What is a local RAG system for codebases?

It's a semantic search tool that embeds your code methods into a vector DB, retrieving exact chunks by meaning — perfect for feeding AI like Claude without wasting tokens on whole files.

How do I build RAG for my Unity or large codebase?

Use the 50-line Python script: pip install chromadb sentence-transformers, set SOURCE_DIR to Assets, run index_all(). Queries embed your question, fetch top methods with line numbers.

Does this RAG work with GPT-4 or other AI coding tools?

Absolutely — any LLM that takes context. Pipe retrieved snippets into prompts for Cursor, GitHub Copilot, or OpenAI APIs. Token savings scale everywhere.

☁️ Cloud & Databases

50-Line RAG Hack Crushes Claude's Token Bloat in 22K-File Codebases

Claude Code users: you're burning thousands of tokens per codebase question. A 50-line local RAG script fixes that, pulling exact methods from 22,000 files without the bloat.

theAIcatchup Apr 10, 2026 4 min read

Python code snippet of 50-line RAG system indexing Unity C# codebase

⚡ Key Takeaways

50-line local RAG indexes code by method, slashing Claude token use 6-10x on big repos. 𝕏
Uses ChromaDB and all-MiniLM-L6-v2 — zero cost, runs offline. 𝕏
Perfect for Unity-scale projects; ports easily to other languages. 𝕏

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theAIcatchup

Community-driven. Code-first.

#ChromaDB #Claude Code #RAG system #code search #codebase search #token-optimization

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Originally reported by Dev.to

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