chat_completion_no_prompts(
         ),
     ],
 )
-def test_streaming_chat_completion(sentry_init, capture_events, messages, request):
+def test_streaming_chat_completion(
+    sentry_init,
+    capture_events,
+    messages,
+    request,
+    get_model_response,
+    server_side_event_chunks,
+):
     sentry_init(
         integrations=[
             OpenAIIntegration(
@@ -585,58 +974,86 @@ def test_streaming_chat_completion(sentry_init, capture_events, messages, reques
     events = capture_events()
 
     client = OpenAI(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=0, delta=ChoiceDelta(content="hel"), finish_reason=None
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=1, delta=ChoiceDelta(content="lo "), finish_reason=None
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=2, delta=ChoiceDelta(content="world"), finish_reason="stop"
-                )
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            [
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content="hel"),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=1,
+                            delta=ChoiceDelta(content="lo "),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=2,
+                            delta=ChoiceDelta(content="world"),
+                            finish_reason="stop",
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
             ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-    ]
-
-    client.chat.completions._post = mock.Mock(return_value=returned_stream)
-    with start_transaction(name="openai tx"):
-        response_stream = client.chat.completions.create(
-            model="some-model",
-            messages=messages,
-            stream=True,
-        )
-        response_string = "".join(
-            map(lambda x: x.choices[0].delta.content, response_stream)
+            include_event_type=False,
         )
+    )
+
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.chat.completions.create(
+                model="some-model",
+                messages=messages,
+                stream=True,
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
+            )
+            response_string = "".join(
+                map(lambda x: x.choices[0].delta.content, response_stream)
+            )
     assert response_string == "hello world"
     tx = events[0]
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     param_id = request.node.callspec.id
     if "blocks" in param_id:
@@ -689,7 +1106,13 @@ def test_streaming_chat_completion(sentry_init, capture_events, messages, reques
     ],
 )
 async def test_streaming_chat_completion_async_no_prompts(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[
@@ -704,67 +1127,93 @@ async def test_streaming_chat_completion_async_no_prompts(
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=0, delta=ChoiceDelta(content="hel"), finish_reason=None
-                    )
-                ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=1, delta=ChoiceDelta(content="lo "), finish_reason=None
-                    )
-                ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=2,
-                        delta=ChoiceDelta(content="world"),
-                        finish_reason="stop",
-                    )
+    returned_stream = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content="hel"),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=1,
+                                delta=ChoiceDelta(content="lo "),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=2,
+                                delta=ChoiceDelta(content="world"),
+                                finish_reason="stop",
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
                 ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-        ]
+                include_event_type=False,
+            )
+        )
     )
 
-    client.chat.completions._post = AsyncMock(return_value=returned_stream)
-    with start_transaction(name="openai tx"):
-        response_stream = await client.chat.completions.create(
-            model="some-model",
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": "hello"},
-            ],
-            stream=True,
-        )
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.chat.completions.create(
+                model="some-model",
+                messages=[
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": "hello"},
+                ],
+                stream=True,
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
+            )
 
-        response_string = ""
-        async for x in response_stream:
-            response_string += x.choices[0].delta.content
+            response_string = ""
+            async for x in response_stream:
+                response_string += x.choices[0].delta.content
 
     assert response_string == "hello world"
     tx = events[0]
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "model-id"
 
@@ -829,7 +1278,13 @@ async def test_streaming_chat_completion_async_no_prompts(
     ],
 )
 async def test_streaming_chat_completion_async(
-    sentry_init, capture_events, messages, request
+    sentry_init,
+    capture_events,
+    messages,
+    request,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[
@@ -844,64 +1299,91 @@ async def test_streaming_chat_completion_async(
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=0, delta=ChoiceDelta(content="hel"), finish_reason=None
-                    )
-                ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=1, delta=ChoiceDelta(content="lo "), finish_reason=None
-                    )
-                ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=2,
-                        delta=ChoiceDelta(content="world"),
-                        finish_reason="stop",
-                    )
+
+    returned_stream = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content="hel"),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=1,
+                                delta=ChoiceDelta(content="lo "),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=2,
+                                delta=ChoiceDelta(content="world"),
+                                finish_reason="stop",
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
                 ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-        ]
+                include_event_type=False,
+            )
+        )
     )
 
-    client.chat.completions._post = AsyncMock(return_value=returned_stream)
-    with start_transaction(name="openai tx"):
-        response_stream = await client.chat.completions.create(
-            model="some-model",
-            messages=messages,
-            stream=True,
-        )
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.chat.completions.create(
+                model="some-model",
+                messages=messages,
+                stream=True,
+                max_tokens=100,
+                presence_penalty=0.1,
+                frequency_penalty=0.2,
+                temperature=0.7,
+                top_p=0.9,
+            )
 
-        response_string = ""
-        async for x in response_stream:
-            response_string += x.choices[0].delta.content
+            response_string = ""
+            async for x in response_stream:
+                response_string += x.choices[0].delta.content
 
     assert response_string == "hello world"
     tx = events[0]
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.chat"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True
+
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "some-model"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_PRESENCE_PENALTY] == 0.1
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_FREQUENCY_PENALTY] == 0.2
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "model-id"
 
@@ -1043,6 +1525,8 @@ def test_embeddings_create_no_pii(
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.embeddings"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "text-embedding-3-large"
 
     assert SPANDATA.GEN_AI_EMBEDDINGS_INPUT not in span["data"]
 
@@ -1123,6 +1607,8 @@ def test_embeddings_create(sentry_init, capture_events, input, request):
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.embeddings"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "text-embedding-3-large"
 
     param_id = request.node.callspec.id
     if param_id == "string":
@@ -1194,6 +1680,8 @@ async def test_embeddings_create_async_no_pii(
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.embeddings"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "text-embedding-3-large"
 
     assert SPANDATA.GEN_AI_EMBEDDINGS_INPUT not in span["data"]
 
@@ -1277,6 +1765,8 @@ async def test_embeddings_create_async(sentry_init, capture_events, input, reque
     assert tx["type"] == "transaction"
     span = tx["spans"][0]
     assert span["op"] == "gen_ai.embeddings"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MODEL] == "text-embedding-3-large"
 
     param_id = request.node.callspec.id
     if param_id == "string":
@@ -1463,7 +1953,9 @@ def test_span_origin_streaming_chat(sentry_init, capture_events):
 
 
 @pytest.mark.asyncio
-async def test_span_origin_streaming_chat_async(sentry_init, capture_events):
+async def test_span_origin_streaming_chat_async(
+    sentry_init, capture_events, async_iterator
+):
     sentry_init(
         integrations=[OpenAIIntegration()],
         traces_sample_rate=1.0,
@@ -1587,7 +2079,8 @@ async def test_span_origin_embeddings_async(sentry_init, capture_events):
     assert event["spans"][0]["origin"] == "auto.ai.openai"
 
 
-def test_calculate_token_usage_a():
+def test_completions_token_usage_from_response():
+    """Token counts are extracted from response.usage using Completions API field names."""
     span = mock.MagicMock()
 
     def count_tokens(msg):
@@ -1604,8 +2097,13 @@ def count_tokens(msg):
     with mock.patch(
         "sentry_sdk.integrations.openai.record_token_usage"
     ) as mock_record_token_usage:
-        _calculate_token_usage(
-            messages, response, span, streaming_message_responses, count_tokens
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=streaming_message_responses,
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
         )
         mock_record_token_usage.assert_called_once_with(
             span,
@@ -1617,7 +2115,46 @@ def count_tokens(msg):
         )
 
 
-def test_calculate_token_usage_b():
+def test_completions_token_usage_with_detailed_fields():
+    """Cached and reasoning token counts are extracted from prompt_tokens_details and completion_tokens_details."""
+    span = mock.MagicMock()
+
+    def count_tokens(msg):
+        return len(str(msg))
+
+    response = mock.MagicMock()
+    response.usage = mock.MagicMock()
+    response.usage.prompt_tokens = 20
+    response.usage.prompt_tokens_details = mock.MagicMock()
+    response.usage.prompt_tokens_details.cached_tokens = 5
+    response.usage.completion_tokens = 10
+    response.usage.completion_tokens_details = mock.MagicMock()
+    response.usage.completion_tokens_details.reasoning_tokens = 8
+    response.usage.total_tokens = 30
+
+    with mock.patch(
+        "sentry_sdk.integrations.openai.record_token_usage"
+    ) as mock_record_token_usage:
+        _calculate_completions_token_usage(
+            messages=[],
+            response=response,
+            span=span,
+            streaming_message_responses=[],
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
+        )
+        mock_record_token_usage.assert_called_once_with(
+            span,
+            input_tokens=20,
+            input_tokens_cached=5,
+            output_tokens=10,
+            output_tokens_reasoning=8,
+            total_tokens=30,
+        )
+
+
+def test_completions_token_usage_manual_input_counting():
+    """When prompt_tokens is missing, input tokens are counted manually from messages."""
     span = mock.MagicMock()
 
     def count_tokens(msg):
@@ -1637,8 +2174,13 @@ def count_tokens(msg):
     with mock.patch(
         "sentry_sdk.integrations.openai.record_token_usage"
     ) as mock_record_token_usage:
-        _calculate_token_usage(
-            messages, response, span, streaming_message_responses, count_tokens
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=streaming_message_responses,
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
         )
         mock_record_token_usage.assert_called_once_with(
             span,
@@ -1650,7 +2192,8 @@ def count_tokens(msg):
         )
 
 
-def test_calculate_token_usage_c():
+def test_completions_token_usage_manual_output_counting_streaming():
+    """When completion_tokens is missing, output tokens are counted from streaming responses."""
     span = mock.MagicMock()
 
     def count_tokens(msg):
@@ -1670,8 +2213,13 @@ def count_tokens(msg):
     with mock.patch(
         "sentry_sdk.integrations.openai.record_token_usage"
     ) as mock_record_token_usage:
-        _calculate_token_usage(
-            messages, response, span, streaming_message_responses, count_tokens
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=streaming_message_responses,
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
         )
         mock_record_token_usage.assert_called_once_with(
             span,
@@ -1683,7 +2231,8 @@ def count_tokens(msg):
         )
 
 
-def test_calculate_token_usage_d():
+def test_completions_token_usage_manual_output_counting_choices():
+    """When completion_tokens is missing, output tokens are counted from response.choices."""
     span = mock.MagicMock()
 
     def count_tokens(msg):
@@ -1694,30 +2243,48 @@ def count_tokens(msg):
     response.usage.prompt_tokens = 20
     response.usage.total_tokens = 20
     response.choices = [
-        mock.MagicMock(message="one"),
-        mock.MagicMock(message="two"),
-        mock.MagicMock(message="three"),
+        Choice(
+            index=0,
+            finish_reason="stop",
+            message=ChatCompletionMessage(role="assistant", content="one"),
+        ),
+        Choice(
+            index=1,
+            finish_reason="stop",
+            message=ChatCompletionMessage(role="assistant", content="two"),
+        ),
+        Choice(
+            index=2,
+            finish_reason="stop",
+            message=ChatCompletionMessage(role="assistant", content="three"),
+        ),
     ]
     messages = []
-    streaming_message_responses = []
+    streaming_message_responses = None
 
     with mock.patch(
         "sentry_sdk.integrations.openai.record_token_usage"
     ) as mock_record_token_usage:
-        _calculate_token_usage(
-            messages, response, span, streaming_message_responses, count_tokens
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=streaming_message_responses,
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
         )
         mock_record_token_usage.assert_called_once_with(
             span,
             input_tokens=20,
             input_tokens_cached=None,
-            output_tokens=None,
+            output_tokens=11,
             output_tokens_reasoning=None,
             total_tokens=20,
         )
 
 
-def test_calculate_token_usage_e():
+def test_completions_token_usage_no_usage_data():
+    """When response has no usage data and no streaming responses, all tokens are None."""
     span = mock.MagicMock()
 
     def count_tokens(msg):
@@ -1730,8 +2297,75 @@ def count_tokens(msg):
     with mock.patch(
         "sentry_sdk.integrations.openai.record_token_usage"
     ) as mock_record_token_usage:
-        _calculate_token_usage(
-            messages, response, span, streaming_message_responses, count_tokens
+        _calculate_completions_token_usage(
+            messages=messages,
+            response=response,
+            span=span,
+            streaming_message_responses=streaming_message_responses,
+            streaming_message_total_token_usage=None,
+            count_tokens=count_tokens,
+        )
+        mock_record_token_usage.assert_called_once_with(
+            span,
+            input_tokens=None,
+            input_tokens_cached=None,
+            output_tokens=None,
+            output_tokens_reasoning=None,
+            total_tokens=None,
+        )
+
+
+@pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
+def test_responses_token_usage_from_response():
+    """Token counts including cached and reasoning tokens are extracted from Responses API."""
+    span = mock.MagicMock()
+
+    def count_tokens(msg):
+        return len(str(msg))
+
+    response = mock.MagicMock()
+    response.usage = mock.MagicMock()
+    response.usage.input_tokens = 20
+    response.usage.input_tokens_details = mock.MagicMock()
+    response.usage.input_tokens_details.cached_tokens = 5
+    response.usage.output_tokens = 10
+    response.usage.output_tokens_details = mock.MagicMock()
+    response.usage.output_tokens_details.reasoning_tokens = 8
+    response.usage.total_tokens = 30
+    input = []
+
+    with mock.patch(
+        "sentry_sdk.integrations.openai.record_token_usage"
+    ) as mock_record_token_usage:
+        _calculate_responses_token_usage(input, response, span, None, count_tokens)
+        mock_record_token_usage.assert_called_once_with(
+            span,
+            input_tokens=20,
+            input_tokens_cached=5,
+            output_tokens=10,
+            output_tokens_reasoning=8,
+            total_tokens=30,
+        )
+
+
+@pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
+def test_responses_token_usage_no_usage_data():
+    """When Responses API response has no usage data, all tokens are None."""
+    span = mock.MagicMock()
+
+    def count_tokens(msg):
+        return len(str(msg))
+
+    response = mock.MagicMock()
+    response.usage = None
+    input = []
+    streaming_message_responses = None
+
+    with mock.patch(
+        "sentry_sdk.integrations.openai.record_token_usage"
+    ) as mock_record_token_usage:
+        _calculate_responses_token_usage(
+            input, response, span, streaming_message_responses, count_tokens
         )
         mock_record_token_usage.assert_called_once_with(
             span,
@@ -1743,6 +2377,70 @@ def count_tokens(msg):
         )
 
 
+@pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
+def test_responses_token_usage_manual_output_counting_response_output():
+    """When output_tokens is missing, output tokens are counted from response.output."""
+    span = mock.MagicMock()
+
+    def count_tokens(msg):
+        return len(str(msg))
+
+    response = mock.MagicMock()
+    response.usage = mock.MagicMock()
+    response.usage.input_tokens = 20
+    response.usage.total_tokens = 20
+    response.output = [
+        ResponseOutputMessage(
+            id="msg-1",
+            content=[
+                ResponseOutputText(
+                    annotations=[],
+                    text="one",
+                    type="output_text",
+                ),
+            ],
+            role="assistant",
+            status="completed",
+            type="message",
+        ),
+        ResponseOutputMessage(
+            id="msg-2",
+            content=[
+                ResponseOutputText(
+                    annotations=[],
+                    text="two",
+                    type="output_text",
+                ),
+                ResponseOutputText(
+                    annotations=[],
+                    text="three",
+                    type="output_text",
+                ),
+            ],
+            role="assistant",
+            status="completed",
+            type="message",
+        ),
+    ]
+    input = []
+    streaming_message_responses = None
+
+    with mock.patch(
+        "sentry_sdk.integrations.openai.record_token_usage"
+    ) as mock_record_token_usage:
+        _calculate_responses_token_usage(
+            input, response, span, streaming_message_responses, count_tokens
+        )
+        mock_record_token_usage.assert_called_once_with(
+            span,
+            input_tokens=20,
+            input_tokens_cached=None,
+            output_tokens=11,
+            output_tokens_reasoning=None,
+            total_tokens=20,
+        )
+
+
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
 def test_ai_client_span_responses_api_no_pii(sentry_init, capture_events):
     sentry_init(
@@ -1759,6 +2457,9 @@ def test_ai_client_span_responses_api_no_pii(sentry_init, capture_events):
             model="gpt-4o",
             instructions="You are a coding assistant that talks like a pirate.",
             input="How do I check if a Python object is an instance of a class?",
+            max_output_tokens=100,
+            temperature=0.7,
+            top_p=0.9,
         )
 
     (transaction,) = events
@@ -1769,8 +2470,12 @@ def test_ai_client_span_responses_api_no_pii(sentry_init, capture_events):
     assert spans[0]["origin"] == "auto.ai.openai"
     assert spans[0]["data"] == {
         "gen_ai.operation.name": "responses",
+        "gen_ai.request.max_tokens": 100,
+        "gen_ai.request.temperature": 0.7,
+        "gen_ai.request.top_p": 0.9,
         "gen_ai.request.model": "gpt-4o",
         "gen_ai.response.model": "response-model-id",
+        "gen_ai.response.streaming": False,
         "gen_ai.system": "openai",
         "gen_ai.usage.input_tokens": 20,
         "gen_ai.usage.input_tokens.cached": 5,
@@ -1869,6 +2574,9 @@ def test_ai_client_span_responses_api(
             model="gpt-4o",
             instructions=instructions,
             input=input,
+            max_output_tokens=100,
+            temperature=0.7,
+            top_p=0.9,
         )
 
     (transaction,) = events
@@ -1880,8 +2588,12 @@ def test_ai_client_span_responses_api(
 
     expected_data = {
         "gen_ai.operation.name": "responses",
+        "gen_ai.request.max_tokens": 100,
+        "gen_ai.request.temperature": 0.7,
+        "gen_ai.request.top_p": 0.9,
         "gen_ai.system": "openai",
         "gen_ai.response.model": "response-model-id",
+        "gen_ai.response.streaming": False,
         "gen_ai.usage.input_tokens": 20,
         "gen_ai.usage.input_tokens.cached": 5,
         "gen_ai.usage.output_tokens": 10,
@@ -2171,6 +2883,9 @@ async def test_ai_client_span_responses_async_api(
             model="gpt-4o",
             instructions=instructions,
             input=input,
+            max_output_tokens=100,
+            temperature=0.7,
+            top_p=0.9,
         )
 
     (transaction,) = events
@@ -2182,9 +2897,13 @@ async def test_ai_client_span_responses_async_api(
 
     expected_data = {
         "gen_ai.operation.name": "responses",
+        "gen_ai.request.max_tokens": 100,
+        "gen_ai.request.temperature": 0.7,
+        "gen_ai.request.top_p": 0.9,
         "gen_ai.request.messages": '["How do I check if a Python object is an instance of a class?"]',
         "gen_ai.request.model": "gpt-4o",
         "gen_ai.response.model": "response-model-id",
+        "gen_ai.response.streaming": False,
         "gen_ai.system": "openai",
         "gen_ai.usage.input_tokens": 20,
         "gen_ai.usage.input_tokens.cached": 5,
@@ -2420,7 +3139,14 @@ async def test_ai_client_span_responses_async_api(
 )
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
 async def test_ai_client_span_streaming_responses_async_api(
-    sentry_init, capture_events, instructions, input, request
+    sentry_init,
+    capture_events,
+    instructions,
+    input,
+    request,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[OpenAIIntegration(include_prompts=True)],
@@ -2430,29 +3156,39 @@ async def test_ai_client_span_streaming_responses_async_api(
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(EXAMPLE_RESPONSES_STREAM)
-    client.responses._post = mock.AsyncMock(return_value=returned_stream)
+    returned_stream = get_model_response(
+        async_iterator(server_side_event_chunks(EXAMPLE_RESPONSES_STREAM))
+    )
 
-    with start_transaction(name="openai tx"):
-        result = await client.responses.create(
-            model="gpt-4o",
-            instructions=instructions,
-            input=input,
-            stream=True,
-        )
-        async for _ in result:
-            pass
+    with mock.patch.object(
+        client.responses._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            result = await client.responses.create(
+                model="gpt-4o",
+                instructions=instructions,
+                input=input,
+                stream=True,
+                max_output_tokens=100,
+                temperature=0.7,
+                top_p=0.9,
+            )
+            async for _ in result:
+                pass
 
     (transaction,) = events
-    spans = transaction["spans"]
+    spans = [span for span in transaction["spans"] if span["op"] == OP.GEN_AI_RESPONSES]
 
     assert len(spans) == 1
-    assert spans[0]["op"] == "gen_ai.responses"
     assert spans[0]["origin"] == "auto.ai.openai"
 
     expected_data = {
         "gen_ai.operation.name": "responses",
+        "gen_ai.request.max_tokens": 100,
+        "gen_ai.request.temperature": 0.7,
+        "gen_ai.request.top_p": 0.9,
         "gen_ai.response.model": "response-model-id",
         "gen_ai.response.streaming": True,
         "gen_ai.system": "openai",
@@ -2742,7 +3478,12 @@ async def test_error_in_responses_async_api(sentry_init, capture_events):
 )
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
 def test_streaming_responses_api(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[
@@ -2756,27 +3497,41 @@ def test_streaming_responses_api(
     events = capture_events()
 
     client = OpenAI(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = EXAMPLE_RESPONSES_STREAM
-    client.responses._post = mock.Mock(return_value=returned_stream)
-
-    with start_transaction(name="openai tx"):
-        response_stream = client.responses.create(
-            model="some-model",
-            input="hello",
-            stream=True,
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            EXAMPLE_RESPONSES_STREAM,
         )
+    )
+
+    with mock.patch.object(
+        client.responses._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.responses.create(
+                model="some-model",
+                input="hello",
+                stream=True,
+                max_output_tokens=100,
+                temperature=0.7,
+                top_p=0.9,
+            )
 
-        response_string = ""
-        for item in response_stream:
-            if hasattr(item, "delta"):
-                response_string += item.delta
+            response_string = ""
+            for item in response_stream:
+                if hasattr(item, "delta"):
+                    response_string += item.delta
 
     assert response_string == "hello world"
 
     (transaction,) = events
     (span,) = transaction["spans"]
     assert span["op"] == "gen_ai.responses"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "response-model-id"
 
@@ -2799,7 +3554,13 @@ def test_streaming_responses_api(
 )
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
 async def test_streaming_responses_api_async(
-    sentry_init, capture_events, send_default_pii, include_prompts
+    sentry_init,
+    capture_events,
+    send_default_pii,
+    include_prompts,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
 ):
     sentry_init(
         integrations=[
@@ -2813,27 +3574,39 @@ async def test_streaming_responses_api_async(
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(EXAMPLE_RESPONSES_STREAM)
-    client.responses._post = AsyncMock(return_value=returned_stream)
+    returned_stream = get_model_response(
+        async_iterator(server_side_event_chunks(EXAMPLE_RESPONSES_STREAM))
+    )
 
-    with start_transaction(name="openai tx"):
-        response_stream = await client.responses.create(
-            model="some-model",
-            input="hello",
-            stream=True,
-        )
+    with mock.patch.object(
+        client.responses._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.responses.create(
+                model="some-model",
+                input="hello",
+                stream=True,
+                max_output_tokens=100,
+                temperature=0.7,
+                top_p=0.9,
+            )
 
-        response_string = ""
-        async for item in response_stream:
-            if hasattr(item, "delta"):
-                response_string += item.delta
+            response_string = ""
+            async for item in response_stream:
+                if hasattr(item, "delta"):
+                    response_string += item.delta
 
     assert response_string == "hello world"
 
     (transaction,) = events
     (span,) = transaction["spans"]
     assert span["op"] == "gen_ai.responses"
+    assert span["data"][SPANDATA.GEN_AI_SYSTEM] == "openai"
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TEMPERATURE] == 0.7
+    assert span["data"][SPANDATA.GEN_AI_REQUEST_TOP_P] == 0.9
 
     assert span["data"][SPANDATA.GEN_AI_RESPONSE_MODEL] == "response-model-id"
 
@@ -2975,7 +3748,9 @@ def test_openai_message_truncation(sentry_init, capture_events):
 
 
 # noinspection PyTypeChecker
-def test_streaming_chat_completion_ttft(sentry_init, capture_events):
+def test_streaming_chat_completion_ttft(
+    sentry_init, capture_events, get_model_response, server_side_event_chunks
+):
     """
     Test that streaming chat completions capture time-to-first-token (TTFT).
     """
@@ -2986,43 +3761,54 @@ def test_streaming_chat_completion_ttft(sentry_init, capture_events):
     events = capture_events()
 
     client = OpenAI(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = [
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=0, delta=ChoiceDelta(content="Hello"), finish_reason=None
-                )
-            ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
-        ),
-        ChatCompletionChunk(
-            id="1",
-            choices=[
-                DeltaChoice(
-                    index=0, delta=ChoiceDelta(content=" world"), finish_reason="stop"
-                )
+    returned_stream = get_model_response(
+        server_side_event_chunks(
+            [
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content="Hello"),
+                            finish_reason=None,
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
+                ChatCompletionChunk(
+                    id="1",
+                    choices=[
+                        DeltaChoice(
+                            index=0,
+                            delta=ChoiceDelta(content=" world"),
+                            finish_reason="stop",
+                        )
+                    ],
+                    created=100000,
+                    model="model-id",
+                    object="chat.completion.chunk",
+                ),
             ],
-            created=100000,
-            model="model-id",
-            object="chat.completion.chunk",
+            include_event_type=False,
         ),
-    ]
-
-    client.chat.completions._post = mock.Mock(return_value=returned_stream)
+    )
 
-    with start_transaction(name="openai tx"):
-        response_stream = client.chat.completions.create(
-            model="some-model",
-            messages=[{"role": "user", "content": "Say hello"}],
-            stream=True,
-        )
-        # Consume the stream
-        for _ in response_stream:
-            pass
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "Say hello"}],
+                stream=True,
+            )
+            # Consume the stream
+            for _ in response_stream:
+                pass
 
     (tx,) = events
     span = tx["spans"][0]
@@ -3037,7 +3823,13 @@ def test_streaming_chat_completion_ttft(sentry_init, capture_events):
 
 # noinspection PyTypeChecker
 @pytest.mark.asyncio
-async def test_streaming_chat_completion_ttft_async(sentry_init, capture_events):
+async def test_streaming_chat_completion_ttft_async(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
     """
     Test that async streaming chat completions capture time-to-first-token (TTFT).
     """
@@ -3048,47 +3840,56 @@ async def test_streaming_chat_completion_ttft_async(sentry_init, capture_events)
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(
-        [
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=0, delta=ChoiceDelta(content="Hello"), finish_reason=None
-                    )
-                ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
-            ),
-            ChatCompletionChunk(
-                id="1",
-                choices=[
-                    DeltaChoice(
-                        index=0,
-                        delta=ChoiceDelta(content=" world"),
-                        finish_reason="stop",
-                    )
+    returned_stream = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content="Hello"),
+                                finish_reason=None,
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
+                    ChatCompletionChunk(
+                        id="1",
+                        choices=[
+                            DeltaChoice(
+                                index=0,
+                                delta=ChoiceDelta(content=" world"),
+                                finish_reason="stop",
+                            )
+                        ],
+                        created=100000,
+                        model="model-id",
+                        object="chat.completion.chunk",
+                    ),
                 ],
-                created=100000,
-                model="model-id",
-                object="chat.completion.chunk",
+                include_event_type=False,
             ),
-        ]
+        )
     )
 
-    client.chat.completions._post = AsyncMock(return_value=returned_stream)
-
-    with start_transaction(name="openai tx"):
-        response_stream = await client.chat.completions.create(
-            model="some-model",
-            messages=[{"role": "user", "content": "Say hello"}],
-            stream=True,
-        )
-        # Consume the stream
-        async for _ in response_stream:
-            pass
+    with mock.patch.object(
+        client.chat._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.chat.completions.create(
+                model="some-model",
+                messages=[{"role": "user", "content": "Say hello"}],
+                stream=True,
+            )
+            # Consume the stream
+            async for _ in response_stream:
+                pass
 
     (tx,) = events
     span = tx["spans"][0]
@@ -3103,7 +3904,9 @@ async def test_streaming_chat_completion_ttft_async(sentry_init, capture_events)
 
 # noinspection PyTypeChecker
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
-def test_streaming_responses_api_ttft(sentry_init, capture_events):
+def test_streaming_responses_api_ttft(
+    sentry_init, capture_events, get_model_response, server_side_event_chunks
+):
     """
     Test that streaming responses API captures time-to-first-token (TTFT).
     """
@@ -3114,19 +3917,24 @@ def test_streaming_responses_api_ttft(sentry_init, capture_events):
     events = capture_events()
 
     client = OpenAI(api_key="z")
-    returned_stream = Stream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = EXAMPLE_RESPONSES_STREAM
-    client.responses._post = mock.Mock(return_value=returned_stream)
+    returned_stream = get_model_response(
+        server_side_event_chunks(EXAMPLE_RESPONSES_STREAM)
+    )
 
-    with start_transaction(name="openai tx"):
-        response_stream = client.responses.create(
-            model="some-model",
-            input="hello",
-            stream=True,
-        )
-        # Consume the stream
-        for _ in response_stream:
-            pass
+    with mock.patch.object(
+        client.responses._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = client.responses.create(
+                model="some-model",
+                input="hello",
+                stream=True,
+            )
+            # Consume the stream
+            for _ in response_stream:
+                pass
 
     (tx,) = events
     span = tx["spans"][0]
@@ -3142,7 +3950,13 @@ def test_streaming_responses_api_ttft(sentry_init, capture_events):
 # noinspection PyTypeChecker
 @pytest.mark.asyncio
 @pytest.mark.skipif(SKIP_RESPONSES_TESTS, reason="Responses API not available")
-async def test_streaming_responses_api_ttft_async(sentry_init, capture_events):
+async def test_streaming_responses_api_ttft_async(
+    sentry_init,
+    capture_events,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
     """
     Test that async streaming responses API captures time-to-first-token (TTFT).
     """
@@ -3153,19 +3967,24 @@ async def test_streaming_responses_api_ttft_async(sentry_init, capture_events):
     events = capture_events()
 
     client = AsyncOpenAI(api_key="z")
-    returned_stream = AsyncStream(cast_to=None, response=None, client=client)
-    returned_stream._iterator = async_iterator(EXAMPLE_RESPONSES_STREAM)
-    client.responses._post = AsyncMock(return_value=returned_stream)
+    returned_stream = get_model_response(
+        async_iterator(server_side_event_chunks(EXAMPLE_RESPONSES_STREAM))
+    )
 
-    with start_transaction(name="openai tx"):
-        response_stream = await client.responses.create(
-            model="some-model",
-            input="hello",
-            stream=True,
-        )
-        # Consume the stream
-        async for _ in response_stream:
-            pass
+    with mock.patch.object(
+        client.responses._client._client,
+        "send",
+        return_value=returned_stream,
+    ):
+        with start_transaction(name="openai tx"):
+            response_stream = await client.responses.create(
+                model="some-model",
+                input="hello",
+                stream=True,
+            )
+            # Consume the stream
+            async for _ in response_stream:
+                pass
 
     (tx,) = events
     span = tx["spans"][0]
diff --git a/tests/integrations/openai_agents/test_openai_agents.py b/tests/integrations/openai_agents/test_openai_agents.py
index 1390455317..7310e86df5 100644
--- a/tests/integrations/openai_agents/test_openai_agents.py
+++ b/tests/integrations/openai_agents/test_openai_agents.py
@@ -1,24 +1,23 @@
 import asyncio
-import re
 import pytest
 from unittest.mock import MagicMock, patch
 import os
 import json
 import logging
+import httpx
 
 import sentry_sdk
 from sentry_sdk import start_span
-from sentry_sdk.consts import SPANDATA
+from sentry_sdk.consts import SPANDATA, OP
 from sentry_sdk.integrations.logging import LoggingIntegration
 from sentry_sdk.integrations.openai_agents import OpenAIAgentsIntegration
 from sentry_sdk.integrations.openai_agents.utils import _set_input_data, safe_serialize
 from sentry_sdk.utils import parse_version, package_version
 
-from openai import AsyncOpenAI
+from openai import AsyncOpenAI, InternalServerError
 from agents.models.openai_responses import OpenAIResponsesModel
 
 from unittest import mock
-from unittest.mock import AsyncMock
 
 import agents
 from agents import (
@@ -51,6 +50,7 @@
     OutputTokensDetails,
 )
 
+
 test_run_config = agents.RunConfig(tracing_disabled=True)
 
 EXAMPLE_RESPONSE = Response(
@@ -90,140 +90,6 @@
 )
 
 
-async def EXAMPLE_STREAMED_RESPONSE(*args, **kwargs):
-    yield ResponseCreatedEvent(
-        response=Response(
-            id="chat-id",
-            output=[],
-            parallel_tool_calls=False,
-            tool_choice="none",
-            tools=[],
-            created_at=10000000,
-            model="response-model-id",
-            object="response",
-        ),
-        type="response.created",
-        sequence_number=0,
-    )
-
-    yield ResponseCompletedEvent(
-        response=Response(
-            id="chat-id",
-            output=[
-                ResponseOutputMessage(
-                    id="message-id",
-                    content=[
-                        ResponseOutputText(
-                            annotations=[],
-                            text="the model response",
-                            type="output_text",
-                        ),
-                    ],
-                    role="assistant",
-                    status="completed",
-                    type="message",
-                ),
-            ],
-            parallel_tool_calls=False,
-            tool_choice="none",
-            tools=[],
-            created_at=10000000,
-            model="response-model-id",
-            object="response",
-            usage=ResponseUsage(
-                input_tokens=20,
-                input_tokens_details=InputTokensDetails(
-                    cached_tokens=5,
-                ),
-                output_tokens=10,
-                output_tokens_details=OutputTokensDetails(
-                    reasoning_tokens=8,
-                ),
-                total_tokens=30,
-            ),
-        ),
-        type="response.completed",
-        sequence_number=1,
-    )
-
-
-async def EXAMPLE_STREAMED_RESPONSE_WITH_DELTA(*args, **kwargs):
-    yield ResponseCreatedEvent(
-        response=Response(
-            id="chat-id",
-            output=[],
-            parallel_tool_calls=False,
-            tool_choice="none",
-            tools=[],
-            created_at=10000000,
-            model="response-model-id",
-            object="response",
-        ),
-        type="response.created",
-        sequence_number=0,
-    )
-
-    yield ResponseTextDeltaEvent(
-        type="response.output_text.delta",
-        item_id="message-id",
-        output_index=0,
-        content_index=0,
-        delta="Hello",
-        logprobs=[],
-        sequence_number=1,
-    )
-
-    yield ResponseTextDeltaEvent(
-        type="response.output_text.delta",
-        item_id="message-id",
-        output_index=0,
-        content_index=0,
-        delta=" world!",
-        logprobs=[],
-        sequence_number=2,
-    )
-
-    yield ResponseCompletedEvent(
-        response=Response(
-            id="chat-id",
-            output=[
-                ResponseOutputMessage(
-                    id="message-id",
-                    content=[
-                        ResponseOutputText(
-                            annotations=[],
-                            text="Hello world!",
-                            type="output_text",
-                        ),
-                    ],
-                    role="assistant",
-                    status="completed",
-                    type="message",
-                ),
-            ],
-            parallel_tool_calls=False,
-            tool_choice="none",
-            tools=[],
-            created_at=10000000,
-            model="response-model-id",
-            object="response",
-            usage=ResponseUsage(
-                input_tokens=20,
-                input_tokens_details=InputTokensDetails(
-                    cached_tokens=5,
-                ),
-                output_tokens=10,
-                output_tokens_details=OutputTokensDetails(
-                    reasoning_tokens=8,
-                ),
-                total_tokens=30,
-            ),
-        ),
-        type="response.completed",
-        sequence_number=3,
-    )
-
-
 @pytest.fixture
 def mock_usage():
     return Usage(
@@ -236,29 +102,6 @@ def mock_usage():
     )
 
 
-@pytest.fixture
-def mock_model_response(mock_usage):
-    return ModelResponse(
-        output=[
-            ResponseOutputMessage(
-                id="msg_123",
-                type="message",
-                status="completed",
-                content=[
-                    ResponseOutputText(
-                        text="Hello, how can I help you?",
-                        type="output_text",
-                        annotations=[],
-                    )
-                ],
-                role="assistant",
-            )
-        ],
-        usage=mock_usage,
-        response_id="resp_123",
-    )
-
-
 @pytest.fixture
 def test_agent():
     """Create a real Agent instance for testing."""
@@ -316,32 +159,46 @@ def test_agent_custom_model():
 
 @pytest.mark.asyncio
 async def test_agent_invocation_span_no_pii(
-    sentry_init, capture_events, test_agent, mock_model_response
+    sentry_init,
+    capture_events,
+    test_agent,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=False,
-            )
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            events = capture_events()
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=False,
+        )
 
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        events = capture_events()
+
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
-            assert result.final_output == "Hello, how can I help you?"
+        assert result is not None
+        assert result.final_output == "Hello, how can I help you?"
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     assert transaction["transaction"] == "test_agent workflow"
     assert transaction["contexts"]["trace"]["origin"] == "auto.ai.openai_agents"
@@ -450,37 +307,44 @@ async def test_agent_invocation_span(
     sentry_init,
     capture_events,
     test_agent_with_instructions,
-    mock_model_response,
+    nonstreaming_responses_model_response,
     instructions,
     input,
     request,
+    get_model_response,
 ):
     """
     Test that the integration creates spans for agent invocations.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent_with_instructions(instructions).clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                test_agent_with_instructions(instructions),
-                input,
-                run_config=test_run_config,
-            )
+        result = await agents.Runner.run(
+            agent,
+            input,
+            run_config=test_run_config,
+        )
 
-            assert result is not None
-            assert result.final_output == "Hello, how can I help you?"
+        assert result is not None
+        assert result.final_output == "Hello, how can I help you?"
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -605,35 +469,46 @@ async def test_agent_invocation_span(
 
 @pytest.mark.asyncio
 async def test_client_span_custom_model(
-    sentry_init, capture_events, test_agent_custom_model, mock_model_response
+    sentry_init,
+    capture_events,
+    test_agent_custom_model,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
     """
     Test that the integration uses the correct model name if a custom model is used.
     """
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="my-custom-model", openai_client=client)
+    agent = test_agent_custom_model.clone(model=model)
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            events = capture_events()
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            result = await agents.Runner.run(
-                test_agent_custom_model, "Test input", run_config=test_run_config
-            )
+        events = capture_events()
+
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
-            assert result.final_output == "Hello, how can I help you?"
+        assert result is not None
+        assert result.final_output == "Hello, how can I help you?"
 
