Friday, March 20, 2026

auyelbekov/rawq: AI Agent Context Retrieval Engine — Semantic and Lexical Codebase Search on GitHub

Unlock Efficient Codebase Searches with rawq!

In the world of AI, efficiency is key. Introducing rawq, a powerful context retrieval engine designed specifically for AI agents. Say goodbye to token waste and irrelevant file reads!

Key Features:

  • Hybrid Search: Combines semantic and lexical approaches for precise results.
  • Fast & Efficient: Returns only relevant code snippets—beneficial in large codebases.
  • Fully Offline: No internet needed after initial model download.
  • GPU Acceleration: Leverages your hardware for lightning-fast searches.

Installation Made Easy:

  • Quick setup via prebuilt binaries or Cargo for Rust users.
  • Seamlessly integrates with your existing workflow.

Unique Capabilities:

  • Incremental indexing with git awareness.
  • API-friendly outputs in JSON format.
  • Supports 16 programming languages, ensuring versatility.

Ready to streamline your code searches? Explore more about rawq and share this summary with your network to spark conversations about AI efficiency!

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