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memorylayer.ai Documentation

Python SDK

The MemoryLayer Python SDK (memorylayer-client) provides an async Python client for interacting with the MemoryLayer server.

Installation

Terminal window
pip install memorylayer-client

Features

  • Async/Await — Full async support with context managers
  • Type-Safe — Complete type hints with Pydantic models
  • Memory Operations — Remember, recall, reflect, forget, decay
  • Relationship Graph — Link memories with typed relationships
  • Session Management — Working memory with TTL and commit
  • Batch Operations — Bulk create, update, delete
  • Error Handling — Comprehensive typed exception hierarchy

Quick Start

from memorylayer import MemoryLayerClient, MemoryType


async with MemoryLayerClient(
    base_url="http://localhost:61001",
    workspace_id="my-workspace"
) as client:
    # Store a memory
    memory = await client.remember(
        content="User prefers Python for backend development",
        type=MemoryType.SEMANTIC,
        importance=0.8,
        tags=["preferences", "programming"]
    )


    # Search memories
    results = await client.recall(
        query="what programming language does the user prefer?",
        limit=5
    )


    for memory in results.memories:
        print(f"{memory.content} (relevance: {memory.importance})")


    # Synthesize memories
    reflection = await client.reflect(
        query="summarize user's technology preferences"
    )
    print(reflection.reflection)

Configuration

client = MemoryLayerClient(
    base_url="http://localhost:61001",  # Server URL
    api_key="your-api-key",             # Optional for local dev
    workspace_id="my-workspace",        # Default workspace
    session_id="sess_123",              # Optional active session
    timeout=30.0                        # Request timeout in seconds
)

Next Steps