     (transaction,) = events
     spans = transaction["spans"]
-    _, ai_client_span = spans
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     assert ai_client_span["description"] == "chat my-custom-model"
     assert ai_client_span["data"]["gen_ai.request.model"] == "my-custom-model"
@@ -643,36 +518,44 @@ def test_agent_invocation_span_sync_no_pii(
     sentry_init,
     capture_events,
     test_agent,
-    mock_model_response,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
     """
     Test that the integration creates spans for agent invocations.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=False,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=False,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = agents.Runner.run_sync(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        result = agents.Runner.run_sync(agent, "Test input", run_config=test_run_config)
 
-            assert result is not None
-            assert result.final_output == "Hello, how can I help you?"
+        assert result is not None
+        assert result.final_output == "Hello, how can I help you?"
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     assert transaction["transaction"] == "test_agent workflow"
     assert transaction["contexts"]["trace"]["origin"] == "auto.ai.openai_agents"
@@ -777,37 +660,44 @@ def test_agent_invocation_span_sync(
     sentry_init,
     capture_events,
     test_agent_with_instructions,
-    mock_model_response,
+    nonstreaming_responses_model_response,
     instructions,
     input,
     request,
+    get_model_response,
 ):
     """
     Test that the integration creates spans for agent invocations.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent_with_instructions(instructions).clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = agents.Runner.run_sync(
-                test_agent_with_instructions(instructions),
-                input,
-                run_config=test_run_config,
-            )
+        result = agents.Runner.run_sync(
+            agent,
+            input,
+            run_config=test_run_config,
+        )
 
-            assert result is not None
-            assert result.final_output == "Hello, how can I help you?"
+        assert result is not None
+        assert result.final_output == "Hello, how can I help you?"
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -917,85 +807,122 @@ def test_agent_invocation_span_sync(
 
 
 @pytest.mark.asyncio
-async def test_handoff_span(sentry_init, capture_events, mock_usage):
+async def test_handoff_span(sentry_init, capture_events, get_model_response):
     """
     Test that handoff spans are created when agents hand off to other agents.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4-mini", openai_client=client)
+
     # Create two simple agents with a handoff relationship
     secondary_agent = agents.Agent(
         name="secondary_agent",
         instructions="You are a secondary agent.",
-        model="gpt-4o-mini",
+        model=model,
     )
 
     primary_agent = agents.Agent(
         name="primary_agent",
         instructions="You are a primary agent that hands off to secondary agent.",
-        model="gpt-4o-mini",
+        model=model,
         handoffs=[secondary_agent],
     )
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Mock two responses:
-            # 1. Primary agent calls handoff tool
-            # 2. Secondary agent provides final response
-            handoff_response = ModelResponse(
-                output=[
-                    ResponseFunctionToolCall(
-                        id="call_handoff_123",
-                        call_id="call_handoff_123",
-                        name="transfer_to_secondary_agent",
-                        type="function_call",
-                        arguments="{}",
-                    )
-                ],
-                usage=mock_usage,
-                response_id="resp_handoff_123",
-            )
+    handoff_response = get_model_response(
+        Response(
+            id="resp_tool_123",
+            output=[
+                ResponseFunctionToolCall(
+                    id="call_handoff_123",
+                    call_id="call_handoff_123",
+                    name="transfer_to_secondary_agent",
+                    type="function_call",
+                    arguments="{}",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="I'm the specialist and I can help with that!",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=mock_usage,
-                response_id="resp_final_123",
-            )
+    final_response = get_model_response(
+        Response(
+            id="resp_final_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="I'm the specialist and I can help with that!",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            mock_get_response.side_effect = [handoff_response, final_response]
+    with patch.object(
+        primary_agent.model._client._client,
+        "send",
+        side_effect=[handoff_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+        events = capture_events()
 
-            events = capture_events()
+        result = await agents.Runner.run(
+            primary_agent,
+            "Please hand off to secondary agent",
+            run_config=test_run_config,
+        )
 
-            result = await agents.Runner.run(
-                primary_agent,
-                "Please hand off to secondary agent",
-                run_config=test_run_config,
-            )
-
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    handoff_span = spans[2]
+    handoff_span = next(span for span in spans if span.get("op") == OP.GEN_AI_HANDOFF)
 
     # Verify handoff span was created
     assert handoff_span is not None
@@ -1006,85 +933,124 @@ async def test_handoff_span(sentry_init, capture_events, mock_usage):
 
 
 @pytest.mark.asyncio
-async def test_max_turns_before_handoff_span(sentry_init, capture_events, mock_usage):
+async def test_max_turns_before_handoff_span(
+    sentry_init, capture_events, get_model_response
+):
     """
     Example raising agents.exceptions.AgentsException after the agent invocation span is complete.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4-mini", openai_client=client)
+
     # Create two simple agents with a handoff relationship
     secondary_agent = agents.Agent(
         name="secondary_agent",
         instructions="You are a secondary agent.",
-        model="gpt-4o-mini",
+        model=model,
     )
 
     primary_agent = agents.Agent(
         name="primary_agent",
         instructions="You are a primary agent that hands off to secondary agent.",
-        model="gpt-4o-mini",
+        model=model,
         handoffs=[secondary_agent],
     )
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Mock two responses:
-            # 1. Primary agent calls handoff tool
-            # 2. Secondary agent provides final response
-            handoff_response = ModelResponse(
-                output=[
-                    ResponseFunctionToolCall(
-                        id="call_handoff_123",
-                        call_id="call_handoff_123",
-                        name="transfer_to_secondary_agent",
-                        type="function_call",
-                        arguments="{}",
-                    )
-                ],
-                usage=mock_usage,
-                response_id="resp_handoff_123",
-            )
-
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="I'm the specialist and I can help with that!",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=mock_usage,
-                response_id="resp_final_123",
-            )
+    handoff_response = get_model_response(
+        Response(
+            id="resp_tool_123",
+            output=[
+                ResponseFunctionToolCall(
+                    id="call_handoff_123",
+                    call_id="call_handoff_123",
+                    name="transfer_to_secondary_agent",
+                    type="function_call",
+                    arguments="{}",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            mock_get_response.side_effect = [handoff_response, final_response]
+    final_response = get_model_response(
+        Response(
+            id="resp_final_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="I'm the specialist and I can help with that!",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    with patch.object(
+        primary_agent.model._client._client,
+        "send",
+        side_effect=[handoff_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            with pytest.raises(MaxTurnsExceeded):
-                await agents.Runner.run(
-                    primary_agent,
-                    "Please hand off to secondary agent",
-                    run_config=test_run_config,
-                    max_turns=1,
-                )
+        with pytest.raises(MaxTurnsExceeded):
+            await agents.Runner.run(
+                primary_agent,
+                "Please hand off to secondary agent",
+                run_config=test_run_config,
+                max_turns=1,
+            )
 
     (error, transaction) = events
     spans = transaction["spans"]
-    handoff_span = spans[2]
+    handoff_span = next(span for span in spans if span.get("op") == OP.GEN_AI_HANDOFF)
 
     # Verify handoff span was created
     assert handoff_span is not None
@@ -1095,7 +1061,13 @@ async def test_max_turns_before_handoff_span(sentry_init, capture_events, mock_u
 
 
 @pytest.mark.asyncio
-async def test_tool_execution_span(sentry_init, capture_events, test_agent):
+async def test_tool_execution_span(
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
+    responses_tool_call_model_responses,
+):
     """
     Test tool execution span creation.
     """
@@ -1106,97 +1078,96 @@ def simple_test_tool(message: str) -> str:
         return f"Tool executed with: {message}"
 
     # Create agent with the tool
-    agent_with_tool = test_agent.clone(tools=[simple_test_tool])
-
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a mock response that includes tool calls
-            tool_call = ResponseFunctionToolCall(
-                id="call_123",
-                call_id="call_123",
-                name="simple_test_tool",
-                type="function_call",
-                arguments='{"message": "hello"}',
-            )
-
-            # First response with tool call
-            tool_response = ModelResponse(
-                output=[tool_call],
-                usage=Usage(
-                    requests=1, input_tokens=10, output_tokens=5, total_tokens=15
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent_with_tool = test_agent.clone(tools=[simple_test_tool], model=model)
+
+    responses = responses_tool_call_model_responses(
+        tool_name="simple_test_tool",
+        arguments='{"message": "hello"}',
+        response_model="gpt-4",
+        response_text="Task completed using the tool",
+        response_ids=iter(["resp_tool_123", "resp_final_123"]),
+        usages=iter(
+            [
+                ResponseUsage(
+                    input_tokens=10,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=5,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=15,
                 ),
-                response_id="resp_tool_123",
-            )
-
-            # Second response with final answer
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="Task completed using the tool",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1, input_tokens=15, output_tokens=10, total_tokens=25
+                ResponseUsage(
+                    input_tokens=15,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=10,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=25,
                 ),
-                response_id="resp_final_123",
-            )
-
-            # Return different responses on successive calls
-            mock_get_response.side_effect = [tool_response, final_response]
+            ]
+        ),
+    )
+    tool_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+    )
+    final_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent_with_tool.model._client._client,
+        "send",
+        side_effect=[tool_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            await agents.Runner.run(
-                agent_with_tool,
-                "Please use the simple test tool",
-                run_config=test_run_config,
-            )
+        await agents.Runner.run(
+            agent_with_tool,
+            "Please use the simple test tool",
+            run_config=test_run_config,
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
-    (
-        agent_span,
-        ai_client_span1,
-        tool_span,
-        ai_client_span2,
-    ) = spans
+    agent_span = next(span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT)
+    ai_client_span1, ai_client_span2 = (
+        span for span in spans if span["op"] == OP.GEN_AI_CHAT
+    )
+    tool_span = next(span for span in spans if span["op"] == OP.GEN_AI_EXECUTE_TOOL)
+
+    available_tool = {
+        "name": "simple_test_tool",
+        "description": "A simple tool",
+        "params_json_schema": {
+            "properties": {"message": {"title": "Message", "type": "string"}},
+            "required": ["message"],
+            "title": "simple_test_tool_args",
+            "type": "object",
+            "additionalProperties": False,
+        },
+        "on_invoke_tool": mock.ANY,
+        "strict_json_schema": True,
+        "is_enabled": True,
+    }
 
-    available_tools = [
-        {
-            "name": "simple_test_tool",
-            "description": "A simple tool",
-            "params_json_schema": {
-                "properties": {"message": {"title": "Message", "type": "string"}},
-                "required": ["message"],
-                "title": "simple_test_tool_args",
-                "type": "object",
-                "additionalProperties": False,
-            },
-            "on_invoke_tool": "<function agents.tool.function_tool.<locals>._create_function_tool.<locals>._on_invoke_tool>",
-            "strict_json_schema": True,
-            "is_enabled": True,
-        }
-    ]
     if parse_version(OPENAI_AGENTS_VERSION) >= (0, 3, 3):
-        available_tools[0].update(
+        available_tool.update(
             {"tool_input_guardrails": None, "tool_output_guardrails": None}
         )
 
@@ -1204,13 +1175,13 @@ def simple_test_tool(message: str) -> str:
         0,
         8,
     ):
-        available_tools[0]["needs_approval"] = False
+        available_tool["needs_approval"] = False
     if parse_version(OPENAI_AGENTS_VERSION) >= (
         0,
         9,
         0,
     ):
-        available_tools[0].update(
+        available_tool.update(
             {
                 "timeout_seconds": None,
                 "timeout_behavior": "error_as_result",
@@ -1218,8 +1189,6 @@ def simple_test_tool(message: str) -> str:
             }
         )
 
-    available_tools = safe_serialize(available_tools)
-
     assert transaction["transaction"] == "test_agent workflow"
     assert transaction["contexts"]["trace"]["origin"] == "auto.ai.openai_agents"
 
@@ -1227,7 +1196,12 @@ def simple_test_tool(message: str) -> str:
     assert agent_span["origin"] == "auto.ai.openai_agents"
     assert agent_span["data"]["gen_ai.agent.name"] == "test_agent"
     assert agent_span["data"]["gen_ai.operation.name"] == "invoke_agent"
-    assert agent_span["data"]["gen_ai.request.available_tools"] == available_tools
+
+    agent_span_available_tool = json.loads(
+        agent_span["data"]["gen_ai.request.available_tools"]
+    )[0]
+    assert all(agent_span_available_tool[k] == v for k, v in available_tool.items())
+
     assert agent_span["data"]["gen_ai.request.max_tokens"] == 100
     assert agent_span["data"]["gen_ai.request.model"] == "gpt-4"
     assert agent_span["data"]["gen_ai.request.temperature"] == 0.7
@@ -1238,7 +1212,14 @@ def simple_test_tool(message: str) -> str:
     assert ai_client_span1["data"]["gen_ai.operation.name"] == "chat"
     assert ai_client_span1["data"]["gen_ai.system"] == "openai"
     assert ai_client_span1["data"]["gen_ai.agent.name"] == "test_agent"
-    assert ai_client_span1["data"]["gen_ai.request.available_tools"] == available_tools
+
+    ai_client_span1_available_tool = json.loads(
+        ai_client_span1["data"]["gen_ai.request.available_tools"]
+    )[0]
+    assert all(
+        ai_client_span1_available_tool[k] == v for k, v in available_tool.items()
+    )
+
     assert ai_client_span1["data"]["gen_ai.request.max_tokens"] == 100
     assert ai_client_span1["data"]["gen_ai.request.messages"] == safe_serialize(
         [
@@ -1278,14 +1259,12 @@ def simple_test_tool(message: str) -> str:
     assert tool_span["description"] == "execute_tool simple_test_tool"
     assert tool_span["data"]["gen_ai.agent.name"] == "test_agent"
     assert tool_span["data"]["gen_ai.operation.name"] == "execute_tool"
-    assert (
-        re.sub(
-            "<.*>(,)",
-            r"'NOT_CHECKED'\1",
-            agent_span["data"]["gen_ai.request.available_tools"],
-        )
-        == available_tools
-    )
+
+    tool_span_available_tool = json.loads(
+        tool_span["data"]["gen_ai.request.available_tools"]
+    )[0]
+    assert all(tool_span_available_tool[k] == v for k, v in available_tool.items())
+
     assert tool_span["data"]["gen_ai.request.max_tokens"] == 100
     assert tool_span["data"]["gen_ai.request.model"] == "gpt-4"
     assert tool_span["data"]["gen_ai.request.temperature"] == 0.7
@@ -1295,19 +1274,17 @@ def simple_test_tool(message: str) -> str:
     assert tool_span["data"]["gen_ai.tool.input"] == '{"message": "hello"}'
     assert tool_span["data"]["gen_ai.tool.name"] == "simple_test_tool"
     assert tool_span["data"]["gen_ai.tool.output"] == "Tool executed with: hello"
-    assert tool_span["data"]["gen_ai.tool.type"] == "function"
-
     assert ai_client_span2["description"] == "chat gpt-4"
     assert ai_client_span2["data"]["gen_ai.agent.name"] == "test_agent"
     assert ai_client_span2["data"]["gen_ai.operation.name"] == "chat"
-    assert (
-        re.sub(
-            "<.*>(,)",
-            r"'NOT_CHECKED'\1",
-            agent_span["data"]["gen_ai.request.available_tools"],
-        )
-        == available_tools
+
+    ai_client_span2_available_tool = json.loads(
+        ai_client_span2["data"]["gen_ai.request.available_tools"]
+    )[0]
+    assert all(
+        ai_client_span2_available_tool[k] == v for k, v in available_tool.items()
     )
+
     assert ai_client_span2["data"]["gen_ai.request.max_tokens"] == 100
     assert ai_client_span2["data"]["gen_ai.request.messages"] == safe_serialize(
         [
@@ -1339,7 +1316,13 @@ def simple_test_tool(message: str) -> str:
 
 
 @pytest.mark.asyncio
-async def test_hosted_mcp_tool_propagation_header_streamed(sentry_init, test_agent):
+async def test_hosted_mcp_tool_propagation_header_streamed(
+    sentry_init,
+    test_agent,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
     """
     Test responses API is given trace propagation headers with HostedMCPTool.
     """
@@ -1356,7 +1339,6 @@ async def test_hosted_mcp_tool_propagation_header_streamed(sentry_init, test_age
     )
 
     client = AsyncOpenAI(api_key="z")
-    client.responses._post = AsyncMock(return_value=EXAMPLE_RESPONSE)
 
     model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
 
@@ -1371,10 +1353,84 @@ async def test_hosted_mcp_tool_propagation_header_streamed(sentry_init, test_age
         release="d08ebdb9309e1b004c6f52202de58a09c2268e42",
     )
 
+    request_headers = {}
+    # openai-agents calls with_streaming_response() if available starting with
+    # https://github.com/openai/openai-agents-python/commit/159beb56130f7d85192acfd593c9168757984dc0.
+    # When using with_streaming_response() the header set below changes the response type:
+    # https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/_response.py#L67.
+    if parse_version(OPENAI_AGENTS_VERSION) >= (0, 10, 3) and hasattr(
+        agent_with_tool.model._client.responses, "with_streaming_response"
+    ):
+        request_headers["X-Stainless-Raw-Response"] = "stream"
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ResponseCreatedEvent(
+                        response=Response(
+                            id="chat-id",
+                            output=[],
+                            parallel_tool_calls=False,
+                            tool_choice="none",
+                            tools=[],
+                            created_at=10000000,
+                            model="response-model-id",
+                            object="response",
+                        ),
+                        type="response.created",
+                        sequence_number=0,
+                    ),
+                    ResponseCompletedEvent(
+                        response=Response(
+                            id="chat-id",
+                            output=[
+                                ResponseOutputMessage(
+                                    id="message-id",
+                                    content=[
+                                        ResponseOutputText(
+                                            annotations=[],
+                                            text="the model response",
+                                            type="output_text",
+                                        ),
+                                    ],
+                                    role="assistant",
+                                    status="completed",
+                                    type="message",
+                                ),
+                            ],
+                            parallel_tool_calls=False,
+                            tool_choice="none",
+                            tools=[],
+                            created_at=10000000,
+                            model="response-model-id",
+                            object="response",
+                            usage=ResponseUsage(
+                                input_tokens=20,
+                                input_tokens_details=InputTokensDetails(
+                                    cached_tokens=5,
+                                ),
+                                output_tokens=10,
+                                output_tokens_details=OutputTokensDetails(
+                                    reasoning_tokens=8,
+                                ),
+                                total_tokens=30,
+                            ),
+                        ),
+                        type="response.completed",
+                        sequence_number=1,
+                    ),
+                ]
+            )
+        ),
+        request_headers=request_headers,
+    )
+
+    # Patching https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/_base_client.py#L1604
     with patch.object(
-        model._client.responses,
-        "create",
-        side_effect=EXAMPLE_STREAMED_RESPONSE,
+        agent_with_tool.model._client._client,
+        "send",
+        return_value=response,
     ) as create, mock.patch(
         "sentry_sdk.tracing_utils.Random.randrange", return_value=500000
     ):
@@ -1392,13 +1448,17 @@ async def test_hosted_mcp_tool_propagation_header_streamed(sentry_init, test_age
             async for event in result.stream_events():
                 pass
 
-            ai_client_span = transaction._span_recorder.spans[-1]
+            ai_client_span = next(
+                span
+                for span in transaction._span_recorder.spans
+                if span.op == OP.GEN_AI_CHAT
+            )
 
         args, kwargs = create.call_args
 
-        assert "tools" in kwargs
-        assert len(kwargs["tools"]) == 1
-        hosted_mcp_tool = kwargs["tools"][0]
+        request = args[0]
+        body = json.loads(request.content.decode("utf-8"))
+        hosted_mcp_tool = body["tools"][0]
 
         assert hosted_mcp_tool["headers"][
             "sentry-trace"
@@ -1423,7 +1483,9 @@ async def test_hosted_mcp_tool_propagation_header_streamed(sentry_init, test_age
 
 
 @pytest.mark.asyncio
-async def test_hosted_mcp_tool_propagation_headers(sentry_init, test_agent):
+async def test_hosted_mcp_tool_propagation_headers(
+    sentry_init, test_agent, get_model_response
+):
     """
     Test responses API is given trace propagation headers with HostedMCPTool.
     """
@@ -1439,9 +1501,7 @@ async def test_hosted_mcp_tool_propagation_headers(sentry_init, test_agent):
         },
     )
 
-    client = AsyncOpenAI(api_key="z")
-    client.responses._post = AsyncMock(return_value=EXAMPLE_RESPONSE)
-
+    client = AsyncOpenAI(api_key="test-key")
     model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
 
     agent_with_tool = test_agent.clone(
@@ -1455,11 +1515,13 @@ async def test_hosted_mcp_tool_propagation_headers(sentry_init, test_agent):
         release="d08ebdb9309e1b004c6f52202de58a09c2268e42",
     )
 
+    response = get_model_response(EXAMPLE_RESPONSE, serialize_pydantic=True)
+
     with patch.object(
-        model._client.responses,
-        "create",
-        wraps=model._client.responses.create,
-    ) as create, mock.patch(
+        agent_with_tool.model._client._client,
+        "send",
+        return_value=response,
+    ) as send, mock.patch(
         "sentry_sdk.tracing_utils.Random.randrange", return_value=500000
     ):
         with sentry_sdk.start_transaction(
@@ -1473,13 +1535,17 @@ async def test_hosted_mcp_tool_propagation_headers(sentry_init, test_agent):
                 run_config=test_run_config,
             )
 
-            ai_client_span = transaction._span_recorder.spans[-1]
+            ai_client_span = next(
+                span
+                for span in transaction._span_recorder.spans
+                if span.op == OP.GEN_AI_CHAT
+            )
 
-        args, kwargs = create.call_args
+        args, kwargs = send.call_args
 
-        assert "tools" in kwargs
-        assert len(kwargs["tools"]) == 1
-        hosted_mcp_tool = kwargs["tools"][0]
+        request = args[0]
+        body = json.loads(request.content.decode("utf-8"))
+        hosted_mcp_tool = body["tools"][0]
 
         assert hosted_mcp_tool["headers"][
             "sentry-trace"
@@ -1631,35 +1697,46 @@ async def test_error_captures_input_data(sentry_init, capture_events, test_agent
     Test that input data is captured even when the API call raises an exception.
     This verifies that _set_input_data is called before the API call.
     """
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.side_effect = Exception("API Error")
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-            sentry_init(
-                integrations=[
-                    OpenAIAgentsIntegration(),
-                    LoggingIntegration(event_level=logging.CRITICAL),
-                ],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    model_request = httpx.Request(
+        "POST",
+        "/responses",
+    )
 
-            events = capture_events()
+    response = httpx.Response(
+        500,
+        request=model_request,
+    )
 
-            with pytest.raises(Exception, match="API Error"):
-                await agents.Runner.run(
-                    test_agent, "Test input", run_config=test_run_config
-                )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[
+                OpenAIAgentsIntegration(),
+                LoggingIntegration(event_level=logging.CRITICAL),
+            ],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
+
+        events = capture_events()
+
+        with pytest.raises(InternalServerError, match="Error code: 500"):
+            await agents.Runner.run(agent, "Test input", run_config=test_run_config)
 
     (
         error_event,
         transaction,
     ) = events
 
-    assert error_event["exception"]["values"][0]["type"] == "Exception"
-    assert error_event["exception"]["values"][0]["value"] == "API Error"
+    assert error_event["exception"]["values"][0]["type"] == "InternalServerError"
+    assert error_event["exception"]["values"][0]["value"] == "Error code: 500"
 
     spans = transaction["spans"]
     ai_client_span = [s for s in spans if s["op"] == "gen_ai.chat"][0]
@@ -1708,79 +1785,108 @@ async def test_span_status_error(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_mcp_tool_execution_spans(sentry_init, capture_events, test_agent):
+async def test_mcp_tool_execution_spans(
+    sentry_init, capture_events, test_agent, get_model_response
+):
     """
     Test that MCP (Model Context Protocol) tool calls create execute_tool spans.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a McpCall object
-            mcp_call = McpCall(
-                id="mcp_call_123",
-                name="test_mcp_tool",
-                arguments='{"query": "search term"}',
-                output="MCP tool executed successfully",
-                error=None,
-                type="mcp_call",
-                server_label="test_server",
-            )
-
-            # Create a ModelResponse with an McpCall in the output
-            mcp_response = ModelResponse(
-                output=[mcp_call],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=10,
-                    output_tokens=5,
-                    total_tokens=15,
+    mcp_response = get_model_response(
+        Response(
+            id="resp_mcp_123",
+            output=[
+                McpCall(
+                    id="mcp_call_123",
+                    name="test_mcp_tool",
+                    arguments='{"query": "search term"}',
+                    output="MCP tool executed successfully",
+                    error=None,
+                    type="mcp_call",
+                    server_label="test_server",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
                 ),
-                response_id="resp_mcp_123",
-            )
-
-            # Final response after MCP tool execution
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="Task completed using MCP tool",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=15,
-                    output_tokens=10,
-                    total_tokens=25,
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
                 ),
-                response_id="resp_final_123",
-            )
-
-            mock_get_response.side_effect = [mcp_response, final_response]
-
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
-
-            events = capture_events()
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            await agents.Runner.run(
-                test_agent,
-                "Please use MCP tool",
-                run_config=test_run_config,
-            )
+    final_response = get_model_response(
+        Response(
+            id="resp_final_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="Task completed using MCP tool",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=15,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=10,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
+                ),
+                total_tokens=25,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
+
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        side_effect=[mcp_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
+
+        events = capture_events()
+
+        await agents.Runner.run(
+            agent,
+            "Please use MCP tool",
+            run_config=test_run_config,
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -1788,17 +1894,13 @@ async def test_mcp_tool_execution_spans(sentry_init, capture_events, test_agent)
     # Find the MCP execute_tool span
     mcp_tool_span = None
     for span in spans:
-        if (
-            span.get("description") == "execute_tool test_mcp_tool"
-            and span.get("data", {}).get("gen_ai.tool.type") == "mcp"
-        ):
+        if span.get("description") == "execute_tool test_mcp_tool":
             mcp_tool_span = span
             break
 
     # Verify the MCP tool span was created
     assert mcp_tool_span is not None, "MCP execute_tool span was not created"
     assert mcp_tool_span["description"] == "execute_tool test_mcp_tool"
-    assert mcp_tool_span["data"]["gen_ai.tool.type"] == "mcp"
     assert mcp_tool_span["data"]["gen_ai.tool.name"] == "test_mcp_tool"
     assert mcp_tool_span["data"]["gen_ai.tool.input"] == '{"query": "search term"}'
     assert (
@@ -1811,79 +1913,108 @@ async def test_mcp_tool_execution_spans(sentry_init, capture_events, test_agent)
 
 
 @pytest.mark.asyncio
-async def test_mcp_tool_execution_with_error(sentry_init, capture_events, test_agent):
+async def test_mcp_tool_execution_with_error(
+    sentry_init, capture_events, test_agent, get_model_response
+):
     """
     Test that MCP tool calls with errors are tracked with error status.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a McpCall object with an error
-            mcp_call_with_error = McpCall(
-                id="mcp_call_error_123",
-                name="failing_mcp_tool",
-                arguments='{"query": "test"}',
-                output=None,
-                error="MCP tool execution failed",
-                type="mcp_call",
-                server_label="test_server",
-            )
-
-            # Create a ModelResponse with a failing McpCall
-            mcp_response = ModelResponse(
-                output=[mcp_call_with_error],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=10,
-                    output_tokens=5,
-                    total_tokens=15,
+    mcp_response = get_model_response(
+        Response(
+            id="resp_mcp_123",
+            output=[
+                McpCall(
+                    id="mcp_call_error_123",
+                    name="failing_mcp_tool",
+                    arguments='{"query": "test"}',
+                    output=None,
+                    error="MCP tool execution failed",
+                    type="mcp_call",
+                    server_label="test_server",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
                 ),
-                response_id="resp_mcp_error_123",
-            )
-
-            # Final response after error
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="The MCP tool encountered an error",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=15,
-                    output_tokens=10,
-                    total_tokens=25,
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
                 ),
-                response_id="resp_final_error_123",
-            )
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            mock_get_response.side_effect = [mcp_response, final_response]
+    final_response = get_model_response(
+        Response(
+            id="resp_final_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="Task completed using MCP tool",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=15,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=10,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
+                ),
+                total_tokens=25,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        side_effect=[mcp_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            await agents.Runner.run(
-                test_agent,
-                "Please use failing MCP tool",
-                run_config=test_run_config,
-            )
+        await agents.Runner.run(
+            agent,
+            "Please use failing MCP tool",
+            run_config=test_run_config,
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -1891,17 +2022,13 @@ async def test_mcp_tool_execution_with_error(sentry_init, capture_events, test_a
     # Find the MCP execute_tool span with error
     mcp_tool_span = None
     for span in spans:
-        if (
-            span.get("description") == "execute_tool failing_mcp_tool"
-            and span.get("data", {}).get("gen_ai.tool.type") == "mcp"
-        ):
+        if span.get("description") == "execute_tool failing_mcp_tool":
             mcp_tool_span = span
             break
 
     # Verify the MCP tool span was created with error status
     assert mcp_tool_span is not None, "MCP execute_tool span was not created"
     assert mcp_tool_span["description"] == "execute_tool failing_mcp_tool"
-    assert mcp_tool_span["data"]["gen_ai.tool.type"] == "mcp"
     assert mcp_tool_span["data"]["gen_ai.tool.name"] == "failing_mcp_tool"
     assert mcp_tool_span["data"]["gen_ai.tool.input"] == '{"query": "test"}'
     assert mcp_tool_span["data"]["gen_ai.tool.output"] is None
@@ -1912,79 +2039,108 @@ async def test_mcp_tool_execution_with_error(sentry_init, capture_events, test_a
 
 
 @pytest.mark.asyncio
-async def test_mcp_tool_execution_without_pii(sentry_init, capture_events, test_agent):
+async def test_mcp_tool_execution_without_pii(
+    sentry_init, capture_events, test_agent, get_model_response
+):
     """
     Test that MCP tool input/output are not included when send_default_pii is False.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a McpCall object
-            mcp_call = McpCall(
-                id="mcp_call_pii_123",
-                name="test_mcp_tool",
-                arguments='{"query": "sensitive data"}',
-                output="Result with sensitive info",
-                error=None,
-                type="mcp_call",
-                server_label="test_server",
-            )
-
-            # Create a ModelResponse with an McpCall
-            mcp_response = ModelResponse(
-                output=[mcp_call],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=10,
-                    output_tokens=5,
-                    total_tokens=15,
+    mcp_response = get_model_response(
+        Response(
+            id="resp_mcp_123",
+            output=[
+                McpCall(
+                    id="mcp_call_pii_123",
+                    name="test_mcp_tool",
+                    arguments='{"query": "sensitive data"}',
+                    output="Result with sensitive info",
+                    error=None,
+                    type="mcp_call",
+                    server_label="test_server",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
                 ),
-                response_id="resp_mcp_123",
-            )
-
-            # Final response
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="Task completed",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=15,
-                    output_tokens=10,
-                    total_tokens=25,
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
                 ),
-                response_id="resp_final_123",
-            )
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            mock_get_response.side_effect = [mcp_response, final_response]
+    final_response = get_model_response(
+        Response(
+            id="resp_final_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="Task completed",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=15,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=10,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=25,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=False,  # PII disabled
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        side_effect=[mcp_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=False,  # PII disabled
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            await agents.Runner.run(
-                test_agent,
-                "Please use MCP tool",
-                run_config=test_run_config,
-            )
+        await agents.Runner.run(
+            agent,
+            "Please use MCP tool",
+            run_config=test_run_config,
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -1992,17 +2148,13 @@ async def test_mcp_tool_execution_without_pii(sentry_init, capture_events, test_
     # Find the MCP execute_tool span
     mcp_tool_span = None
     for span in spans:
-        if (
-            span.get("description") == "execute_tool test_mcp_tool"
-            and span.get("data", {}).get("gen_ai.tool.type") == "mcp"
-        ):
+        if span.get("description") == "execute_tool test_mcp_tool":
             mcp_tool_span = span
             break
 
     # Verify the MCP tool span was created but without input/output
     assert mcp_tool_span is not None, "MCP execute_tool span was not created"
     assert mcp_tool_span["description"] == "execute_tool test_mcp_tool"
-    assert mcp_tool_span["data"]["gen_ai.tool.type"] == "mcp"
     assert mcp_tool_span["data"]["gen_ai.tool.name"] == "test_mcp_tool"
 
     # Verify input and output are not included when send_default_pii is False
@@ -2012,34 +2164,44 @@ async def test_mcp_tool_execution_without_pii(sentry_init, capture_events, test_
 
 @pytest.mark.asyncio
 async def test_multiple_agents_asyncio(
-    sentry_init, capture_events, test_agent, mock_model_response
+    sentry_init,
+    capture_events,
+    test_agent,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
     """
     Test that multiple agents can be run at the same time in asyncio tasks
     without interfering with each other.
     """
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            async def run():
-                await agents.Runner.run(
-                    starting_agent=test_agent,
-                    input="Test input",
-                    run_config=test_run_config,
-                )
+        async def run():
+            await agents.Runner.run(
+                starting_agent=agent,
+                input="Test input",
+                run_config=test_run_config,
+            )
 
-            await asyncio.gather(*[run() for _ in range(3)])
+        await asyncio.gather(*[run() for _ in range(3)])
 
     assert len(events) == 3
     txn1, txn2, txn3 = events
@@ -2095,7 +2257,13 @@ def test_openai_agents_message_role_mapping(
 
 
 @pytest.mark.asyncio
-async def test_tool_execution_error_tracing(sentry_init, capture_events, test_agent):
+async def test_tool_execution_error_tracing(
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
+    responses_tool_call_model_responses,
+):
     """
     Test that tool execution errors are properly tracked via error tracing patch.
 
@@ -2113,70 +2281,72 @@ def failing_tool(message: str) -> str:
         raise ValueError("Tool execution failed")
 
     # Create agent with the failing tool
-    agent_with_tool = test_agent.clone(tools=[failing_tool])
-
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a mock response that includes tool call
-            tool_call = ResponseFunctionToolCall(
-                id="call_123",
-                call_id="call_123",
-                name="failing_tool",
-                type="function_call",
-                arguments='{"message": "test"}',
-            )
-
-            # First response with tool call
-            tool_response = ModelResponse(
-                output=[tool_call],
-                usage=Usage(
-                    requests=1, input_tokens=10, output_tokens=5, total_tokens=15
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent_with_tool = test_agent.clone(tools=[failing_tool], model=model)
+
+    responses = responses_tool_call_model_responses(
+        tool_name="failing_tool",
+        arguments='{"message": "test"}',
+        response_model="gpt-4-0613",
+        response_text="An error occurred while running the tool",
+        response_ids=iter(["resp_1", "resp_2"]),
+        usages=iter(
+            [
+                ResponseUsage(
+                    input_tokens=10,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=5,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=15,
                 ),
-                response_id="resp_tool_123",
-            )
-
-            # Second response after tool error (agents library handles the error and continues)
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="An error occurred while running the tool",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1, input_tokens=15, output_tokens=10, total_tokens=25
+                ResponseUsage(
+                    input_tokens=15,
+                    input_tokens_details=InputTokensDetails(
+                        cached_tokens=0,
+                    ),
+                    output_tokens=10,
+                    output_tokens_details=OutputTokensDetails(
+                        reasoning_tokens=0,
+                    ),
+                    total_tokens=25,
                 ),
-                response_id="resp_final_123",
-            )
-
-            mock_get_response.side_effect = [tool_response, final_response]
+            ]
+        ),
+    )
+    tool_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+    )
+    final_response = get_model_response(
+        next(responses),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent_with_tool.model._client._client,
+        "send",
+        side_effect=[tool_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            # Note: The agents library catches tool exceptions internally,
-            # so we don't expect this to raise
-            await agents.Runner.run(
-                agent_with_tool,
-                "Please use the failing tool",
-                run_config=test_run_config,
-            )
+        # Note: The agents library catches tool exceptions internally,
+        # so we don't expect this to raise
+        await agents.Runner.run(
+            agent_with_tool,
+            "Please use the failing tool",
+            run_config=test_run_config,
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -2184,7 +2354,10 @@ def failing_tool(message: str) -> str:
     # Find the execute_tool span
     execute_tool_span = None
     for span in spans:
-        if span.get("description", "").startswith("execute_tool failing_tool"):
+        description = span.get("description", "")
+        if description is not None and description.startswith(
+            "execute_tool failing_tool"
+        ):
             execute_tool_span = span
             break
 
@@ -2201,56 +2374,82 @@ def failing_tool(message: str) -> str:
 
 @pytest.mark.asyncio
 async def test_invoke_agent_span_includes_usage_data(
-    sentry_init, capture_events, test_agent, mock_usage
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
 ):
     """
     Test that invoke_agent spans include aggregated usage data from context_wrapper.
     This verifies the new functionality added to track token usage in invoke_agent spans.
     """
+    client = AsyncOpenAI(api_key="z")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # Create a response with usage data
-            response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_123",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="Response with usage",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=mock_usage,
-                response_id="resp_123",
-            )
-            mock_get_response.return_value = response
+    response = get_model_response(
+        Response(
+            id="resp_123",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_123",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="Response with usage",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
 
     # Verify invoke_agent span has usage data from context_wrapper
     assert invoke_agent_span["description"] == "invoke_agent test_agent"
@@ -2258,7 +2457,6 @@ async def test_invoke_agent_span_includes_usage_data(
     assert "gen_ai.usage.output_tokens" in invoke_agent_span["data"]
     assert "gen_ai.usage.total_tokens" in invoke_agent_span["data"]
 
-    # The usage should match the mock_usage values (aggregated across all calls)
     assert invoke_agent_span["data"]["gen_ai.usage.input_tokens"] == 10
     assert invoke_agent_span["data"]["gen_ai.usage.output_tokens"] == 20
     assert invoke_agent_span["data"]["gen_ai.usage.total_tokens"] == 30
@@ -2268,23 +2466,23 @@ async def test_invoke_agent_span_includes_usage_data(
 
 @pytest.mark.asyncio
 async def test_ai_client_span_includes_response_model(
-    sentry_init, capture_events, test_agent
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
 ):
     """
     Test that ai_client spans (gen_ai.chat) include the response model from the actual API response.
     This verifies we capture the actual model used (which may differ from the requested model).
     """
+    client = AsyncOpenAI(api_key="z")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        # Mock the _fetch_response method to return a response with a model field
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel._fetch_response"
-        ) as mock_fetch_response:
-            # Create a mock OpenAI Response object with a specific model version
-            mock_response = MagicMock()
-            mock_response.model = "gpt-4.1-2025-04-14"  # The actual response model
-            mock_response.id = "resp_123"
-            mock_response.output = [
+    response = get_model_response(
+        Response(
+            id="resp_123",
+            output=[
                 ResponseOutputMessage(
                     id="msg_123",
                     type="message",
@@ -2298,37 +2496,50 @@ async def test_ai_client_span_includes_response_model(
                     ],
                     role="assistant",
                 )
-            ]
-            mock_response.usage = MagicMock()
-            mock_response.usage.input_tokens = 10
-            mock_response.usage.output_tokens = 20
-            mock_response.usage.total_tokens = 30
-            mock_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=0
-            )
-            mock_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=5
-            )
-
-            mock_fetch_response.return_value = mock_response
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    _, ai_client_span = spans
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     # Verify ai_client span has response model from API response
     assert ai_client_span["description"] == "chat gpt-4"
@@ -2338,29 +2549,28 @@ async def test_ai_client_span_includes_response_model(
 
 @pytest.mark.asyncio
 async def test_ai_client_span_response_model_with_chat_completions(
-    sentry_init, capture_events
+    sentry_init,
+    capture_events,
+    get_model_response,
 ):
     """
     Test that response model is captured when using ChatCompletions API (not Responses API).
     This ensures our implementation works with different OpenAI model types.
     """
     # Create agent that uses ChatCompletions model
+    client = AsyncOpenAI(api_key="z")
+    model = OpenAIResponsesModel(model="gpt-4o-mini", openai_client=client)
+
     agent = Agent(
         name="chat_completions_agent",
         instructions="Test agent using ChatCompletions",
-        model="gpt-4o-mini",
+        model=model,
     )
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        # Mock the _fetch_response method
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel._fetch_response"
-        ) as mock_fetch_response:
-            # Create a mock Response object
-            mock_response = MagicMock()
-            mock_response.model = "gpt-4o-mini-2024-07-18"
-            mock_response.id = "resp_123"
-            mock_response.output = [
+    response = get_model_response(
+        Response(
+            id="resp_123",
+            output=[
                 ResponseOutputMessage(
                     id="msg_123",
                     type="message",
@@ -2374,36 +2584,49 @@ async def test_ai_client_span_response_model_with_chat_completions(
                     ],
                     role="assistant",
                 )
-            ]
-            mock_response.usage = MagicMock()
-            mock_response.usage.input_tokens = 15
-            mock_response.usage.output_tokens = 25
-            mock_response.usage.total_tokens = 40
-            mock_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=0
-            )
-            mock_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=0
-            )
-
-            mock_fetch_response.return_value = mock_response
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4o-mini-2024-07-18",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=15,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=25,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=40,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                agent, "Test input", run_config=test_run_config
-            )
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    _, ai_client_span = spans
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     # Verify response model from API response is captured
     assert "gen_ai.response.model" in ai_client_span["data"]
@@ -2412,7 +2635,7 @@ async def test_ai_client_span_response_model_with_chat_completions(
 
 @pytest.mark.asyncio
 async def test_multiple_llm_calls_aggregate_usage(
-    sentry_init, capture_events, test_agent
+    sentry_init, capture_events, test_agent, get_model_response
 ):
     """
     Test that invoke_agent spans show aggregated usage across multiple LLM calls
@@ -2424,181 +2647,136 @@ def calculator(a: int, b: int) -> int:
         """Add two numbers"""
         return a + b
 
