lyonzin/knowledge-rag

v3.2.0 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 2mo 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

Parallel BM25 + Semantic Search runs simultaneously, reducing latency ~50%, and adjacent chunk retrieval expands matched results with surrounding context.

Full changelog

New Features

Parallel BM25 + Semantic Search

Both search engines now run simultaneously in threads. ~50% latency reduction in hybrid mode.

Adjacent Chunk Retrieval

Matched chunks are automatically expanded with surrounding context. When a chunk matches your query, the system fetches the chunks immediately before and after it (from the same document) and merges them into a single expanded result.

Results include context_expanded: true when adjacent chunks were merged
Content grows from ~650 chars to ~1500 chars per result (more context for the LLM)
Zero impact on retrieval precision — the matching still happens on the original chunk

Inspired by PrivateGPT's SentenceWindow pattern and Kotaemon's parallel retrieval.

Upgrade

pip install --upgrade knowledge-rag

Full Changelog

https://github.com/lyonzin/knowledge-rag/compare/v3.1.1...v3.2.0

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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