Welcome to Mem0 Open Source
Mem0 is a self-improving memory layer for LLM applications that enables personalized AI experiences while saving costs and delighting users. The open-source version gives you complete control over your memory infrastructure.Why Choose Mem0 Open Source?
Mem0 open-source provides a powerful, flexible foundation for AI memory management with these key advantages:- Complete Control: Deploy and manage your own memory infrastructure with full customization capabilities. Perfect for organizations that need data sovereignty and custom integrations.
- Flexible Architecture: Choose from multiple vector databases (Pinecone, Qdrant, Weaviate, Chroma, PGVector), graph stores (Neo4j, Memgraph), and embedding models to fit your specific needs.
-
Advanced Memory Organization: Organize memories using
user_id
,agent_id
, andrun_id
parameters for sophisticated multi-agent, multi-session applications with precise context control. - Rich Integration Ecosystem: Seamlessly integrate with popular frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, and Vercel AI SDK.
Core Features
Memory Management
- Synchronous & Asynchronous Operations: Choose between sync and async memory operations based on your application needs
- Smart Memory Retrieval: Intelligent search and retrieval with semantic understanding
- Memory Persistence: Long-term storage with automatic optimization and cleanup
Advanced Organization
- User Context: Organize memories by user for personalized experiences
- Agent Isolation: Separate memories by AI agent for specialized knowledge domains
- Session Tracking: Use run IDs to maintain context across different conversation sessions
Flexible Storage
- Vector Databases: Support for Pinecone, Qdrant, Weaviate, Chroma, and PGVector
- Graph Stores: Neo4j and Memgraph integration for relationship-based memory
- Embedding Models: Multiple embedding providers for optimal performance
Getting Started
Choose your preferred approach:- Python Quickstart: Get started with Python SDK
- Node.js Quickstart: Use Mem0 with Node.js/TypeScript
- Examples: Explore real-world use cases and implementations
Next Steps
- Explore specific features in detail
- Learn about graph memory capabilities
- Set up vector databases and LLM integrations
- Check out our examples for practical implementations
- Join our Discord community for support