-    agent_with_tool = test_agent.clone(tools=[calculator])
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent_with_tool = test_agent.clone(tools=[calculator], model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            # First call: agent decides to use tool (10 input, 5 output tokens)
-            tool_call_response = ModelResponse(
-                output=[
-                    ResponseFunctionToolCall(
-                        id="call_123",
-                        call_id="call_123",
-                        name="calculator",
-                        type="function_call",
-                        arguments='{"a": 5, "b": 3}',
-                    )
-                ],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=10,
-                    output_tokens=5,
-                    total_tokens=15,
-                    input_tokens_details=InputTokensDetails(cached_tokens=0),
-                    output_tokens_details=OutputTokensDetails(reasoning_tokens=0),
+    tool_call_response = get_model_response(
+        Response(
+            id="resp_1",
+            output=[
+                ResponseFunctionToolCall(
+                    id="call_123",
+                    call_id="call_123",
+                    name="calculator",
+                    type="function_call",
+                    arguments='{"a": 5, "b": 3}',
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
                 ),
-                response_id="resp_tool_call",
-            )
-
-            # Second call: agent uses tool result to respond (20 input, 15 output tokens)
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="The result is 8",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1,
-                    input_tokens=20,
-                    output_tokens=15,
-                    total_tokens=35,
-                    input_tokens_details=InputTokensDetails(cached_tokens=5),
-                    output_tokens_details=OutputTokensDetails(reasoning_tokens=3),
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
                 ),
-                response_id="resp_final",
-            )
-
-            mock_get_response.side_effect = [tool_call_response, final_response]
-
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
-
-            events = capture_events()
-
-            result = await agents.Runner.run(
-                agent_with_tool,
-                "What is 5 + 3?",
-                run_config=test_run_config,
-            )
-
-            assert result is not None
-
-    (transaction,) = events
-    spans = transaction["spans"]
-    invoke_agent_span = spans[0]
-
-    # Verify invoke_agent span has aggregated usage from both API calls
-    # Total: 10 + 20 = 30 input tokens, 5 + 15 = 20 output tokens, 15 + 35 = 50 total
-    assert invoke_agent_span["data"]["gen_ai.usage.input_tokens"] == 30
-    assert invoke_agent_span["data"]["gen_ai.usage.output_tokens"] == 20
-    assert invoke_agent_span["data"]["gen_ai.usage.total_tokens"] == 50
-    # Cached tokens should be aggregated: 0 + 5 = 5
-    assert invoke_agent_span["data"]["gen_ai.usage.input_tokens.cached"] == 5
-    # Reasoning tokens should be aggregated: 0 + 3 = 3
-    assert invoke_agent_span["data"]["gen_ai.usage.output_tokens.reasoning"] == 3
-
-
-@pytest.mark.asyncio
-async def test_response_model_not_set_when_unavailable(
-    sentry_init, capture_events, test_agent
-):
-    """
-    Test that response model is not set if the API response doesn't have a model field.
-    The request model should still be set correctly.
-    """
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel._fetch_response"
-        ) as mock_fetch_response:
-            # Create a mock response without a model field
-            mock_response = MagicMock()
-            mock_response.model = None  # No model in response
-            mock_response.id = "resp_123"
-            mock_response.output = [
+    final_response = get_model_response(
+        Response(
+            id="resp_2",
+            output=[
                 ResponseOutputMessage(
-                    id="msg_123",
+                    id="msg_final",
                     type="message",
                     status="completed",
                     content=[
                         ResponseOutputText(
-                            text="Response without model field",
+                            text="The result is 8",
                             type="output_text",
                             annotations=[],
                         )
                     ],
                     role="assistant",
                 )
-            ]
-            mock_response.usage = MagicMock()
-            mock_response.usage.input_tokens = 10
-            mock_response.usage.output_tokens = 20
-            mock_response.usage.total_tokens = 30
-            mock_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=0
-            )
-            mock_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=0
-            )
-
-            mock_fetch_response.return_value = mock_response
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4-0613",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=20,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=5,
+                ),
+                output_tokens=15,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=3,
+                ),
+                total_tokens=35,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    with patch.object(
+        agent_with_tool.model._client._client,
+        "send",
+        side_effect=[tool_call_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        result = await agents.Runner.run(
+            agent_with_tool,
+            "What is 5 + 3?",
+            run_config=test_run_config,
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    _, ai_client_span = spans
+    invoke_agent_span = spans[0]
 
-    # Response model should NOT be set when API doesn't return it
-    assert "gen_ai.response.model" not in ai_client_span["data"]
-    # But request model should still be set
-    assert "gen_ai.request.model" in ai_client_span["data"]
-    assert ai_client_span["data"]["gen_ai.request.model"] == "gpt-4"
+    # Verify invoke_agent span has aggregated usage from both API calls
+    # Total: 10 + 20 = 30 input tokens, 5 + 15 = 20 output tokens, 15 + 35 = 50 total
+    assert invoke_agent_span["data"]["gen_ai.usage.input_tokens"] == 30
+    assert invoke_agent_span["data"]["gen_ai.usage.output_tokens"] == 20
+    assert invoke_agent_span["data"]["gen_ai.usage.total_tokens"] == 50
+    # Cached tokens should be aggregated: 0 + 5 = 5
+    assert invoke_agent_span["data"]["gen_ai.usage.input_tokens.cached"] == 5
+    # Reasoning tokens should be aggregated: 0 + 3 = 3
+    assert invoke_agent_span["data"]["gen_ai.usage.output_tokens.reasoning"] == 3
 
 
 @pytest.mark.asyncio
 async def test_invoke_agent_span_includes_response_model(
-    sentry_init, capture_events, test_agent
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
 ):
     """
     Test that invoke_agent spans include the response model from the API response.
     """
+    client = AsyncOpenAI(api_key="z")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel._fetch_response"
-        ) as mock_fetch_response:
-            # Create a mock OpenAI Response object with a specific model version
-            mock_response = MagicMock()
-            mock_response.model = "gpt-4.1-2025-04-14"  # The actual response model
-            mock_response.id = "resp_123"
-            mock_response.output = [
+    response = get_model_response(
+        Response(
+            id="resp_123",
+            output=[
                 ResponseOutputMessage(
                     id="msg_123",
                     type="message",
@@ -2612,37 +2790,53 @@ async def test_invoke_agent_span_includes_response_model(
                     ],
                     role="assistant",
                 )
-            ]
-            mock_response.usage = MagicMock()
-            mock_response.usage.input_tokens = 10
-            mock_response.usage.output_tokens = 20
-            mock_response.usage.total_tokens = 30
-            mock_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=0
-            )
-            mock_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=5
-            )
-
-            mock_fetch_response.return_value = mock_response
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=20,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     # Verify invoke_agent span has response model from API
     assert invoke_agent_span["description"] == "invoke_agent test_agent"
@@ -2656,7 +2850,10 @@ async def test_invoke_agent_span_includes_response_model(
 
 @pytest.mark.asyncio
 async def test_invoke_agent_span_uses_last_response_model(
-    sentry_init, capture_events, test_agent
+    sentry_init,
+    capture_events,
+    test_agent,
+    get_model_response,
 ):
     """
     Test that when an agent makes multiple LLM calls (e.g., with tools),
@@ -2668,17 +2865,14 @@ def calculator(a: int, b: int) -> int:
         """Add two numbers"""
         return a + b
 
-    agent_with_tool = test_agent.clone(tools=[calculator])
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent_with_tool = test_agent.clone(tools=[calculator], model=model)
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel._fetch_response"
-        ) as mock_fetch_response:
-            # First call: gpt-4 model returns tool call
-            first_response = MagicMock()
-            first_response.model = "gpt-4-0613"
-            first_response.id = "resp_1"
-            first_response.output = [
+    first_response = get_model_response(
+        Response(
+            id="resp_1",
+            output=[
                 ResponseFunctionToolCall(
                     id="call_123",
                     call_id="call_123",
@@ -2686,65 +2880,87 @@ def calculator(a: int, b: int) -> int:
                     type="function_call",
                     arguments='{"a": 5, "b": 3}',
                 )
-            ]
-            first_response.usage = MagicMock()
-            first_response.usage.input_tokens = 10
-            first_response.usage.output_tokens = 5
-            first_response.usage.total_tokens = 15
-            first_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=0
-            )
-            first_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=0
-            )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4-0613",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
+                ),
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            # Second call: different model version returns final message
-            second_response = MagicMock()
-            second_response.model = "gpt-4.1-2025-04-14"
-            second_response.id = "resp_2"
-            second_response.output = [
+    second_response = get_model_response(
+        Response(
+            id="resp_2",
+            output=[
                 ResponseOutputMessage(
                     id="msg_final",
                     type="message",
                     status="completed",
                     content=[
                         ResponseOutputText(
-                            text="The result is 8",
+                            text="I'm the specialist and I can help with that!",
                             type="output_text",
                             annotations=[],
                         )
                     ],
                     role="assistant",
                 )
-            ]
-            second_response.usage = MagicMock()
-            second_response.usage.input_tokens = 20
-            second_response.usage.output_tokens = 15
-            second_response.usage.total_tokens = 35
-            second_response.usage.input_tokens_details = InputTokensDetails(
-                cached_tokens=5
-            )
-            second_response.usage.output_tokens_details = OutputTokensDetails(
-                reasoning_tokens=3
-            )
-
-            mock_fetch_response.side_effect = [first_response, second_response]
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4.1-2025-04-14",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=20,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
+                ),
+                output_tokens=15,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=5,
+                ),
+                total_tokens=35,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-                send_default_pii=True,
-            )
+    with patch.object(
+        agent_with_tool.model._client._client,
+        "send",
+        side_effect=[first_response, second_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+            send_default_pii=True,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            result = await agents.Runner.run(
-                agent_with_tool,
-                "What is 5 + 3?",
-                run_config=test_run_config,
-            )
+        result = await agents.Runner.run(
+            agent_with_tool,
+            "What is 5 + 3?",
+            run_config=test_run_config,
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -2854,7 +3070,13 @@ async def test_streaming_span_update_captures_response_data(
 
 
 @pytest.mark.asyncio
-async def test_streaming_ttft_on_chat_span(sentry_init, test_agent):
+async def test_streaming_ttft_on_chat_span(
+    sentry_init,
+    test_agent,
+    get_model_response,
+    async_iterator,
+    server_side_event_chunks,
+):
     """
     Test that time-to-first-token (TTFT) is recorded on chat spans during streaming.
 
@@ -2869,7 +3091,6 @@ async def test_streaming_ttft_on_chat_span(sentry_init, test_agent):
     should NOT trigger TTFT.
     """
     client = AsyncOpenAI(api_key="z")
-    client.responses._post = AsyncMock(return_value=EXAMPLE_RESPONSE)
 
     model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
 
@@ -2882,10 +3103,102 @@ async def test_streaming_ttft_on_chat_span(sentry_init, test_agent):
         traces_sample_rate=1.0,
     )
 
+    request_headers = {}
+    # openai-agents calls with_streaming_response() if available starting with
+    # https://github.com/openai/openai-agents-python/commit/159beb56130f7d85192acfd593c9168757984dc0.
+    # When using with_streaming_response() the header set below changes the response type:
+    # https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/_response.py#L67.
+    if parse_version(OPENAI_AGENTS_VERSION) >= (0, 10, 3) and hasattr(
+        agent_with_tool.model._client.responses, "with_streaming_response"
+    ):
+        request_headers["X-Stainless-Raw-Response"] = "stream"
+
+    response = get_model_response(
+        async_iterator(
+            server_side_event_chunks(
+                [
+                    ResponseCreatedEvent(
+                        response=Response(
+                            id="chat-id",
+                            output=[],
+                            parallel_tool_calls=False,
+                            tool_choice="none",
+                            tools=[],
+                            created_at=10000000,
+                            model="response-model-id",
+                            object="response",
+                        ),
+                        type="response.created",
+                        sequence_number=0,
+                    ),
+                    ResponseTextDeltaEvent(
+                        type="response.output_text.delta",
+                        item_id="message-id",
+                        output_index=0,
+                        content_index=0,
+                        delta="Hello",
+                        logprobs=[],
+                        sequence_number=1,
+                    ),
+                    ResponseTextDeltaEvent(
+                        type="response.output_text.delta",
+                        item_id="message-id",
+                        output_index=0,
+                        content_index=0,
+                        delta=" world!",
+                        logprobs=[],
+                        sequence_number=2,
+                    ),
+                    ResponseCompletedEvent(
+                        response=Response(
+                            id="chat-id",
+                            output=[
+                                ResponseOutputMessage(
+                                    id="message-id",
+                                    content=[
+                                        ResponseOutputText(
+                                            annotations=[],
+                                            text="Hello world!",
+                                            type="output_text",
+                                        ),
+                                    ],
+                                    role="assistant",
+                                    status="completed",
+                                    type="message",
+                                ),
+                            ],
+                            parallel_tool_calls=False,
+                            tool_choice="none",
+                            tools=[],
+                            created_at=10000000,
+                            model="response-model-id",
+                            object="response",
+                            usage=ResponseUsage(
+                                input_tokens=20,
+                                input_tokens_details=InputTokensDetails(
+                                    cached_tokens=5,
+                                ),
+                                output_tokens=10,
+                                output_tokens_details=OutputTokensDetails(
+                                    reasoning_tokens=8,
+                                ),
+                                total_tokens=30,
+                            ),
+                        ),
+                        type="response.completed",
+                        sequence_number=3,
+                    ),
+                ]
+            )
+        ),
+        request_headers=request_headers,
+    )
+
+    # Patching https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/_base_client.py#L1604
     with patch.object(
-        model._client.responses,
-        "create",
-        side_effect=EXAMPLE_STREAMED_RESPONSE_WITH_DELTA,
+        agent_with_tool.model._client._client,
+        "send",
+        return_value=response,
     ) as _:
         with sentry_sdk.start_transaction(
             name="test_ttft", sampled=True
@@ -2916,37 +3229,51 @@ async def test_streaming_ttft_on_chat_span(sentry_init, test_agent):
 )
 @pytest.mark.asyncio
 async def test_conversation_id_on_all_spans(
-    sentry_init, capture_events, test_agent, mock_model_response
+    sentry_init,
+    capture_events,
+    test_agent,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
     """
     Test that gen_ai.conversation.id is set on all AI-related spans when passed to Runner.run().
     """
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            events = capture_events()
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            result = await agents.Runner.run(
-                test_agent,
-                "Test input",
-                run_config=test_run_config,
-                conversation_id="conv_test_123",
-            )
+        events = capture_events()
+
+        result = await agents.Runner.run(
+            agent,
+            "Test input",
+            run_config=test_run_config,
+            conversation_id="conv_test_123",
+        )
 
-            assert result is not None
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     # Verify workflow span (transaction) has conversation_id
     assert (
@@ -2966,7 +3293,9 @@ async def test_conversation_id_on_all_spans(
     reason="conversation_id support requires openai-agents >= 0.4.0",
 )
 @pytest.mark.asyncio
-async def test_conversation_id_on_tool_span(sentry_init, capture_events, test_agent):
+async def test_conversation_id_on_tool_span(
+    sentry_init, capture_events, test_agent, get_model_response
+):
     """
     Test that gen_ai.conversation.id is set on tool execution spans when passed to Runner.run().
     """
@@ -2976,65 +3305,100 @@ def simple_tool(message: str) -> str:
         """A simple tool"""
         return f"Result: {message}"
 
-    agent_with_tool = test_agent.clone(tools=[simple_tool])
-
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            tool_call = ResponseFunctionToolCall(
-                id="call_123",
-                call_id="call_123",
-                name="simple_tool",
-                type="function_call",
-                arguments='{"message": "hello"}',
-            )
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent_with_tool = test_agent.clone(tools=[simple_tool], model=model)
 
-            tool_response = ModelResponse(
-                output=[tool_call],
-                usage=Usage(
-                    requests=1, input_tokens=10, output_tokens=5, total_tokens=15
+    tool_response = get_model_response(
+        Response(
+            id="call_123",
+            output=[
+                ResponseFunctionToolCall(
+                    id="call_123",
+                    call_id="call_123",
+                    name="simple_tool",
+                    type="function_call",
+                    arguments='{"message": "hello"}',
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=10,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=0,
                 ),
-                response_id="resp_tool_456",
-            )
-
-            final_response = ModelResponse(
-                output=[
-                    ResponseOutputMessage(
-                        id="msg_final",
-                        type="message",
-                        status="completed",
-                        content=[
-                            ResponseOutputText(
-                                text="Done",
-                                type="output_text",
-                                annotations=[],
-                            )
-                        ],
-                        role="assistant",
-                    )
-                ],
-                usage=Usage(
-                    requests=1, input_tokens=15, output_tokens=10, total_tokens=25
+                output_tokens=5,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=0,
                 ),
-                response_id="resp_final_789",
-            )
+                total_tokens=15,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            mock_get_response.side_effect = [tool_response, final_response]
+    final_response = get_model_response(
+        Response(
+            id="resp_final_789",
+            output=[
+                ResponseOutputMessage(
+                    id="msg_final",
+                    type="message",
+                    status="completed",
+                    content=[
+                        ResponseOutputText(
+                            text="Done",
+                            type="output_text",
+                            annotations=[],
+                        )
+                    ],
+                    role="assistant",
+                )
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="gpt-4",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=20,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=5,
+                ),
+                output_tokens=10,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=8,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        serialize_pydantic=True,
+    )
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    with patch.object(
+        agent_with_tool.model._client._client,
+        "send",
+        side_effect=[tool_response, final_response],
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            events = capture_events()
+        events = capture_events()
 
-            await agents.Runner.run(
-                agent_with_tool,
-                "Use the tool",
-                run_config=test_run_config,
-                conversation_id="conv_tool_test_456",
-            )
+        await agents.Runner.run(
+            agent_with_tool,
+            "Use the tool",
+            run_config=test_run_config,
+            conversation_id="conv_tool_test_456",
+        )
 
     (transaction,) = events
     spans = transaction["spans"]
@@ -3063,35 +3427,49 @@ def simple_tool(message: str) -> str:
 )
 @pytest.mark.asyncio
 async def test_no_conversation_id_when_not_provided(
-    sentry_init, capture_events, test_agent, mock_model_response
+    sentry_init,
+    capture_events,
+    test_agent,
+    nonstreaming_responses_model_response,
+    get_model_response,
 ):
     """
     Test that gen_ai.conversation.id is not set when not passed to Runner.run().
     """
 
-    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
-        with patch(
-            "agents.models.openai_responses.OpenAIResponsesModel.get_response"
-        ) as mock_get_response:
-            mock_get_response.return_value = mock_model_response
+    client = AsyncOpenAI(api_key="test-key")
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+    agent = test_agent.clone(model=model)
 
-            sentry_init(
-                integrations=[OpenAIAgentsIntegration()],
-                traces_sample_rate=1.0,
-            )
+    response = get_model_response(
+        nonstreaming_responses_model_response, serialize_pydantic=True
+    )
 
-            events = capture_events()
+    with patch.object(
+        agent.model._client._client,
+        "send",
+        return_value=response,
+    ) as _:
+        sentry_init(
+            integrations=[OpenAIAgentsIntegration()],
+            traces_sample_rate=1.0,
+        )
 
-            # Don't pass conversation_id
-            result = await agents.Runner.run(
-                test_agent, "Test input", run_config=test_run_config
-            )
+        events = capture_events()
 
-            assert result is not None
+        # Don't pass conversation_id
+        result = await agents.Runner.run(
+            agent, "Test input", run_config=test_run_config
+        )
+
+        assert result is not None
 
     (transaction,) = events
     spans = transaction["spans"]
-    invoke_agent_span, ai_client_span = spans
+    invoke_agent_span = next(
+        span for span in spans if span["op"] == OP.GEN_AI_INVOKE_AGENT
+    )
+    ai_client_span = next(span for span in spans if span["op"] == OP.GEN_AI_CHAT)
 
     # Verify conversation_id is NOT set on any spans
     assert "gen_ai.conversation.id" not in transaction["contexts"]["trace"].get(
diff --git a/tests/integrations/opentelemetry/test_span_processor.py b/tests/integrations/opentelemetry/test_span_processor.py
index af5cbdd3fb..e1cd849b94 100644
--- a/tests/integrations/opentelemetry/test_span_processor.py
+++ b/tests/integrations/opentelemetry/test_span_processor.py
@@ -68,7 +68,9 @@ def test_get_trace_data_with_span_and_trace():
     parent_context = {}
 
     span_processor = SentrySpanProcessor()
-    sentry_trace_data = span_processor._get_trace_data(otel_span, parent_context)
+    sentry_trace_data = span_processor._get_trace_data(
+        otel_span.get_span_context(), otel_span.parent, parent_context
+    )
     assert sentry_trace_data["trace_id"] == "1234567890abcdef1234567890abcdef"
     assert sentry_trace_data["span_id"] == "1234567890abcdef"
     assert sentry_trace_data["parent_span_id"] is None
@@ -90,7 +92,9 @@ def test_get_trace_data_with_span_and_trace_and_parent():
     parent_context = {}
 
     span_processor = SentrySpanProcessor()
-    sentry_trace_data = span_processor._get_trace_data(otel_span, parent_context)
+    sentry_trace_data = span_processor._get_trace_data(
+        otel_span.get_span_context(), otel_span.parent, parent_context
+    )
     assert sentry_trace_data["trace_id"] == "1234567890abcdef1234567890abcdef"
     assert sentry_trace_data["span_id"] == "1234567890abcdef"
     assert sentry_trace_data["parent_span_id"] == "abcdef1234567890"
@@ -121,7 +125,9 @@ def test_get_trace_data_with_sentry_trace():
         ],
     ):
         span_processor = SentrySpanProcessor()
-        sentry_trace_data = span_processor._get_trace_data(otel_span, parent_context)
+        sentry_trace_data = span_processor._get_trace_data(
+            otel_span.get_span_context(), otel_span.parent, parent_context
+        )
         assert sentry_trace_data["trace_id"] == "1234567890abcdef1234567890abcdef"
         assert sentry_trace_data["span_id"] == "1234567890abcdef"
         assert sentry_trace_data["parent_span_id"] == "abcdef1234567890"
@@ -138,7 +144,9 @@ def test_get_trace_data_with_sentry_trace():
         ],
     ):
         span_processor = SentrySpanProcessor()
-        sentry_trace_data = span_processor._get_trace_data(otel_span, parent_context)
+        sentry_trace_data = span_processor._get_trace_data(
+            otel_span.get_span_context(), otel_span.parent, parent_context
+        )
         assert sentry_trace_data["trace_id"] == "1234567890abcdef1234567890abcdef"
         assert sentry_trace_data["span_id"] == "1234567890abcdef"
         assert sentry_trace_data["parent_span_id"] == "abcdef1234567890"
@@ -175,7 +183,9 @@ def test_get_trace_data_with_sentry_trace_and_baggage():
         ],
     ):
         span_processor = SentrySpanProcessor()
-        sentry_trace_data = span_processor._get_trace_data(otel_span, parent_context)
+        sentry_trace_data = span_processor._get_trace_data(
+            otel_span.get_span_context(), otel_span.parent, parent_context
+        )
         assert sentry_trace_data["trace_id"] == "1234567890abcdef1234567890abcdef"
         assert sentry_trace_data["span_id"] == "1234567890abcdef"
         assert sentry_trace_data["parent_span_id"] == "abcdef1234567890"
diff --git a/tests/integrations/otlp/test_otlp.py b/tests/integrations/otlp/test_otlp.py
index 191bf5b7f4..e085a22ac0 100644
--- a/tests/integrations/otlp/test_otlp.py
+++ b/tests/integrations/otlp/test_otlp.py
@@ -32,6 +32,11 @@ def mock_otlp_ingest():
         url="https://bla.ingest.sentry.io/api/12312012/integration/otlp/v1/traces/",
         status=200,
     )
+    responses.add(
+        responses.POST,
+        url="https://my-collector.example.com/v1/traces",
+        status=200,
+    )
 
     yield
 
@@ -233,6 +238,67 @@ def test_propagator_inject_continue_trace(sentry_init):
     detach(token)
 
 
+def test_collector_url_sets_endpoint(sentry_init):
+    sentry_init(
+        dsn="https://mysecret@bla.ingest.sentry.io/12312012",
+        integrations=[
+            OTLPIntegration(collector_url="https://my-collector.example.com/v1/traces")
+        ],
+    )
+
+    tracer_provider = get_tracer_provider()
+    assert isinstance(tracer_provider, TracerProvider)
+
+    (span_processor,) = tracer_provider._active_span_processor._span_processors
+    assert isinstance(span_processor, BatchSpanProcessor)
+
+    exporter = span_processor.span_exporter
+    assert isinstance(exporter, OTLPSpanExporter)
+    assert exporter._endpoint == "https://my-collector.example.com/v1/traces"
+    assert exporter._headers is None or "X-Sentry-Auth" not in exporter._headers
+
+
+def test_collector_url_takes_precedence_over_dsn(sentry_init):
+    sentry_init(
+        dsn="https://mysecret@bla.ingest.sentry.io/12312012",
+        integrations=[
+            OTLPIntegration(collector_url="https://my-collector.example.com/v1/traces")
+        ],
+    )
+
+    tracer_provider = get_tracer_provider()
+    assert isinstance(tracer_provider, TracerProvider)
+
+    (span_processor,) = tracer_provider._active_span_processor._span_processors
+    exporter = span_processor.span_exporter
+    assert isinstance(exporter, OTLPSpanExporter)
+    # Should use collector_url, NOT the DSN-derived endpoint
+    assert exporter._endpoint == "https://my-collector.example.com/v1/traces"
+    assert (
+        exporter._endpoint
+        != "https://bla.ingest.sentry.io/api/12312012/integration/otlp/v1/traces/"
+    )
+
+
+def test_collector_url_none_falls_back_to_dsn(sentry_init):
+    sentry_init(
+        dsn="https://mysecret@bla.ingest.sentry.io/12312012",
+        integrations=[OTLPIntegration(collector_url=None)],
+    )
+
+    tracer_provider = get_tracer_provider()
+    assert isinstance(tracer_provider, TracerProvider)
+
+    (span_processor,) = tracer_provider._active_span_processor._span_processors
+    exporter = span_processor.span_exporter
+    assert isinstance(exporter, OTLPSpanExporter)
+    assert (
+        exporter._endpoint
+        == "https://bla.ingest.sentry.io/api/12312012/integration/otlp/v1/traces/"
+    )
+    assert "X-Sentry-Auth" in exporter._headers
+
+
 def test_capture_exceptions_enabled(sentry_init, capture_events):
     sentry_init(
         dsn="https://mysecret@bla.ingest.sentry.io/12312012",
diff --git a/tests/integrations/pydantic_ai/test_pydantic_ai.py b/tests/integrations/pydantic_ai/test_pydantic_ai.py
index b0bde0301d..50ce155f5b 100644
--- a/tests/integrations/pydantic_ai/test_pydantic_ai.py
+++ b/tests/integrations/pydantic_ai/test_pydantic_ai.py
@@ -12,43 +12,48 @@
 from sentry_sdk.integrations.pydantic_ai import PydanticAIIntegration
 from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
 from sentry_sdk.integrations.pydantic_ai.spans.utils import _set_usage_data
-
 from pydantic_ai import Agent
-from pydantic_ai.messages import BinaryContent, UserPromptPart
+from pydantic_ai.messages import BinaryContent, ImageUrl, UserPromptPart
 from pydantic_ai.usage import RequestUsage
-from pydantic_ai.models.test import TestModel
 from pydantic_ai.exceptions import ModelRetry, UnexpectedModelBehavior
+from pydantic_ai.models.function import FunctionModel
 
 
 @pytest.fixture
-def test_agent():
-    """Create a test agent with model settings."""
-    return Agent(
-        "test",
-        name="test_agent",
-        system_prompt="You are a helpful test assistant.",
-    )
+def get_test_agent():
+    def inner():
+        """Create a test agent with model settings."""
+        return Agent(
+            "test",
+            name="test_agent",
+            system_prompt="You are a helpful test assistant.",
+        )
+
+    return inner
 
 
 @pytest.fixture
-def test_agent_with_settings():
-    """Create a test agent with explicit model settings."""
-    from pydantic_ai import ModelSettings
+def get_test_agent_with_settings():
+    def inner():
+        """Create a test agent with explicit model settings."""
+        from pydantic_ai import ModelSettings
+
+        return Agent(
+            "test",
+            name="test_agent_settings",
+            system_prompt="You are a test assistant with settings.",
+            model_settings=ModelSettings(
+                temperature=0.7,
+                max_tokens=100,
+                top_p=0.9,
+            ),
+        )
 
-    return Agent(
-        "test",
-        name="test_agent_settings",
-        system_prompt="You are a test assistant with settings.",
-        model_settings=ModelSettings(
-            temperature=0.7,
-            max_tokens=100,
-            top_p=0.9,
-        ),
-    )
+    return inner
 
 
 @pytest.mark.asyncio
-async def test_agent_run_async(sentry_init, capture_events, test_agent):
+async def test_agent_run_async(sentry_init, capture_events, get_test_agent):
     """
     Test that the integration creates spans for async agent runs.
     """
@@ -60,6 +65,7 @@ async def test_agent_run_async(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     result = await test_agent.run("Test input")
 
     assert result is not None
@@ -90,7 +96,36 @@ async def test_agent_run_async(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_agent_run_async_usage_data(sentry_init, capture_events, test_agent):
+async def test_agent_run_async_model_error(sentry_init, capture_events):
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+    )
+
+    events = capture_events()
+
+    def failing_model(messages, info):
+        raise RuntimeError("model exploded")
+
+    agent = Agent(
+        FunctionModel(failing_model),
+        name="test_agent",
+    )
+
+    with pytest.raises(RuntimeError, match="model exploded"):
+        await agent.run("Test input")
+
+    (error, transaction) = events
+    assert error["level"] == "error"
+
+    spans = transaction["spans"]
+    assert len(spans) == 1
+
+    assert spans[0]["status"] == "internal_error"
+
+
+@pytest.mark.asyncio
+async def test_agent_run_async_usage_data(sentry_init, capture_events, get_test_agent):
     """
     Test that the invoke_agent span includes token usage and model data.
     """
@@ -102,6 +137,7 @@ async def test_agent_run_async_usage_data(sentry_init, capture_events, test_agen
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     result = await test_agent.run("Test input")
 
     assert result is not None
@@ -134,7 +170,7 @@ async def test_agent_run_async_usage_data(sentry_init, capture_events, test_agen
     assert trace_data["gen_ai.response.model"] == "test"  # Test model name
 
 
-def test_agent_run_sync(sentry_init, capture_events, test_agent):
+def test_agent_run_sync(sentry_init, capture_events, get_test_agent):
     """
     Test that the integration creates spans for sync agent runs.
     """
@@ -146,6 +182,7 @@ def test_agent_run_sync(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     result = test_agent.run_sync("Test input")
 
     assert result is not None
@@ -167,8 +204,36 @@ def test_agent_run_sync(sentry_init, capture_events, test_agent):
         assert chat_span["data"]["gen_ai.response.streaming"] is False
 
 
+def test_agent_run_sync_model_error(sentry_init, capture_events):
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+    )
+
+    events = capture_events()
+
+    def failing_model(messages, info):
+        raise RuntimeError("model exploded")
+
+    agent = Agent(
+        FunctionModel(failing_model),
+        name="test_agent",
+    )
+
+    with pytest.raises(RuntimeError, match="model exploded"):
+        agent.run_sync("Test input")
+
+    (error, transaction) = events
+    assert error["level"] == "error"
+
+    spans = transaction["spans"]
+    assert len(spans) == 1
+
+    assert spans[0]["status"] == "internal_error"
+
+
 @pytest.mark.asyncio
-async def test_agent_run_stream(sentry_init, capture_events, test_agent):
+async def test_agent_run_stream(sentry_init, capture_events, get_test_agent):
     """
     Test that the integration creates spans for streaming agent runs.
     """
@@ -180,6 +245,7 @@ async def test_agent_run_stream(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     async with test_agent.run_stream("Test input") as result:
         # Consume the stream
         async for _ in result.stream_output():
@@ -209,7 +275,7 @@ async def test_agent_run_stream(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_agent_run_stream_events(sentry_init, capture_events, test_agent):
+async def test_agent_run_stream_events(sentry_init, capture_events, get_test_agent):
     """
     Test that run_stream_events creates spans (it uses run internally, so non-streaming).
     """
@@ -222,6 +288,7 @@ async def test_agent_run_stream_events(sentry_init, capture_events, test_agent):
     events = capture_events()
 
     # Consume all events
+    test_agent = get_test_agent()
     async for _ in test_agent.run_stream_events("Test input"):
         pass
 
@@ -241,22 +308,23 @@ async def test_agent_run_stream_events(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_agent_with_tools(sentry_init, capture_events, test_agent):
+async def test_agent_with_tools(sentry_init, capture_events, get_test_agent):
     """
     Test that tool execution creates execute_tool spans.
     """
-
-    @test_agent.tool_plain
-    def add_numbers(a: int, b: int) -> int:
-        """Add two numbers together."""
-        return a + b
-
     sentry_init(
         integrations=[PydanticAIIntegration()],
         traces_sample_rate=1.0,
         send_default_pii=True,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def add_numbers(a: int, b: int) -> int:
+        """Add two numbers together."""
+        return a + b
+
     events = capture_events()
 
     result = await test_agent.run("What is 5 + 3?")
@@ -277,7 +345,6 @@ def add_numbers(a: int, b: int) -> int:
     tool_span = tool_spans[0]
     assert "execute_tool" in tool_span["description"]
     assert tool_span["data"]["gen_ai.operation.name"] == "execute_tool"
-    assert tool_span["data"]["gen_ai.tool.type"] == "function"
     assert tool_span["data"]["gen_ai.tool.name"] == "add_numbers"
     assert "gen_ai.tool.input" in tool_span["data"]
     assert "gen_ai.tool.output" in tool_span["data"]
@@ -296,14 +363,25 @@ def add_numbers(a: int, b: int) -> int:
 )
 @pytest.mark.asyncio
 async def test_agent_with_tool_model_retry(
-    sentry_init, capture_events, test_agent, handled_tool_call_exceptions
+    sentry_init, capture_events, get_test_agent, handled_tool_call_exceptions
 ):
     """
     Test that a handled exception is captured when a tool raises ModelRetry.
     """
+    sentry_init(
+        integrations=[
+            PydanticAIIntegration(
+                handled_tool_call_exceptions=handled_tool_call_exceptions
+            )
+        ],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
 
     retries = 0
 
+    test_agent = get_test_agent()
+
     @test_agent.tool_plain
     def add_numbers(a: int, b: int) -> float:
         """Add two numbers together, but raises an exception on the first attempt."""
@@ -313,16 +391,6 @@ def add_numbers(a: int, b: int) -> float:
             raise ModelRetry(message="Try again with the same arguments.")
         return a + b
 
-    sentry_init(
-        integrations=[
-            PydanticAIIntegration(
-                handled_tool_call_exceptions=handled_tool_call_exceptions
-            )
-        ],
-        traces_sample_rate=1.0,
-        send_default_pii=True,
-    )
-
     events = capture_events()
 
     result = await test_agent.run("What is 5 + 3?")
@@ -350,14 +418,12 @@ def add_numbers(a: int, b: int) -> float:
     model_retry_tool_span = tool_spans[0]
     assert "execute_tool" in model_retry_tool_span["description"]
     assert model_retry_tool_span["data"]["gen_ai.operation.name"] == "execute_tool"
-    assert model_retry_tool_span["data"]["gen_ai.tool.type"] == "function"
     assert model_retry_tool_span["data"]["gen_ai.tool.name"] == "add_numbers"
     assert "gen_ai.tool.input" in model_retry_tool_span["data"]
 
     tool_span = tool_spans[1]
     assert "execute_tool" in tool_span["description"]
     assert tool_span["data"]["gen_ai.operation.name"] == "execute_tool"
-    assert tool_span["data"]["gen_ai.tool.type"] == "function"
     assert tool_span["data"]["gen_ai.tool.name"] == "add_numbers"
     assert "gen_ai.tool.input" in tool_span["data"]
     assert "gen_ai.tool.output" in tool_span["data"]
@@ -376,17 +442,11 @@ def add_numbers(a: int, b: int) -> float:
 )
 @pytest.mark.asyncio
 async def test_agent_with_tool_validation_error(
-    sentry_init, capture_events, test_agent, handled_tool_call_exceptions
+    sentry_init, capture_events, get_test_agent, handled_tool_call_exceptions
 ):
     """
     Test that a handled exception is captured when a tool has unsatisfiable constraints.
     """
-
-    @test_agent.tool_plain
-    def add_numbers(a: Annotated[int, Field(gt=0, lt=0)], b: int) -> int:
-        """Add two numbers together."""
-        return a + b
-
     sentry_init(
         integrations=[
             PydanticAIIntegration(
@@ -397,6 +457,13 @@ def add_numbers(a: Annotated[int, Field(gt=0, lt=0)], b: int) -> int:
         send_default_pii=True,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def add_numbers(a: Annotated[int, Field(gt=0, lt=0)], b: int) -> int:
+        """Add two numbers together."""
+        return a + b
+
     events = capture_events()
 
     result = None
@@ -429,7 +496,6 @@ def add_numbers(a: Annotated[int, Field(gt=0, lt=0)], b: int) -> int:
     model_retry_tool_span = tool_spans[0]
     assert "execute_tool" in model_retry_tool_span["description"]
     assert model_retry_tool_span["data"]["gen_ai.operation.name"] == "execute_tool"
-    assert model_retry_tool_span["data"]["gen_ai.tool.type"] == "function"
     assert model_retry_tool_span["data"]["gen_ai.tool.name"] == "add_numbers"
     assert "gen_ai.tool.input" in model_retry_tool_span["data"]
 
@@ -442,22 +508,23 @@ def add_numbers(a: Annotated[int, Field(gt=0, lt=0)], b: int) -> int:
 
 
 @pytest.mark.asyncio
-async def test_agent_with_tools_streaming(sentry_init, capture_events, test_agent):
+async def test_agent_with_tools_streaming(sentry_init, capture_events, get_test_agent):
     """
     Test that tool execution works correctly with streaming.
     """
-
-    @test_agent.tool_plain
-    def multiply(a: int, b: int) -> int:
-        """Multiply two numbers."""
-        return a * b
-
     sentry_init(
         integrations=[PydanticAIIntegration()],
         traces_sample_rate=1.0,
         send_default_pii=True,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def multiply(a: int, b: int) -> int:
+        """Multiply two numbers."""
+        return a * b
+
     events = capture_events()
 
     async with test_agent.run_stream("What is 7 times 8?") as result:
@@ -486,7 +553,9 @@ def multiply(a: int, b: int) -> int:
 
 
 @pytest.mark.asyncio
-async def test_model_settings(sentry_init, capture_events, test_agent_with_settings):
+async def test_model_settings(
+    sentry_init, capture_events, get_test_agent_with_settings
+):
     """
     Test that model settings are captured in spans.
     """
@@ -497,6 +566,7 @@ async def test_model_settings(sentry_init, capture_events, test_agent_with_setti
 
     events = capture_events()
 
+    test_agent_with_settings = get_test_agent_with_settings()
     await test_agent_with_settings.run("Test input")
 
     (transaction,) = events
@@ -598,7 +668,7 @@ async def test_error_handling(sentry_init, capture_events):
 
 
 @pytest.mark.asyncio
-async def test_without_pii(sentry_init, capture_events, test_agent):
+async def test_without_pii(sentry_init, capture_events, get_test_agent):
     """
     Test that PII is not captured when send_default_pii is False.
     """
@@ -610,6 +680,7 @@ async def test_without_pii(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     await test_agent.run("Sensitive input")
 
     (transaction,) = events
@@ -625,22 +696,23 @@ async def test_without_pii(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_without_pii_tools(sentry_init, capture_events, test_agent):
+async def test_without_pii_tools(sentry_init, capture_events, get_test_agent):
     """
     Test that tool input/output are not captured when send_default_pii is False.
     """
-
-    @test_agent.tool_plain
-    def sensitive_tool(data: str) -> str:
-        """A tool with sensitive data."""
-        return f"Processed: {data}"
-
     sentry_init(
         integrations=[PydanticAIIntegration()],
         traces_sample_rate=1.0,
         send_default_pii=False,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def sensitive_tool(data: str) -> str:
+        """A tool with sensitive data."""
+        return f"Processed: {data}"
+
     events = capture_events()
 
     await test_agent.run("Use sensitive tool with private data")
@@ -658,7 +730,7 @@ def sensitive_tool(data: str) -> str:
 
 
 @pytest.mark.asyncio
-async def test_multiple_agents_concurrent(sentry_init, capture_events, test_agent):
+async def test_multiple_agents_concurrent(sentry_init, capture_events, get_test_agent):
     """
     Test that multiple agents can run concurrently without interfering.
     """
@@ -669,6 +741,8 @@ async def test_multiple_agents_concurrent(sentry_init, capture_events, test_agen
 
     events = capture_events()
 
+    test_agent = get_test_agent()
+
     async def run_agent(input_text):
         return await test_agent.run(input_text)
 
@@ -739,7 +813,7 @@ async def test_message_history(sentry_init, capture_events):
 
