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Cognee

Builds a knowledge graph plus vector store for hybrid GraphRAG.

Cognee is an open-source Python framework for building memory layers for AI agents and LLM applications. It ingests data (documents, conversations, code) and constructs queryable knowledge graphs combined with vector embeddings, replacing ad-hoc RAG pipelines with a structured, persistent memory. It supports multiple graph and vector store backends and exposes a pipeline-based API for loading, cognifying, and searching data.

Repository

topoteretes/cognee

Language

Python

What you'd build with it

  • Giving an AI agent persistent, structured long-term memory across sessions instead of stateless context windows
  • Building a graph-plus-vector RAG layer that links entities and facts across a document corpus for more accurate retrieval
  • Turning unstructured data (chats, PDFs, code) into a queryable knowledge graph that an LLM can reason over

Tags

graphragmemoryknowledge-graph