RAG for Developers — Built for Code, Not Just Text (Review Requested)

Source: Dev.to

Code-Aware RAG Tool — Looking for Developer Feedback

We’ve been building a code‑first RAG tool that actually understands how codebases work, not just how text looks in embeddings. The goal is simple: when you ask a question, you get the right functions, related calls, and supporting code, not random nearby snippets.

What’s Inside

• AST‑based code chunking with Tree‑sitter (Python, JavaScript, TypeScript)
• Extraction of functions, classes, imports, calls, docstrings explicitly
• A clean async ingestion pipeline with strict tool → agent → storage boundaries
• Semantic vector search as the starting point, not the end
• In‑memory dependency graph expansion
  • Built lazily from chunk metadata
  • No persistence, no globals, no backend shortcuts
• Stable qualified IDs (file::entity)
• Context expansion via BFS over calls and imports to pull in code that’s actually connected
• Backend‑agnostic vector store layer, so storage can change without rewriting logic

Why We Think This Is Useful

• You get related code paths, not just similar text
• Context stays small, relevant, and debuggable
• The architecture avoids hidden state and scaling surprises

What We’d Love Feedback On

If you’ve worked with large repos or built RAG systems before, we’d really value your thoughts on:

• The “graph as derived state” design
• Chunk metadata choices (calls, imports, QIDs)
• Retrieval + expansion flow
• Any edge cases you think would show up in real production codebases

Even quick reactions or gut checks are welcome.