pingcap/autoflow

Health v2 · maintenance only

Adoption not part of the score

2971 stars · 195 forks observed · 2026-08-28

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

AutoFlow is an open-source Graph RAG knowledge base tool that builds knowledge graphs over crawled documentation and answers questions via conversational search, built on TiDB Serverless Vector Storage, LlamaIndex, and DSPy. It ships as a deployable web application (Docker Compose) with an embeddable JavaScript chat widget, demonstrated at tidb.ai.

Use cases

• build a conversational knowledge base over my product docs
• add a Perplexity-style search page to my documentation site
• embed a chat widget that answers questions from my website content
• crawl a sitemap and index docs into a knowledge graph for RAG
• self-host a Graph RAG question-answering assistant
• answer user questions with citations from a knowledge graph

When to choose

• you want a self-hosted Graph RAG assistant over documentation or websites
• you already use TiDB or want TiDB Serverless vector storage
• you need an embeddable conversational search widget for your site

When to avoid

• you need a production-hardened, stable RAG platform (project is early stage)
• you want a simple vector-only RAG without knowledge graph overhead
• you cannot run Docker Compose with ~4 CPU cores and 8GB RAM

Facets

application · maturity experimental

rag search-engine chatbot web-scraping vector-database llm-inference large-language-models chatbots self-hosted python graphrag knowledge-base tidb llamaindex dspy conversational-search embeddable-widget retrieval-augmented-generation search knowledge-graphs docker web-server typescript

Member repositories

For agents

markdown · JSON · MCP: product_card(name="pingcap/autoflow")