stair-lab/kg-gen

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1260 stars · 199 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

kg-gen is a Python library that extracts knowledge graphs from arbitrary plain text or conversation messages using LLMs, with model routing via LiteLLM and structured output via DSPy. It also ships the MINE benchmark and an MCP server for knowledge graph generation.

Use cases

• extract a knowledge graph from plain text with an llm
• build a graph to improve rag retrieval
• generate synthetic graph data for model training
• structure unstructured text into entities and relations
• analyze relationships between concepts in documents
• run a knowledge graph extraction benchmark

When to choose

• you want a ready-made Python API to turn text or chat messages into knowledge graphs
• you need provider flexibility across OpenAI, Anthropic, Gemini, Ollama, and other local or API models
• you want graph-structured data to augment RAG pipelines or training datasets

When to avoid

• you need deterministic, non-LLM graph extraction with no API or model costs
• you need a full graph database or graph visualization product rather than an extraction library
• your project requires a permissive license - the repo currently lists no license

Facets

library · maturity active

rag nlp llm-inference data-generation large-language-models machine-learning python knowledge-graph graph-extraction litellm dspy structured-output benchmark mcp natural-language-processing retrieval-augmented-generation

Member repositories

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markdown · JSON · MCP: product_card(name="stair-lab/kg-gen")