langchain-ai/langmem

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1626 stars · 186 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LangMem is a Python library that helps AI agents learn and adapt from their interactions over time by extracting information from conversations, refining prompts, and maintaining long-term memory. It provides storage-agnostic memory primitives plus native integration with LangGraph's Long-term Memory Store.

Use cases

• add long-term memory to a langgraph agent
• extract important facts from chat conversations automatically
• let an agent record and search its own memories during conversations
• personalize agent responses based on past interactions
• run a background memory manager that consolidates agent knowledge
• refine agent prompts based on accumulated experience
• persist agent memory across sessions with a postgres-backed store

When to choose

• you are building agents with LangGraph and want persistent, searchable memory
• you need agents that personalize behavior across sessions
• you want both hot-path memory tools and background memory consolidation
• you want a memory API that works with any storage backend

When to avoid

• you need a full standalone agent framework rather than a memory layer
• your project does not use Python or the LangChain/LangGraph ecosystem
• you only need simple short-term conversation context without persistence

Facets

library · maturity active

agent-framework rag llm-inference prompt-engineering machine-learning artificial-intelligence large-language-models developer-tools python long-term-memory langgraph memory-management agent-personalization conversation-memory ai-agents retrieval-augmented-generation

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markdown · JSON · MCP: product_card(name="langchain-ai/langmem")