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tomohiro-owada/devrag

v1.4.4 Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 1mo MCP Developer Tools
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

claude-code developer-tools documentation embeddings go local-ai
+7 more
markdown mcp onnx llm semantic-search sqlite vector-db

Summary

AI summary

Fixed search crash with zero‑vector chunks and enabled CoreML GPU acceleration on Apple Silicon.

Full changelog

Bug Fixes

  • Fix search crash with zero-vector chunks (#22): vec_distance_cosine() returns NULL for zero vectors (stored as a fallback when chunk embedding fails). The scanner now handles NULL distances gracefully and skips those chunks instead of crashing.
  • Fix CoreML GPU acceleration on Apple Silicon (#21): The MLComputeUnits option value was CPU_AND_GPU (underscore) but ONNX Runtime expects CPUAndGPU (CamelCase). M1/M2/M3 Macs will now correctly use CoreML GPU acceleration instead of falling back to CPU.

Full Changelog: https://github.com/tomohiro-owada/devrag/compare/v1.4.3...v1.4.4

View diff on GitHub

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About tomohiro-owada/devrag

Lightweight local RAG MCP server for semantic vector search over markdown documents. Reduces token consumption by 40x with sqlite-vec and multilingual-e5-small embeddings. Supports filtered search by directory and filename patterns.

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Related context

Beta — feedback welcome: [email protected]