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💾

LangMem

by LangChain

Memory modules for LangChain agents

LangMem provides various memory implementations for LangChain agents, including conversation buffers, summaries, knowledge graphs, and vector store-backed memory.

Ease of Use
0/10
Community
0/10
Performance
0/10
Documentation
0/10

🎯 Key Features

Conversation buffer memory

Conversation summary memory

Entity memory

Knowledge graph memory

Vector store memory

Token buffer memory

Combined memory

Custom memory classes

Strengths

Multiple memory types

Flexible architecture

Large ecosystem

Well documented

Free and open-source

Limitations

Requires manual configuration

No built-in UI

Performance depends on backend

Requires LangChain

Best For

  • LangChain-based applications
  • Custom memory implementations
  • Flexible memory architectures
  • Research and experimentation

Not Recommended For