Chris Coutinho
6cfd7e2729
Added support for two fusion algorithms (RRF and DBSF) to combine dense semantic and sparse BM25 search results, with comprehensive documentation and unit tests. Changes: - Added fusion parameter to nc_semantic_search and nc_semantic_search_answer tools - Updated ADR-014 with detailed comparison of RRF vs DBSF fusion algorithms - Added unit tests for fusion algorithm initialization and validation - Updated search_method in responses to include fusion type (e.g., "bm25_hybrid_rrf") Fusion Algorithms: - RRF (Reciprocal Rank Fusion): Default, rank-based, general-purpose - DBSF (Distribution-Based Score Fusion): Score normalization using statistics RRF is recommended for most use cases due to its robustness and established track record. DBSF may provide better results when retrieval systems have very different score distributions. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""Unit tests for BM25 hybrid search algorithm."""
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import pytest
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from qdrant_client import models
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from nextcloud_mcp_server.search.bm25_hybrid import BM25HybridSearchAlgorithm
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@pytest.mark.unit
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def test_bm25_hybrid_initialization_default():
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"""Test BM25HybridSearchAlgorithm initializes with default RRF fusion."""
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algo = BM25HybridSearchAlgorithm()
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assert algo.score_threshold == 0.0
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assert algo.fusion == models.Fusion.RRF
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assert algo.fusion_name == "rrf"
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assert algo.name == "bm25_hybrid"
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@pytest.mark.unit
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def test_bm25_hybrid_initialization_with_rrf():
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"""Test BM25HybridSearchAlgorithm initializes with explicit RRF fusion."""
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algo = BM25HybridSearchAlgorithm(score_threshold=0.5, fusion="rrf")
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assert algo.score_threshold == 0.5
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assert algo.fusion == models.Fusion.RRF
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assert algo.fusion_name == "rrf"
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@pytest.mark.unit
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def test_bm25_hybrid_initialization_with_dbsf():
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"""Test BM25HybridSearchAlgorithm initializes with DBSF fusion."""
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algo = BM25HybridSearchAlgorithm(score_threshold=0.7, fusion="dbsf")
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assert algo.score_threshold == 0.7
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assert algo.fusion == models.Fusion.DBSF
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assert algo.fusion_name == "dbsf"
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@pytest.mark.unit
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def test_bm25_hybrid_invalid_fusion_raises_error():
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"""Test BM25HybridSearchAlgorithm raises ValueError for invalid fusion."""
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with pytest.raises(ValueError) as exc_info:
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BM25HybridSearchAlgorithm(fusion="invalid")
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assert "Invalid fusion algorithm 'invalid'" in str(exc_info.value)
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assert "Must be 'rrf' or 'dbsf'" in str(exc_info.value)
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@pytest.mark.unit
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def test_bm25_hybrid_requires_vector_db():
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"""Test BM25HybridSearchAlgorithm reports it requires vector database."""
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algo = BM25HybridSearchAlgorithm()
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assert algo.requires_vector_db is True
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