Graphiti

Graphiti

Graphiti is a framework designed for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti continuously integrates user interactions, structured and unstructured enterprise data, and external information into a coherent, queryable graph.

Key Features:

• Real-Time Incremental Updates: Integrates new data episodes immediately without batch recomputation.
• Bi-Temporal Data Model: Tracks event occurrence and ingestion times for accurate point-in-time queries.
• Efficient Hybrid Retrieval: Combines semantic embeddings, keyword search, and graph traversal for low-latency queries.
• Custom Entity Definitions: Supports developer-defined entities through Pydantic models.
• Scalability: Efficiently manages large datasets with parallel processing suitable for enterprise environments.

Benefits:

• Enables state-based reasoning and task automation for agents.
• Facilitates complex, evolving data queries with semantic, keyword, and graph-based methods.
• Powers the core of Zep's memory layer for AI agents, enhancing their memory capabilities.

Highlights:

• Open-source framework with active development and community contributions.
• Supports integration with various LLM services like OpenAI and Google Gemini.
• Comprehensive documentation and quick start guides available for developers.