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Unit tests for Long-Term User Memory, Reciprocal Rank Fusion (RRF), and Semantic Cache.
"""
from __future__ import annotations
import pytest
import numpy as np
from services.rrf_service import compute_rrf
from services.reranker import RankedChunk
from services.cache import cache_service
def test_rrf_fusion():
c1 = RankedChunk("Text A", 0.9, "doc1", "a.txt", 1, "hr")
c2 = RankedChunk("Text B", 0.8, "doc2", "b.txt", 1, "hr")
dense = [c1, c2]
sparse = [c2, c1]
merged = compute_rrf(dense, sparse, k=60, top_n=2)
assert len(merged) == 2
assert merged[0].score > 0.0
def test_semantic_cache():
v1 = [1.0, 0.0, 0.0]
v2 = [0.99, 0.01, 0.0] # High similarity with v1
v3 = [0.0, 1.0, 0.0] # Low similarity with v1
res_data = {"response": "Cached answer"}
cache_service.set_semantic(v1, res_data)
# High similarity query hit
hit = cache_service.get_semantic(v2, similarity_threshold=0.90)
assert hit is not None
assert hit["response"] == "Cached answer"
# Low similarity query miss
miss = cache_service.get_semantic(v3, similarity_threshold=0.90)
assert miss is None
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