332d9a2ad1
- Added vector index building and serving capabilities to the docs chat. - Introduced new scripts for generating embeddings and serving the chat API using vector search. - Updated package.json with new commands for vector index operations. - Enhanced README with instructions for the new RAG pipeline and legacy keyword pipeline. - Removed outdated Vercel configuration file.
2.4 KiB
Docs Chat
Docs chatbot that uses RAG (Retrieval-Augmented Generation) to answer questions from the OpenClaw documentation via semantic search.
RAG Pipeline (Recommended)
The vector-based RAG pipeline uses OpenAI embeddings and LanceDB for semantic search. This provides much better results than keyword matching.
Build the vector index
OPENAI_API_KEY=sk-... pnpm docs:chat:index:vector
This generates embeddings for all doc chunks and stores them in
scripts/docs-chat/.lance-db/ (gitignored).
Run the RAG API
OPENAI_API_KEY=sk-... pnpm docs:chat:serve:vector
Defaults to http://localhost:3001. Health check:
curl http://localhost:3001/health
# Returns: {"ok":true,"chunks":N,"mode":"vector"}
Legacy Keyword Pipeline
The original keyword-based implementation is still available for backward compatibility.
Build the keyword index
pnpm docs:chat:index
This generates scripts/docs-chat/search-index.json from docs/**/*.md.
Run the keyword API
OPENAI_API_KEY=sk-... pnpm docs:chat:serve
Pipeline Integration
CI rebuilds the keyword index whenever docs change so PRs keep
scripts/docs-chat/search-index.json in sync. For production deployments with
RAG, run pnpm docs:chat:index:vector during deploy.
Mintlify widget
Mintlify loads any .js in the docs content directory on every page.
docs/assets/docs-chat-widget.js injects a floating "Ask Molty" button and
calls the API at:
window.DOCS_CHAT_API_URL || "http://localhost:3001"
To use a deployed API, set window.DOCS_CHAT_API_URL before the widget runs
(for example by adding another small .js file in docs/assets/ that sets it).
Architecture
docs/**/*.md
│
▼
┌─────────────────┐
│ build-vector- │ Chunking + OpenAI Embeddings
│ index.ts │
└────────┬────────┘
│
▼
┌─────────────────┐
│ .lance-db/ │ LanceDB Vector Store
└────────┬────────┘
│
▼
┌─────────────────┐
│ serve.ts │ Hybrid Retrieval (Vector + Keyword Boost)
│ │ → GPT-4o-mini Streaming Response
└─────────────────┘