 
 @pytest.mark.asyncio
-async def test_gen_ai_system(sentry_init, capture_events, test_agent):
+async def test_gen_ai_system(sentry_init, capture_events, get_test_agent):
     """
     Test that gen_ai.system is set from the model.
     """
@@ -750,6 +824,7 @@ async def test_gen_ai_system(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     await test_agent.run("Test input")
 
     (transaction,) = events
@@ -766,7 +841,7 @@ async def test_gen_ai_system(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_include_prompts_false(sentry_init, capture_events, test_agent):
+async def test_include_prompts_false(sentry_init, capture_events, get_test_agent):
     """
     Test that prompts are not captured when include_prompts=False.
     """
@@ -778,6 +853,7 @@ async def test_include_prompts_false(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     await test_agent.run("Sensitive prompt")
 
     (transaction,) = events
@@ -793,7 +869,7 @@ async def test_include_prompts_false(sentry_init, capture_events, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_include_prompts_true(sentry_init, capture_events, test_agent):
+async def test_include_prompts_true(sentry_init, capture_events, get_test_agent):
     """
     Test that prompts are captured when include_prompts=True (default).
     """
@@ -805,6 +881,7 @@ async def test_include_prompts_true(sentry_init, capture_events, test_agent):
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     await test_agent.run("Test prompt")
 
     (transaction,) = events
@@ -821,23 +898,24 @@ async def test_include_prompts_true(sentry_init, capture_events, test_agent):
 
 @pytest.mark.asyncio
 async def test_include_prompts_false_with_tools(
-    sentry_init, capture_events, test_agent
+    sentry_init, capture_events, get_test_agent
 ):
     """
     Test that tool input/output are not captured when include_prompts=False.
     """
-
-    @test_agent.tool_plain
-    def test_tool(value: int) -> int:
-        """A test tool."""
-        return value * 2
-
     sentry_init(
         integrations=[PydanticAIIntegration(include_prompts=False)],
         traces_sample_rate=1.0,
         send_default_pii=True,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def test_tool(value: int) -> int:
+        """A test tool."""
+        return value * 2
+
     events = capture_events()
 
     await test_agent.run("Use the test tool with value 5")
@@ -855,7 +933,9 @@ def test_tool(value: int) -> int:
 
 
 @pytest.mark.asyncio
-async def test_include_prompts_requires_pii(sentry_init, capture_events, test_agent):
+async def test_include_prompts_requires_pii(
+    sentry_init, capture_events, get_test_agent
+):
     """
     Test that include_prompts requires send_default_pii=True.
     """
@@ -867,6 +947,7 @@ async def test_include_prompts_requires_pii(sentry_init, capture_events, test_ag
 
     events = capture_events()
 
+    test_agent = get_test_agent()
     await test_agent.run("Test prompt")
 
     (transaction,) = events
@@ -891,7 +972,7 @@ async def test_mcp_tool_execution_spans(sentry_init, capture_events):
     """
     pytest.importorskip("mcp")
 
-    from unittest.mock import AsyncMock, MagicMock
+    from unittest.mock import MagicMock
     from pydantic_ai.mcp import MCPServerStdio
     from pydantic_ai import Agent
     from pydantic_ai.toolsets.combined import CombinedToolset
@@ -1017,7 +1098,7 @@ async def mock_map_tool_result_part(part):
 
 
 @pytest.mark.asyncio
-async def test_context_cleanup_after_run(sentry_init, test_agent):
+async def test_context_cleanup_after_run(sentry_init, get_test_agent):
     """
     Test that the pydantic_ai_agent context is properly cleaned up after agent execution.
     """
@@ -1033,13 +1114,14 @@ async def test_context_cleanup_after_run(sentry_init, test_agent):
     assert "pydantic_ai_agent" not in scope._contexts
 
     # Run the agent
+    test_agent = get_test_agent()
     await test_agent.run("Test input")
 
     # Verify context is cleaned up after run
     assert "pydantic_ai_agent" not in scope._contexts
 
 
-def test_context_cleanup_after_run_sync(sentry_init, test_agent):
+def test_context_cleanup_after_run_sync(sentry_init, get_test_agent):
     """
     Test that the pydantic_ai_agent context is properly cleaned up after sync agent execution.
     """
@@ -1055,6 +1137,7 @@ def test_context_cleanup_after_run_sync(sentry_init, test_agent):
     assert "pydantic_ai_agent" not in scope._contexts
 
     # Run the agent synchronously
+    test_agent = get_test_agent()
     test_agent.run_sync("Test input")
 
     # Verify context is cleaned up after run
@@ -1062,7 +1145,7 @@ def test_context_cleanup_after_run_sync(sentry_init, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_context_cleanup_after_streaming(sentry_init, test_agent):
+async def test_context_cleanup_after_streaming(sentry_init, get_test_agent):
     """
     Test that the pydantic_ai_agent context is properly cleaned up after streaming execution.
     """
@@ -1077,6 +1160,7 @@ async def test_context_cleanup_after_streaming(sentry_init, test_agent):
     scope = sentry_sdk.get_current_scope()
     assert "pydantic_ai_agent" not in scope._contexts
 
+    test_agent = get_test_agent()
     # Run the agent with streaming
     async with test_agent.run_stream("Test input") as result:
         async for _ in result.stream_output():
@@ -1087,23 +1171,25 @@ async def test_context_cleanup_after_streaming(sentry_init, test_agent):
 
 
 @pytest.mark.asyncio
-async def test_context_cleanup_on_error(sentry_init, test_agent):
+async def test_context_cleanup_on_error(sentry_init, get_test_agent):
     """
     Test that the pydantic_ai_agent context is cleaned up even when an error occurs.
     """
     import sentry_sdk
 
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+    )
+
+    test_agent = get_test_agent()
+
     # Create an agent with a tool that raises an error
     @test_agent.tool_plain
     def failing_tool() -> str:
         """A tool that always fails."""
         raise ValueError("Tool error")
 
-    sentry_init(
-        integrations=[PydanticAIIntegration()],
-        traces_sample_rate=1.0,
-    )
-
     # Verify context is not set before run
     scope = sentry_sdk.get_current_scope()
     assert "pydantic_ai_agent" not in scope._contexts
@@ -1119,7 +1205,7 @@ def failing_tool() -> str:
 
 
 @pytest.mark.asyncio
-async def test_context_isolation_concurrent_agents(sentry_init, test_agent):
+async def test_context_isolation_concurrent_agents(sentry_init, get_test_agent):
     """
     Test that concurrent agent executions maintain isolated contexts.
     """
@@ -1152,6 +1238,7 @@ async def run_and_check_context(agent, agent_name):
 
         return agent_name
 
+    test_agent = get_test_agent()
     # Run both agents concurrently
     results = await asyncio.gather(
         run_and_check_context(test_agent, "agent1"),
@@ -1381,7 +1468,6 @@ async def test_agent_data_from_scope(sentry_init, capture_events):
     """
     Test that agent data can be retrieved from Sentry scope when not passed directly.
     """
-    import sentry_sdk
 
     agent = Agent(
         "test",
@@ -1406,22 +1492,23 @@ async def test_agent_data_from_scope(sentry_init, capture_events):
 
 @pytest.mark.asyncio
 async def test_available_tools_without_description(
-    sentry_init, capture_events, test_agent
+    sentry_init, capture_events, get_test_agent
 ):
     """
     Test that available tools are captured even when description is missing.
     """
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+    )
+
+    test_agent = get_test_agent()
 
     @test_agent.tool_plain
     def tool_without_desc(x: int) -> int:
         # No docstring = no description
         return x * 2
 
-    sentry_init(
-        integrations=[PydanticAIIntegration()],
-        traces_sample_rate=1.0,
-    )
-
     events = capture_events()
 
     await test_agent.run("Use the tool with 5")
@@ -1438,22 +1525,23 @@ def tool_without_desc(x: int) -> int:
 
 
 @pytest.mark.asyncio
-async def test_output_with_tool_calls(sentry_init, capture_events, test_agent):
+async def test_output_with_tool_calls(sentry_init, capture_events, get_test_agent):
     """
     Test that tool calls in model response are captured correctly.
     """
-
-    @test_agent.tool_plain
-    def calc_tool(value: int) -> int:
-        """Calculate something."""
-        return value + 10
-
     sentry_init(
         integrations=[PydanticAIIntegration()],
         traces_sample_rate=1.0,
         send_default_pii=True,
     )
 
+    test_agent = get_test_agent()
+
+    @test_agent.tool_plain
+    def calc_tool(value: int) -> int:
+        """Calculate something."""
+        return value + 10
+
     events = capture_events()
 
     await test_agent.run("Use calc_tool with 5")
@@ -1640,7 +1728,6 @@ async def test_input_messages_error_handling(sentry_init, capture_events):
     Test that _set_input_messages handles errors gracefully.
     """
     import sentry_sdk
-    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
 
     sentry_init(
         integrations=[PydanticAIIntegration()],
@@ -1755,7 +1842,7 @@ async def test_message_parts_with_tool_return(sentry_init, capture_events):
     """
     Test that ToolReturnPart messages are handled correctly.
     """
-    from pydantic_ai import Agent, messages
+    from pydantic_ai import Agent
 
     agent = Agent(
         "test",
@@ -1794,7 +1881,6 @@ async def test_message_parts_with_list_content(sentry_init, capture_events):
     """
     import sentry_sdk
     from unittest.mock import MagicMock
-    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
 
     sentry_init(
         integrations=[PydanticAIIntegration()],
@@ -1901,7 +1987,6 @@ async def test_message_with_system_prompt_part(sentry_init, capture_events):
     """
     import sentry_sdk
     from unittest.mock import MagicMock
-    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
     from pydantic_ai import messages
 
     sentry_init(
@@ -1938,7 +2023,6 @@ async def test_message_with_instructions(sentry_init, capture_events):
     """
     import sentry_sdk
     from unittest.mock import MagicMock
-    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
 
     sentry_init(
         integrations=[PydanticAIIntegration()],
@@ -1973,7 +2057,6 @@ async def test_set_input_messages_without_prompts(sentry_init, capture_events):
     Test that _set_input_messages respects _should_send_prompts().
     """
     import sentry_sdk
-    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import _set_input_messages
 
     sentry_init(
         integrations=[PydanticAIIntegration(include_prompts=False)],
@@ -2386,7 +2469,9 @@ async def test_execute_tool_span_with_mcp_type(sentry_init, capture_events):
     Test execute_tool span with MCP tool type.
     """
     import sentry_sdk
-    from sentry_sdk.integrations.pydantic_ai.spans.execute_tool import execute_tool_span
+    from sentry_sdk.integrations.pydantic_ai.spans.execute_tool import (
+        execute_tool_span,
+    )
 
     sentry_init(
         integrations=[PydanticAIIntegration()],
@@ -2509,7 +2594,6 @@ async def test_tool_execution_without_span_context(sentry_init, capture_events):
     This tests the code path where current_span is None in _patch_tool_execution.
     """
     # Import the patching function
-    from unittest.mock import AsyncMock, MagicMock
 
     sentry_init(
         integrations=[PydanticAIIntegration()],
@@ -2794,3 +2878,186 @@ async def test_set_usage_data_with_cache_tokens(sentry_init, capture_events):
     (span_data,) = event["spans"]
     assert span_data["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHED] == 80
     assert span_data["data"][SPANDATA.GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE] == 20
+
+
+@pytest.mark.parametrize(
+    "url,image_url_kwargs,expected_content",
+    [
+        pytest.param(
+            "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {},
+            BLOB_DATA_SUBSTITUTE,
+            id="base64_data_url",
+        ),
+        pytest.param(
+            "https://example.com/image.png",
+            {},
+            "https://example.com/image.png",
+            id="http_url_no_redaction",
+        ),
+        pytest.param(
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {"media_type": "image/png"},
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            id="http_url_with_base64_query_param",
+        ),
+        pytest.param(
+            "data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciLz4=",
+            {},
+            BLOB_DATA_SUBSTITUTE,
+            id="complex_mime_type",
+        ),
+        pytest.param(
+            "data:image/png;name=file.png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {},
+            BLOB_DATA_SUBSTITUTE,
+            id="optional_parameters",
+        ),
+        pytest.param(
+            "data:text/plain;charset=utf-8;name=hello.txt;base64,SGVsbG8sIFdvcmxkIQ==",
+            {},
+            BLOB_DATA_SUBSTITUTE,
+            id="multiple_optional_parameters",
+        ),
+    ],
+)
+def test_image_url_base64_content_in_span(
+    sentry_init, capture_events, url, image_url_kwargs, expected_content
+):
+    from sentry_sdk.integrations.pydantic_ai.spans.ai_client import ai_client_span
+
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+
+    events = capture_events()
+
+    with sentry_sdk.start_transaction(op="test", name="test"):
+        image_url = ImageUrl(url=url, **image_url_kwargs)
+        user_part = UserPromptPart(content=["Look at this image:", image_url])
+        mock_msg = MagicMock()
+        mock_msg.parts = [user_part]
+        mock_msg.instructions = None
+
+        span = ai_client_span([mock_msg], None, None, None)
+        span.finish()
+
+    (event,) = events
+    chat_spans = [s for s in event["spans"] if s["op"] == "gen_ai.chat"]
+    assert len(chat_spans) >= 1
+    messages_data = _get_messages_from_span(chat_spans[0]["data"])
+
+    found_image = False
+    for msg in messages_data:
+        if "content" not in msg:
+            continue
+        for content_item in msg["content"]:
+            if content_item.get("type") == "image":
+                found_image = True
+                assert content_item["content"] == expected_content
+
+    assert found_image, "Image content item should be found in messages data"
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "url, image_url_kwargs, expected_content",
+    [
+        pytest.param(
+            "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {},
+            BLOB_DATA_SUBSTITUTE,
+            id="base64_data_url_redacted",
+        ),
+        pytest.param(
+            "https://example.com/image.png",
+            {},
+            "https://example.com/image.png",
+            id="http_url_no_redaction",
+        ),
+        pytest.param(
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {},
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            id="http_url_with_base64_query_param",
+        ),
+        pytest.param(
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            {"media_type": "image/png"},
+            "https://example.com/api?data=iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs",
+            id="http_url_with_base64_query_param_and_media_type",
+        ),
+    ],
+)
+async def test_invoke_agent_image_url(
+    sentry_init, capture_events, url, image_url_kwargs, expected_content
+):
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+
+    agent = Agent("test", name="test_image_url_agent")
+
+    events = capture_events()
+    image_url = ImageUrl(url=url, **image_url_kwargs)
+    await agent.run([image_url, "Describe this image"])
+
+    (transaction,) = events
+
+    found_image = False
+
+    chat_spans = [s for s in transaction["spans"] if s["op"] == "gen_ai.chat"]
+    for chat_span in chat_spans:
+        messages_data = _get_messages_from_span(chat_span["data"])
+        for msg in messages_data:
+            if "content" not in msg:
+                continue
+            for content_item in msg["content"]:
+                if content_item.get("type") == "image":
+                    assert content_item["content"] == expected_content
+                    found_image = True
+
+    assert found_image, "Image content item should be found in messages data"
+
+
+@pytest.mark.asyncio
+async def test_tool_description_in_execute_tool_span(sentry_init, capture_events):
+    """
+    Test that tool description from the tool's docstring is included in execute_tool spans.
+    """
+    agent = Agent(
+        "test",
+        name="test_agent",
+        system_prompt="You are a helpful test assistant.",
+    )
+
+    @agent.tool_plain
+    def multiply_numbers(a: int, b: int) -> int:
+        """Multiply two numbers and return the product."""
+        return a * b
+
+    sentry_init(
+        integrations=[PydanticAIIntegration()],
+        traces_sample_rate=1.0,
+        send_default_pii=True,
+    )
+
+    events = capture_events()
+
+    result = await agent.run("What is 5 times 3?")
+    assert result is not None
+
+    (transaction,) = events
+    spans = transaction["spans"]
+
+    tool_spans = [s for s in spans if s["op"] == "gen_ai.execute_tool"]
+    assert len(tool_spans) >= 1
+
+    tool_span = tool_spans[0]
+    assert tool_span["data"]["gen_ai.tool.name"] == "multiply_numbers"
+    assert SPANDATA.GEN_AI_TOOL_DESCRIPTION in tool_span["data"]
+    assert "Multiply two numbers" in tool_span["data"][SPANDATA.GEN_AI_TOOL_DESCRIPTION]
diff --git a/tests/integrations/pymongo/test_pymongo.py b/tests/integrations/pymongo/test_pymongo.py
index 0669f73c30..b57061b0a0 100644
--- a/tests/integrations/pymongo/test_pymongo.py
+++ b/tests/integrations/pymongo/test_pymongo.py
@@ -52,11 +52,13 @@ def test_transactions(sentry_init, capture_events, mongo_server, with_pii):
     common_tags = {
         "db.name": "test_db",
         "db.system": "mongodb",
+        "db.driver.name": "pymongo",
         "net.peer.name": mongo_server.host,
         "net.peer.port": str(mongo_server.port),
     }
     for span in find, insert_success, insert_fail:
         assert span["data"][SPANDATA.DB_SYSTEM] == "mongodb"
+        assert span["data"][SPANDATA.DB_DRIVER_NAME] == "pymongo"
         assert span["data"][SPANDATA.DB_NAME] == "test_db"
         assert span["data"][SPANDATA.SERVER_ADDRESS] == "localhost"
         assert span["data"][SPANDATA.SERVER_PORT] == mongo_server.port
@@ -136,6 +138,7 @@ def test_breadcrumbs(sentry_init, capture_events, mongo_server, with_pii):
     assert crumb["data"] == {
         "db.name": "test_db",
         "db.system": "mongodb",
+        "db.driver.name": "pymongo",
         "db.operation": "find",
         "net.peer.name": mongo_server.host,
         "net.peer.port": str(mongo_server.port),
diff --git a/tests/integrations/pyramid/test_pyramid.py b/tests/integrations/pyramid/test_pyramid.py
index cd200f7f7b..95efe8172b 100644
--- a/tests/integrations/pyramid/test_pyramid.py
+++ b/tests/integrations/pyramid/test_pyramid.py
@@ -6,6 +6,7 @@
 import pytest
 from pyramid.authorization import ACLAuthorizationPolicy
 from pyramid.response import Response
+from packaging.version import Version
 from werkzeug.test import Client
 
 from sentry_sdk import capture_message, add_breadcrumb
@@ -18,7 +19,7 @@
 try:
     from importlib.metadata import version
 
-    PYRAMID_VERSION = tuple(map(int, version("pyramid").split(".")))
+    PYRAMID_VERSION = Version(version("pyramid")).release
 
 except ImportError:
     # < py3.8
diff --git a/tests/integrations/pyreqwest/__init__.py b/tests/integrations/pyreqwest/__init__.py
new file mode 100644
index 0000000000..dfdd787852
--- /dev/null
+++ b/tests/integrations/pyreqwest/__init__.py
@@ -0,0 +1,9 @@
+import os
+import sys
+import pytest
+
+pytest.importorskip("pyreqwest")
+
+# Load `pyreqwest_helpers` into the module search path to test request source path names relative to module. See
+# `test_request_source_with_module_in_search_path`
+sys.path.insert(0, os.path.join(os.path.dirname(__file__)))
diff --git a/tests/integrations/pyreqwest/pyreqwest_helpers/__init__.py b/tests/integrations/pyreqwest/pyreqwest_helpers/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/tests/integrations/pyreqwest/pyreqwest_helpers/helpers.py b/tests/integrations/pyreqwest/pyreqwest_helpers/helpers.py
new file mode 100644
index 0000000000..3abc554522
--- /dev/null
+++ b/tests/integrations/pyreqwest/pyreqwest_helpers/helpers.py
@@ -0,0 +1,2 @@
+def get_request_with_client(client, url):
+    client.get(url).build().send()
diff --git a/tests/integrations/pyreqwest/test_pyreqwest.py b/tests/integrations/pyreqwest/test_pyreqwest.py
new file mode 100644
index 0000000000..ad20e2b08a
--- /dev/null
+++ b/tests/integrations/pyreqwest/test_pyreqwest.py
@@ -0,0 +1,484 @@
+import datetime
+import os
+from contextlib import contextmanager
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from threading import Thread
+from unittest import mock
+import pytest
+
+from pyreqwest.client import ClientBuilder, SyncClientBuilder
+from pyreqwest.simple.request import pyreqwest_get as async_pyreqwest_get
+from pyreqwest.simple.sync_request import pyreqwest_get as sync_pyreqwest_get
+
+import sentry_sdk
+from sentry_sdk import start_transaction
+from sentry_sdk.consts import MATCH_ALL, SPANDATA
+from sentry_sdk.integrations.pyreqwest import PyreqwestIntegration
+from tests.conftest import get_free_port
+
+
+class PyreqwestMockHandler(BaseHTTPRequestHandler):
+    captured_requests = []
+
+    def do_GET(self) -> None:
+        self.captured_requests.append(
+            {
+                "path": self.path,
+                "headers": {k.lower(): v for k, v in self.headers.items()},
+            }
+        )
+
+        code = 200
+        if "/status/" in self.path:
+            try:
+                code = int(self.path.split("/")[-1])
+            except (ValueError, IndexError):
+                code = 200
+
+        self.send_response(code)
+        self.end_headers()
+        self.wfile.write(b"OK")
+
+    def log_message(self, format: str, *args: object) -> None:
+        pass
+
+
+@pytest.fixture(scope="module")
+def server_port():
+    port = get_free_port()
+    server = HTTPServer(("localhost", port), PyreqwestMockHandler)
+    thread = Thread(target=server.serve_forever)
+    thread.daemon = True
+    thread.start()
+    yield port
+    server.shutdown()
+
+
+@pytest.fixture(autouse=True)
+def clear_captured_requests():
+    PyreqwestMockHandler.captured_requests.clear()
+
+
+def test_sync_client_spans(sentry_init, capture_events, server_port):
+    sentry_init(integrations=[PyreqwestIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello?q=test#frag"
+    with start_transaction(name="test_transaction"):
+        client = SyncClientBuilder().build()
+        response = client.get(url).build().send()
+        assert response.status == 200
+
+    (event,) = events
+    assert len(event["spans"]) == 1
+    span = event["spans"][0]
+    assert span["op"] == "http.client"
+    assert span["description"] == f"GET http://localhost:{server_port}/hello"
+    assert span["data"]["url"] == f"http://localhost:{server_port}/hello"
+    assert span["data"][SPANDATA.HTTP_METHOD] == "GET"
+    assert span["data"][SPANDATA.HTTP_STATUS_CODE] == 200
+    assert span["data"][SPANDATA.HTTP_QUERY] == "q=test"
+    assert span["data"][SPANDATA.HTTP_FRAGMENT] == "frag"
+    assert span["origin"] == "auto.http.pyreqwest"
+
+
+@pytest.mark.asyncio
+async def test_async_client_spans(sentry_init, capture_events, server_port):
+    sentry_init(integrations=[PyreqwestIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+    async with ClientBuilder().build() as client:
+        with start_transaction(name="test_transaction"):
+            response = await client.get(url).build().send()
+            assert response.status == 200
+
+    (event,) = events
+    assert len(event["spans"]) == 1
+    span = event["spans"][0]
+    assert span["op"] == "http.client"
+    assert span["description"] == f"GET {url}"
+    assert span["data"]["url"] == url
+    assert span["data"][SPANDATA.HTTP_METHOD] == "GET"
+    assert span["data"][SPANDATA.HTTP_STATUS_CODE] == 200
+    assert span["origin"] == "auto.http.pyreqwest"
+
+
+def test_sync_simple_request_spans(sentry_init, capture_events, server_port):
+    sentry_init(integrations=[PyreqwestIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello-simple"
+    with start_transaction(name="test_transaction"):
+        response = sync_pyreqwest_get(url).send()
+        assert response.status == 200
+
+    (event,) = events
+    assert len(event["spans"]) == 1
+    span = event["spans"][0]
+    assert span["op"] == "http.client"
+    assert span["description"] == f"GET {url}"
+    assert span["data"]["url"] == url
+    assert span["data"][SPANDATA.HTTP_METHOD] == "GET"
+    assert span["data"][SPANDATA.HTTP_STATUS_CODE] == 200
+    assert span["origin"] == "auto.http.pyreqwest"
+
+
+@pytest.mark.asyncio
+async def test_async_simple_request_spans(sentry_init, capture_events, server_port):
+    sentry_init(integrations=[PyreqwestIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello-simple-async"
+    with start_transaction(name="test_transaction"):
+        response = await async_pyreqwest_get(url).send()
+        assert response.status == 200
+
+    (event,) = events
+    assert len(event["spans"]) == 1
+    span = event["spans"][0]
+    assert span["op"] == "http.client"
+    assert span["description"] == f"GET {url}"
+    assert span["data"]["url"] == url
+    assert span["data"][SPANDATA.HTTP_METHOD] == "GET"
+    assert span["data"][SPANDATA.HTTP_STATUS_CODE] == 200
+    assert span["origin"] == "auto.http.pyreqwest"
+
+
+def test_span_origin(sentry_init, capture_events, server_port):
+    sentry_init(integrations=[PyreqwestIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/origin"
+    with start_transaction(name="test_transaction"):
+        client = SyncClientBuilder().build()
+        client.get(url).build().send()
+
+    (event,) = events
+    assert event["spans"][0]["origin"] == "auto.http.pyreqwest"
+
+
+def test_outgoing_trace_headers(sentry_init, server_port):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        trace_propagation_targets=["localhost"],
+    )
+
+    url = f"http://localhost:{server_port}/trace"
+    with start_transaction(
+        name="test_transaction", trace_id="01234567890123456789012345678901"
+    ):
+        client = SyncClientBuilder().build()
+        response = client.get(url).build().send()
+        assert response.status == 200
+
+    assert len(PyreqwestMockHandler.captured_requests) == 1
+    headers = PyreqwestMockHandler.captured_requests[0]["headers"]
+
+    assert "sentry-trace" in headers
+    assert headers["sentry-trace"].startswith("01234567890123456789012345678901")
+    assert "baggage" in headers
+    assert "sentry-trace_id=01234567890123456789012345678901" in headers["baggage"]
+
+
+def test_outgoing_trace_headers_append_to_baggage(sentry_init, server_port):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        trace_propagation_targets=["localhost"],
+        release="d08ebdb9309e1b004c6f52202de58a09c2268e42",
+    )
+
+    url = f"http://localhost:{server_port}/baggage"
+
+    with mock.patch("sentry_sdk.tracing_utils.Random.randrange", return_value=500000):
+        with start_transaction(
+            name="/interactions/other-dogs/new-dog",
+            op="greeting.sniff",
+            trace_id="01234567890123456789012345678901",
+        ):
+            client = SyncClientBuilder().build()
+            client.get(url).header("baggage", "custom=data").build().send()
+
+    assert len(PyreqwestMockHandler.captured_requests) == 1
+    headers = PyreqwestMockHandler.captured_requests[0]["headers"]
+
+    assert "baggage" in headers
+    baggage = headers["baggage"]
+    assert "custom=data" in baggage
+    assert "sentry-trace_id=01234567890123456789012345678901" in baggage
+    assert "sentry-sample_rand=0.500000" in baggage
+    assert "sentry-environment=production" in baggage
+    assert "sentry-release=d08ebdb9309e1b004c6f52202de58a09c2268e42" in baggage
+    assert "sentry-transaction=/interactions/other-dogs/new-dog" in baggage
+    assert "sentry-sample_rate=1.0" in baggage
+    assert "sentry-sampled=true" in baggage
+
+
+@pytest.mark.parametrize(
+    "trace_propagation_targets,trace_propagated",
+    [
+        [None, False],
+        [[], False],
+        [[MATCH_ALL], True],
+        [["localhost"], True],
+        [[r"https?:\/\/[\w\-]+(\.[\w\-]+)+\.net"], False],
+    ],
+)
+def test_trace_propagation_targets(
+    sentry_init, server_port, trace_propagation_targets, trace_propagated
+):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        trace_propagation_targets=trace_propagation_targets,
+        traces_sample_rate=1.0,
+    )
+
+    url = f"http://localhost:{server_port}/propagation"
+
+    with start_transaction():
+        client = SyncClientBuilder().build()
+        client.get(url).build().send()
+
+    assert len(PyreqwestMockHandler.captured_requests) == 1
+    headers = PyreqwestMockHandler.captured_requests[0]["headers"]
+
+    if trace_propagated:
+        assert "sentry-trace" in headers
+    else:
+        assert "sentry-trace" not in headers
+
+
+@pytest.mark.tests_internal_exceptions
+def test_omit_url_data_if_parsing_fails(sentry_init, capture_events, server_port):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/parse-fail"
+
+    with start_transaction(name="test_transaction"):
+        with mock.patch(
+            "sentry_sdk.integrations.pyreqwest.parse_url",
+            side_effect=ValueError,
+        ):
+            client = SyncClientBuilder().build()
+            client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][0]
+
+    assert span["description"] == "GET [Filtered]"
+    assert span["data"][SPANDATA.HTTP_METHOD] == "GET"
+    assert span["data"][SPANDATA.HTTP_STATUS_CODE] == 200
+    assert "url" not in span["data"]
+    assert SPANDATA.HTTP_QUERY not in span["data"]
+    assert SPANDATA.HTTP_FRAGMENT not in span["data"]
+
+
+def test_request_source_disabled(sentry_init, capture_events, server_port):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        enable_http_request_source=False,
+        http_request_source_threshold_ms=0,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+        client = SyncClientBuilder().build()
+        client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][0]
+    data = span.get("data", {})
+
+    assert SPANDATA.CODE_LINENO not in data
+    assert SPANDATA.CODE_NAMESPACE not in data
+    assert SPANDATA.CODE_FILEPATH not in data
+    assert SPANDATA.CODE_FUNCTION not in data
+
+
+@pytest.mark.parametrize("enable_http_request_source", [None, True])
+def test_request_source_enabled(
+    sentry_init, capture_events, server_port, enable_http_request_source
+):
+    sentry_options = {
+        "integrations": [PyreqwestIntegration()],
+        "traces_sample_rate": 1.0,
+        "http_request_source_threshold_ms": 0,
+    }
+    if enable_http_request_source is not None:
+        sentry_options["enable_http_request_source"] = enable_http_request_source
+
+    sentry_init(**sentry_options)
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+        client = SyncClientBuilder().build()
+        client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][0]
+    data = span.get("data", {})
+
+    assert SPANDATA.CODE_LINENO in data
+    assert SPANDATA.CODE_NAMESPACE in data
+    assert SPANDATA.CODE_FILEPATH in data
+    assert SPANDATA.CODE_FUNCTION in data
+
+
+def test_request_source(sentry_init, capture_events, server_port):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        enable_http_request_source=True,
+        http_request_source_threshold_ms=0,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+        client = SyncClientBuilder().build()
+        client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][0]
+    data = span.get("data", {})
+
+    assert type(data.get(SPANDATA.CODE_LINENO)) == int
+    assert data.get(SPANDATA.CODE_LINENO) > 0
+    assert (
+        data.get(SPANDATA.CODE_NAMESPACE)
+        == "tests.integrations.pyreqwest.test_pyreqwest"
+    )
+    assert data.get(SPANDATA.CODE_FILEPATH).endswith(
+        "tests/integrations/pyreqwest/test_pyreqwest.py"
+    )
+
+    is_relative_path = data.get(SPANDATA.CODE_FILEPATH)[0] != os.sep
+    assert is_relative_path
+
+    assert data.get(SPANDATA.CODE_FUNCTION) == "test_request_source"
+
+
+def test_request_source_with_module_in_search_path(
+    sentry_init, capture_events, server_port
+):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        enable_http_request_source=True,
+        http_request_source_threshold_ms=0,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+        from pyreqwest_helpers.helpers import get_request_with_client
+
+        client = SyncClientBuilder().build()
+        get_request_with_client(client, url)
+
+    (event,) = events
+    span = event["spans"][0]
+    data = span.get("data", {})
+
+    assert type(data.get(SPANDATA.CODE_LINENO)) == int
+    assert data.get(SPANDATA.CODE_LINENO) > 0
+    assert data.get(SPANDATA.CODE_NAMESPACE) == "pyreqwest_helpers.helpers"
+    assert data.get(SPANDATA.CODE_FILEPATH) == "pyreqwest_helpers/helpers.py"
+
+    is_relative_path = data.get(SPANDATA.CODE_FILEPATH)[0] != os.sep
+    assert is_relative_path
+
+    assert data.get(SPANDATA.CODE_FUNCTION) == "get_request_with_client"
+
+
+def test_no_request_source_if_duration_too_short(
+    sentry_init, capture_events, server_port
+):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        enable_http_request_source=True,
+        http_request_source_threshold_ms=100,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+
+        @contextmanager
+        def fake_start_span(*args, **kwargs):
+            with sentry_sdk.start_span(*args, **kwargs) as span:
+                pass
+            span.start_timestamp = datetime.datetime(2024, 1, 1, microsecond=0)
+            span.timestamp = datetime.datetime(2024, 1, 1, microsecond=99999)
+            yield span
+
+        with mock.patch(
+            "sentry_sdk.integrations.pyreqwest.start_span",
+            fake_start_span,
+        ):
+            client = SyncClientBuilder().build()
+            client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][-1]
+    data = span.get("data", {})
+
+    assert SPANDATA.CODE_LINENO not in data
+    assert SPANDATA.CODE_NAMESPACE not in data
+    assert SPANDATA.CODE_FILEPATH not in data
+    assert SPANDATA.CODE_FUNCTION not in data
+
+
+def test_request_source_if_duration_over_threshold(
+    sentry_init, capture_events, server_port
+):
+    sentry_init(
+        integrations=[PyreqwestIntegration()],
+        traces_sample_rate=1.0,
+        enable_http_request_source=True,
+        http_request_source_threshold_ms=100,
+    )
+    events = capture_events()
+
+    url = f"http://localhost:{server_port}/hello"
+
+    with start_transaction(name="test_transaction"):
+
+        @contextmanager
+        def fake_start_span(*args, **kwargs):
+            with sentry_sdk.start_span(*args, **kwargs) as span:
+                pass
+            span.start_timestamp = datetime.datetime(2024, 1, 1, microsecond=0)
+            span.timestamp = datetime.datetime(2024, 1, 1, microsecond=100001)
+            yield span
+
+        with mock.patch(
+            "sentry_sdk.integrations.pyreqwest.start_span",
+            fake_start_span,
+        ):
+            client = SyncClientBuilder().build()
+            client.get(url).build().send()
+
+    (event,) = events
+    span = event["spans"][-1]
+    data = span.get("data", {})
+
+    assert SPANDATA.CODE_LINENO in data
+    assert SPANDATA.CODE_NAMESPACE in data
+    assert SPANDATA.CODE_FILEPATH in data
+    assert SPANDATA.CODE_FUNCTION in data
diff --git a/tests/integrations/redis/test_redis.py b/tests/integrations/redis/test_redis.py
index 1861e7116f..84c5699d14 100644
--- a/tests/integrations/redis/test_redis.py
+++ b/tests/integrations/redis/test_redis.py
@@ -262,6 +262,7 @@ def test_db_connection_attributes_client(sentry_init, capture_events):
     assert span["op"] == "db.redis"
     assert span["description"] == "GET 'foobar'"
     assert span["data"][SPANDATA.DB_SYSTEM] == "redis"
+    assert span["data"][SPANDATA.DB_DRIVER_NAME] == "redis-py"
     assert span["data"][SPANDATA.DB_NAME] == "1"
     assert span["data"][SPANDATA.SERVER_ADDRESS] == "localhost"
     assert span["data"][SPANDATA.SERVER_PORT] == 63791
@@ -288,6 +289,7 @@ def test_db_connection_attributes_pipeline(sentry_init, capture_events):
     assert span["op"] == "db.redis"
     assert span["description"] == "redis.pipeline.execute"
     assert span["data"][SPANDATA.DB_SYSTEM] == "redis"
+    assert span["data"][SPANDATA.DB_DRIVER_NAME] == "redis-py"
     assert span["data"][SPANDATA.DB_NAME] == "1"
     assert span["data"][SPANDATA.SERVER_ADDRESS] == "localhost"
     assert span["data"][SPANDATA.SERVER_PORT] == 63791
diff --git a/tests/integrations/rust_tracing/test_rust_tracing.py b/tests/integrations/rust_tracing/test_rust_tracing.py
index 893fc86966..a3e367f7e9 100644
--- a/tests/integrations/rust_tracing/test_rust_tracing.py
+++ b/tests/integrations/rust_tracing/test_rust_tracing.py
@@ -78,7 +78,7 @@ def test_on_new_span_on_close(sentry_init, capture_events):
         rust_tracing.new_span(RustTracingLevel.Info, 3)
 
         sentry_first_rust_span = sentry_sdk.get_current_span()
-        _, rust_first_rust_span = rust_tracing.spans[3]
+        rust_first_rust_span = rust_tracing.spans[3]
 
         assert sentry_first_rust_span == rust_first_rust_span
 
@@ -120,24 +120,22 @@ def test_nested_on_new_span_on_close(sentry_init, capture_events):
 
         rust_tracing.new_span(RustTracingLevel.Info, 3, index_arg=10)
         sentry_first_rust_span = sentry_sdk.get_current_span()
-        _, rust_first_rust_span = rust_tracing.spans[3]
+        rust_first_rust_span = rust_tracing.spans[3]
 
         # Use a different `index_arg` value for the inner span to help
         # distinguish the two at the end of the test
         rust_tracing.new_span(RustTracingLevel.Info, 5, index_arg=9)
         sentry_second_rust_span = sentry_sdk.get_current_span()
-        rust_parent_span, rust_second_rust_span = rust_tracing.spans[5]
+        rust_second_rust_span = rust_tracing.spans[5]
 
         assert rust_second_rust_span == sentry_second_rust_span
-        assert rust_parent_span == sentry_first_rust_span
-        assert rust_parent_span == rust_first_rust_span
-        assert rust_parent_span != rust_second_rust_span
 
         rust_tracing.close_span(5)
 
         # Ensure the current sentry span was moved back to the parent
         sentry_span_after_close = sentry_sdk.get_current_span()
         assert sentry_span_after_close == sentry_first_rust_span
+        assert sentry_span_after_close == rust_first_rust_span
 
         rust_tracing.close_span(3)
 
diff --git a/tests/integrations/sqlalchemy/test_sqlalchemy.py b/tests/integrations/sqlalchemy/test_sqlalchemy.py
index d2a31a55d5..7c7ce3d845 100644
--- a/tests/integrations/sqlalchemy/test_sqlalchemy.py
+++ b/tests/integrations/sqlalchemy/test_sqlalchemy.py
@@ -127,6 +127,7 @@ class Address(Base):
 
     for span in event["spans"]:
         assert span["data"][SPANDATA.DB_SYSTEM] == "sqlite"
+        assert span["data"][SPANDATA.DB_DRIVER_NAME] == "pysqlite"
         assert span["data"][SPANDATA.DB_NAME] == ":memory:"
         assert SPANDATA.SERVER_ADDRESS not in span["data"]
         assert SPANDATA.SERVER_PORT not in span["data"]
@@ -201,6 +202,7 @@ class Address(Base):
 
     for span in event["spans"]:
         assert span["data"][SPANDATA.DB_SYSTEM] == "sqlite"
+        assert span["data"][SPANDATA.DB_DRIVER_NAME] == "pysqlite"
         assert SPANDATA.DB_NAME not in span["data"]
         assert SPANDATA.SERVER_ADDRESS not in span["data"]
         assert SPANDATA.SERVER_PORT not in span["data"]
@@ -301,7 +303,7 @@ def test_engine_name_not_string(sentry_init):
 def test_query_source_disabled(sentry_init, capture_events):
     sentry_options = {
         "integrations": [SqlalchemyIntegration()],
-        "enable_tracing": True,
+        "traces_sample_rate": 1.0,
         "enable_db_query_source": False,
         "db_query_source_threshold_ms": 0,
     }
@@ -352,7 +354,7 @@ class Person(Base):
 def test_query_source_enabled(sentry_init, capture_events, enable_db_query_source):
     sentry_options = {
         "integrations": [SqlalchemyIntegration()],
-        "enable_tracing": True,
+        "traces_sample_rate": 1.0,
         "db_query_source_threshold_ms": 0,
     }
     if enable_db_query_source is not None:
@@ -403,7 +405,7 @@ class Person(Base):
 def test_query_source(sentry_init, capture_events):
     sentry_init(
         integrations=[SqlalchemyIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=0,
     )
@@ -468,7 +470,7 @@ def test_query_source_with_module_in_search_path(sentry_init, capture_events):
     """
     sentry_init(
         integrations=[SqlalchemyIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=0,
     )
@@ -531,7 +533,7 @@ class Person(Base):
 def test_no_query_source_if_duration_too_short(sentry_init, capture_events):
     sentry_init(
         integrations=[SqlalchemyIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=100,
     )
@@ -597,7 +599,7 @@ def __exit__(self, type, value, traceback):
 def test_query_source_if_duration_over_threshold(sentry_init, capture_events):
     sentry_init(
         integrations=[SqlalchemyIntegration()],
-        enable_tracing=True,
+        traces_sample_rate=1.0,
         enable_db_query_source=True,
         db_query_source_threshold_ms=100,
     )
diff --git a/tests/integrations/stdlib/test_httplib.py b/tests/integrations/stdlib/test_httplib.py
index ad6b0688b9..cdbf6cd68c 100644
--- a/tests/integrations/stdlib/test_httplib.py
+++ b/tests/integrations/stdlib/test_httplib.py
@@ -1,6 +1,5 @@
 import os
 import datetime
-import socket
 from http.client import HTTPConnection, HTTPSConnection
 from http.server import BaseHTTPRequestHandler, HTTPServer
 from socket import SocketIO
diff --git a/tests/integrations/strawberry/test_strawberry.py b/tests/integrations/strawberry/test_strawberry.py
index ba645da257..d3174ed857 100644
--- a/tests/integrations/strawberry/test_strawberry.py
+++ b/tests/integrations/strawberry/test_strawberry.py
@@ -5,7 +5,6 @@
 pytest.importorskip("fastapi")
 pytest.importorskip("flask")
 
-from unittest import mock
 
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
diff --git a/tests/integrations/wsgi/test_wsgi.py b/tests/integrations/wsgi/test_wsgi.py
index 1878be4866..a95a1d63fa 100644
--- a/tests/integrations/wsgi/test_wsgi.py
+++ b/tests/integrations/wsgi/test_wsgi.py
@@ -6,7 +6,11 @@
 
 import sentry_sdk
 from sentry_sdk import capture_message
-from sentry_sdk.integrations.wsgi import SentryWsgiMiddleware, _ScopedResponse
+from sentry_sdk.integrations.wsgi import (
+    SentryWsgiMiddleware,
+    _ScopedResponse,
+    get_request_url,
+)
 
 
 @pytest.fixture
@@ -135,26 +139,50 @@ def test_keyboard_interrupt_is_captured(sentry_init, capture_events):
     assert event["level"] == "error"
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_transaction_with_error(
     sentry_init,
     crashing_app,
     capture_events,
+    capture_items,
     DictionaryContaining,  # noqa:N803
+    span_streaming,
 ):
     def dogpark(environ, start_response):
         raise ValueError("Fetch aborted. The ball was not returned.")
 
