neo4j-graphrag-python and graphrag-api
The Neo4j GraphRAG library provides the core Python implementation for graph-based retrieval-augmented generation, while the GraphRAG Server wraps and exposes that functionality (or similar implementations) as an API service, making them complementary tools for different deployment patterns.
About neo4j-graphrag-python
neo4j/neo4j-graphrag-python
Neo4j GraphRAG for Python
Supports automated knowledge graph construction from unstructured text and PDFs via LLM-powered entity/relation extraction, alongside multiple retrieval strategies (vector search, graph traversal, hybrid, and Text2Cypher). Integrates with major LLM providers (OpenAI, Anthropic, Google, Cohere, Ollama, MistralAI) and optional external vector stores (Weaviate, Pinecone, Qdrant), with experimental NLP components using spaCy for semantic resolution.
About graphrag-api
noworneverev/graphrag-api
GraphRAG Server
FastAPI wrapper exposing Microsoft GraphRAG's four search modes (Global, Local, DRIFT, Basic) through REST endpoints, enabling flexible querying across knowledge graphs at different abstraction levels. Operates on pre-indexed GraphRAG project directories containing output artifacts and configuration, with tunable parameters like community hierarchy depth and extraction settings. Integrates seamlessly with the GraphRAG Visualizer frontend or custom clients via standard HTTP APIs.
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