Reachy RAG: Intelligent Knowledge Base

[BioInfo]

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

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This is a roadmap item tracked at runreachyrun.com