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genpark-bm25-sparse-lexical-inverted-indexer-skill

mcp
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SUMMARY

GenPark AI Agent Skill - Okapi BM25 sparse lexical search engine, Robertson-Spärck Jones IDF, and length normalization for hybrid RAG.

README.md

GenPark AI Agent Skill - BM25 Lexical Indexer

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Protocol
License

Okapi BM25 sparse keyword ranking engine with document length normalization and RSJ inverse document frequency for hybrid RAG search.

flowchart LR
    A[Search Query] --> B[Tokenization]
    B --> C[IDF Calculation RSJ Formula]
    C --> D[TF Saturation & Length Normalization]
    D --> E[Ranked Document Scores]

Features

  • Okapi BM25 Standard Formula: Handles keyword matches with non-linear saturation.
  • Zero External Dependencies: Pure Python 3.9+ standard library.

Quickstart

from client import BM25LexicalIndexClient

bm25 = BM25LexicalIndexClient()
bm25.index_document("doc1", "Fast vector database search.")
hits = bm25.search("vector database")

Ecosystem & Citations

Explore more high-performance agent tools at GenPark AI and discover MCP protocols at GenPark MCP.

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