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(dogpark)
     client = Client(app)
-    events = capture_events()
+
+    if span_streaming:
+        items = capture_items("event", "span")
+    else:
+        events = capture_events()
 
     with pytest.raises(ValueError):
         client.get("http://dogs.are.great/sit/stay/rollover/")
 
-    error_event, envelope = events
+    sentry_sdk.flush()
+
+    if span_streaming:
+        assert len(items) == 2
+        assert items[0].type == "event"
+        assert items[1].type == "span"
+
+        error_event = items[0].payload
+        span_item = items[1].payload
+    else:
+        error_event, envelope = events
+
+        assert error_event["transaction"] == "generic WSGI request"
 
-    assert error_event["transaction"] == "generic WSGI request"
     assert error_event["contexts"]["trace"]["op"] == "http.server"
     assert error_event["exception"]["values"][0]["type"] == "ValueError"
     assert error_event["exception"]["values"][0]["mechanism"]["type"] == "wsgi"
@@ -164,75 +192,145 @@ def dogpark(environ, start_response):
         == "Fetch aborted. The ball was not returned."
     )
 
-    assert envelope["type"] == "transaction"
+    if span_streaming:
+        assert span_item["trace_id"] == error_event["contexts"]["trace"]["trace_id"]
+        assert span_item["span_id"] == error_event["contexts"]["trace"]["span_id"]
+        assert span_item["status"] == "error"
+    else:
+        assert envelope["type"] == "transaction"
 
-    # event trace context is a subset of envelope trace context
-    assert envelope["contexts"]["trace"] == DictionaryContaining(
-        error_event["contexts"]["trace"]
-    )
-    assert envelope["contexts"]["trace"]["status"] == "internal_error"
-    assert envelope["transaction"] == error_event["transaction"]
-    assert envelope["request"] == error_event["request"]
+        # event trace context is a subset of envelope trace context
+        assert envelope["contexts"]["trace"] == DictionaryContaining(
+            error_event["contexts"]["trace"]
+        )
+        assert envelope["contexts"]["trace"]["status"] == "internal_error"
+        assert envelope["transaction"] == error_event["transaction"]
+        assert envelope["request"] == error_event["request"]
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_transaction_no_error(
     sentry_init,
     capture_events,
+    capture_items,
     DictionaryContaining,  # noqa:N803
+    span_streaming,
 ):
     def dogpark(environ, start_response):
         start_response("200 OK", [])
         return ["Go get the ball! Good dog!"]
 
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(dogpark)
     client = Client(app)
-    events = capture_events()
+
+    if span_streaming:
+        items = capture_items("span")
+    else:
+        events = capture_events()
 
     client.get("/dogs/are/great/")
 
-    envelope = events[0]
+    sentry_sdk.flush()
 
-    assert envelope["type"] == "transaction"
-    assert envelope["transaction"] == "generic WSGI request"
-    assert envelope["contexts"]["trace"]["op"] == "http.server"
-    assert envelope["request"] == DictionaryContaining(
-        {"method": "GET", "url": "http://localhost/dogs/are/great/"}
-    )
+    if span_streaming:
+        assert len(items) == 1
+        span = items[0].payload
+
+        assert span["is_segment"] is True
+        assert span["name"] == "generic WSGI request"
+        assert span["attributes"]["sentry.op"] == "http.server"
+        assert span["attributes"]["sentry.span.source"] == "route"
+        assert span["attributes"]["http.request.method"] == "GET"
+        assert span["attributes"]["url.full"] == "http://localhost/dogs/are/great/"
+        assert span["attributes"]["http.response.status_code"] == 200
+        assert span["status"] == "ok"
+    else:
+        envelope = events[0]
+
+        assert envelope["type"] == "transaction"
+        assert envelope["transaction"] == "generic WSGI request"
+        assert envelope["contexts"]["trace"]["op"] == "http.server"
+        assert envelope["request"] == DictionaryContaining(
+            {"method": "GET", "url": "http://localhost/dogs/are/great/"}
+        )
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_has_trace_if_performance_enabled(
     sentry_init,
     capture_events,
+    capture_items,
+    span_streaming,
 ):
     def dogpark(environ, start_response):
         capture_message("Attempting to fetch the ball")
         raise ValueError("Fetch aborted. The ball was not returned.")
 
-    sentry_init(traces_sample_rate=1.0)
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(dogpark)
     client = Client(app)
-    events = capture_events()
+
+    if span_streaming:
+        items = capture_items("event", "span")
+    else:
+        events = capture_events()
 
     with pytest.raises(ValueError):
         client.get("http://dogs.are.great/sit/stay/rollover/")
 
-    msg_event, error_event, transaction_event = events
+    sentry_sdk.flush()
+
+    if span_streaming:
+        msg_event, error_event, span_item = items
 
-    assert msg_event["contexts"]["trace"]
-    assert "trace_id" in msg_event["contexts"]["trace"]
+        assert msg_event.type == "event"
+        msg_event = msg_event.payload
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
 
-    assert error_event["contexts"]["trace"]
-    assert "trace_id" in error_event["contexts"]["trace"]
+        assert error_event.type == "event"
+        error_event = error_event.payload
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
 
-    assert transaction_event["contexts"]["trace"]
-    assert "trace_id" in transaction_event["contexts"]["trace"]
+        assert span_item.type == "span"
+        span_item = span_item.payload
+        assert span_item["trace_id"] is not None
 
-    assert (
-        msg_event["contexts"]["trace"]["trace_id"]
-        == error_event["contexts"]["trace"]["trace_id"]
-        == transaction_event["contexts"]["trace"]["trace_id"]
-    )
+        assert (
+            msg_event["contexts"]["trace"]["trace_id"]
+            == error_event["contexts"]["trace"]["trace_id"]
+            == span_item["trace_id"]
+        )
+    else:
+        msg_event, error_event, transaction_event = events
+
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
+
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
+
+        assert transaction_event["contexts"]["trace"]
+        assert "trace_id" in transaction_event["contexts"]["trace"]
+
+        assert (
+            msg_event["contexts"]["trace"]["trace_id"]
+            == error_event["contexts"]["trace"]["trace_id"]
+            == transaction_event["contexts"]["trace"]["trace_id"]
+        )
 
 
 def test_has_trace_if_performance_disabled(
@@ -260,18 +358,30 @@ def dogpark(environ, start_response):
     assert "trace_id" in error_event["contexts"]["trace"]
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_trace_from_headers_if_performance_enabled(
     sentry_init,
     capture_events,
+    capture_items,
+    span_streaming,
 ):
     def dogpark(environ, start_response):
         capture_message("Attempting to fetch the ball")
         raise ValueError("Fetch aborted. The ball was not returned.")
 
-    sentry_init(traces_sample_rate=1.0)
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(dogpark)
     client = Client(app)
-    events = capture_events()
+
+    if span_streaming:
+        items = capture_items("event", "span")
+    else:
+        events = capture_events()
 
     trace_id = "582b43a4192642f0b136d5159a501701"
     sentry_trace_header = "{}-{}-{}".format(trace_id, "6e8f22c393e68f19", 1)
@@ -282,20 +392,29 @@ def dogpark(environ, start_response):
             headers={"sentry-trace": sentry_trace_header},
         )
 
-    msg_event, error_event, transaction_event = events
+    sentry_sdk.flush()
 
-    assert msg_event["contexts"]["trace"]
-    assert "trace_id" in msg_event["contexts"]["trace"]
+    if span_streaming:
+        msg_event, error_event, span_item = items
 
-    assert error_event["contexts"]["trace"]
-    assert "trace_id" in error_event["contexts"]["trace"]
+        assert msg_event.payload["contexts"]["trace"]["trace_id"] == trace_id
+        assert error_event.payload["contexts"]["trace"]["trace_id"] == trace_id
+        assert span_item.payload["trace_id"] == trace_id
+    else:
+        msg_event, error_event, transaction_event = events
 
-    assert transaction_event["contexts"]["trace"]
-    assert "trace_id" in transaction_event["contexts"]["trace"]
+        assert msg_event["contexts"]["trace"]
+        assert "trace_id" in msg_event["contexts"]["trace"]
 
-    assert msg_event["contexts"]["trace"]["trace_id"] == trace_id
-    assert error_event["contexts"]["trace"]["trace_id"] == trace_id
-    assert transaction_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert error_event["contexts"]["trace"]
+        assert "trace_id" in error_event["contexts"]["trace"]
+
+        assert transaction_event["contexts"]["trace"]
+        assert "trace_id" in transaction_event["contexts"]["trace"]
+
+        assert msg_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert error_event["contexts"]["trace"]["trace_id"] == trace_id
+        assert transaction_event["contexts"]["trace"]["trace_id"] == trace_id
 
 
 def test_trace_from_headers_if_performance_disabled(
@@ -331,37 +450,65 @@ def dogpark(environ, start_response):
     assert error_event["contexts"]["trace"]["trace_id"] == trace_id
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_traces_sampler_gets_correct_values_in_sampling_context(
     sentry_init,
     DictionaryContaining,  # noqa:N803
+    span_streaming,
 ):
     def app(environ, start_response):
         start_response("200 OK", [])
         return ["Go get the ball! Good dog!"]
 
     traces_sampler = mock.Mock(return_value=True)
-    sentry_init(send_default_pii=True, traces_sampler=traces_sampler)
+    sentry_init(
+        send_default_pii=True,
+        traces_sampler=traces_sampler,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(app)
     client = Client(app)
 
     client.get("/dogs/are/great/")
 
-    traces_sampler.assert_any_call(
-        DictionaryContaining(
-            {
-                "wsgi_environ": DictionaryContaining(
-                    {
-                        "PATH_INFO": "/dogs/are/great/",
-                        "REQUEST_METHOD": "GET",
-                    },
-                ),
-            }
+    if span_streaming:
+        traces_sampler.assert_any_call(
+            DictionaryContaining(
+                {
+                    "span_context": DictionaryContaining(
+                        {
+                            "name": "generic WSGI request",
+                        },
+                    ),
+                    "wsgi_environ": DictionaryContaining(
+                        {
+                            "PATH_INFO": "/dogs/are/great/",
+                            "REQUEST_METHOD": "GET",
+                        },
+                    ),
+                }
+            )
+        )
+    else:
+        traces_sampler.assert_any_call(
+            DictionaryContaining(
+                {
+                    "wsgi_environ": DictionaryContaining(
+                        {
+                            "PATH_INFO": "/dogs/are/great/",
+                            "REQUEST_METHOD": "GET",
+                        },
+                    ),
+                }
+            )
         )
-    )
 
 
+@pytest.mark.parametrize("span_streaming", [True, False])
 def test_session_mode_defaults_to_request_mode_in_wsgi_handler(
-    capture_envelopes, sentry_init
+    capture_envelopes, sentry_init, span_streaming
 ):
     """
     Test that ensures that even though the default `session_mode` for
@@ -374,7 +521,13 @@ def app(environ, start_response):
         return ["Go get the ball! Good dog!"]
 
     traces_sampler = mock.Mock(return_value=True)
-    sentry_init(send_default_pii=True, traces_sampler=traces_sampler)
+    sentry_init(
+        send_default_pii=True,
+        traces_sampler=traces_sampler,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(app)
     envelopes = capture_envelopes()
 
@@ -384,7 +537,11 @@ def app(environ, start_response):
 
     sentry_sdk.flush()
 
-    sess = envelopes[1]
+    session_envelopes = [
+        e for e in envelopes if any(item.type == "sessions" for item in e.items)
+    ]
+    assert len(session_envelopes) == 1
+    sess = session_envelopes[0]
     assert len(sess.items) == 1
     sess_event = sess.items[0].payload.json
 
@@ -393,7 +550,10 @@ def app(environ, start_response):
     assert aggregates[0]["exited"] == 1
 
 
-def test_auto_session_tracking_with_aggregates(sentry_init, capture_envelopes):
+@pytest.mark.parametrize("span_streaming", [True, False])
+def test_auto_session_tracking_with_aggregates(
+    sentry_init, capture_envelopes, span_streaming
+):
     """
     Test for correct session aggregates in auto session tracking.
     """
@@ -406,7 +566,13 @@ def sample_app(environ, start_response):
         return ["Go get the ball! Good dog!"]
 
     traces_sampler = mock.Mock(return_value=True)
-    sentry_init(send_default_pii=True, traces_sampler=traces_sampler)
+    sentry_init(
+        send_default_pii=True,
+        traces_sampler=traces_sampler,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(sample_app)
     envelopes = capture_envelopes()
     assert len(envelopes) == 0
@@ -423,14 +589,21 @@ def sample_app(environ, start_response):
 
     count_item_types = Counter()
     for envelope in envelopes:
-        count_item_types[envelope.items[0].type] += 1
+        for item in envelope.items:
+            count_item_types[item.type] += 1
 
-    assert count_item_types["transaction"] == 3
+    if span_streaming:
+        assert count_item_types["span"] == 3
+    else:
+        assert count_item_types["transaction"] == 3
     assert count_item_types["event"] == 1
     assert count_item_types["sessions"] == 1
-    assert len(envelopes) == 5
 
-    session_aggregates = envelopes[-1].items[0].payload.json["aggregates"]
+    session_envelopes = [
+        e for e in envelopes if any(item.type == "sessions" for item in e.items)
+    ]
+    assert len(session_envelopes) == 1
+    session_aggregates = session_envelopes[0].items[0].payload.json["aggregates"]
     assert session_aggregates[0]["exited"] == 2
     assert session_aggregates[0]["crashed"] == 1
     assert len(session_aggregates) == 1
@@ -463,43 +636,73 @@ def test_app(environ, start_response):
     assert len(profiles) == 1
 
 
-def test_span_origin_manual(sentry_init, capture_events):
+@pytest.mark.parametrize("span_streaming", [True, False])
+def test_span_origin_manual(sentry_init, capture_events, capture_items, span_streaming):
     def dogpark(environ, start_response):
         start_response("200 OK", [])
         return ["Go get the ball! Good dog!"]
 
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(dogpark)
 
-    events = capture_events()
+    if span_streaming:
+        items = capture_items("span")
+    else:
+        events = capture_events()
 
     client = Client(app)
     client.get("/dogs/are/great/")
 
-    (event,) = events
+    sentry_sdk.flush()
 
-    assert event["contexts"]["trace"]["origin"] == "manual"
+    if span_streaming:
+        assert len(items) == 1
+        assert items[0].payload["attributes"]["sentry.origin"] == "manual"
+    else:
+        (event,) = events
+        assert event["contexts"]["trace"]["origin"] == "manual"
 
 
-def test_span_origin_custom(sentry_init, capture_events):
+@pytest.mark.parametrize("span_streaming", [True, False])
+def test_span_origin_custom(sentry_init, capture_events, capture_items, span_streaming):
     def dogpark(environ, start_response):
         start_response("200 OK", [])
         return ["Go get the ball! Good dog!"]
 
-    sentry_init(send_default_pii=True, traces_sample_rate=1.0)
+    sentry_init(
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream" if span_streaming else "static",
+        },
+    )
     app = SentryWsgiMiddleware(
         dogpark,
         span_origin="auto.dogpark.deluxe",
     )
 
-    events = capture_events()
+    if span_streaming:
+        items = capture_items("span")
+    else:
+        events = capture_events()
 
     client = Client(app)
     client.get("/dogs/are/great/")
 
-    (event,) = events
+    sentry_sdk.flush()
 
-    assert event["contexts"]["trace"]["origin"] == "auto.dogpark.deluxe"
+    if span_streaming:
+        assert len(items) == 1
+        assert items[0].payload["attributes"]["sentry.origin"] == "auto.dogpark.deluxe"
+    else:
+        (event,) = events
+        assert event["contexts"]["trace"]["origin"] == "auto.dogpark.deluxe"
 
 
 @pytest.mark.parametrize(
@@ -547,3 +750,94 @@ def app(environ, start_response):
         assert isinstance(result, _ScopedResponse)
     else:
         assert result is response_mock
+
+
+@pytest.mark.parametrize(
+    "environ,use_x_forwarded_for,expected_url",
+    [
+        # Without use_x_forwarded_for, wsgi.url_scheme is used
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "SERVER_NAME": "example.com",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+                "HTTP_X_FORWARDED_PROTO": "https",
+            },
+            False,
+            "http://example.com/test",
+        ),
+        # With use_x_forwarded_for, HTTP_X_FORWARDED_PROTO is respected
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "SERVER_NAME": "example.com",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+                "HTTP_X_FORWARDED_PROTO": "https",
+            },
+            True,
+            "https://example.com/test",
+        ),
+        # With use_x_forwarded_for but no forwarded proto, wsgi.url_scheme is used
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "SERVER_NAME": "example.com",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+            },
+            True,
+            "http://example.com/test",
+        ),
+        # Forwarded host with default https port is stripped using forwarded proto
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "SERVER_NAME": "internal",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+                "HTTP_X_FORWARDED_PROTO": "https",
+                "HTTP_X_FORWARDED_HOST": "example.com:443",
+            },
+            True,
+            "https://example.com/test",
+        ),
+        # Forwarded host with non-default port is preserved
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "SERVER_NAME": "internal",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+                "HTTP_X_FORWARDED_PROTO": "https",
+                "HTTP_X_FORWARDED_HOST": "example.com:8443",
+            },
+            True,
+            "https://example.com:8443/test",
+        ),
+        # Forwarded proto with HTTP_HOST (no forwarded host) strips default port
+        (
+            {
+                "wsgi.url_scheme": "http",
+                "HTTP_HOST": "example.com:443",
+                "SERVER_NAME": "internal",
+                "SERVER_PORT": "80",
+                "PATH_INFO": "/test",
+                "HTTP_X_FORWARDED_PROTO": "https",
+            },
+            True,
+            "https://example.com/test",
+        ),
+    ],
+    ids=[
+        "ignores_forwarded_proto_when_disabled",
+        "respects_forwarded_proto_when_enabled",
+        "falls_back_to_url_scheme_when_no_forwarded_proto",
+        "strips_default_https_port_from_forwarded_host",
+        "preserves_non_default_port_on_forwarded_host",
+        "strips_default_port_from_http_host_with_forwarded_proto",
+    ],
+)
+def test_get_request_url_x_forwarded_proto(environ, use_x_forwarded_for, expected_url):
+    assert get_request_url(environ, use_x_forwarded_for) == expected_url
diff --git a/tests/profiler/test_continuous_profiler.py b/tests/profiler/test_continuous_profiler.py
index e4f5cb5e25..f0c3b5a27f 100644
--- a/tests/profiler/test_continuous_profiler.py
+++ b/tests/profiler/test_continuous_profiler.py
@@ -621,3 +621,67 @@ def test_continuous_profiler_manual_start_and_stop_noop_when_using_trace_lifecyl
     ) as mock_teardown:
         stop_profiler_func()
         mock_teardown.assert_not_called()
+
+
+@mock.patch("sentry_sdk.profiler.continuous_profiler.PROFILE_BUFFER_SECONDS", 0.01)
+def test_continuous_profiler_run_does_not_null_buffer(
+    sentry_init,
+    capture_envelopes,
+    teardown_profiling,
+):
+    """
+    Verifies that ContinuousScheduler.run() does not set self.buffer = None
+    after exiting its sampling loop.
+
+    Previously, run() would execute `self.buffer = None` after the while
+    loop exited. During rapid stop/start cycles, this could race with
+    ensure_running() which creates a new buffer: the old thread's cleanup
+    would destroy the newly-created buffer, causing the new profiler thread
+    to silently drop all samples (self.buffer is None in the sampler).
+
+    The fix uses a local buffer reference for flushing and never sets
+    self.buffer = None from run().
+    """
+    from sentry_sdk.profiler import continuous_profiler as cp
+
+    options = get_client_options(True)(
+        mode="thread", profile_session_sample_rate=1.0, lifecycle="manual"
+    )
+    sentry_init(traces_sample_rate=1.0, **options)
+    envelopes = capture_envelopes()
+    thread = threading.current_thread()
+
+    # Start and verify profiler works
+    start_profiler()
+    envelopes.clear()
+    with sentry_sdk.start_transaction(name="profiling"):
+        with sentry_sdk.start_span(op="op"):
+            time.sleep(0.1)
+    assert_single_transaction_with_profile_chunks(envelopes, thread)
+
+    # Get the scheduler and create a sentinel buffer.
+    # We'll call run() directly to verify it doesn't null out self.buffer.
+    scheduler = cp._scheduler
+    assert scheduler is not None
+
+    # Stop the profiler so the thread exits cleanly
+    stop_profiler()
+
+    # Now set up a fresh buffer and mark the scheduler as not running
+    # (simulating the state right after ensure_running() created a new buffer
+    # but the old thread hasn't done cleanup yet).
+    scheduler.reset_buffer()
+    buffer_before = scheduler.buffer
+    assert buffer_before is not None
+
+    # Simulate what happens when run() exits its while loop:
+    # self.running is already False, so the while loop exits immediately.
+    scheduler.running = False
+    scheduler.run()
+
+    # After the fix, run() should NOT have set self.buffer = None.
+    # It should only flush using a local reference.
+    assert scheduler.buffer is not None, (
+        "run() must not set self.buffer = None; "
+        "this would destroy buffers created by concurrent ensure_running() calls"
+    )
diff --git a/tests/test_ai_integration_deactivation.py b/tests/test_ai_integration_deactivation.py
index b02b64c6ee..683de2f0b2 100644
--- a/tests/test_ai_integration_deactivation.py
+++ b/tests/test_ai_integration_deactivation.py
@@ -190,7 +190,6 @@ def test_langchain_and_openai_both_explicit_both_active(
 def test_no_langchain_means_openai_and_anthropic_can_auto_enable(
     sentry_init, reset_integrations, monkeypatch
 ):
-    import sys
     import sentry_sdk.integrations
 
     old_iter = sentry_sdk.integrations.iter_default_integrations
diff --git a/tests/test_ai_monitoring.py b/tests/test_ai_monitoring.py
index 969d14658d..406ac05edb 100644
--- a/tests/test_ai_monitoring.py
+++ b/tests/test_ai_monitoring.py
@@ -1,19 +1,14 @@
-import json
-import uuid
-
 import pytest
 
 import sentry_sdk
 from sentry_sdk._types import (
     AnnotatedValue,
-    SENSITIVE_DATA_SUBSTITUTE,
     BLOB_DATA_SUBSTITUTE,
 )
 from sentry_sdk.ai.monitoring import ai_track
 from sentry_sdk.ai.utils import (
     MAX_GEN_AI_MESSAGE_BYTES,
     MAX_SINGLE_MESSAGE_CONTENT_CHARS,
-    set_data_normalized,
     truncate_and_annotate_messages,
     truncate_messages_by_size,
     _find_truncation_index,
@@ -27,7 +22,6 @@
     transform_content_part,
     transform_message_content,
 )
-from sentry_sdk.serializer import serialize
 from sentry_sdk.utils import safe_serialize
 
 
@@ -318,6 +312,105 @@ def test_single_message_truncation(self):
         assert user_msgs[0]["content"].endswith("...")
         assert len(user_msgs[0]["content"]) < len(large_content)
 
+    def test_single_message_truncation_list_content_exceeds_limit(self):
+        """Test that list-based content (e.g. pydantic-ai multimodal format) is truncated."""
+        large_text = "A" * 200_000
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": large_text},
+                ],
+            },
+        ]
+
+        result, _ = truncate_messages_by_size(messages)
+
+        text_part = result[0]["content"][0]
+        assert text_part["text"].endswith("...")
+        assert len(text_part["text"]) == MAX_SINGLE_MESSAGE_CONTENT_CHARS + 3
+
+    def test_single_message_truncation_list_content_under_limit(self):
+        """Test that small text parts are preserved when non-text parts push size over byte limit."""
+        short_text = "Hello world"
+        large_data_url = "data:image/png;base64," + "A" * 200_000
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": short_text},
+                    {"type": "image_url", "image_url": {"url": large_data_url}},
+                ],
+            },
+        ]
+
+        result, _ = truncate_messages_by_size(messages)
+
+        text_part = result[0]["content"][0]
+        assert text_part["text"] == short_text
+
+    def test_single_message_truncation_list_content_mixed_parts(self):
+        """Test truncation with mixed content types (text + non-text parts)."""
+        max_chars = 50
+        large_data_url = "data:image/png;base64," + "X" * 200_000
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "A" * 30},
+                    {"type": "image_url", "image_url": {"url": large_data_url}},
+                    {"type": "text", "text": "B" * 30},
+                ],
+            },
+        ]
+
+        result, _ = truncate_messages_by_size(
+            messages, max_single_message_chars=max_chars
+        )
+
+        parts = result[0]["content"]
+        # First text part uses 30 chars of the 50 budget
+        assert parts[0]["text"] == "A" * 30
+        # Image part is unchanged
+        assert parts[1]["type"] == "image_url"
+        # Second text part is truncated to remaining 20 chars
+        assert parts[2]["text"] == "B" * 20 + "..."
+
+    def test_single_message_truncation_list_content_multiple_text_parts(self):
+        """Test that budget is distributed across multiple text parts."""
+        max_chars = 10
+        # Two large text parts that together exceed 128KB byte limit
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "A" * 100_000},
+                    {"type": "text", "text": "B" * 100_000},
+                ],
+            },
+        ]
+
+        result, _ = truncate_messages_by_size(
+            messages, max_single_message_chars=max_chars
+        )
+
+        parts = result[0]["content"]
+        # First part is truncated to the full budget
+        assert parts[0]["text"] == "A" * 10 + "..."
+        # Second part gets truncated to 0 chars + ellipsis
+        assert parts[1]["text"] == "..."
+
+    @pytest.mark.parametrize("content", [None, 42, 3.14, True])
+    def test_single_message_truncation_non_str_non_list_content(self, content):
+        messages = [{"role": "user", "content": content}]
+
+        result, _ = truncate_messages_by_size(messages)
+
+        assert result[0]["content"] is content
+
 
 class TestTruncateAndAnnotateMessages:
     def test_only_keeps_last_message(self, sample_messages):
@@ -721,6 +814,71 @@ def test_redacts_blobs_in_multiple_messages(self):
         assert result[1]["content"] == "I see the image."  # Unchanged
         assert result[2]["content"][1]["content"] == BLOB_DATA_SUBSTITUTE
 
+    def test_redacts_single_blob_within_image_url_content(self):
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "text": "How many ponies do you see in the image?",
+                        "type": "text",
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": "data:image/jpeg;base64,/9j/4AAQSkZJRg=="},
+                    },
+                ],
+            }
+        ]
+
+        original_blob_content = messages[0]["content"][1]
+
+        result = redact_blob_message_parts(messages)
+
+        assert messages[0]["content"][1] == original_blob_content
+
+        assert (
+            result[0]["content"][0]["text"]
+            == "How many ponies do you see in the image?"
+        )
+        assert result[0]["content"][0]["type"] == "text"
+        assert result[0]["content"][1]["type"] == "image_url"
+        assert result[0]["content"][1]["image_url"]["url"] == BLOB_DATA_SUBSTITUTE
+
+    def test_does_not_redact_image_url_content_with_non_blobs(self):
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "text": "How many ponies do you see in the image?",
+                        "type": "text",
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": "https://example.com/image.jpg"},
+                    },
+                ],
+            }
+        ]
+
+        original_blob_content = messages[0]["content"][1]
+
+        result = redact_blob_message_parts(messages)
+
+        assert messages[0]["content"][1] == original_blob_content
+
+        assert (
+            result[0]["content"][0]["text"]
+            == "How many ponies do you see in the image?"
+        )
+        assert result[0]["content"][0]["type"] == "text"
+        assert result[0]["content"][1]["type"] == "image_url"
+        assert (
+            result[0]["content"][1]["image_url"]["url"]
+            == "https://example.com/image.jpg"
+        )
+
     def test_no_blobs_returns_original_list(self):
         """Test that messages without blobs are returned as-is (performance optimization)"""
         messages = [
diff --git a/tests/test_basics.py b/tests/test_basics.py
index da836462d8..afbbf929f2 100644
--- a/tests/test_basics.py
+++ b/tests/test_basics.py
@@ -1092,7 +1092,7 @@ def test_classmethod_instance_tracing(sentry_init, capture_events):
 
 
 def test_last_event_id(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     assert last_event_id() is None
 
@@ -1102,7 +1102,7 @@ def test_last_event_id(sentry_init):
 
 
 def test_last_event_id_transaction(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     assert last_event_id() is None
 
@@ -1113,7 +1113,7 @@ def test_last_event_id_transaction(sentry_init):
 
 
 def test_last_event_id_scope(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     # Should not crash
     with isolation_scope() as scope:
diff --git a/tests/test_client.py b/tests/test_client.py
index 96ebcf1790..7e6a474016 100644
--- a/tests/test_client.py
+++ b/tests/test_client.py
@@ -26,9 +26,22 @@
 from sentry_sdk.spotlight import DEFAULT_SPOTLIGHT_URL
 from sentry_sdk.utils import capture_internal_exception
 from sentry_sdk.integrations.executing import ExecutingIntegration
-from sentry_sdk.transport import Transport
+from sentry_sdk.integrations.asyncio import AsyncioIntegration
+from sentry_sdk.transport import Transport, AsyncHttpTransport
 from sentry_sdk.serializer import MAX_DATABAG_BREADTH
 from sentry_sdk.consts import DEFAULT_MAX_BREADCRUMBS, DEFAULT_MAX_VALUE_LENGTH
+from sentry_sdk._compat import PY38
+
+try:
+    import gevent  # noqa: F401
+
+    running_under_gevent = True
+except ImportError:
+    running_under_gevent = False
+
+skip_under_gevent = pytest.mark.skipif(
+    running_under_gevent, reason="Async tests not compatible with gevent"
+)
 
 from typing import TYPE_CHECKING
 
@@ -43,6 +56,241 @@
     reason="Since Python 3.13, `FrameLocalsProxy` skips items of `locals()` that have non-`str` keys; this is a CPython implementation detail: https://github.com/python/cpython/blame/7b413952e817ae87bfda2ac85dd84d30a6ce743b/Objects/frameobject.c#L148",
 )
 
+PROXY_TESTCASES = [
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": "https://localhost/123",
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": "https://localhost/123",
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": "https://localhost/123",
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": None,
+    },
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": None,
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": None,
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": "",
+        "arg_https_proxy": "",
+        "expected_proxy_scheme": None,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": None,
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "",
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": "",
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "",
+        "expected_proxy_scheme": None,
+    },
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": "https://localhost/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    # NO_PROXY testcases
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": "http://localhost/123",
+        "env_https_proxy": None,
+        "env_no_proxy": "sentry.io,example.com",
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": None,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": "https://localhost/123",
+        "env_no_proxy": "example.com,sentry.io",
+        "arg_http_proxy": None,
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": None,
+    },
+    {
+        "dsn": "http://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "env_no_proxy": "sentry.io,example.com",
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": None,
+        "expected_proxy_scheme": "http",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "env_no_proxy": "sentry.io,example.com",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "https://localhost/123",
+        "expected_proxy_scheme": "https",
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "env_http_proxy": None,
+        "env_https_proxy": None,
+        "env_no_proxy": "sentry.io,example.com",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "https://localhost/123",
+        "expected_proxy_scheme": "https",
+        "arg_proxy_headers": {"Test-Header": "foo-bar"},
+    },
+]
+
+SOCKS_PROXY_TESTCASES = [
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": "http://localhost/123",
+        "arg_https_proxy": None,
+        "should_be_socks_proxy": False,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": "socks4a://localhost/123",
+        "arg_https_proxy": None,
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": "socks4://localhost/123",
+        "arg_https_proxy": None,
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": "socks5h://localhost/123",
+        "arg_https_proxy": None,
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": "socks5://localhost/123",
+        "arg_https_proxy": None,
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "socks4a://localhost/123",
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "socks4://localhost/123",
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "socks5h://localhost/123",
+        "should_be_socks_proxy": True,
+    },
+    {
+        "dsn": "https://foo@sentry.io/123",
+        "arg_http_proxy": None,
+        "arg_https_proxy": "socks5://localhost/123",
+        "should_be_socks_proxy": True,
+    },
+]
+
 
 class EnvelopeCapturedError(Exception):
     pass
@@ -68,186 +316,7 @@ def test_transport_option(monkeypatch):
     assert str(Client(transport=transport).dsn) == dsn
 
 
-@pytest.mark.parametrize(
-    "testcase",
-    [
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": "https://localhost/123",
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": "https://localhost/123",
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": "https://localhost/123",
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": None,
-        },
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": None,
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": None,
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": "",
-            "arg_https_proxy": "",
-            "expected_proxy_scheme": None,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": None,
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "",
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": "",
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "",
-            "expected_proxy_scheme": None,
-        },
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": "https://localhost/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        # NO_PROXY testcases
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": "http://localhost/123",
-            "env_https_proxy": None,
-            "env_no_proxy": "sentry.io,example.com",
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": None,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": "https://localhost/123",
-            "env_no_proxy": "example.com,sentry.io",
-            "arg_http_proxy": None,
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": None,
-        },
-        {
-            "dsn": "http://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "env_no_proxy": "sentry.io,example.com",
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": None,
-            "expected_proxy_scheme": "http",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "env_no_proxy": "sentry.io,example.com",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "https://localhost/123",
-            "expected_proxy_scheme": "https",
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "env_http_proxy": None,
-            "env_https_proxy": None,
-            "env_no_proxy": "sentry.io,example.com",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "https://localhost/123",
-            "expected_proxy_scheme": "https",
-            "arg_proxy_headers": {"Test-Header": "foo-bar"},
-        },
-    ],
-)
+@pytest.mark.parametrize("testcase", PROXY_TESTCASES)
 @pytest.mark.parametrize(
     "http2", [True, False] if sys.version_info >= (3, 8) else [False]
 )
@@ -300,65 +369,7 @@ def test_proxy(monkeypatch, testcase, http2):
             assert proxy_headers == testcase["arg_proxy_headers"]
 
 
-@pytest.mark.parametrize(
-    "testcase",
-    [
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": "http://localhost/123",
-            "arg_https_proxy": None,
-            "should_be_socks_proxy": False,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": "socks4a://localhost/123",
-            "arg_https_proxy": None,
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": "socks4://localhost/123",
-            "arg_https_proxy": None,
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": "socks5h://localhost/123",
-            "arg_https_proxy": None,
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": "socks5://localhost/123",
-            "arg_https_proxy": None,
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "socks4a://localhost/123",
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "socks4://localhost/123",
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "socks5h://localhost/123",
-            "should_be_socks_proxy": True,
-        },
-        {
-            "dsn": "https://foo@sentry.io/123",
-            "arg_http_proxy": None,
-            "arg_https_proxy": "socks5://localhost/123",
-            "should_be_socks_proxy": True,
-        },
-    ],
-)
+@pytest.mark.parametrize("testcase", SOCKS_PROXY_TESTCASES)
 @pytest.mark.parametrize(
     "http2", [True, False] if sys.version_info >= (3, 8) else [False]
 )
@@ -1585,3 +1596,266 @@ def test_keep_alive(env_value, arg_value, expected_value):
         )
 
     assert transport_cls.options["keep_alive"] is expected_value
+
+
+@pytest.mark.parametrize("testcase", PROXY_TESTCASES)
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async transport requires Python 3.8+")
+async def test_async_proxy(monkeypatch, testcase):
+    # These are just the same tests as the sync ones, but they need to be run in an event loop
+    # and respect the shutdown behavior of the async transport
+    if testcase["env_http_proxy"] is not None:
+        monkeypatch.setenv("HTTP_PROXY", testcase["env_http_proxy"])
+    if testcase["env_https_proxy"] is not None:
+        monkeypatch.setenv("HTTPS_PROXY", testcase["env_https_proxy"])
+    if testcase.get("env_no_proxy") is not None:
+        monkeypatch.setenv("NO_PROXY", testcase["env_no_proxy"])
+
+    kwargs = {
+        "_experiments": {"transport_async": True},
+        "integrations": [AsyncioIntegration()],
+    }
+
+    if testcase["arg_http_proxy"] is not None:
+        kwargs["http_proxy"] = testcase["arg_http_proxy"]
+    if testcase["arg_https_proxy"] is not None:
+        kwargs["https_proxy"] = testcase["arg_https_proxy"]
+    if testcase.get("arg_proxy_headers") is not None:
+        kwargs["proxy_headers"] = testcase["arg_proxy_headers"]
+
+    client = Client(testcase["dsn"], **kwargs)
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    proxy = getattr(
+        client.transport._pool,
+        "proxy",
+        getattr(client.transport._pool, "_proxy_url", None),
+    )
+    if testcase["expected_proxy_scheme"] is None:
+        assert proxy is None
+    else:
+        scheme = (
+            proxy.scheme.decode("ascii")
+            if isinstance(proxy.scheme, bytes)
+            else proxy.scheme
+        )
+        assert scheme == testcase["expected_proxy_scheme"]
+
+        if testcase.get("arg_proxy_headers") is not None:
+            proxy_headers = dict(
+                (k.decode("ascii"), v.decode("ascii"))
+                for k, v in client.transport._pool._proxy_headers
+            )
+            assert proxy_headers == testcase["arg_proxy_headers"]
+
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_close_with_async_transport_warns():
+    """Test close() with AsyncHttpTransport emits a warning."""
+    import warnings as _warnings
+
+    client = Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    with _warnings.catch_warnings(record=True) as w:
+        _warnings.simplefilter("always")
+        client.close()
+        assert any("close_async()" in str(warning.message) for warning in w)
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_close_async_with_async_transport():
+    """Test close_async() properly closes async transport."""
+    client = Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    await client.close_async(timeout=1.0)
+    assert client.transport is None
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_close_async_with_sync_transport():
+    """Test close_async() aborts with non-async transport."""
+    client = Client("https://foo@sentry.io/123")
+    assert not isinstance(client.transport, AsyncHttpTransport)
+
+    with mock.patch("sentry_sdk.client.logger") as mock_logger:
+        await client.close_async()
+        mock_logger.debug.assert_any_call(
+            "close_async() used with non-async transport, aborting. Please use close() instead."
+        )
+    # Transport should NOT have been set to None
+    assert client.transport is not None
+    client.close()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_close_async_no_transport():
+    """Test close_async() does nothing when transport is None."""
+    client = Client("https://foo@sentry.io/123")
+    client.transport = None
+    # Should not raise
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_flush_with_async_transport_warns():
+    """Test flush() with AsyncHttpTransport emits a warning and returns."""
+    import warnings as _warnings
+
+    client = Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    with _warnings.catch_warnings(record=True) as w:
+        _warnings.simplefilter("always")
+        client.flush(timeout=1.0)
+        assert any("flush_async()" in str(warning.message) for warning in w)
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_flush_async_with_async_transport():
+    """Test flush_async() works with async transport."""
+    client = Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    # Should not raise
+    await client.flush_async(timeout=1.0)
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_flush_async_uses_shutdown_timeout_default():
+    """Test flush_async() uses shutdown_timeout when no timeout provided."""
+    client = Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+        shutdown_timeout=5.0,
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    with mock.patch.object(client.transport, "flush", return_value=None) as mock_flush:
+        await client.flush_async()
+        mock_flush.assert_called_once_with(timeout=5.0, callback=None)
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_flush_async_with_sync_transport():
+    """Test flush_async() aborts with non-async transport."""
+    client = Client("https://foo@sentry.io/123")
+    assert not isinstance(client.transport, AsyncHttpTransport)
+
+    with mock.patch("sentry_sdk.client.logger") as mock_logger:
+        await client.flush_async()
+        mock_logger.debug.assert_any_call(
+            "flush_async() used with non-async transport, aborting. Please use flush() instead."
+        )
+    client.close()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_flush_async_no_transport():
+    """Test flush_async() does nothing when transport is None."""
+    client = Client("https://foo@sentry.io/123")
+    client.transport = None
+    # Should not raise
+    await client.flush_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_client_async_context_manager():
+    """Test Client works as async context manager."""
+    async with Client(
+        "https://foo@sentry.io/123",
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    ) as client:
+        assert isinstance(client.transport, AsyncHttpTransport)
+        assert client.is_active()
+    # After __aexit__, transport should be None
+    assert client.transport is None
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async client methods require Python 3.8+")
+async def test_client_async_context_manager_with_sync_transport():
+    """Test Client async context manager with sync transport is safe."""
+    async with Client("https://foo@sentry.io/123") as client:
+        assert client.is_active()
+    # close_async with sync transport is a no-op for transport cleanup
+    # Transport won't be None because close_async aborts for non-async transport
+    assert client.transport is not None
+    client.close()
+
+
+@pytest.mark.parametrize("testcase", SOCKS_PROXY_TESTCASES)
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async transport requires Python 3.8+")
+async def test_async_socks_proxy(testcase):
+    # These are just the same tests as the sync ones, but they need to be run in an event loop
+    # and respect the shutdown behavior of the async transport
+
+    kwargs = {
+        "_experiments": {"transport_async": True},
+        "integrations": [AsyncioIntegration()],
+    }
+
+    if testcase["arg_http_proxy"] is not None:
+        kwargs["http_proxy"] = testcase["arg_http_proxy"]
+    if testcase["arg_https_proxy"] is not None:
+        kwargs["https_proxy"] = testcase["arg_https_proxy"]
+
+    client = Client(testcase["dsn"], **kwargs)
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    assert ("socks" in str(type(client.transport._pool)).lower()) == testcase[
+        "should_be_socks_proxy"
+    ], (
+        f"Expected {kwargs} to result in SOCKS == {testcase['should_be_socks_proxy']}"
+        f"but got {str(type(client.transport._pool))}"
+    )
+
+    await client.close_async()
diff --git a/tests/test_crons.py b/tests/test_crons.py
index 493cc44272..8bd4d8b1ff 100644
--- a/tests/test_crons.py
+++ b/tests/test_crons.py
@@ -262,6 +262,22 @@ def test_monitor_config(sentry_init, capture_envelopes):
     assert "monitor_config" not in check_in
 
