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Hyper-Extract

Knowledge-extraction CLI: LLMs turn documents into structured graphs, hypergraphs and spatio-temporal knowledge — with an MCP server for agents and Obsidian vault export.

3,083 368 Python NOASSERTIONupdated 6 days ago
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Curator's take

The pitch beyond ordinary KG extraction is the hypergraph: relations that connect MORE than two entities survive instead of being flattened into pairwise triples. One command per document, query the abstracts over MCP from Claude Desktop or your IDE, export to Obsidian wikilinks. NOT a graph database (it extracts, storage stays simple) and no standard license resolution at review time — verify before building on it; extraction quality tracks the LLM you plug in.

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README.md
Hyper-Extract Logo

Smart Knowledge Extraction CLI

Transform documents into structured knowledge with one command.

📖 English Version · 中文版

Trendshift

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"Stop reading. Start understanding."
"告别文档焦虑，让信息一目了然"


Hero & Workflow

📰 What's New

  • 🔌 MCP Server — Query your knowledge abstracts from Claude Desktop and IDE agents with he-mcp. (PR #40)
  • 🧠 Anthropic Claude Support — Use claude-opus-4-8, claude-sonnet-4-6, and claude-haiku-4-5 directly as your LLM provider. (PR #38)
  • 📝 Obsidian Export — Turn any graph into an Obsidian vault with Markdown notes linked by [[wikilinks]]. (PR #37)
  • 🧹 he clean — Remove a KA's index or the whole knowledge abstract in one command. (PR #39)
  • 🔧 Reliability Fixes — True mean for multi-chunk embeddings, capped OpenAI-compatible batch sizes, and resolved multi-word llm_* merge strategies. (PRs #35, #36, #41)

See the full changelog in the GitHub releases.

Hyper-Extract is an intelligent, LLM-powered knowledge extraction and evolution framework. It radically simplifies transforming highly unstructured texts into persistent, predictable, and strongly-typed Knowledge Abstracts. It effortlessly extracts information into a wide spectrum of formats—ranging from simple Collections (Lists/Sets) and Pydantic Models, to complex Knowledge Graphs, Hypergraphs, and even Spatio-Temporal Graphs.

✨ Core Features
🔷 8 Knowledge Structures From simple Lists to advanced Graphs, Hypergraphs, and Spatio-Temporal Graphs
🧠 10+ Extraction Engines GraphRAG, LightRAG, Hyper-RAG, KG-Gen, and more — ready to use
📝 80+ YAML Templates Zero-code extraction across Finance, Legal, Medical, TCM, Industry, and General domains
🔄 Incremental Evolution Feed new documents anytime to expand and refine your knowledge base
📤 Obsidian Export Turn any extracted graph into an Obsidian vault — Markdown notes linked by [[wikilinks]]

🎯 What Can You Do With It?

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