robert-mcdermott/ai-knowledge-graph

Health v2 · maintenance only

Adoption not part of the score

3088 stars · 418 forks observed · 2026-09-27

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

A Python CLI tool that uses an LLM to extract Subject-Predicate-Object triplets from unstructured text documents and renders them as an interactive knowledge graph HTML visualization. It works with any OpenAI-compatible API endpoint including Ollama, LM Studio, OpenAI, and vLLM.

Use cases

• extract a knowledge graph from unstructured text documents
• visualize entity relationships from text as an interactive graph
• use a local LLM like Ollama to build knowledge graphs
• convert free-form text into structured SPO triplets
• map connections between concepts in a large document
• build an entity-relationship graph without hand-coded extraction rules

When to choose

• you want an automated LLM-powered pipeline from raw text to an interactive knowledge graph
• you need to work with local models via Ollama or any OpenAI-compatible endpoint
• you want entity standardization and relationship inference built in
• you prefer a simple CLI workflow with configurable chunking and LLM settings

When to avoid

• you need a production-grade graph database or RDF/SPARQL support
• you want deterministic, non-LLM extraction with hand-coded rules
• you need real-time or streaming graph updates
• you lack access to any LLM endpoint, since extraction depends entirely on one

Facets

cli-tool · maturity active

llm-inference nlp data-visualization rag cli artificial-intelligence large-language-models data-visualization developer-tools python cli cross-platform knowledge-graph llm networkx pyvis entity-extraction spo-triplets ollama openai-compatible natural-language-processing

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