 
+def test_monitor_config_with_owner(sentry_init, capture_envelopes):
+    sentry_init()
+    envelopes = capture_envelopes()
+
+    monitor_config = {
+        "schedule": {"type": "crontab", "value": "0 0 * * *"},
+        "owner": "team:6",
+    }
+
+    capture_checkin(monitor_slug="abc123", monitor_config=monitor_config)
+    check_in = envelopes[0].items[0].payload.json
+
+    assert check_in["monitor_slug"] == "abc123"
+    assert check_in["monitor_config"]["owner"] == "team:6"
+
+
 def test_decorator_monitor_config(sentry_init, capture_envelopes):
     sentry_init()
     envelopes = capture_envelopes()
diff --git a/tests/test_exceptiongroup.py b/tests/test_exceptiongroup.py
index 4c7afc58eb..c0d057abf8 100644
--- a/tests/test_exceptiongroup.py
+++ b/tests/test_exceptiongroup.py
@@ -306,3 +306,171 @@ def test_simple_exception():
 
     exception_values = event["exception"]["values"]
     assert exception_values == expected_exception_values
+
+
+@minimum_python_311
+def test_exceptiongroup_starlette_collapse():
+    """
+    Simulates the Starlette collapse_excgroups() pattern where a single-exception
+    ExceptionGroup is caught and the inner exception is unwrapped and re-raised.
+
+    See: https://github.com/Kludex/starlette/blob/0e88e92b592bfa11fd92e331869a8d49ba34b541/starlette/_utils.py#L79-L87
+
+    When using FastAPI with multiple BaseHTTPMiddleware instances, anyio wraps
+    exceptions in ExceptionGroups. Starlette's collapse_excgroups() then unwraps
+    single-exception groups and re-raises the inner exception.
+
+    When re-raising the unwrapped exception, Python implicitly sets __context__
+    on it pointing back to the ExceptionGroup (because the re-raise happens
+    inside the except block that caught the ExceptionGroup), creating a cycle:
+
+        ExceptionGroup -> .exceptions[0] -> ValueError -> __context__ -> ExceptionGroup
+
+    Without cycle detection in exceptions_from_error(), this causes infinite
+    recursion and a silent RecursionError that drops the event.
+    """
+    exception_group = None
+
+    try:
+        try:
+            raise RuntimeError("something")
+        except RuntimeError:
+            raise ExceptionGroup(
+                "nested",
+                [
+                    ValueError(654),
+                ],
+            )
+    except ExceptionGroup as exc:
+        exception_group = exc
+        unwrapped = exc.exceptions[0]
+        try:
+            raise unwrapped
+        except Exception:
+            pass
+
+    (event, _) = event_from_exception(
+        exception_group,
+        client_options={
+            "include_local_variables": True,
+            "include_source_context": True,
+            "max_value_length": 1024,
+        },
+        mechanism={"type": "test_suite", "handled": False},
+    )
+
+    values = event["exception"]["values"]
+
+    # For this test the stacktrace and the module is not important
+    for x in values:
+        if "stacktrace" in x:
+            del x["stacktrace"]
+        if "module" in x:
+            del x["module"]
+
+    expected_values = [
+        {
+            "mechanism": {
+                "exception_id": 2,
+                "handled": False,
+                "parent_id": 0,
+                "source": "exceptions[0]",
+                "type": "chained",
+            },
+            "type": "ValueError",
+            "value": "654",
+        },
+        {
+            "mechanism": {
+                "exception_id": 1,
+                "handled": False,
+                "parent_id": 0,
+                "source": "__context__",
+                "type": "chained",
+            },
+            "type": "RuntimeError",
+            "value": "something",
+        },
+        {
+            "mechanism": {
+                "exception_id": 0,
+                "handled": False,
+                "is_exception_group": True,
+                "type": "test_suite",
+            },
+            "type": "ExceptionGroup",
+            "value": "nested",
+        },
+    ]
+
+    assert values == expected_values
+
+
+@minimum_python_311
+def test_cyclic_exception_group_cause():
+    """
+    Test case related to `test_exceptiongroup_starlette_collapse` above. We want to make sure that
+    the same cyclic loop cannot happen via the __cause__ as well as the __context__
+    """
+
+    original = ValueError("original error")
+    group = ExceptionGroup("unhandled errors in a TaskGroup", [original])
+    original.__cause__ = group
+    original.__suppress_context__ = True
+
+    # When the ExceptionGroup is the top-level exception, exceptions_from_error
+    # is called directly (not walk_exception_chain which has cycle detection).
+    (event, _) = event_from_exception(
+        group,
+        client_options={
+            "include_local_variables": True,
+            "include_source_context": True,
+            "max_value_length": 1024,
+        },
+        mechanism={"type": "test_suite", "handled": False},
+    )
+
+    exception_values = event["exception"]["values"]
+
+    # Must produce a finite list of exceptions without hitting RecursionError.
+    assert len(exception_values) >= 1
+    exc_types = [v["type"] for v in exception_values]
+    assert "ExceptionGroup" in exc_types
+    assert "ValueError" in exc_types
+
+
+@minimum_python_311
+def test_deeply_nested_cyclic_exception_group():
+    """
+    Related to the `test_exceptiongroup_starlette_collapse` test above.
+
+    Testing a more complex cycle: ExceptionGroup -> ValueError -> __cause__ ->
+    ExceptionGroup (nested) -> TypeError -> __cause__ -> original ExceptionGroup
+    """
+    inner_error = TypeError("inner")
+    outer_error = ValueError("outer")
+    inner_group = ExceptionGroup("inner group", [inner_error])
+    outer_group = ExceptionGroup("outer group", [outer_error])
+
+    # Create a cycle spanning two ExceptionGroups
+    outer_error.__cause__ = inner_group
+    outer_error.__suppress_context__ = True
+    inner_error.__cause__ = outer_group
+    inner_error.__suppress_context__ = True
+
+    (event, _) = event_from_exception(
+        outer_group,
+        client_options={
+            "include_local_variables": True,
+            "include_source_context": True,
+            "max_value_length": 1024,
+        },
+        mechanism={"type": "test_suite", "handled": False},
+    )
+
+    exception_values = event["exception"]["values"]
+    assert len(exception_values) >= 1
+    exc_types = [v["type"] for v in exception_values]
+    assert "ExceptionGroup" in exc_types
+    assert "ValueError" in exc_types
+    assert "TypeError" in exc_types
diff --git a/tests/test_logs.py b/tests/test_logs.py
index d9c8a79f8c..86861cfe90 100644
--- a/tests/test_logs.py
+++ b/tests/test_logs.py
@@ -9,7 +9,7 @@
 import sentry_sdk
 import sentry_sdk.logger
 from sentry_sdk import get_client
-from sentry_sdk.envelope import Envelope, Item, PayloadRef
+from sentry_sdk.envelope import Envelope
 from sentry_sdk.types import Log
 from sentry_sdk.consts import SPANDATA, VERSION
 
@@ -19,8 +19,7 @@
 
 
 def otel_attributes_to_dict(otel_attrs: "Mapping[str, Any]") -> "Mapping[str, Any]":
-    def _convert_attr(attr):
-        # type: (Mapping[str, Union[str, float, bool]]) -> Any
+    def _convert_attr(attr: "Mapping[str, Union[str, float, bool]]") -> "Any":
         if attr["type"] == "boolean":
             return attr["value"]
         if attr["type"] == "double":
@@ -784,3 +783,39 @@ def before_send_log(log, _):
     )
 
     get_client().flush()
+
+
+@minimum_python_37
+@pytest.mark.timeout(5)
+def test_reentrant_add_does_not_deadlock(sentry_init, capture_envelopes):
+    """Adding to the batcher from within a flush must not deadlock.
+
+    This covers the scenario where GC emits a ResourceWarning during
+    _add_to_envelope (or _flush_event.wait/set), and the warning is
+    routed through the logging integration back into batcher.add().
+    See https://github.com/getsentry/sentry-python/issues/5681
+    """
+    sentry_init(enable_logs=True)
+    capture_envelopes()
+
+    client = sentry_sdk.get_client()
+    batcher = client.log_batcher
+
+    reentrant_add_called = False
+    original_add_to_envelope = batcher._add_to_envelope
+
+    def add_to_envelope_with_reentrant_add(envelope):
+        nonlocal reentrant_add_called
+        # Simulate a GC warning routing back into add() during flush
+        batcher.add({"fake": "log"})
+        reentrant_add_called = True
+        original_add_to_envelope(envelope)
+
+    batcher._add_to_envelope = add_to_envelope_with_reentrant_add
+
+    sentry_sdk.logger.warning("test log")
+    client.flush()
+
+    assert reentrant_add_called
+    # If the re-entrancy guard didn't work, this test would hang and it'd
+    # eventually be timed out by pytest-timeout
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
index ada50d645d..3ad3f6042d 100644
--- a/tests/test_metrics.py
+++ b/tests/test_metrics.py
@@ -1,9 +1,6 @@
-import json
-import sys
-from typing import List, Any, Mapping
+from typing import List
 from unittest import mock
 
-import pytest
 
 import sentry_sdk
 from sentry_sdk import get_client
diff --git a/tests/test_scope.py b/tests/test_scope.py
index 710ce33849..44510adaa8 100644
--- a/tests/test_scope.py
+++ b/tests/test_scope.py
@@ -876,7 +876,7 @@ def test_set_tags():
 
 
 def test_last_event_id(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     assert Scope.last_event_id() is None
 
@@ -886,7 +886,7 @@ def test_last_event_id(sentry_init):
 
 
 def test_last_event_id_transaction(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     assert Scope.last_event_id() is None
 
@@ -897,7 +897,7 @@ def test_last_event_id_transaction(sentry_init):
 
 
 def test_last_event_id_cleared(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     # Make sure last_event_id is set
     sentry_sdk.capture_exception(Exception("test"))
diff --git a/tests/test_shadowed_module.py b/tests/test_shadowed_module.py
index 10d86f285b..8beb93dc36 100644
--- a/tests/test_shadowed_module.py
+++ b/tests/test_shadowed_module.py
@@ -7,7 +7,6 @@
 import pytest
 
 from sentry_sdk import integrations
-from sentry_sdk.integrations import _DEFAULT_INTEGRATIONS, Integration
 
 
 def pytest_generate_tests(metafunc):
diff --git a/tests/test_spotlight.py b/tests/test_spotlight.py
index f554ff7c5b..1e304e5e54 100644
--- a/tests/test_spotlight.py
+++ b/tests/test_spotlight.py
@@ -1,7 +1,6 @@
 import pytest
 
 import sentry_sdk
-from sentry_sdk.spotlight import DEFAULT_SPOTLIGHT_URL
 
 
 @pytest.fixture
diff --git a/tests/test_transport.py b/tests/test_transport.py
index 8601a4f138..a121d3f1be 100644
--- a/tests/test_transport.py
+++ b/tests/test_transport.py
@@ -3,6 +3,7 @@
 import os
 import socket
 import sys
+import asyncio
 from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from unittest import mock
@@ -15,6 +16,17 @@
 except (ImportError, ModuleNotFoundError):
     httpcore = None
 
+try:
+    import gevent  # noqa: F401
+
+    running_under_gevent = True
+except ImportError:
+    running_under_gevent = False
+
+skip_under_gevent = pytest.mark.skipif(
+    running_under_gevent, reason="Async tests not compatible with gevent"
+)
+
 import sentry_sdk
 from sentry_sdk import (
     Client,
@@ -29,14 +41,37 @@
 from sentry_sdk.transport import (
     KEEP_ALIVE_SOCKET_OPTIONS,
     _parse_rate_limits,
+    AsyncHttpTransport,
     HttpTransport,
 )
 from sentry_sdk.integrations.logging import LoggingIntegration, ignore_logger
+from sentry_sdk.integrations.asyncio import AsyncioIntegration
 
 
 server = None
 
 
+def _make_async_transport_options(**overrides):
+    defaults = {
+        "dsn": "https://foo@sentry.io/123",
+        "transport": None,
+        "_experiments": {"transport_async": True},
+        "integrations": [AsyncioIntegration()],
+        "send_client_reports": True,
+        "transport_queue_size": 100,
+        "keep_alive": False,
+        "socket_options": None,
+        "ca_certs": None,
+        "cert_file": None,
+        "key_file": None,
+        "http_proxy": None,
+        "https_proxy": None,
+        "proxy_headers": None,
+    }
+    defaults.update(overrides)
+    return defaults
+
+
 @pytest.fixture(scope="module", autouse=True)
 def make_capturing_server(request):
     global server
@@ -841,3 +876,168 @@ def test_record_lost_event_transaction_item(capturing_server, make_client, span_
         "reason": "test",
         "quantity": span_count + 1,
     } in discarded_events
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.parametrize("debug", (True, False))
+@pytest.mark.parametrize("client_flush_method", ["close", "flush"])
+@pytest.mark.parametrize("use_pickle", (True, False))
+@pytest.mark.parametrize("compression_level", (0, 9, None))
+@pytest.mark.parametrize("compression_algo", ("gzip", "br", "<invalid>", None))
+@pytest.mark.skipif(not PY38, reason="Async transport only supported in Python 3.8+")
+async def test_transport_works_async(
+    capturing_server,
+    request,
+    capsys,
+    caplog,
+    debug,
+    make_client,
+    client_flush_method,
+    use_pickle,
+    compression_level,
+    compression_algo,
+):
+    caplog.set_level(logging.DEBUG)
+
+    experiments = {}
+    if compression_level is not None:
+        experiments["transport_compression_level"] = compression_level
+
+    if compression_algo is not None:
+        experiments["transport_compression_algo"] = compression_algo
+
+    # Enable async transport
+    experiments["transport_async"] = True
+
+    client = make_client(
+        debug=debug,
+        _experiments=experiments,
+        integrations=[AsyncioIntegration()],
+    )
+
+    if use_pickle:
+        client = pickle.loads(pickle.dumps(client))
+
+    # Verify we're using async transport
+    assert isinstance(client.transport, AsyncHttpTransport), (
+        "Expected AsyncHttpTransport"
+    )
+
+    sentry_sdk.get_global_scope().set_client(client)
+    request.addfinalizer(lambda: sentry_sdk.get_global_scope().set_client(None))
+
+    add_breadcrumb(
+        level="info", message="i like bread", timestamp=datetime.now(timezone.utc)
+    )
+    capture_message("löl")
+
+    if client_flush_method == "close":
+        await client.close_async(timeout=2.0)
+    if client_flush_method == "flush":
+        await client.flush_async(timeout=2.0)
+
+    out, err = capsys.readouterr()
+    assert not err and not out
+    assert capturing_server.captured
+    should_compress = (
+        # default is to compress with brotli if available, gzip otherwise
+        (compression_level is None)
+        or (
+            # setting compression level to 0 means don't compress
+            compression_level > 0
+        )
+    ) and (
+        # if we couldn't resolve to a known algo, we don't compress
+        compression_algo != "<invalid>"
+    )
+
+    assert capturing_server.captured[0].compressed == should_compress
+    # After flush, the worker task is still running, but the end of the test will shut down the event loop
+    # Therefore, we need to explicitly close the client to clean up the worker task
+    assert any("Sending envelope" in record.msg for record in caplog.records) == debug
+    if client_flush_method == "flush":
+        await client.close_async(timeout=2.0)
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async transport requires Python 3.8+")
+async def test_async_two_way_ssl_authentication():
+    current_dir = os.path.dirname(__file__)
+    cert_file = f"{current_dir}/test.pem"
+    key_file = f"{current_dir}/test.key"
+
+    client = Client(
+        "https://foo@sentry.io/123",
+        cert_file=cert_file,
+        key_file=key_file,
+        _experiments={"transport_async": True},
+        integrations=[AsyncioIntegration()],
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+
+    options = client.transport._get_pool_options()
+    assert options["ssl_context"] is not None
+
+    await client.close_async()
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async transport requires Python 3.8+")
+async def test_async_transport_concurrent_requests(
+    capturing_server, make_client, caplog
+):
+    """Test multiple simultaneous envelope submissions"""
+    caplog.set_level(logging.DEBUG)
+    client = make_client(
+        _experiments={"transport_async": True}, integrations=[AsyncioIntegration()]
+    )
+    assert isinstance(client.transport, AsyncHttpTransport)
+    sentry_sdk.get_global_scope().set_client(client)
+
+    num_messages = 15
+
+    async def send_message(i):
+        capture_message(f"concurrent message {i}")
+
+    tasks = [send_message(i) for i in range(num_messages)]
+    await asyncio.gather(*tasks)
+    await client.close_async(timeout=2.0)
+    assert len(capturing_server.captured) == num_messages
+
+
+@skip_under_gevent
+@pytest.mark.asyncio
+@pytest.mark.skipif(not PY38, reason="Async transport requires Python 3.8+")
+async def test_async_transport_rate_limiting_with_concurrency(
+    capturing_server, make_client, request
+):
+    """Test async transport rate limiting with concurrent requests"""
+    client = make_client(
+        _experiments={"transport_async": True}, integrations=[AsyncioIntegration()]
+    )
+
+    assert isinstance(client.transport, AsyncHttpTransport)
+    sentry_sdk.get_global_scope().set_client(client)
+    request.addfinalizer(lambda: sentry_sdk.get_global_scope().set_client(None))
+    capturing_server.respond_with(
+        code=429, headers={"X-Sentry-Rate-Limits": "60:error:organization"}
+    )
+
+    # Send one request first to trigger rate limiting
+    capture_message("initial message")
+    await asyncio.sleep(0.1)  # Wait for request to execute
+    assert client.transport._check_disabled("error") is True
+    capturing_server.clear_captured()
+
+    async def send_message(i):
+        capture_message(f"message {i}")
+        await asyncio.sleep(0.01)
+
+    await asyncio.gather(*[send_message(i) for i in range(5)])
+    await asyncio.sleep(0.1)
+    # New request should be dropped due to rate limiting
+    assert len(capturing_server.captured) == 0
+    await client.close_async(timeout=2.0)
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 1fc651f805..0fa116a57e 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -7,7 +7,6 @@
 import pytest
 
 import sentry_sdk
-from sentry_sdk._compat import PY38
 from sentry_sdk.integrations import Integration
 from sentry_sdk._queue import Queue
 from sentry_sdk.utils import (
@@ -942,14 +941,12 @@ def target():
     assert (main_thread.ident, main_thread.name) == results.get(timeout=1)
 
 
-@pytest.mark.skipif(PY38, reason="Flakes a lot on 3.8 in CI.")
 def test_get_current_thread_meta_failed_to_get_main_thread():
     results = Queue(maxsize=1)
 
     def target():
-        with mock.patch("threading.current_thread", side_effect=["fake thread"]):
-            with mock.patch("threading.current_thread", side_effect=["fake thread"]):
-                results.put(get_current_thread_meta())
+        with mock.patch("threading.current_thread", return_value="fake thread"):
+            results.put(get_current_thread_meta())
 
     main_thread = threading.main_thread()
 
diff --git a/tests/tracing/test_decorator.py b/tests/tracing/test_decorator.py
index 70dc186ba0..15432f5862 100644
--- a/tests/tracing/test_decorator.py
+++ b/tests/tracing/test_decorator.py
@@ -1,5 +1,4 @@
 import inspect
-import sys
 from unittest import mock
 
 import pytest
diff --git a/tests/tracing/test_deprecated.py b/tests/tracing/test_deprecated.py
index ac3b8d7463..f030a465ff 100644
--- a/tests/tracing/test_deprecated.py
+++ b/tests/tracing/test_deprecated.py
@@ -4,9 +4,6 @@
 
 import sentry_sdk
 import sentry_sdk.tracing
-from sentry_sdk import start_span
-
-from sentry_sdk.tracing import Span
 
 
 @pytest.mark.parametrize(
diff --git a/tests/tracing/test_misc.py b/tests/tracing/test_misc.py
index 8895c98dbc..c6fd6df84e 100644
--- a/tests/tracing/test_misc.py
+++ b/tests/tracing/test_misc.py
@@ -478,7 +478,7 @@ def test_start_transaction_updates_scope_name_source(sentry_init):
 
 @pytest.mark.parametrize("sampled", (True, None))
 def test_transaction_dropped_debug_not_started(sentry_init, sampled):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     tx = Transaction(sampled=sampled)
 
@@ -498,7 +498,7 @@ def test_transaction_dropped_debug_not_started(sentry_init, sampled):
 
 
 def test_transaction_dropeed_sampled_false(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     tx = Transaction(sampled=False)
 
@@ -516,7 +516,7 @@ def test_transaction_dropeed_sampled_false(sentry_init):
 
 
 def test_transaction_not_started_warning(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     tx = Transaction()
 
diff --git a/tests/tracing/test_propagation.py b/tests/tracing/test_propagation.py
index 730bf2672b..77993d9c33 100644
--- a/tests/tracing/test_propagation.py
+++ b/tests/tracing/test_propagation.py
@@ -3,7 +3,7 @@
 
 
 def test_standalone_span_iter_headers(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     with sentry_sdk.start_span(op="test") as span:
         with pytest.raises(StopIteration):
@@ -12,7 +12,7 @@ def test_standalone_span_iter_headers(sentry_init):
 
 
 def test_span_in_span_iter_headers(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     with sentry_sdk.start_span(op="test"):
         with sentry_sdk.start_span(op="test2") as span_inner:
@@ -22,7 +22,7 @@ def test_span_in_span_iter_headers(sentry_init):
 
 
 def test_span_in_transaction(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     with sentry_sdk.start_transaction(op="test"):
         with sentry_sdk.start_span(op="test2") as span:
@@ -31,7 +31,7 @@ def test_span_in_transaction(sentry_init):
 
 
 def test_span_in_span_in_transaction(sentry_init):
-    sentry_init(enable_tracing=True)
+    sentry_init(traces_sample_rate=1.0)
 
     with sentry_sdk.start_transaction(op="test"):
         with sentry_sdk.start_span(op="test2"):
diff --git a/tests/tracing/test_sampling.py b/tests/tracing/test_sampling.py
index c0f307ecf7..93c1106c99 100644
--- a/tests/tracing/test_sampling.py
+++ b/tests/tracing/test_sampling.py
@@ -5,7 +5,7 @@
 import pytest
 
 import sentry_sdk
-from sentry_sdk import start_span, start_transaction, capture_exception, continue_trace
+from sentry_sdk import start_span, start_transaction, capture_exception
 from sentry_sdk.tracing_utils import Baggage
 from sentry_sdk.utils import logger
 
