CodeRAG

About CodeRAG

🔎 CodeRAG A standalone, local-first semantic code-search engine for large and custom codebases. CodeRAG indexes a whole codebase into a hybrid (vector + keyword) search index and answers questions like "where is retry/backoff handled?" with the exact functions, classes, and files that matter — ranked by meaning, not just string match. It runs entirely on your machine with no API key (a local ONNX embedding model is the default), keeps its index up to date as you edit, and is built to stay fast on large codebases.

ai ai-assistant ai-code ai-tools code-search faiss openai-gpt rag retrieval-augmented-generation vector

Quick Facts

Stars	211
Forks	34
Language	Python
Category	Agent Tool
Quality Score	65.5205672327872/100
Open Issues	3
Last Updated	2026-06-16
Created	2024-09-08
Platforms	python
Est. Tokens	~15k

Compatible Skills

These tools work well together with CodeRAG for enhanced workflows:

RAGLight — semantic(0.35)+complementary+rare_topics+same_lang+similar_pop+shared_platform (66%)
local_faiss_mcp — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
snippy — semantic(0.25)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (62%)
mcp-memory-service — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)

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Frequently Asked Questions

What is CodeRAG?

CodeRAG is CodeRAG is an AI-powered tool for real-time codebase querying and augmentation using OpenAI and vector search.. It is categorized as a Agent Tool with 211 GitHub stars.

What programming language is CodeRAG written in?

CodeRAG is primarily written in Python. It covers topics such as ai, ai-assistant, ai-code.

How do I install or use CodeRAG?

You can find installation instructions and usage details in the CodeRAG GitHub repository at github.com/Neverdecel/CodeRAG. The project has 211 stars and 34 forks, indicating an active community.

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