embedding_similarity

Active

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

declared in 1.0.0

Compute text similarity using local algorithms (Bag of Words, TF-IDF, Character N-grams). No API key needed — runs entirely in-process. NOT real embeddings: for true semantic similarity with vector embeddings, use run_semantic_tests with mode="embeddings" and your OpenAI API key. Supports single pair or batch mode with pipe-separated pairs. Useful for RAG retrieval testing, semantic search evaluation, and text deduplication.

Parameters schema

{
  "type": "object",
  "properties": {
    "batch": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "text_a",
          "text_b"
        ],
        "properties": {
          "text_a": {
            "type": "string"
          },
          "text_b": {
            "type": "string"
          }
        }
      },
      "description": "Batch mode: array of { text_a, text_b } pairs. Overrides text_a/text_b if provided."
    },
    "text_a": {
      "type": "string",
      "description": "First text to compare (single-pair mode)"
    },
    "text_b": {
      "type": "string",
      "description": "Second text to compare (single-pair mode)"
    },
    "methods": {
      "type": "array",
      "items": {
        "enum": [
          "bow",
          "tfidf",
          "ngram"
        ],
        "type": "string"
      },
      "description": "Algorithms to use (default: all three). Options: \"bow\", \"tfidf\", \"ngram\""
    }
  }
}

What this tool wraps· 0 endpoints

min confidence0.70 0.50

No endpoints wrapped at confidence ≥ 0.70.

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

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

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