diff --git a/tests/tracing/test_span_streaming.py b/tests/tracing/test_span_streaming.py
new file mode 100644
index 0000000000..44f504cc26
--- /dev/null
+++ b/tests/tracing/test_span_streaming.py
@@ -0,0 +1,1555 @@
+import asyncio
+import re
+import sys
+import time
+from unittest import mock
+from typing import Any
+
+import pytest
+
+import sentry_sdk
+from sentry_sdk.profiler.continuous_profiler import get_profiler_id
+from sentry_sdk.traces import NoOpStreamedSpan, SpanStatus, StreamedSpan
+
+
+minimum_python_38 = pytest.mark.skipif(
+    sys.version_info < (3, 8), reason="Asyncio tests need Python >= 3.8"
+)
+
+
+def envelopes_to_spans(envelopes):
+    res: "list[dict[str, Any]]" = []
+    for envelope in envelopes:
+        for item in envelope.items:
+            if item.type == "span":
+                for span_json in item.payload.json["items"]:
+                    span = {
+                        "start_timestamp": span_json["start_timestamp"],
+                        "end_timestamp": span_json.get("end_timestamp"),
+                        "trace_id": span_json["trace_id"],
+                        "span_id": span_json["span_id"],
+                        "name": span_json["name"],
+                        "status": span_json["status"],
+                        "is_segment": span_json["is_segment"],
+                        "parent_span_id": span_json.get("parent_span_id"),
+                        "attributes": {
+                            k: v["value"] for (k, v) in span_json["attributes"].items()
+                        },
+                    }
+                    res.append(span)
+    return res
+
+
+def test_start_span(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment") as segment:
+        assert segment._is_segment() is True
+        with sentry_sdk.traces.start_span(name="child") as child:
+            assert child._is_segment() is False
+            assert child._segment == segment
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    child, segment = spans
+
+    assert segment["name"] == "segment"
+    assert segment["attributes"]["sentry.segment.name"] == "segment"
+    assert child["name"] == "child"
+    assert child["attributes"]["sentry.segment.name"] == "segment"
+
+    assert segment["is_segment"] is True
+    assert segment["parent_span_id"] is None
+    assert child["is_segment"] is False
+    assert child["parent_span_id"] == segment["span_id"]
+    assert child["trace_id"] == segment["trace_id"]
+
+    assert segment["start_timestamp"] is not None
+    assert child["start_timestamp"] is not None
+    assert segment["end_timestamp"] is not None
+    assert child["end_timestamp"] is not None
+
+    assert child["status"] == "ok"
+    assert segment["status"] == "ok"
+
+
+def test_start_span_no_context_manager(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    segment = sentry_sdk.traces.start_span(name="segment")
+    child = sentry_sdk.traces.start_span(name="child")
+    assert child._segment == segment
+    child.end()
+    segment.end()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    child, segment = spans
+
+    assert segment["name"] == "segment"
+    assert segment["attributes"]["sentry.segment.name"] == "segment"
+    assert child["name"] == "child"
+    assert child["attributes"]["sentry.segment.name"] == "segment"
+
+    assert segment["is_segment"] is True
+    assert child["is_segment"] is False
+    assert child["parent_span_id"] == segment["span_id"]
+    assert child["trace_id"] == segment["trace_id"]
+
+    assert segment["start_timestamp"] is not None
+    assert child["start_timestamp"] is not None
+    assert segment["end_timestamp"] is not None
+    assert child["end_timestamp"] is not None
+
+    assert child["status"] == "ok"
+    assert segment["status"] == "ok"
+
+
+def test_span_sampled_when_created(sentry_init, capture_envelopes):
+    # Test that if a span is created without the context manager, it is sampled
+    # at start_span() time
+
+    def traces_sampler(sampling_context):
+        assert "delayed_attribute" not in sampling_context["span_context"]["attributes"]
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    segment = sentry_sdk.traces.start_span(name="segment")
+    segment.set_attribute("delayed_attribute", 12)
+    segment.end()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (segment,) = spans
+
+    assert segment["name"] == "segment"
+    assert segment["attributes"]["delayed_attribute"] == 12
+
+
+def test_start_span_attributes(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(
+        name="segment", attributes={"my_attribute": "my_value"}
+    ):
+        ...
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "segment"
+    assert span["attributes"]["my_attribute"] == "my_value"
+
+
+def test_start_span_attributes_in_traces_sampler(sentry_init, capture_envelopes):
+    def traces_sampler(sampling_context):
+        assert "attributes" in sampling_context["span_context"]
+        assert "my_attribute" in sampling_context["span_context"]["attributes"]
+        assert (
+            sampling_context["span_context"]["attributes"]["my_attribute"] == "my_value"
+        )
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(
+        name="segment", attributes={"my_attribute": "my_value"}
+    ):
+        ...
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "segment"
+    assert span["attributes"]["my_attribute"] == "my_value"
+
+
+def test_sampling_context(sentry_init, capture_envelopes):
+    received_trace_id = None
+
+    def traces_sampler(sampling_context):
+        nonlocal received_trace_id
+
+        assert "trace_id" in sampling_context["span_context"]
+        received_trace_id = sampling_context["span_context"]["trace_id"]
+
+        assert "parent_span_id" in sampling_context["span_context"]
+        assert sampling_context["span_context"]["parent_span_id"] is None
+
+        assert "parent_sampled" in sampling_context["span_context"]
+        assert sampling_context["span_context"]["parent_sampled"] is None
+
+        assert "attributes" in sampling_context["span_context"]
+
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="span") as span:
+        trace_id = span._trace_id
+
+    assert received_trace_id == trace_id
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+
+
+def test_custom_sampling_context(sentry_init):
+    class MyClass: ...
+
+    my_class = MyClass()
+
+    def traces_sampler(sampling_context):
+        assert "class" in sampling_context
+        assert "string" in sampling_context
+        assert sampling_context["class"] == my_class
+        assert sampling_context["string"] == "my string"
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    sentry_sdk.get_current_scope().set_custom_sampling_context(
+        {
+            "class": my_class,
+            "string": "my string",
+        }
+    )
+
+    with sentry_sdk.traces.start_span(name="span"):
+        ...
+
+
+def test_custom_sampling_context_update_to_context_value_persists(sentry_init):
+    def traces_sampler(sampling_context):
+        if sampling_context["span_context"]["attributes"]["first"] is True:
+            assert sampling_context["custom_value"] == 1
+        else:
+            assert sampling_context["custom_value"] == 2
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    sentry_sdk.traces.new_trace()
+
+    sentry_sdk.get_current_scope().set_custom_sampling_context({"custom_value": 1})
+
+    with sentry_sdk.traces.start_span(name="span", attributes={"first": True}):
+        ...
+
+    sentry_sdk.traces.new_trace()
+
+    sentry_sdk.get_current_scope().set_custom_sampling_context({"custom_value": 2})
+
+    with sentry_sdk.traces.start_span(name="span", attributes={"first": False}):
+        ...
+
+
+def test_span_attributes(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(
+        name="segment", attributes={"attribute1": "value"}
+    ) as span:
+        assert span.get_attributes()["attribute1"] == "value"
+        span.set_attribute("attribute2", 47)
+        span.remove_attribute("attribute1")
+        span.set_attributes({"attribute3": 4.5, "attribute4": False})
+        assert "attribute1" not in span.get_attributes()
+        attributes = span.get_attributes()
+        assert attributes["attribute2"] == 47
+        assert attributes["attribute3"] == 4.5
+        assert attributes["attribute4"] is False
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "segment"
+    assert "attribute1" not in span["attributes"]
+    assert span["attributes"]["attribute2"] == 47
+    assert span["attributes"]["attribute3"] == 4.5
+    assert span["attributes"]["attribute4"] is False
+
+
+def test_span_attributes_serialize_early(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    class Class:
+        pass
+
+    with sentry_sdk.traces.start_span(name="span") as span:
+        span.set_attributes(
+            {
+                # arrays of different types will be serialized
+                "attribute1": [123, "text"],
+                # so will custom class instances
+                "attribute2": Class(),
+            }
+        )
+        attributes = span.get_attributes()
+        assert isinstance(attributes["attribute1"], str)
+        assert attributes["attribute1"] == "[123, 'text']"
+        assert isinstance(attributes["attribute2"], str)
+        assert "Class" in attributes["attribute2"]
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["attributes"]["attribute1"] == "[123, 'text']"
+    assert "Class" in span["attributes"]["attribute2"]
+
+
+def test_traces_sampler_drops_span(sentry_init, capture_envelopes):
+    def traces_sampler(sampling_context):
+        assert "attributes" in sampling_context["span_context"]
+        assert "drop" in sampling_context["span_context"]["attributes"]
+
+        if sampling_context["span_context"]["attributes"]["drop"] is True:
+            return 0.0
+
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="dropped", attributes={"drop": True}):
+        ...
+    with sentry_sdk.traces.start_span(name="retained", attributes={"drop": False}):
+        ...
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "retained"
+    assert span["attributes"]["drop"] is False
+
+
+def test_traces_sampler_called_once_per_segment(sentry_init):
+    traces_sampler_called = 0
+    span_name_in_traces_sampler = None
+
+    def traces_sampler(sampling_context):
+        nonlocal traces_sampler_called, span_name_in_traces_sampler
+        traces_sampler_called += 1
+        span_name_in_traces_sampler = sampling_context["span_context"]["name"]
+        return 1.0
+
+    sentry_init(
+        traces_sampler=traces_sampler,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    with sentry_sdk.traces.start_span(name="segment") as segment:
+        with sentry_sdk.traces.start_span(name="child1"):
+            ...
+        with sentry_sdk.traces.start_span(name="child2"):
+            with sentry_sdk.traces.start_span(name="child3"):
+                ...
+
+    assert traces_sampler_called == 1
+    assert span_name_in_traces_sampler == segment.name
+
+
+def test_start_inactive_span(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment") as segment:
+        with sentry_sdk.traces.start_span(name="child1", active=False):
+            with sentry_sdk.traces.start_span(name="child2"):
+                # Should have segment as parent since child1 is inactive
+                pass
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 3
+    child2, child1, segment = spans
+
+    assert segment["is_segment"] is True
+    assert segment["name"] == "segment"
+    assert segment["attributes"]["sentry.segment.name"] == "segment"
+
+    assert child1["is_segment"] is False
+    assert child1["name"] == "child1"
+    assert child1["attributes"]["sentry.segment.name"] == "segment"
+    assert child1["parent_span_id"] == segment["span_id"]
+    assert child1["trace_id"] == segment["trace_id"]
+
+    assert child2["is_segment"] is False
+    assert child2["name"] == "child2"
+    assert child2["attributes"]["sentry.segment.name"] == "segment"
+    assert child2["parent_span_id"] == segment["span_id"]
+    assert child2["trace_id"] == segment["trace_id"]
+
+
+def test_start_span_override_parent(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment") as segment:
+        with sentry_sdk.traces.start_span(name="child1"):
+            with sentry_sdk.traces.start_span(name="child2", parent_span=segment):
+                pass
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 3
+    child2, child1, segment = spans
+
+    assert segment["name"] == "segment"
+    assert segment["attributes"]["sentry.segment.name"] == "segment"
+
+    assert child1["name"] == "child1"
+    assert child1["attributes"]["sentry.segment.name"] == "segment"
+
+    assert child2["name"] == "child2"
+    assert child2["attributes"]["sentry.segment.name"] == "segment"
+
+    assert segment["is_segment"] is True
+
+    assert child1["is_segment"] is False
+    assert child1["parent_span_id"] == segment["span_id"]
+    assert child1["trace_id"] == segment["trace_id"]
+
+    assert child2["is_segment"] is False
+    assert child2["parent_span_id"] == segment["span_id"]
+    assert child2["trace_id"] == segment["trace_id"]
+
+
+def test_sibling_segments(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment1"):
+        ...
+
+    with sentry_sdk.traces.start_span(name="segment2"):
+        ...
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    segment1, segment2 = spans
+
+    assert segment1["name"] == "segment1"
+    assert segment1["attributes"]["sentry.segment.name"] == "segment1"
+    assert segment1["is_segment"] is True
+    assert segment1["parent_span_id"] is None
+
+    assert segment2["name"] == "segment2"
+    assert segment2["attributes"]["sentry.segment.name"] == "segment2"
+    assert segment2["is_segment"] is True
+    assert segment2["parent_span_id"] is None
+
+    assert segment1["trace_id"] == segment2["trace_id"]
+
+
+def test_sibling_segments_new_trace(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment1"):
+        ...
+
+    sentry_sdk.traces.new_trace()
+
+    with sentry_sdk.traces.start_span(name="segment2"):
+        ...
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    segment1, segment2 = spans
+
+    assert segment1["name"] == "segment1"
+    assert segment1["attributes"]["sentry.segment.name"] == "segment1"
+    assert segment1["is_segment"] is True
+    assert segment1["parent_span_id"] is None
+
+    assert segment2["name"] == "segment2"
+    assert segment2["attributes"]["sentry.segment.name"] == "segment2"
+    assert segment2["is_segment"] is True
+    assert segment2["parent_span_id"] is None
+
+    assert segment1["trace_id"] != segment2["trace_id"]
+
+
+def test_continue_trace_sampled(sentry_init, capture_envelopes):
+    sentry_init(
+        # parent sampling decision takes precedence over traces_sample_rate
+        traces_sample_rate=0.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    trace_id = "0af7651916cd43dd8448eb211c80319c"
+    parent_span_id = "b7ad6b7169203331"
+    sample_rand = "0.222222"
+    sampled = "1"
+
+    sentry_sdk.traces.continue_trace(
+        {
+            "sentry-trace": f"{trace_id}-{parent_span_id}-{sampled}",
+            "baggage": f"sentry-trace_id={trace_id},sentry-sample_rate=0.5,sentry-sample_rand={sample_rand}",
+        }
+    )
+
+    with sentry_sdk.traces.start_span(name="segment") as span:
+        ...
+
+    assert span.sampled is True
+    assert span.trace_id == trace_id
+    assert span._parent_span_id == parent_span_id
+    assert span._sample_rand == float(sample_rand)
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (segment,) = spans
+
+    assert segment["is_segment"] is True
+    assert segment["parent_span_id"] == parent_span_id
+    assert segment["trace_id"] == trace_id
+
+
+def test_continue_trace_unsampled(sentry_init, capture_envelopes):
+    sentry_init(
+        # parent sampling decision takes precedence over traces_sample_rate
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    trace_id = "0af7651916cd43dd8448eb211c80319c"
+    parent_span_id = "b7ad6b7169203331"
+    sample_rand = "0.999999"
+    sampled = "0"
+
+    sentry_sdk.traces.continue_trace(
+        {
+            "sentry-trace": f"{trace_id}-{parent_span_id}-{sampled}",
+            "baggage": f"sentry-trace_id={trace_id},sentry-sample_rate=0.5,sentry-sample_rand={sample_rand}",
+        }
+    )
+
+    with sentry_sdk.traces.start_span(name="segment") as span:
+        ...
+
+    assert span.sampled is False
+    assert span.name == ""
+    assert span.trace_id == "00000000000000000000000000000000"
+    assert span.span_id == "0000000000000000"
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 0
+
+
+def test_unsampled_spans_produce_client_report(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    sentry_init(
+        traces_sample_rate=0.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    envelopes = capture_envelopes()
+    record_lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="segment"):
+        with sentry_sdk.traces.start_span(name="child1"):
+            pass
+        with sentry_sdk.traces.start_span(name="child2"):
+            pass
+
+    sentry_sdk.get_client().flush()
+
+    spans = envelopes_to_spans(envelopes)
+    assert not spans
+
+    assert record_lost_event_calls == [
+        ("sample_rate", "span", None, 1),
+        ("sample_rate", "span", None, 1),
+        ("sample_rate", "span", None, 1),
+    ]
+
+
+def test_no_client_reports_if_tracing_is_off(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    sentry_init(
+        traces_sample_rate=None,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    envelopes = capture_envelopes()
+    record_lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="segment"):
+        with sentry_sdk.traces.start_span(name="child1"):
+            pass
+        with sentry_sdk.traces.start_span(name="child2"):
+            pass
+
+    sentry_sdk.get_client().flush()
+
+    spans = envelopes_to_spans(envelopes)
+    assert not spans
+    assert not record_lost_event_calls
+
+
+def test_continue_trace_no_sample_rand(sentry_init, capture_envelopes):
+    sentry_init(
+        # parent sampling decision takes precedence over traces_sample_rate
+        traces_sample_rate=0.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    trace_id = "0af7651916cd43dd8448eb211c80319c"
+    parent_span_id = "b7ad6b7169203331"
+    sampled = "1"
+
+    sentry_sdk.traces.continue_trace(
+        {
+            "sentry-trace": f"{trace_id}-{parent_span_id}-{sampled}",
+            "baggage": f"sentry-trace_id={trace_id},sentry-sample_rate=0.5",
+        }
+    )
+
+    with sentry_sdk.traces.start_span(name="segment") as span:
+        ...
+
+    assert span.sampled is True
+    assert span.trace_id == trace_id
+    assert span._parent_span_id == parent_span_id
+    assert isinstance(span._sample_rand, float)
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (segment,) = spans
+
+    assert segment["is_segment"] is True
+    assert segment["parent_span_id"] == parent_span_id
+    assert segment["trace_id"] == trace_id
+
+
+def test_outgoing_traceparent_and_baggage(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    sentry_sdk.traces.new_trace()
+
+    with sentry_sdk.traces.start_span(name="span") as span:
+        assert span.sampled is True
+
+        trace_id = span.trace_id
+        span_id = span.span_id
+
+        traceparent = sentry_sdk.get_traceparent()
+        assert traceparent == f"{trace_id}-{span_id}-1"
+
+        baggage = sentry_sdk.get_baggage()
+        baggage_items = dict(tuple(item.split("=")) for item in baggage.split(","))
+        assert "sentry-trace_id" in baggage_items
+        assert baggage_items["sentry-trace_id"] == trace_id
+        assert "sentry-sampled" in baggage_items
+        assert baggage_items["sentry-sampled"] == "true"
+
+
+def test_outgoing_traceparent_and_baggage_when_noop_span_is_active(
+    sentry_init, capture_envelopes
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    sentry_sdk.traces.new_trace()
+
+    propagation_context = (
+        sentry_sdk.get_current_scope().get_active_propagation_context()
+    )
+    propagation_trace_id = propagation_context.trace_id
+    propagation_span_id = propagation_context.span_id
+
+    with sentry_sdk.traces.start_span(name="ignored") as span:
+        assert span.sampled is False
+
+        noop_trace_id = span.trace_id
+        noop_span_id = span.span_id
+
+        traceparent = sentry_sdk.get_traceparent()
+        assert traceparent != f"{noop_trace_id}-{noop_span_id}"
+        assert traceparent == f"{propagation_trace_id}-{propagation_span_id}"
+
+        baggage = sentry_sdk.get_baggage()
+        baggage_items = dict(tuple(item.split("=")) for item in baggage.split(","))
+        assert "sentry-trace_id" in baggage_items
+        assert baggage_items["sentry-trace_id"] != noop_trace_id
+        assert baggage_items["sentry-trace_id"] == propagation_trace_id
+
+
+def test_trace_decorator(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace
+    def traced_function(): ...
+
+    traced_function()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert (
+        span["name"]
+        == "test_span_streaming.test_trace_decorator.<locals>.traced_function"
+    )
+    assert span["status"] == "ok"
+
+
+def test_trace_decorator_arguments(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace(name="traced", attributes={"traced.attribute": 123})
+    def traced_function(): ...
+
+    traced_function()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "traced"
+    assert span["attributes"]["traced.attribute"] == 123
+    assert span["status"] == "ok"
+
+
+def test_trace_decorator_inactive(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace(name="outer", active=False)
+    def traced_function():
+        with sentry_sdk.traces.start_span(name="inner"):
+            ...
+
+    traced_function()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    (span1, span2) = spans
+
+    assert span1["name"] == "inner"
+    assert span1["parent_span_id"] != span2["span_id"]
+
+    assert span2["name"] == "outer"
+
+
+@minimum_python_38
+def test_trace_decorator_async(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace
+    async def traced_function(): ...
+
+    asyncio.run(traced_function())
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert (
+        span["name"]
+        == "test_span_streaming.test_trace_decorator_async.<locals>.traced_function"
+    )
+    assert span["status"] == "ok"
+
+
+@minimum_python_38
+def test_trace_decorator_async_arguments(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace(name="traced", attributes={"traced.attribute": 123})
+    async def traced_function(): ...
+
+    asyncio.run(traced_function())
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["name"] == "traced"
+    assert span["attributes"]["traced.attribute"] == 123
+    assert span["status"] == "ok"
+
+
+@minimum_python_38
+def test_trace_decorator_async_inactive(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    @sentry_sdk.traces.trace(name="outer", active=False)
+    async def traced_function():
+        with sentry_sdk.traces.start_span(name="inner"):
+            ...
+
+    asyncio.run(traced_function())
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    (span1, span2) = spans
+
+    assert span1["name"] == "inner"
+    assert span1["parent_span_id"] != span2["span_id"]
+
+    assert span2["name"] == "outer"
+
+
+def test_set_span_status(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="span") as span:
+        span.status = SpanStatus.ERROR
+
+    with sentry_sdk.traces.start_span(name="span") as span:
+        span.status = "error"
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    (span1, span2) = spans
+
+    assert span1["status"] == "error"
+    assert span2["status"] == "error"
+
+
+def test_set_span_status_on_error(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    events = capture_envelopes()
+
+    with pytest.raises(ValueError):
+        with sentry_sdk.traces.start_span(name="span") as span:
+            raise ValueError("oh no!")
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+
+    assert span["status"] == "error"
+
+
+def test_set_span_status_on_ignored_span(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream", "ignore_spans": ["ignored"]},
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="ignored") as span:
+        span.status = "error"
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 0
+
+
+@pytest.mark.parametrize(
+    ("ignore_spans", "name", "attributes", "ignored"),
+    [
+        # no regexes
+        ([], "/health", {}, False),
+        ([{}], "/health", {}, False),
+        (["/health"], "/health", {}, True),
+        (["/health"], "/health", {"custom": "custom"}, True),
+        ([{"name": "/health"}], "/health", {}, True),
+        ([{"name": "/health"}], "/health", {"custom": "custom"}, True),
+        ([{"attributes": {"custom": "custom"}}], "/health", {"custom": "custom"}, True),
+        ([{"attributes": {"custom": "custom"}}], "/health", {}, False),
+        (
+            [{"name": "/nothealth", "attributes": {"custom": "custom"}}],
+            "/health",
+            {"custom": "custom"},
+            False,
+        ),
+        (
+            [{"name": "/health", "attributes": {"custom": "notcustom"}}],
+            "/health",
+            {"custom": "custom"},
+            False,
+        ),
+        (
+            [{"name": "/health", "attributes": {"custom": "custom"}}],
+            "/health",
+            {"custom": "custom"},
+            True,
+        ),
+        # test cases with regexes
+        ([re.compile("/hea.*")], "/health", {}, True),
+        ([re.compile("/hea.*")], "/health", {"custom": "custom"}, True),
+        ([{"name": re.compile("/hea.*")}], "/health", {}, True),
+        ([{"name": re.compile("/hea.*")}], "/health", {"custom": "custom"}, True),
+        (
+            [{"attributes": {"custom": re.compile("c.*")}}],
+            "/health",
+            {"custom": "custom"},
+            True,
+        ),
+        ([{"attributes": {"custom": re.compile("c.*")}}], "/health", {}, False),
+        (
+            [
+                {
+                    "name": re.compile("/nothea.*"),
+                    "attributes": {"custom": re.compile("c.*")},
+                }
+            ],
+            "/health",
+            {"custom": "custom"},
+            False,
+        ),
+        (
+            [
+                {
+                    "name": re.compile("/hea.*"),
+                    "attributes": {"custom": re.compile("notc.*")},
+                }
+            ],
+            "/health",
+            {"custom": "custom"},
+            False,
+        ),
+        (
+            [
+                {
+                    "name": re.compile("/hea.*"),
+                    "attributes": {"custom": re.compile("c.*")},
+                }
+            ],
+            "/health",
+            {"custom": "custom"},
+            True,
+        ),
+        (
+            [{"attributes": {"listattr": re.compile(r"\[.*\]")}}],
+            "/a",
+            {"listattr": [1, 2, 3]},
+            False,
+        ),
+    ],
+)
+def test_ignore_spans(
+    sentry_init, capture_envelopes, ignore_spans, name, attributes, ignored
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ignore_spans,
+        },
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name=name, attributes=attributes) as span:
+        if ignored:
+            assert span.sampled is False
+            assert isinstance(span, NoOpStreamedSpan)
+        else:
+            assert span.sampled is True
+            assert isinstance(span, StreamedSpan)
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    if ignored:
+        assert len(spans) == 0
+    else:
+        assert len(spans) == 1
+        (span,) = spans
+        assert span["name"] == name
+
+
+def test_ignore_spans_basic(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+    lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="ignored") as ignored_span:
+        assert ignored_span.sampled is False
+
+    with sentry_sdk.traces.start_span(name="not ignored") as span:
+        assert span.sampled is True
+
+    sentry_sdk.get_client().flush()
+
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 1
+    (span,) = spans
+    assert span["name"] == "not ignored"
+    assert span["parent_span_id"] is None
+
+    assert len(lost_event_calls) == 1
+    assert lost_event_calls[0] == ("ignored", "span", None, 1)
+
+
+def test_ignore_spans_ignored_segment_drops_whole_tree(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    # Ignored segments should drop the whole span tree.
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+    lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="ignored") as ignored_span:
+        assert ignored_span.sampled is False
+        assert isinstance(ignored_span, NoOpStreamedSpan)
+
+        with sentry_sdk.traces.start_span(name="not ignored") as span1:
+            assert span1.sampled is False
+            assert isinstance(span1, NoOpStreamedSpan)
+
+            with sentry_sdk.traces.start_span(name="not ignored") as span2:
+                assert span2.sampled is False
+                assert isinstance(span2, NoOpStreamedSpan)
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 0
+
+    assert len(lost_event_calls) == 3
+    for lost_event_call in lost_event_calls:
+        assert lost_event_call == ("ignored", "span", None, 1)
+
+
+def test_ignore_spans_ignored_segment_drops_whole_tree_explicit_parent_span(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    # Ignored segments should drop the whole span tree.
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+    lost_event_calls = capture_record_lost_event_calls()
+
+    ignored_span = sentry_sdk.traces.start_span(name="ignored")
+    assert isinstance(ignored_span, NoOpStreamedSpan)
+    assert ignored_span.sampled is False
+
+    span1 = sentry_sdk.traces.start_span(name="not ignored 1", parent_span=ignored_span)
+    assert isinstance(span1, NoOpStreamedSpan)
+    assert span1.sampled is False
+
+    span2 = sentry_sdk.traces.start_span(name="not ignored 2", parent_span=ignored_span)
+    assert isinstance(span2, NoOpStreamedSpan)
+    assert span2.sampled is False
+
+    span1.end()
+    span2.end()
+    ignored_span.end()
+
+    sentry_sdk.get_client().flush()
+
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 0
+
+    assert len(lost_event_calls) == 3
+    for lost_event_call in lost_event_calls:
+        assert lost_event_call == ("ignored", "span", None, 1)
+
+
+def test_ignore_spans_set_ignored_child_span_as_parent(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    # Ignored non-segment spans should NOT drop the whole subtree under them.
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+    lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="segment") as segment:
+        assert segment.sampled is True
+
+        with sentry_sdk.traces.start_span(name="ignored") as ignored_span1:
+            assert ignored_span1.sampled is False
+
+            with sentry_sdk.traces.start_span(name="ignored") as ignored_span2:
+                assert ignored_span2.sampled is False
+
+                with sentry_sdk.traces.start_span(name="child") as span:
+                    assert span.sampled is True
+                    assert span._parent_span_id == segment.span_id
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    (child, segment) = spans
+    assert segment["name"] == "segment"
+    assert child["name"] == "child"
+    assert child["parent_span_id"] == segment["span_id"]  # reparented to segment
+
+    assert len(lost_event_calls) == 2
+    for lost_event_call in lost_event_calls:
+        assert lost_event_call == ("ignored", "span", None, 1)
+
+
+def test_ignore_spans_set_ignored_child_span_as_parent_explicit_parent_span(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    # Ignored non-segment spans should NOT drop the whole subtree under them.
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+    lost_event_calls = capture_record_lost_event_calls()
+
+    segment = sentry_sdk.traces.start_span(name="segment")
+    assert not isinstance(segment, NoOpStreamedSpan)
+    assert segment.sampled is True
+    assert segment._parent_span_id is None
+
+    ignored_span1 = sentry_sdk.traces.start_span(name="ignored", parent_span=segment)
+    assert isinstance(ignored_span1, NoOpStreamedSpan)
+    assert ignored_span1.sampled is False
+
+    ignored_span2 = sentry_sdk.traces.start_span(
+        name="ignored", parent_span=ignored_span1
+    )
+    assert isinstance(ignored_span2, NoOpStreamedSpan)
+    assert ignored_span2.sampled is False
+
+    span = sentry_sdk.traces.start_span(name="child", parent_span=ignored_span2)
+    assert not isinstance(span, NoOpStreamedSpan)
+    assert span.sampled is True
+    assert span._parent_span_id == segment.span_id
+    span.end()
+
+    ignored_span2.end()
+    ignored_span1.end()
+    segment.end()
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 2
+    (child, segment) = spans
+    assert segment["name"] == "segment"
+    assert child["name"] == "child"
+    assert child["parent_span_id"] == segment["span_id"]  # reparented to segment
+
+    assert len(lost_event_calls) == 2
+    for lost_event_call in lost_event_calls:
+        assert lost_event_call == ("ignored", "span", None, 1)
+
+
+def test_ignore_spans_reparenting(sentry_init, capture_envelopes):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "ignore_spans": ["ignored"],
+        },
+    )
+
+    events = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment") as span1:
+        assert span1.sampled is True
+        assert span1._parent_span_id is None
+
+        with sentry_sdk.traces.start_span(name="ignored") as span2:
+            assert span2.sampled is False
+
+            with sentry_sdk.traces.start_span(name="child 1") as span3:
+                assert span3.sampled is True
+                assert span3._parent_span_id == span1.span_id
+
+                with sentry_sdk.traces.start_span(name="ignored") as span4:
+                    assert span4.sampled is False
+
+                    with sentry_sdk.traces.start_span(name="child 2") as span5:
+                        assert span5.sampled is True
+                        assert span5._parent_span_id == span3.span_id
+
+    sentry_sdk.get_client().flush()
+    spans = envelopes_to_spans(events)
+
+    assert len(spans) == 3
+    (span5, span3, span1) = spans
+    assert span1["name"] == "segment"
+    assert span3["name"] == "child 1"
+    assert span5["name"] == "child 2"
+    assert span3["parent_span_id"] == span1["span_id"]
+    assert span5["parent_span_id"] == span3["span_id"]
+
+
+def test_ignored_spans_produce_client_report(
+    sentry_init, capture_envelopes, capture_record_lost_event_calls
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream", "ignore_spans": ["ignored"]},
+    )
+
+    envelopes = capture_envelopes()
+    record_lost_event_calls = capture_record_lost_event_calls()
+
+    with sentry_sdk.traces.start_span(name="ignored"):
+        with sentry_sdk.traces.start_span(name="span1"):
+            pass
+        with sentry_sdk.traces.start_span(name="span2"):
+            pass
+
+    sentry_sdk.get_client().flush()
+
+    spans = envelopes_to_spans(envelopes)
+    assert not spans
+
+    # All three spans will be ignored since the segment is ignored
+    assert record_lost_event_calls == [
+        ("ignored", "span", None, 1),
+        ("ignored", "span", None, 1),
+        ("ignored", "span", None, 1),
+    ]
+
+
+@mock.patch("sentry_sdk.profiler.continuous_profiler.DEFAULT_SAMPLING_FREQUENCY", 21)
+def test_segment_span_has_profiler_id(
+    sentry_init, capture_envelopes, teardown_profiling
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        profile_lifecycle="trace",
+        profiler_mode="thread",
+        profile_session_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "continuous_profiling_auto_start": True,
+        },
+    )
+    envelopes = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="profiled segment"):
+        time.sleep(0.1)
+
+    sentry_sdk.get_client().flush()
+    time.sleep(0.3)  # wait for profiler to flush
+
+    spans = envelopes_to_spans(envelopes)
+    assert len(spans) == 1
+    assert "sentry.profiler_id" in spans[0]["attributes"]
+
+    profile_chunks = [
+        item
+        for envelope in envelopes
+        for item in envelope.items
+        if item.type == "profile_chunk"
+    ]
+    assert len(profile_chunks) > 0
+
+
+def test_segment_span_no_profiler_id_when_unsampled(
+    sentry_init, capture_envelopes, teardown_profiling
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        profile_lifecycle="trace",
+        profiler_mode="thread",
+        profile_session_sample_rate=0.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "continuous_profiling_auto_start": True,
+        },
+    )
+    envelopes = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment"):
+        time.sleep(0.05)
+
+    sentry_sdk.get_client().flush()
+    time.sleep(0.2)
+
+    spans = envelopes_to_spans(envelopes)
+    assert len(spans) == 1
+    assert "sentry.profiler_id" not in spans[0]["attributes"]
+
+    profile_chunks = [
+        item
+        for envelope in envelopes
+        for item in envelope.items
+        if item.type == "profile_chunk"
+    ]
+    assert len(profile_chunks) == 0
+
+
+@mock.patch("sentry_sdk.profiler.continuous_profiler.DEFAULT_SAMPLING_FREQUENCY", 21)
+def test_profile_stops_when_segment_ends(
+    sentry_init, capture_envelopes, teardown_profiling
+):
+    sentry_init(
+        traces_sample_rate=1.0,
+        profile_lifecycle="trace",
+        profiler_mode="thread",
+        profile_session_sample_rate=1.0,
+        _experiments={
+            "trace_lifecycle": "stream",
+            "continuous_profiling_auto_start": True,
+        },
+    )
+    capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="segment") as span:
+        time.sleep(0.1)
+        assert span._continuous_profile is not None
+        assert span._continuous_profile.active is True
+
+    assert span._continuous_profile.active is False
+
+    time.sleep(0.3)
+    assert get_profiler_id() is None, "profiler should have stopped"
+
+
+def test_transport_format(sentry_init, capture_envelopes):
+    sentry_init(
+        server_name="test-server",
+        release="1.0.0",
+        traces_sample_rate=1.0,
+        _experiments={"trace_lifecycle": "stream"},
+    )
+
+    envelopes = capture_envelopes()
+
+    with sentry_sdk.traces.start_span(name="test"):
+        ...
+
+    sentry_sdk.get_client().flush()
+
+    assert len(envelopes) == 1
+    assert len(envelopes[0].items) == 1
+    item = envelopes[0].items[0]
+
+    assert item.type == "span"
+    assert item.headers == {
+        "type": "span",
+        "item_count": 1,
+        "content_type": "application/vnd.sentry.items.span.v2+json",
+    }
+    assert item.payload.json == {
+        "items": [
+            {
+                "trace_id": mock.ANY,
+                "span_id": mock.ANY,
+                "name": "test",
+                "status": "ok",
+                "is_segment": True,
+                "start_timestamp": mock.ANY,
+                "end_timestamp": mock.ANY,
+                "attributes": {
+                    "thread.id": {"value": mock.ANY, "type": "string"},
+                    "thread.name": {"value": "MainThread", "type": "string"},
+                    "sentry.segment.id": {"value": mock.ANY, "type": "string"},
+                    "sentry.segment.name": {"value": "test", "type": "string"},
+                    "sentry.sdk.name": {"value": "sentry.python", "type": "string"},
+                    "sentry.sdk.version": {"value": mock.ANY, "type": "string"},
+                    "server.address": {"value": "test-server", "type": "string"},
+                    "sentry.environment": {"value": "production", "type": "string"},
+                    "sentry.release": {"value": "1.0.0", "type": "string"},
+                },
+            }
+        ]
+    }
diff --git a/tox.ini b/tox.ini
index 7be1a30eec..9c05085698 100644
--- a/tox.ini
+++ b/tox.ini
@@ -59,82 +59,97 @@ envlist =
     {py3.10,py3.12,py3.13}-mcp-v1.15.0
     {py3.10,py3.12,py3.13}-mcp-v1.19.0
     {py3.10,py3.12,py3.13}-mcp-v1.23.3
-    {py3.10,py3.12,py3.13}-mcp-v1.26.0
+    {py3.10,py3.12,py3.13}-mcp-v1.27.0
+    {py3.10,py3.12,py3.13}-mcp-latest
 
     {py3.10,py3.13,py3.14,py3.14t}-fastmcp-v0.1.0
     {py3.10,py3.13,py3.14,py3.14t}-fastmcp-v0.4.1
     {py3.10,py3.13,py3.14,py3.14t}-fastmcp-v1.0
-    {py3.10,py3.12,py3.13}-fastmcp-v2.14.5
-    {py3.10,py3.12,py3.13}-fastmcp-v3.0.2
+    {py3.10,py3.12,py3.13}-fastmcp-v2.14.7
+    {py3.10,py3.12,py3.13}-fastmcp-v3.2.4
+    {py3.10,py3.12,py3.13}-fastmcp-latest
 
 
     # ~~~ Agents ~~~
     {py3.10,py3.11,py3.12}-openai_agents-v0.0.19
-    {py3.10,py3.12,py3.13}-openai_agents-v0.3.3
-    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-v0.6.9
-    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-v0.10.1
+    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-v0.5.1
+    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-v0.10.5
+    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-v0.14.2
+    {py3.10,py3.13,py3.14,py3.14t}-openai_agents-latest
 
     {py3.10,py3.12,py3.13}-pydantic_ai-v1.0.18
-    {py3.10,py3.12,py3.13}-pydantic_ai-v1.21.0
-    {py3.10,py3.12,py3.13}-pydantic_ai-v1.42.0
-    {py3.10,py3.13,py3.14}-pydantic_ai-v1.63.0
+    {py3.10,py3.12,py3.13}-pydantic_ai-v1.28.0
+    {py3.10,py3.12,py3.13}-pydantic_ai-v1.57.0
+    {py3.10,py3.13,py3.14}-pydantic_ai-v1.84.1
+    {py3.10,py3.13,py3.14}-pydantic_ai-latest
 
 
     # ~~~ AI Workflow ~~~
     {py3.9,py3.11,py3.12}-langchain-base-v0.1.20
-    {py3.9,py3.12,py3.13}-langchain-base-v0.3.27
-    {py3.10,py3.13,py3.14}-langchain-base-v1.2.10
+    {py3.9,py3.12,py3.13}-langchain-base-v0.3.28
+    {py3.10,py3.13,py3.14}-langchain-base-v1.2.15
+    {py3.10,py3.13,py3.14}-langchain-base-latest
 
     {py3.9,py3.11,py3.12}-langchain-notiktoken-v0.1.20
-    {py3.9,py3.12,py3.13}-langchain-notiktoken-v0.3.27
-    {py3.10,py3.13,py3.14}-langchain-notiktoken-v1.2.10
+    {py3.9,py3.12,py3.13}-langchain-notiktoken-v0.3.28
+    {py3.10,py3.13,py3.14}-langchain-notiktoken-v1.2.15
+    {py3.10,py3.13,py3.14}-langchain-notiktoken-latest
 
     {py3.9,py3.13,py3.14}-langgraph-v0.6.11
-    {py3.10,py3.12,py3.13}-langgraph-v1.0.9
+    {py3.10,py3.12,py3.13}-langgraph-v1.1.8
+    {py3.10,py3.12,py3.13}-langgraph-latest
 
 
     # ~~~ AI ~~~
     {py3.8,py3.11,py3.12}-anthropic-v0.16.0
-    {py3.8,py3.11,py3.12}-anthropic-v0.38.0
-    {py3.8,py3.12,py3.13}-anthropic-v0.60.0
-    {py3.9,py3.13,py3.14,py3.14t}-anthropic-v0.83.0
+    {py3.8,py3.11,py3.12}-anthropic-v0.43.1
+    {py3.8,py3.12,py3.13}-anthropic-v0.70.0
+    {py3.9,py3.13,py3.14,py3.14t}-anthropic-v0.96.0
+    {py3.9,py3.13,py3.14,py3.14t}-anthropic-latest
 
     {py3.9,py3.10,py3.11}-cohere-v5.4.0
-    {py3.9,py3.11,py3.12}-cohere-v5.10.0
-    {py3.9,py3.11,py3.12}-cohere-v5.15.0
-    {py3.9,py3.13,py3.14}-cohere-v5.20.6
+    {py3.9,py3.13,py3.14}-cohere-v5.21.1
+    {py3.10,py3.13,py3.14}-cohere-v6.1.0
+    {py3.10,py3.13,py3.14}-cohere-latest
 
     {py3.9,py3.12,py3.13}-google_genai-v1.29.0
-    {py3.9,py3.12,py3.13}-google_genai-v1.41.0
-    {py3.10,py3.13,py3.14,py3.14t}-google_genai-v1.53.0
-    {py3.10,py3.13,py3.14,py3.14t}-google_genai-v1.64.0
+    {py3.9,py3.12,py3.13}-google_genai-v1.44.0
+    {py3.10,py3.13,py3.14,py3.14t}-google_genai-v1.59.0
+    {py3.10,py3.13,py3.14,py3.14t}-google_genai-v1.73.1
+    {py3.10,py3.13,py3.14,py3.14t}-google_genai-latest
 
     {py3.8,py3.10,py3.11}-huggingface_hub-v0.24.7
     {py3.8,py3.12,py3.13}-huggingface_hub-v0.36.2
-    {py3.9,py3.13,py3.14,py3.14t}-huggingface_hub-v1.4.1
+    {py3.10,py3.13,py3.14,py3.14t}-huggingface_hub-v1.11.0
+    {py3.10,py3.13,py3.14,py3.14t}-huggingface_hub-latest
 
     {py3.9,py3.12,py3.13}-litellm-v1.77.7
-    {py3.9,py3.12,py3.13}-litellm-v1.78.7
     {py3.9,py3.12,py3.13}-litellm-v1.79.3
-    {py3.9,py3.12,py3.13}-litellm-v1.81.15
+    {py3.9,py3.12,py3.13}-litellm-v1.81.16
+    {py3.10,py3.12,py3.13}-litellm-v1.83.10
+    {py3.10,py3.12,py3.13}-litellm-latest
 
     {py3.8,py3.11,py3.12}-openai-base-v1.0.1
     {py3.8,py3.12,py3.13}-openai-base-v1.109.1
-    {py3.9,py3.13,py3.14,py3.14t}-openai-base-v2.23.0
+    {py3.9,py3.13,py3.14,py3.14t}-openai-base-v2.32.0
+    {py3.9,py3.13,py3.14,py3.14t}-openai-base-latest
 
     {py3.8,py3.11,py3.12}-openai-notiktoken-v1.0.1
     {py3.8,py3.12,py3.13}-openai-notiktoken-v1.109.1
-    {py3.9,py3.13,py3.14,py3.14t}-openai-notiktoken-v2.23.0
+    {py3.9,py3.13,py3.14,py3.14t}-openai-notiktoken-v2.32.0
+    {py3.9,py3.13,py3.14,py3.14t}-openai-notiktoken-latest
 
 
     # ~~~ Cloud ~~~
     {py3.6,py3.7}-boto3-v1.12.49
     {py3.6,py3.9,py3.10}-boto3-v1.21.46
     {py3.7,py3.11,py3.12}-boto3-v1.33.13
-    {py3.9,py3.13,py3.14,py3.14t}-boto3-v1.42.55
+    {py3.9,py3.13,py3.14,py3.14t}-boto3-v1.42.91
+    {py3.9,py3.13,py3.14,py3.14t}-boto3-latest
 
     {py3.6,py3.7,py3.8}-chalice-v1.16.0
     {py3.9,py3.12,py3.13}-chalice-v1.32.0
+    {py3.9,py3.12,py3.13}-chalice-latest
 
 
     # ~~~ DBs ~~~
@@ -142,178 +157,224 @@ envlist =
     {py3.7,py3.9,py3.10}-asyncpg-v0.26.0
     {py3.8,py3.11,py3.12}-asyncpg-v0.29.0
     {py3.9,py3.13,py3.14,py3.14t}-asyncpg-v0.31.0
+    {py3.9,py3.13,py3.14,py3.14t}-asyncpg-latest
 
     {py3.9,py3.13,py3.14}-clickhouse_driver-v0.2.10
+    {py3.9,py3.13,py3.14}-clickhouse_driver-latest
 
     {py3.6}-pymongo-v3.5.1
     {py3.6,py3.10,py3.11}-pymongo-v3.13.0
     {py3.9,py3.13,py3.14,py3.14t}-pymongo-v4.16.0
+    {py3.9,py3.13,py3.14,py3.14t}-pymongo-latest
 
     {py3.6}-redis-v2.10.6
     {py3.6,py3.7,py3.8}-redis-v3.5.3
     {py3.7,py3.10,py3.11}-redis-v4.6.0
     {py3.8,py3.11,py3.12}-redis-v5.3.1
     {py3.9,py3.12,py3.13}-redis-v6.4.0
-    {py3.10,py3.13,py3.14,py3.14t}-redis-v7.2.0
+    {py3.10,py3.13,py3.14,py3.14t}-redis-v7.4.0
+    {py3.10,py3.13,py3.14,py3.14t}-redis-v8.0.0b2
+    {py3.10,py3.13,py3.14,py3.14t}-redis-latest
 
     {py3.6}-redis_py_cluster_legacy-v1.3.6
     {py3.6,py3.7,py3.8}-redis_py_cluster_legacy-v2.1.3
+    {py3.6,py3.7,py3.8}-redis_py_cluster_legacy-latest
 
     {py3.6,py3.8,py3.9}-sqlalchemy-v1.2.19
     {py3.6,py3.11,py3.12}-sqlalchemy-v1.4.54
-    {py3.7,py3.12,py3.13}-sqlalchemy-v2.0.46
-    {py3.10,py3.13,py3.14,py3.14t}-sqlalchemy-v2.1.0b1
+    {py3.7,py3.12,py3.13}-sqlalchemy-v2.0.49
+    {py3.10,py3.13,py3.14,py3.14t}-sqlalchemy-v2.1.0b2
+    {py3.7,py3.12,py3.13}-sqlalchemy-latest
 
 
     # ~~~ Flags ~~~
     {py3.8,py3.12,py3.13}-launchdarkly-v9.8.1
-    {py3.10,py3.13,py3.14,py3.14t}-launchdarkly-v9.15.0
+    {py3.10,py3.13,py3.14,py3.14t}-launchdarkly-v9.15.1
+    {py3.10,py3.13,py3.14,py3.14t}-launchdarkly-latest
 
     {py3.8,py3.13,py3.14,py3.14t}-openfeature-v0.7.5
     {py3.9,py3.13,py3.14,py3.14t}-openfeature-v0.8.4
+    {py3.9,py3.13,py3.14,py3.14t}-openfeature-latest
 
     {py3.7,py3.13,py3.14}-statsig-v0.55.3
-    {py3.7,py3.13,py3.14}-statsig-v0.70.2
+    {py3.7,py3.13,py3.14}-statsig-v0.71.6
+    {py3.7,py3.13,py3.14}-statsig-latest
 
     {py3.8,py3.12,py3.13}-unleash-v6.0.1
-    {py3.8,py3.12,py3.13}-unleash-v6.5.2
+    {py3.8,py3.12,py3.13}-unleash-v6.7.0
+    {py3.8,py3.12,py3.13}-unleash-latest
 
 
     # ~~~ GraphQL ~~~
     {py3.8,py3.10,py3.11}-ariadne-v0.20.1
-    {py3.10,py3.13,py3.14,py3.14t}-ariadne-v0.29.0
+    {py3.10,py3.13,py3.14,py3.14t}-ariadne-v1.0.1
+    {py3.10,py3.13,py3.14,py3.14t}-ariadne-v1.1.0a2
+    {py3.10,py3.13,py3.14,py3.14t}-ariadne-latest
 
     {py3.6,py3.9,py3.10}-gql-v3.4.1
     {py3.9,py3.12,py3.13}-gql-v4.0.0
-    {py3.9,py3.13,py3.14,py3.14t}-gql-v4.3.0b0
+    {py3.9,py3.13,py3.14,py3.14t}-gql-v4.3.0b2
+    {py3.9,py3.12,py3.13}-gql-latest
 
     {py3.6,py3.9,py3.10}-graphene-v3.3
     {py3.8,py3.12,py3.13}-graphene-v3.4.3
+    {py3.8,py3.12,py3.13}-graphene-latest
 
     {py3.8,py3.10,py3.11}-strawberry-v0.209.8
-    {py3.10,py3.13,py3.14,py3.14t}-strawberry-v0.306.0
+    {py3.10,py3.13,py3.14,py3.14t}-strawberry-v0.314.3
+    {py3.10,py3.13,py3.14,py3.14t}-strawberry-latest
 
 
     # ~~~ Network ~~~
     {py3.7,py3.8}-grpc-v1.32.0
-    {py3.7,py3.9,py3.10}-grpc-v1.47.5
-    {py3.7,py3.11,py3.12}-grpc-v1.62.3
-    {py3.9,py3.13,py3.14}-grpc-v1.78.1
+    {py3.7,py3.9,py3.10}-grpc-v1.48.2
+    {py3.8,py3.11,py3.12}-grpc-v1.64.3
+    {py3.9,py3.13,py3.14}-grpc-v1.80.0
+    {py3.9,py3.13,py3.14}-grpc-latest
 
     {py3.6,py3.8,py3.9}-httpx-v0.16.1
     {py3.6,py3.9,py3.10}-httpx-v0.20.0
     {py3.7,py3.10,py3.11}-httpx-v0.24.1
     {py3.9,py3.11,py3.12}-httpx-v0.28.1
+    {py3.9,py3.11,py3.12}-httpx-latest
+
+    {py3.11,py3.13,py3.14}-pyreqwest-v0.11.7
+    {py3.11,py3.13,py3.14}-pyreqwest-latest
 
     {py3.6}-requests-v2.12.5
-    {py3.9,py3.13,py3.14,py3.14t}-requests-v2.32.5
+    {py3.10,py3.13,py3.14,py3.14t}-requests-v2.33.1
+    {py3.10,py3.13,py3.14,py3.14t}-requests-latest
 
 
     # ~~~ Tasks ~~~
     {py3.7,py3.9,py3.10}-arq-v0.23
-    {py3.9,py3.12,py3.13}-arq-v0.27.0
+    {py3.9,py3.13,py3.14,py3.14t}-arq-v0.28.0
+    {py3.9,py3.13,py3.14,py3.14t}-arq-latest
 
     {py3.7}-beam-v2.14.0
-    {py3.10,py3.12,py3.13}-beam-v2.71.0
+    {py3.10,py3.12,py3.13}-beam-v2.72.0
+    {py3.10,py3.13,py3.14}-beam-v2.73.0rc1
+    {py3.10,py3.12,py3.13}-beam-latest
 
     {py3.6,py3.7,py3.8}-celery-v4.4.7
-    {py3.9,py3.12,py3.13}-celery-v5.6.2
+    {py3.9,py3.12,py3.13}-celery-v5.6.3
+    {py3.9,py3.12,py3.13}-celery-latest
 
     {py3.6,py3.7}-dramatiq-v1.9.0
-    {py3.10,py3.13,py3.14,py3.14t}-dramatiq-v2.0.1
+    {py3.10,py3.13,py3.14,py3.14t}-dramatiq-v2.1.0
+    {py3.10,py3.13,py3.14,py3.14t}-dramatiq-latest
 
     {py3.6,py3.7}-huey-v2.1.3
-    {py3.6,py3.13,py3.14,py3.14t}-huey-v2.6.0
+    {py3.6,py3.13,py3.14,py3.14t}-huey-v3.0.0
+    {py3.6,py3.13,py3.14,py3.14t}-huey-latest
 
     {py3.9,py3.10}-ray-v2.7.2
-    {py3.10,py3.12,py3.13}-ray-v2.54.0
+    {py3.10,py3.13,py3.14}-ray-v2.55.0
+    {py3.10,py3.13,py3.14}-ray-latest
 
     {py3.6}-rq-v0.6.0
     {py3.6,py3.7}-rq-v0.13.0
     {py3.7,py3.11,py3.12}-rq-v1.16.2
-    {py3.9,py3.13,py3.14,py3.14t}-rq-v2.7.0
+    {py3.9,py3.12,py3.13}-rq-v2.8.0
+    {py3.9,py3.12,py3.13}-rq-latest
 
     {py3.8,py3.9}-spark-v3.0.3
     {py3.8,py3.10,py3.11}-spark-v3.5.8
     {py3.10,py3.13,py3.14}-spark-v4.1.1
+    {py3.10,py3.13,py3.14}-spark-latest
 
 
     # ~~~ Web 1 ~~~
     {py3.6,py3.7}-django-v1.11.29
     {py3.6,py3.8,py3.9}-django-v2.2.28
     {py3.6,py3.9,py3.10}-django-v3.2.25
-    {py3.8,py3.11,py3.12}-django-v4.2.28
-    {py3.10,py3.13,py3.14,py3.14t}-django-v5.2.11
-    {py3.12,py3.13,py3.14,py3.14t}-django-v6.0.2
+    {py3.8,py3.11,py3.12}-django-v4.2.30
+    {py3.10,py3.13,py3.14,py3.14t}-django-v5.2.13
+    {py3.12,py3.13,py3.14,py3.14t}-django-v6.0.4
+    {py3.12,py3.13,py3.14,py3.14t}-django-latest
 
     {py3.6,py3.7,py3.8}-flask-v1.1.4
     {py3.8,py3.13,py3.14,py3.14t}-flask-v2.3.3
     {py3.9,py3.13,py3.14,py3.14t}-flask-v3.1.3
+    {py3.9,py3.13,py3.14,py3.14t}-flask-latest
 
     {py3.6,py3.9,py3.10}-starlette-v0.16.0
-    {py3.7,py3.10,py3.11}-starlette-v0.28.0
-    {py3.8,py3.12,py3.13}-starlette-v0.40.0
     {py3.10,py3.13,py3.14,py3.14t}-starlette-v0.52.1
-    {py3.10,py3.13,py3.14,py3.14t}-starlette-v1.0.0rc1
+    {py3.10,py3.13,py3.14,py3.14t}-starlette-v1.0.0
+    {py3.10,py3.13,py3.14,py3.14t}-starlette-latest
 
     {py3.6,py3.9,py3.10}-fastapi-v0.79.1
-    {py3.7,py3.10,py3.11}-fastapi-v0.97.0
-    {py3.8,py3.12,py3.13}-fastapi-v0.115.14
-    {py3.10,py3.13,py3.14,py3.14t}-fastapi-v0.133.0
+    {py3.7,py3.10,py3.11}-fastapi-v0.98.0
+    {py3.8,py3.12,py3.13}-fastapi-v0.117.1
+    {py3.10,py3.13,py3.14,py3.14t}-fastapi-v0.136.0
+    {py3.10,py3.13,py3.14,py3.14t}-fastapi-latest
 
