Reachy RAG: Intelligent Knowledge Base #1
Description
Overview
RAG-powered knowledge base for the Reachy project that can answer questions about SDK documentation, troubleshooting, project history, and session logs.
Features
- Vector database (ChromaDB or LanceDB) indexing all documentation
- Embedding model for semantic search
- LLM for response generation with retrieved context
- Gradio UI for chat interface
Data Sources
- Official Reachy Mini SDK docs
- Local CLAUDE.md files
- Session logs from ~/apps/reachy/sessions/
- Devlog content
- HuggingFace app READMEs
Why This Matters
As the project grows, finding relevant information becomes harder. A RAG system provides instant access to institutional knowledge and accelerates debugging.
Technical Notes
- Start with local vector DB (no external dependencies)
- Use sentence-transformers for embeddings
- Consider streaming responses for better UX
- Add ability to cite sources in responses
This is a roadmap item tracked at runreachyrun.com