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title Memory Types & Models
description Reference for the atomic Enums and Pydantic models used by the MemMachine server.
icon cube

The server utilizes a standardized set of types and models to ensure that data is validated and typed consistently across the Service and Router layers. These types are the "Source of Truth" for how the server interprets incoming requests.

API Enumerations

Enums are used to route logic within the service layer and categorize data in the persistent stores.

MemoryType

Defined in memmachine_common.api, this enum determines which store and service logic a request should target.

Member Value Description
Episodic "episodic" Targets session-based conversational stores.
Semantic "semantic" Targets the structured knowledge graph and tag stores.

EpisodeType

Used within episodic memory to distinguish between different kinds of events.

Member Value Description
MESSAGE "message" Represents a standard conversational exchange (User/Assistant).

Core Specification Models (DTOs)

The server relies on Pydantic models defined in spec.py to validate and parse incoming data.

MemoryMessage

The primary unit of ingestion for Episodic memory.

class MemoryMessage(BaseModel):
    content: str        # The raw text of the message
    producer: str       # The ID of the human or agent creator
    produced_for: str   # The recipient ID
    timestamp: datetime # Standardized UTC timestamp
    role: str           # e.g., "user", "assistant", or "system"
    metadata: dict      # Custom JSON metadata

SemanticFeature

The standardized output format for knowledge retrieved from the Semantic store.

Field Type Description
id str Unique UUID for the semantic tag.
category_id str The parent category this tag belongs to.
value str The actual knowledge value (e.g., "Likes Spicy Food").
metadata dict Contextual data regarding the source of the knowledge.

Content and Serialization

ContentType (Enum)

Specifies the format of data stored within an entry.

Member Value Description
STRING "string" The content is a standard UTF-8 text string.

While the current implementation primarily uses STRING, the server architecture is designed to support future serialization of vector embeddings or binary objects without altering the core schema.

Legacy Structures

The GroupConfiguration and MemoryContext objects from v1 are deprecated in the v2 API. The server now uses an Org/Project/Session hierarchy for secure data isolation, which is managed via the _WithOrgAndProj base model in spec.py.