 
     # ~~~ Web 2 ~~~
     {py3.7}-aiohttp-v3.4.4
     {py3.7,py3.8,py3.9}-aiohttp-v3.7.4
     {py3.8,py3.12,py3.13}-aiohttp-v3.10.11
-    {py3.9,py3.13,py3.14,py3.14t}-aiohttp-v3.13.3
+    {py3.9,py3.13,py3.14,py3.14t}-aiohttp-v3.13.5
+    {py3.9,py3.13,py3.14,py3.14t}-aiohttp-latest
 
     {py3.6,py3.7}-bottle-v0.12.25
     {py3.8,py3.12,py3.13}-bottle-v0.13.4
+    {py3.8,py3.12,py3.13}-bottle-latest
 
     {py3.6}-falcon-v1.4.1
     {py3.6,py3.7}-falcon-v2.0.0
     {py3.6,py3.11,py3.12}-falcon-v3.1.3
     {py3.9,py3.11,py3.12}-falcon-v4.2.0
+    {py3.9,py3.11,py3.12}-falcon-latest
 
     {py3.8,py3.10,py3.11}-litestar-v2.0.1
     {py3.8,py3.11,py3.12}-litestar-v2.7.2
     {py3.8,py3.12,py3.13}-litestar-v2.14.0
-    {py3.8,py3.12,py3.13}-litestar-v2.21.0
+    {py3.8,py3.12,py3.13}-litestar-v2.21.1
+    {py3.8,py3.12,py3.13}-litestar-latest
 
     {py3.6}-pyramid-v1.8.6
     {py3.6,py3.8,py3.9}-pyramid-v1.10.8
-    {py3.6,py3.10,py3.11}-pyramid-v2.0.2
+    {py3.10,py3.13,py3.14}-pyramid-v2.1
+    {py3.10,py3.13,py3.14}-pyramid-latest
 
     {py3.7,py3.9,py3.10}-quart-v0.16.3
     {py3.9,py3.13,py3.14,py3.14t}-quart-v0.20.0
+    {py3.9,py3.13,py3.14,py3.14t}-quart-latest
 
     {py3.6}-sanic-v0.8.3
     {py3.6,py3.8,py3.9}-sanic-v20.12.7
     {py3.8,py3.10,py3.11}-sanic-v23.12.2
     {py3.10,py3.13,py3.14}-sanic-v25.12.0
+    {py3.10,py3.13,py3.14}-sanic-latest
 
     {py3.8,py3.10,py3.11}-starlite-v1.48.1
     {py3.8,py3.10,py3.11}-starlite-v1.51.16
+    {py3.8,py3.10,py3.11}-starlite-latest
 
     {py3.6,py3.7,py3.8}-tornado-v6.0.4
-    {py3.9,py3.12,py3.13}-tornado-v6.5.4
+    {py3.9,py3.12,py3.13}-tornado-v6.5.5
+    {py3.9,py3.12,py3.13}-tornado-latest
 
 
     # ~~~ Misc ~~~
     {py3.6,py3.12,py3.13}-loguru-v0.7.3
+    {py3.6,py3.12,py3.13}-loguru-latest
 
     {py3.6,py3.7,py3.8}-pure_eval-v0.0.3
     {py3.7,py3.12,py3.13}-pure_eval-v0.2.3
+    {py3.7,py3.12,py3.13}-pure_eval-latest
 
     {py3.6}-trytond-v4.6.22
     {py3.6}-trytond-v4.8.18
     {py3.6,py3.7,py3.8}-trytond-v5.8.16
     {py3.8,py3.10,py3.11}-trytond-v6.8.17
-    {py3.9,py3.12,py3.13}-trytond-v7.8.4
+    {py3.9,py3.12,py3.13}-trytond-v7.8.7
+    {py3.9,py3.12,py3.13}-trytond-latest
 
     {py3.7,py3.12,py3.13}-typer-v0.15.4
     {py3.10,py3.13,py3.14,py3.14t}-typer-v0.24.1
+    {py3.10,py3.13,py3.14,py3.14t}-typer-latest
 
 
 
@@ -326,14 +387,17 @@ deps =
 
     linters: -r requirements-linting.txt
     linters: werkzeug<2.3.0
+    linters: httpcore[asyncio]
 
     mypy: -r requirements-linting.txt
     mypy: werkzeug<2.3.0
+    mypy: httpcore[asyncio]
     ruff: -r requirements-linting.txt
 
     # === Common ===
     py3.8-common: hypothesis
     common: pytest-asyncio
+    common: httpcore[asyncio]
     # See https://github.com/pytest-dev/pytest/issues/9621
     # and https://github.com/pytest-dev/pytest-forked/issues/67
     # for justification of the upper bound on pytest
@@ -388,98 +452,119 @@ deps =
     mcp-v1.15.0: mcp==1.15.0
     mcp-v1.19.0: mcp==1.19.0
     mcp-v1.23.3: mcp==1.23.3
-    mcp-v1.26.0: mcp==1.26.0
+    mcp-v1.27.0: mcp==1.27.0
+    mcp-latest: mcp==1.27.0
     mcp: pytest-asyncio
 
     fastmcp-v0.1.0: fastmcp==0.1.0
     fastmcp-v0.4.1: fastmcp==0.4.1
     fastmcp-v1.0: fastmcp==1.0
-    fastmcp-v2.14.5: fastmcp==2.14.5
-    fastmcp-v3.0.2: fastmcp==3.0.2
+    fastmcp-v2.14.7: fastmcp==2.14.7
+    fastmcp-v3.2.4: fastmcp==3.2.4
+    fastmcp-latest: fastmcp==3.2.4
     fastmcp: pytest-asyncio
 
 
     # ~~~ Agents ~~~
     openai_agents-v0.0.19: openai-agents==0.0.19
-    openai_agents-v0.3.3: openai-agents==0.3.3
-    openai_agents-v0.6.9: openai-agents==0.6.9
-    openai_agents-v0.10.1: openai-agents==0.10.1
+    openai_agents-v0.5.1: openai-agents==0.5.1
+    openai_agents-v0.10.5: openai-agents==0.10.5
+    openai_agents-v0.14.2: openai-agents==0.14.2
+    openai_agents-latest: openai-agents==0.14.2
     openai_agents: pytest-asyncio
 
     pydantic_ai-v1.0.18: pydantic-ai==1.0.18
-    pydantic_ai-v1.21.0: pydantic-ai==1.21.0
-    pydantic_ai-v1.42.0: pydantic-ai==1.42.0
-    pydantic_ai-v1.63.0: pydantic-ai==1.63.0
+    pydantic_ai-v1.28.0: pydantic-ai==1.28.0
+    pydantic_ai-v1.57.0: pydantic-ai==1.57.0
+    pydantic_ai-v1.84.1: pydantic-ai==1.84.1
+    pydantic_ai-latest: pydantic-ai==1.84.1
     pydantic_ai: pytest-asyncio
 
 
     # ~~~ AI Workflow ~~~
     langchain-base-v0.1.20: langchain==0.1.20
-    langchain-base-v0.3.27: langchain==0.3.27
-    langchain-base-v1.2.10: langchain==1.2.10
+    langchain-base-v0.3.28: langchain==0.3.28
+    langchain-base-v1.2.15: langchain==1.2.15
+    langchain-base-latest: langchain==1.2.15
     langchain-base: pytest-asyncio
     langchain-base: openai
     langchain-base: tiktoken
     langchain-base: langchain-openai
-    langchain-base-v0.3.27: langchain-community
-    langchain-base-v1.2.10: langchain-community
-    langchain-base-v1.2.10: langchain-classic
+    langchain-base-v0.3.28: langchain-community
+    langchain-base-v1.2.15: langchain-community
+    langchain-base-v1.2.15: langchain-classic
+    langchain-base-latest: langchain-community
+    langchain-base-latest: langchain-classic
 
     langchain-notiktoken-v0.1.20: langchain==0.1.20
-    langchain-notiktoken-v0.3.27: langchain==0.3.27
-    langchain-notiktoken-v1.2.10: langchain==1.2.10
+    langchain-notiktoken-v0.3.28: langchain==0.3.28
+    langchain-notiktoken-v1.2.15: langchain==1.2.15
+    langchain-notiktoken-latest: langchain==1.2.15
     langchain-notiktoken: pytest-asyncio
     langchain-notiktoken: openai
     langchain-notiktoken: langchain-openai
-    langchain-notiktoken-v0.3.27: langchain-community
-    langchain-notiktoken-v1.2.10: langchain-community
-    langchain-notiktoken-v1.2.10: langchain-classic
+    langchain-notiktoken-v0.3.28: langchain-community
+    langchain-notiktoken-v1.2.15: langchain-community
+    langchain-notiktoken-v1.2.15: langchain-classic
+    langchain-notiktoken-latest: langchain-community
+    langchain-notiktoken-latest: langchain-classic
 
     langgraph-v0.6.11: langgraph==0.6.11
-    langgraph-v1.0.9: langgraph==1.0.9
+    langgraph-v1.1.8: langgraph==1.1.8
+    langgraph-latest: langgraph==1.1.8
 
 
     # ~~~ AI ~~~
     anthropic-v0.16.0: anthropic==0.16.0
-    anthropic-v0.38.0: anthropic==0.38.0
-    anthropic-v0.60.0: anthropic==0.60.0
-    anthropic-v0.83.0: anthropic==0.83.0
+    anthropic-v0.43.1: anthropic==0.43.1
+    anthropic-v0.70.0: anthropic==0.70.0
+    anthropic-v0.96.0: anthropic==0.96.0
+    anthropic-latest: anthropic==0.96.0
     anthropic: pytest-asyncio
     anthropic-v0.16.0: httpx<0.28.0
-    anthropic-v0.38.0: httpx<0.28.0
+    anthropic-v0.43.1: httpx<0.28.0
+    {py3.8}-anthropic: tokenizers<0.20.4
 
     cohere-v5.4.0: cohere==5.4.0
-    cohere-v5.10.0: cohere==5.10.0
-    cohere-v5.15.0: cohere==5.15.0
-    cohere-v5.20.6: cohere==5.20.6
+    cohere-v5.21.1: cohere==5.21.1
+    cohere-v6.1.0: cohere==6.1.0
+    cohere-latest: cohere==6.1.0
 
     google_genai-v1.29.0: google-genai==1.29.0
-    google_genai-v1.41.0: google-genai==1.41.0
-    google_genai-v1.53.0: google-genai==1.53.0
-    google_genai-v1.64.0: google-genai==1.64.0
+    google_genai-v1.44.0: google-genai==1.44.0
+    google_genai-v1.59.0: google-genai==1.59.0
+    google_genai-v1.73.1: google-genai==1.73.1
+    google_genai-latest: google-genai==1.73.1
     google_genai: pytest-asyncio
 
     huggingface_hub-v0.24.7: huggingface_hub==0.24.7
     huggingface_hub-v0.36.2: huggingface_hub==0.36.2
-    huggingface_hub-v1.4.1: huggingface_hub==1.4.1
+    huggingface_hub-v1.11.0: huggingface_hub==1.11.0
+    huggingface_hub-latest: huggingface_hub==1.11.0
     huggingface_hub: responses
     huggingface_hub: pytest-httpx
 
     litellm-v1.77.7: litellm==1.77.7
-    litellm-v1.78.7: litellm==1.78.7
     litellm-v1.79.3: litellm==1.79.3
-    litellm-v1.81.15: litellm==1.81.15
+    litellm-v1.81.16: litellm==1.81.16
+    litellm-v1.83.10: litellm==1.83.10
+    litellm-latest: litellm==1.83.10
+    litellm: anthropic
+    litellm: google-genai
+    litellm: pytest-asyncio
 
     openai-base-v1.0.1: openai==1.0.1
     openai-base-v1.109.1: openai==1.109.1
-    openai-base-v2.23.0: openai==2.23.0
+    openai-base-v2.32.0: openai==2.32.0
+    openai-base-latest: openai==2.32.0
     openai-base: pytest-asyncio
     openai-base: tiktoken
     openai-base-v1.0.1: httpx<0.28
 
     openai-notiktoken-v1.0.1: openai==1.0.1
     openai-notiktoken-v1.109.1: openai==1.109.1
-    openai-notiktoken-v2.23.0: openai==2.23.0
+    openai-notiktoken-v2.32.0: openai==2.32.0
+    openai-notiktoken-latest: openai==2.32.0
     openai-notiktoken: pytest-asyncio
     openai-notiktoken-v1.0.1: httpx<0.28
 
@@ -488,11 +573,13 @@ deps =
     boto3-v1.12.49: boto3==1.12.49
     boto3-v1.21.46: boto3==1.21.46
     boto3-v1.33.13: boto3==1.33.13
-    boto3-v1.42.55: boto3==1.42.55
+    boto3-v1.42.91: boto3==1.42.91
+    boto3-latest: boto3==1.42.91
     {py3.7,py3.8}-boto3: urllib3<2.0.0
 
     chalice-v1.16.0: chalice==1.16.0
     chalice-v1.32.0: chalice==1.32.0
+    chalice-latest: chalice==1.32.0
     chalice: pytest-chalice
     chalice: setuptools<82
 
@@ -502,13 +589,16 @@ deps =
     asyncpg-v0.26.0: asyncpg==0.26.0
     asyncpg-v0.29.0: asyncpg==0.29.0
     asyncpg-v0.31.0: asyncpg==0.31.0
+    asyncpg-latest: asyncpg==0.31.0
     asyncpg: pytest-asyncio
 
     clickhouse_driver-v0.2.10: clickhouse-driver==0.2.10
+    clickhouse_driver-latest: clickhouse-driver==0.2.10
 
     pymongo-v3.5.1: pymongo==3.5.1
     pymongo-v3.13.0: pymongo==3.13.0
     pymongo-v4.16.0: pymongo==4.16.0
+    pymongo-latest: pymongo==4.16.0
     pymongo: mockupdb
 
     redis-v2.10.6: redis==2.10.6
@@ -516,7 +606,9 @@ deps =
     redis-v4.6.0: redis==4.6.0
     redis-v5.3.1: redis==5.3.1
     redis-v6.4.0: redis==6.4.0
-    redis-v7.2.0: redis==7.2.0
+    redis-v7.4.0: redis==7.4.0
+    redis-v8.0.0b2: redis==8.0.0b2
+    redis-latest: redis==7.4.0
     redis: fakeredis!=1.7.4
     redis: pytest<8.0.0
     redis-v4.6.0: fakeredis<2.31.0
@@ -525,41 +617,51 @@ deps =
 
     redis_py_cluster_legacy-v1.3.6: redis-py-cluster==1.3.6
     redis_py_cluster_legacy-v2.1.3: redis-py-cluster==2.1.3
+    redis_py_cluster_legacy-latest: redis-py-cluster==2.1.3
 
     sqlalchemy-v1.2.19: sqlalchemy==1.2.19
     sqlalchemy-v1.4.54: sqlalchemy==1.4.54
-    sqlalchemy-v2.0.46: sqlalchemy==2.0.46
-    sqlalchemy-v2.1.0b1: sqlalchemy==2.1.0b1
+    sqlalchemy-v2.0.49: sqlalchemy==2.0.49
+    sqlalchemy-v2.1.0b2: sqlalchemy==2.1.0b2
+    sqlalchemy-latest: sqlalchemy==2.0.49
 
 
     # ~~~ Flags ~~~
     launchdarkly-v9.8.1: launchdarkly-server-sdk==9.8.1
-    launchdarkly-v9.15.0: launchdarkly-server-sdk==9.15.0
+    launchdarkly-v9.15.1: launchdarkly-server-sdk==9.15.1
+    launchdarkly-latest: launchdarkly-server-sdk==9.15.1
 
     openfeature-v0.7.5: openfeature-sdk==0.7.5
     openfeature-v0.8.4: openfeature-sdk==0.8.4
+    openfeature-latest: openfeature-sdk==0.8.4
 
     statsig-v0.55.3: statsig==0.55.3
-    statsig-v0.70.2: statsig==0.70.2
+    statsig-v0.71.6: statsig==0.71.6
+    statsig-latest: statsig==0.71.6
     statsig: typing_extensions
 
     unleash-v6.0.1: UnleashClient==6.0.1
-    unleash-v6.5.2: UnleashClient==6.5.2
+    unleash-v6.7.0: UnleashClient==6.7.0
+    unleash-latest: UnleashClient==6.7.0
 
 
     # ~~~ GraphQL ~~~
     ariadne-v0.20.1: ariadne==0.20.1
-    ariadne-v0.29.0: ariadne==0.29.0
+    ariadne-v1.0.1: ariadne==1.0.1
+    ariadne-v1.1.0a2: ariadne==1.1.0a2
+    ariadne-latest: ariadne==1.0.1
     ariadne: fastapi
     ariadne: flask
     ariadne: httpx
 
     gql-v3.4.1: gql[all]==3.4.1
     gql-v4.0.0: gql[all]==4.0.0
-    gql-v4.3.0b0: gql[all]==4.3.0b0
+    gql-v4.3.0b2: gql[all]==4.3.0b2
+    gql-latest: gql[all]==4.0.0
 
     graphene-v3.3: graphene==3.3
     graphene-v3.4.3: graphene==3.4.3
+    graphene-latest: graphene==3.4.3
     graphene: blinker
     graphene: fastapi
     graphene: flask
@@ -567,16 +669,18 @@ deps =
     {py3.6}-graphene: aiocontextvars
 
     strawberry-v0.209.8: strawberry-graphql[fastapi,flask]==0.209.8
-    strawberry-v0.306.0: strawberry-graphql[fastapi,flask]==0.306.0
+    strawberry-v0.314.3: strawberry-graphql[fastapi,flask]==0.314.3
+    strawberry-latest: strawberry-graphql[fastapi,flask]==0.314.3
     strawberry: httpx
     strawberry-v0.209.8: pydantic<2.11
 
 
     # ~~~ Network ~~~
     grpc-v1.32.0: grpcio==1.32.0
-    grpc-v1.47.5: grpcio==1.47.5
-    grpc-v1.62.3: grpcio==1.62.3
-    grpc-v1.78.1: grpcio==1.78.1
+    grpc-v1.48.2: grpcio==1.48.2
+    grpc-v1.64.3: grpcio==1.64.3
+    grpc-v1.80.0: grpcio==1.80.0
+    grpc-latest: grpcio==1.80.0
     grpc: protobuf
     grpc: mypy-protobuf
     grpc: types-protobuf
@@ -586,47 +690,64 @@ deps =
     httpx-v0.20.0: httpx==0.20.0
     httpx-v0.24.1: httpx==0.24.1
     httpx-v0.28.1: httpx==0.28.1
-    httpx: anyio<4.0.0
+    httpx-latest: httpx==0.28.1
+    httpx: anyio>=3,<5
+    httpx-v0.16.1: anyio<4
+    httpx-v0.20.0: anyio<4
     httpx-v0.16.1: pytest-httpx==0.10.0
     httpx-v0.20.0: pytest-httpx==0.14.0
     httpx-v0.24.1: pytest-httpx==0.22.0
     httpx-v0.28.1: pytest-httpx==0.35.0
+    httpx-latest: pytest-httpx==0.35.0
+
+    pyreqwest-v0.11.7: pyreqwest==0.11.7
+    pyreqwest-latest: pyreqwest==0.11.7
+    pyreqwest: pytest-asyncio
 
     requests-v2.12.5: requests==2.12.5
-    requests-v2.32.5: requests==2.32.5
+    requests-v2.33.1: requests==2.33.1
+    requests-latest: requests==2.33.1
 
 
     # ~~~ Tasks ~~~
     arq-v0.23: arq==0.23
-    arq-v0.27.0: arq==0.27.0
+    arq-v0.28.0: arq==0.28.0
+    arq-latest: arq==0.28.0
     arq: async-timeout
     arq: pytest-asyncio
     arq: fakeredis>=2.2.0,<2.8
     arq-v0.23: pydantic<2
 
     beam-v2.14.0: apache-beam==2.14.0
-    beam-v2.71.0: apache-beam==2.71.0
+    beam-v2.72.0: apache-beam==2.72.0
+    beam-v2.73.0rc1: apache-beam==2.73.0rc1
+    beam-latest: apache-beam==2.72.0
     beam: dill
 
     celery-v4.4.7: celery==4.4.7
-    celery-v5.6.2: celery==5.6.2
+    celery-v5.6.3: celery==5.6.3
+    celery-latest: celery==5.6.3
     celery: newrelic<10.17.0
     celery: redis
     {py3.7}-celery: importlib-metadata<5.0
 
     dramatiq-v1.9.0: dramatiq==1.9.0
-    dramatiq-v2.0.1: dramatiq==2.0.1
+    dramatiq-v2.1.0: dramatiq==2.1.0
+    dramatiq-latest: dramatiq==2.1.0
 
     huey-v2.1.3: huey==2.1.3
-    huey-v2.6.0: huey==2.6.0
+    huey-v3.0.0: huey==3.0.0
+    huey-latest: huey==3.0.0
 
     ray-v2.7.2: ray==2.7.2
-    ray-v2.54.0: ray==2.54.0
+    ray-v2.55.0: ray==2.55.0
+    ray-latest: ray==2.55.0
 
     rq-v0.6.0: rq==0.6.0
     rq-v0.13.0: rq==0.13.0
     rq-v1.16.2: rq==1.16.2
-    rq-v2.7.0: rq==2.7.0
+    rq-v2.8.0: rq==2.8.0
+    rq-latest: rq==2.8.0
     rq: fakeredis<2.28.0
     rq-v0.6.0: fakeredis<1.0
     rq-v0.6.0: redis<3.2.2
@@ -636,29 +757,31 @@ deps =
     spark-v3.0.3: pyspark==3.0.3
     spark-v3.5.8: pyspark==3.5.8
     spark-v4.1.1: pyspark==4.1.1
+    spark-latest: pyspark==4.1.1
 
 
     # ~~~ Web 1 ~~~
     django-v1.11.29: django==1.11.29
     django-v2.2.28: django==2.2.28
     django-v3.2.25: django==3.2.25
-    django-v4.2.28: django==4.2.28
-    django-v5.2.11: django==5.2.11
-    django-v6.0.2: django==6.0.2
+    django-v4.2.30: django==4.2.30
+    django-v5.2.13: django==5.2.13
+    django-v6.0.4: django==6.0.4
+    django-latest: django==6.0.4
     django: psycopg2-binary
     django: djangorestframework
     django: pytest-django
     django: Werkzeug
     django-v2.2.28: channels[daphne]
     django-v3.2.25: channels[daphne]
-    django-v4.2.28: channels[daphne]
-    django-v5.2.11: channels[daphne]
-    django-v6.0.2: channels[daphne]
+    django-v4.2.30: channels[daphne]
+    django-v5.2.13: channels[daphne]
+    django-v6.0.4: channels[daphne]
     django-v2.2.28: six
     django-v3.2.25: pytest-asyncio
-    django-v4.2.28: pytest-asyncio
-    django-v5.2.11: pytest-asyncio
-    django-v6.0.2: pytest-asyncio
+    django-v4.2.30: pytest-asyncio
+    django-v5.2.13: pytest-asyncio
+    django-v6.0.4: pytest-asyncio
     django-v1.11.29: djangorestframework>=3.0,<4.0
     django-v1.11.29: Werkzeug<2.1.0
     django-v2.2.28: djangorestframework>=3.0,<4.0
@@ -668,20 +791,22 @@ deps =
     django-v1.11.29: pytest-django<4.0
     django-v2.2.28: pytest-django<4.0
     {py3.14,py3.14t}-django: coverage==7.11.0
+    django-latest: channels[daphne]
+    django-latest: pytest-asyncio
 
     flask-v1.1.4: flask==1.1.4
     flask-v2.3.3: flask==2.3.3
     flask-v3.1.3: flask==3.1.3
+    flask-latest: flask==3.1.3
     flask: flask-login
     flask: werkzeug
     flask-v1.1.4: werkzeug<2.1.0
     flask-v1.1.4: markupsafe<2.1.0
 
     starlette-v0.16.0: starlette==0.16.0
-    starlette-v0.28.0: starlette==0.28.0
-    starlette-v0.40.0: starlette==0.40.0
     starlette-v0.52.1: starlette==0.52.1
-    starlette-v1.0.0rc1: starlette==1.0.0rc1
+    starlette-v1.0.0: starlette==1.0.0
+    starlette-latest: starlette==1.0.0
     starlette: pytest-asyncio
     starlette: python-multipart
     starlette: requests
@@ -689,20 +814,22 @@ deps =
     starlette: jinja2
     starlette: httpx
     starlette-v0.16.0: httpx<0.28.0
-    starlette-v0.28.0: httpx<0.28.0
     {py3.6}-starlette: aiocontextvars
 
     fastapi-v0.79.1: fastapi==0.79.1
-    fastapi-v0.97.0: fastapi==0.97.0
-    fastapi-v0.115.14: fastapi==0.115.14
-    fastapi-v0.133.0: fastapi==0.133.0
+    fastapi-v0.98.0: fastapi==0.98.0
+    fastapi-v0.117.1: fastapi==0.117.1
+    fastapi-v0.136.0: fastapi==0.136.0
+    fastapi-latest: fastapi==0.136.0
     fastapi: httpx
     fastapi: pytest-asyncio
     fastapi: python-multipart
     fastapi: requests
-    fastapi: anyio<4
+    fastapi: anyio>=3,<5
+    fastapi: jinja2
     fastapi-v0.79.1: httpx<0.28.0
-    fastapi-v0.97.0: httpx<0.28.0
+    fastapi-v0.98.0: httpx<0.28.0
+    fastapi-v0.79.1: anyio<4
     {py3.6}-fastapi: aiocontextvars
 
 
@@ -710,24 +837,29 @@ deps =
     aiohttp-v3.4.4: aiohttp==3.4.4
     aiohttp-v3.7.4: aiohttp==3.7.4
     aiohttp-v3.10.11: aiohttp==3.10.11
-    aiohttp-v3.13.3: aiohttp==3.13.3
+    aiohttp-v3.13.5: aiohttp==3.13.5
+    aiohttp-latest: aiohttp==3.13.5
     aiohttp: pytest-aiohttp
     aiohttp-v3.10.11: pytest-asyncio
-    aiohttp-v3.13.3: pytest-asyncio
+    aiohttp-v3.13.5: pytest-asyncio
+    aiohttp-latest: pytest-asyncio
 
     bottle-v0.12.25: bottle==0.12.25
     bottle-v0.13.4: bottle==0.13.4
+    bottle-latest: bottle==0.13.4
     bottle: werkzeug<2.1.0
 
     falcon-v1.4.1: falcon==1.4.1
     falcon-v2.0.0: falcon==2.0.0
     falcon-v3.1.3: falcon==3.1.3
     falcon-v4.2.0: falcon==4.2.0
+    falcon-latest: falcon==4.2.0
 
     litestar-v2.0.1: litestar==2.0.1
     litestar-v2.7.2: litestar==2.7.2
     litestar-v2.14.0: litestar==2.14.0
-    litestar-v2.21.0: litestar==2.21.0
+    litestar-v2.21.1: litestar==2.21.1
+    litestar-latest: litestar==2.21.1
     litestar: pytest-asyncio
     litestar: python-multipart
     litestar: requests
@@ -737,11 +869,13 @@ deps =
 
     pyramid-v1.8.6: pyramid==1.8.6
     pyramid-v1.10.8: pyramid==1.10.8
-    pyramid-v2.0.2: pyramid==2.0.2
+    pyramid-v2.1: pyramid==2.1
+    pyramid-latest: pyramid==2.1
     pyramid: werkzeug<2.1.0
 
     quart-v0.16.3: quart==0.16.3
     quart-v0.20.0: quart==0.20.0
+    quart-latest: quart==0.20.0
     quart: quart-auth
     quart: pytest-asyncio
     quart: Werkzeug
@@ -751,20 +885,24 @@ deps =
     quart-v0.16.3: Werkzeug<2.3.0
     quart-v0.16.3: hypercorn<0.15.0
     {py3.8}-quart: taskgroup==0.0.0a4
+    quart-latest: quart-flask-patch
 
     sanic-v0.8.3: sanic==0.8.3
     sanic-v20.12.7: sanic==20.12.7
     sanic-v23.12.2: sanic==23.12.2
     sanic-v25.12.0: sanic==25.12.0
+    sanic-latest: sanic==25.12.0
     sanic: websockets<11.0
     sanic: aiohttp
     sanic-v23.12.2: sanic-testing
     sanic-v25.12.0: sanic-testing
     {py3.6}-sanic: aiocontextvars==0.2.1
     {py3.8}-sanic: tracerite<1.1.2
+    sanic-latest: sanic-testing
 
     starlite-v1.48.1: starlite==1.48.1
     starlite-v1.51.16: starlite==1.51.16
+    starlite-latest: starlite==1.51.16
     starlite: pytest-asyncio
     starlite: python-multipart
     starlite: requests
@@ -773,7 +911,8 @@ deps =
     starlite: httpx<0.28
 
     tornado-v6.0.4: tornado==6.0.4
-    tornado-v6.5.4: tornado==6.5.4
+    tornado-v6.5.5: tornado==6.5.5
+    tornado-latest: tornado==6.5.5
     tornado: pytest
     tornado-v6.0.4: pytest<8.2
     {py3.6}-tornado: aiocontextvars
@@ -781,21 +920,25 @@ deps =
 
     # ~~~ Misc ~~~
     loguru-v0.7.3: loguru==0.7.3
+    loguru-latest: loguru==0.7.3
 
     pure_eval-v0.0.3: pure_eval==0.0.3
     pure_eval-v0.2.3: pure_eval==0.2.3
+    pure_eval-latest: pure_eval==0.2.3
 
     trytond-v4.6.22: trytond==4.6.22
     trytond-v4.8.18: trytond==4.8.18
     trytond-v5.8.16: trytond==5.8.16
     trytond-v6.8.17: trytond==6.8.17
-    trytond-v7.8.4: trytond==7.8.4
+    trytond-v7.8.7: trytond==7.8.7
+    trytond-latest: trytond==7.8.7
     trytond: werkzeug
     trytond-v4.6.22: werkzeug<1.0
     trytond-v4.8.18: werkzeug<1.0
 
     typer-v0.15.4: typer==0.15.4
     typer-v0.24.1: typer==0.24.1
+    typer-latest: typer==0.24.1
 
 
 
@@ -816,84 +959,86 @@ setenv =
     gevent: PYTEST_ADDOPTS="--ignore=tests/test_shadowed_module.py"
 
     # TESTPATH definitions for test suites not managed by toxgen
-    common: TESTPATH=tests
-    gevent: TESTPATH=tests
-    integration_deactivation: TESTPATH=tests/test_ai_integration_deactivation.py
-    shadowed_module: TESTPATH=tests/test_shadowed_module.py
-    asgi: TESTPATH=tests/integrations/asgi
-    aws_lambda: TESTPATH=tests/integrations/aws_lambda
-    cloud_resource_context: TESTPATH=tests/integrations/cloud_resource_context
-    gcp: TESTPATH=tests/integrations/gcp
-    opentelemetry: TESTPATH=tests/integrations/opentelemetry
-    otlp: TESTPATH=tests/integrations/otlp
-    potel: TESTPATH=tests/integrations/opentelemetry
-    socket: TESTPATH=tests/integrations/socket
+    common: _TESTPATH=tests
+    gevent: _TESTPATH=tests
+    integration_deactivation: _TESTPATH=tests/test_ai_integration_deactivation.py
+    shadowed_module: _TESTPATH=tests/test_shadowed_module.py
+    asgi: _TESTPATH=tests/integrations/asgi
+    aws_lambda: _TESTPATH=tests/integrations/aws_lambda
+    cloud_resource_context: _TESTPATH=tests/integrations/cloud_resource_context
+    gcp: _TESTPATH=tests/integrations/gcp
+    opentelemetry: _TESTPATH=tests/integrations/opentelemetry
+    otlp: _TESTPATH=tests/integrations/otlp
+    potel: _TESTPATH=tests/integrations/opentelemetry
+    socket: _TESTPATH=tests/integrations/socket
 
     # These TESTPATH definitions are auto-generated by toxgen
-    aiohttp: TESTPATH=tests/integrations/aiohttp
-    anthropic: TESTPATH=tests/integrations/anthropic
-    ariadne: TESTPATH=tests/integrations/ariadne
-    arq: TESTPATH=tests/integrations/arq
-    asyncpg: TESTPATH=tests/integrations/asyncpg
-    beam: TESTPATH=tests/integrations/beam
-    boto3: TESTPATH=tests/integrations/boto3
-    bottle: TESTPATH=tests/integrations/bottle
-    celery: TESTPATH=tests/integrations/celery
-    chalice: TESTPATH=tests/integrations/chalice
-    clickhouse_driver: TESTPATH=tests/integrations/clickhouse_driver
-    cohere: TESTPATH=tests/integrations/cohere
-    django: TESTPATH=tests/integrations/django
-    dramatiq: TESTPATH=tests/integrations/dramatiq
-    falcon: TESTPATH=tests/integrations/falcon
-    fastapi: TESTPATH=tests/integrations/fastapi
-    fastmcp: TESTPATH=tests/integrations/fastmcp
-    flask: TESTPATH=tests/integrations/flask
-    google_genai: TESTPATH=tests/integrations/google_genai
-    gql: TESTPATH=tests/integrations/gql
-    graphene: TESTPATH=tests/integrations/graphene
-    grpc: TESTPATH=tests/integrations/grpc
-    httpx: TESTPATH=tests/integrations/httpx
-    huey: TESTPATH=tests/integrations/huey
-    huggingface_hub: TESTPATH=tests/integrations/huggingface_hub
-    langchain-base: TESTPATH=tests/integrations/langchain
-    langchain-notiktoken: TESTPATH=tests/integrations/langchain
-    langgraph: TESTPATH=tests/integrations/langgraph
-    launchdarkly: TESTPATH=tests/integrations/launchdarkly
-    litellm: TESTPATH=tests/integrations/litellm
-    litestar: TESTPATH=tests/integrations/litestar
-    loguru: TESTPATH=tests/integrations/loguru
-    mcp: TESTPATH=tests/integrations/mcp
-    openai-base: TESTPATH=tests/integrations/openai
-    openai-notiktoken: TESTPATH=tests/integrations/openai
-    openai_agents: TESTPATH=tests/integrations/openai_agents
-    openfeature: TESTPATH=tests/integrations/openfeature
-    pure_eval: TESTPATH=tests/integrations/pure_eval
-    pydantic_ai: TESTPATH=tests/integrations/pydantic_ai
-    pymongo: TESTPATH=tests/integrations/pymongo
-    pyramid: TESTPATH=tests/integrations/pyramid
-    quart: TESTPATH=tests/integrations/quart
-    ray: TESTPATH=tests/integrations/ray
-    redis: TESTPATH=tests/integrations/redis
-    redis_py_cluster_legacy: TESTPATH=tests/integrations/redis_py_cluster_legacy
-    requests: TESTPATH=tests/integrations/requests
-    rq: TESTPATH=tests/integrations/rq
-    sanic: TESTPATH=tests/integrations/sanic
-    spark: TESTPATH=tests/integrations/spark
-    sqlalchemy: TESTPATH=tests/integrations/sqlalchemy
-    starlette: TESTPATH=tests/integrations/starlette
-    starlite: TESTPATH=tests/integrations/starlite
-    statsig: TESTPATH=tests/integrations/statsig
-    strawberry: TESTPATH=tests/integrations/strawberry
-    tornado: TESTPATH=tests/integrations/tornado
-    trytond: TESTPATH=tests/integrations/trytond
-    typer: TESTPATH=tests/integrations/typer
-    unleash: TESTPATH=tests/integrations/unleash
+    aiohttp: _TESTPATH=tests/integrations/aiohttp
+    anthropic: _TESTPATH=tests/integrations/anthropic
+    ariadne: _TESTPATH=tests/integrations/ariadne
+    arq: _TESTPATH=tests/integrations/arq
+    asyncpg: _TESTPATH=tests/integrations/asyncpg
+    beam: _TESTPATH=tests/integrations/beam
+    boto3: _TESTPATH=tests/integrations/boto3
+    bottle: _TESTPATH=tests/integrations/bottle
+    celery: _TESTPATH=tests/integrations/celery
+    chalice: _TESTPATH=tests/integrations/chalice
+    clickhouse_driver: _TESTPATH=tests/integrations/clickhouse_driver
+    cohere: _TESTPATH=tests/integrations/cohere
+    django: _TESTPATH=tests/integrations/django
+    dramatiq: _TESTPATH=tests/integrations/dramatiq
+    falcon: _TESTPATH=tests/integrations/falcon
+    fastapi: _TESTPATH=tests/integrations/fastapi
+    fastmcp: _TESTPATH=tests/integrations/fastmcp
+    flask: _TESTPATH=tests/integrations/flask
+    google_genai: _TESTPATH=tests/integrations/google_genai
+    gql: _TESTPATH=tests/integrations/gql
+    graphene: _TESTPATH=tests/integrations/graphene
+    grpc: _TESTPATH=tests/integrations/grpc
+    httpx: _TESTPATH=tests/integrations/httpx
+    huey: _TESTPATH=tests/integrations/huey
+    huggingface_hub: _TESTPATH=tests/integrations/huggingface_hub
+    langchain-base: _TESTPATH=tests/integrations/langchain
+    langchain-notiktoken: _TESTPATH=tests/integrations/langchain
+    langgraph: _TESTPATH=tests/integrations/langgraph
+    launchdarkly: _TESTPATH=tests/integrations/launchdarkly
+    litellm: _TESTPATH=tests/integrations/litellm
+    litestar: _TESTPATH=tests/integrations/litestar
+    loguru: _TESTPATH=tests/integrations/loguru
+    mcp: _TESTPATH=tests/integrations/mcp
+    openai-base: _TESTPATH=tests/integrations/openai
+    openai-notiktoken: _TESTPATH=tests/integrations/openai
+    openai_agents: _TESTPATH=tests/integrations/openai_agents
+    openfeature: _TESTPATH=tests/integrations/openfeature
+    pure_eval: _TESTPATH=tests/integrations/pure_eval
+    pydantic_ai: _TESTPATH=tests/integrations/pydantic_ai
+    pymongo: _TESTPATH=tests/integrations/pymongo
+    pyramid: _TESTPATH=tests/integrations/pyramid
+    pyreqwest: _TESTPATH=tests/integrations/pyreqwest
+    quart: _TESTPATH=tests/integrations/quart
+    ray: _TESTPATH=tests/integrations/ray
+    redis: _TESTPATH=tests/integrations/redis
+    redis_py_cluster_legacy: _TESTPATH=tests/integrations/redis_py_cluster_legacy
+    requests: _TESTPATH=tests/integrations/requests
+    rq: _TESTPATH=tests/integrations/rq
+    sanic: _TESTPATH=tests/integrations/sanic
+    spark: _TESTPATH=tests/integrations/spark
+    sqlalchemy: _TESTPATH=tests/integrations/sqlalchemy
+    starlette: _TESTPATH=tests/integrations/starlette
+    starlite: _TESTPATH=tests/integrations/starlite
+    statsig: _TESTPATH=tests/integrations/statsig
+    strawberry: _TESTPATH=tests/integrations/strawberry
+    tornado: _TESTPATH=tests/integrations/tornado
+    trytond: _TESTPATH=tests/integrations/trytond
+    typer: _TESTPATH=tests/integrations/typer
+    unleash: _TESTPATH=tests/integrations/unleash
 
 passenv =
     SENTRY_PYTHON_TEST_POSTGRES_HOST
     SENTRY_PYTHON_TEST_POSTGRES_USER
     SENTRY_PYTHON_TEST_POSTGRES_PASSWORD
     SENTRY_PYTHON_TEST_POSTGRES_NAME
+    TESTPATH
 
 usedevelop = True
 
@@ -931,7 +1076,7 @@ commands =
     ; Running `pytest` as an executable suffers from an import error
     ; when loading tests in scenarios. In particular, django fails to
     ; load the settings from the test module.
-    python -m pytest -W error::pytest.PytestUnraisableExceptionWarning {env:TESTPATH} -o junit_suite_name={envname} {posargs}
+    python -m pytest -W error::pytest.PytestUnraisableExceptionWarning {env:TESTPATH:{env:_TESTPATH}} -o junit_suite_name={envname} {posargs}
 
 [testenv:linters]
 commands =