bm25_score

Active

Tool of IA-QA — 130+ QA & Dev Tools for AI Agents

declared in 1.0.0

Compute BM25 relevance score between a query and one or more documents. BM25 is the industry-standard keyword-based ranking algorithm used in Elasticsearch, OpenSearch, and Weaviate hybrid search. Returns ranked results with normalized scores.

Parameters schema

{
  "type": "object",
  "required": [
    "query",
    "documents"
  ],
  "properties": {
    "b": {
      "type": "number",
      "description": "Length normalization factor (default: 0.75)"
    },
    "k1": {
      "type": "number",
      "description": "Term frequency saturation (default: 1.5)"
    },
    "query": {
      "type": "string",
      "description": "The search query"
    },
    "top_k": {
      "type": "number",
      "description": "Return top K results (default: all)"
    },
    "documents": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Array of documents to rank"
    }
  }
}

What this tool wraps· 1 endpoint

min confidence0.70 0.50

Data resourceWeaviate Vector Database
Weaviate · database
name mention0.70

Parent server

IA-QA — 130+ QA & Dev Tools for AI Agents

https://github.com/jcjamet/ia-qa

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