lyonzin/knowledge-rag

v3.5.0 Breaking

This release includes breaking changes for platform teams planning a safe upgrade.

Published 1mo MCP Developer Tools

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

Topics

antigravity claude claude-code claude-code-cli codex cursor-ai

+14 more

document-search hybrid-search inteligencia-artificial knowledge-base local-ai mcp mcp-server llm rag-chatbot rag-pipeline reranking retrieval-augmented-generation semantic-search vector-db

Summary

AI summary

GPU‑accelerated ONNX embeddings can be enabled for up to 10× faster indexing.

Full changelog

What's New

GPU-Accelerated Embeddings (Optional)

ONNX embeddings can now run on NVIDIA GPUs for 5-10x faster indexing. Opt-in — CPU remains the default.

pip install knowledge-rag[gpu]

models:
  embedding:
    gpu: true

Falls back to CPU automatically if CUDA is unavailable.

README Audit

Full rewrite — removed 5 obsolete "What's New" sections, fixed stale data (format counts, cache paths, Ollama references), consolidated changelog, added supported formats table. 1462 → 1089 lines (-25%).

Supported Formats Table

12 formats documented with parser type, default status, and notes:
MD, TXT, PDF, PY, JSON, CSV, DOCX, XLSX, PPTX, IPYNB, MQH, MQ4

Install/Upgrade:

pip install --upgrade knowledge-rag
# With GPU:
pip install --upgrade knowledge-rag[gpu]

Full Changelog: https://github.com/lyonzin/knowledge-rag/compare/v3.4.3...v3.5.0

View diff on GitHub

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About lyonzin/knowledge-rag

Local RAG system for Claude Code with hybrid search (BM25 + semantic), cross-encoder reranking, markdown-aware chunking, query expansion, and 12 MCP tools. Runs entirely offline with zero external servers.

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