circlemind-ai/fast-graphrag

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3849 stars · 248 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

fast-graphrag is a Python library providing a streamlined, promptable GraphRAG framework for interpretable, high-precision retrieval workflows built on knowledge graphs. It uses PageRank-based graph exploration, supports incremental updates, and is designed to be fast and low-cost compared to alternatives like Microsoft's graphrag.

Use cases

• build a graph-based RAG pipeline over my documents
• query unstructured text with knowledge graph retrieval
• cheaper alternative to Microsoft graphrag
• incrementally update a knowledge graph as data changes
• visualize and debug extracted knowledge from documents
• add interpretable retrieval to an LLM application

When to choose

• you want graph-based RAG with interpretable, navigable knowledge
• cost and speed matter more than heavyweight agentic orchestration
• your data evolves and you need incremental graph updates
• you want a typed, async Python library that fits into an existing pipeline

When to avoid

• you need simple vector-only semantic search without graph structure
• you want a turnkey hosted RAG service rather than a library
• your stack is not Python
• you need a battle-tested, long-established solution with large ecosystem support

Facets

library · maturity active

rag llm-inference search-engine agent-framework nlp large-language-models artificial-intelligence python cross-platform graphrag knowledge-graph pagerank retrieval-pipeline openai async retrieval-augmented-generation natural-language-processing search

Member repositories

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markdown · JSON · MCP: product_card(name="circlemind-ai/fast-graphrag")