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Tests for Semantic Cache
Tests that the cache:
- Stores and retrieves query/answer pairs
- Detects similar queries (>0.90 similarity threshold)
- Improves with repeated queries
- Handles edge cases (empty, duplicate, etc.)
"""
import pytest
import numpy as np
import tempfile
import os
from backend.cache.semantic_cache import SemanticCache, CachedAnswer
from backend.config import settings
from backend.database import init_db, close_db
class TestCacheInitialization:
"""Test cache initialization."""
def test_cache_creation(self):
"""Test that cache initializes without error."""
cache = SemanticCache()
assert cache.embedder is not None
assert len(cache.cached_queries) == 0
assert cache.faiss_index is None
def test_cache_empty_stats(self):
"""Test stats on empty cache."""
cache = SemanticCache()
stats = cache.get_cache_stats()
assert stats == {} # Empty cache returns empty dict
class TestCacheStorage:
"""Test cache storage and retrieval."""
def test_cache_store_and_retrieve(self):
"""Test storing and retrieving from cache."""
cache = SemanticCache()
query = "What is photosynthesis?"
answer = "Photosynthesis is the process by which plants convert light into chemical energy."
cache_id = cache.store_in_cache(
query=query,
answer=answer,
context_tokens_used=150,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.75,
source_pages="23,24"
)
assert cache_id > 0
assert cache_id in cache.cached_queries
cached = cache.cached_queries[cache_id]
assert cached.query_text == query
assert cached.answer == answer
assert cached.context_tokens_used == 150
def test_cache_similarity_threshold(self):
"""Test that cache respects similarity threshold."""
cache = SemanticCache()
# Two very similar queries
query1 = "What is photosynthesis?"
query2 = "What is the process of photosynthesis?" # Slightly different
# Store first query
cache.store_in_cache(
query=query1,
answer="Answer 1",
context_tokens_used=100,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages="20"
)
# Check if similar query hits cache
result = cache.check_cache(query2, textbook_id=1)
# Result might be None (if threshold not met) or a cached answer
# This depends on embedding similarity, so we just check it doesn't crash
assert result is None or isinstance(result, dict)
def test_cache_identical_query(self):
"""Test that identical queries hit cache."""
cache = SemanticCache()
query = "What is photosynthesis?"
answer = "Photosynthesis is..."
# Store query
cache_id = cache.store_in_cache(
query=query,
answer=answer,
context_tokens_used=100,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages="20"
)
# Check identical query
result = cache.check_cache(query, textbook_id=1)
# Should either hit cache or be very close
assert result is None or result['cache_hit'] or result['similarity'] > 0.99
class TestCacheSimilarity:
"""Test embedding similarity computation."""
def test_embedder_similarity(self):
"""Test similarity between embeddings."""
cache = SemanticCache()
embedder = cache.embedder
text1 = "What is photosynthesis?"
text2 = "How does photosynthesis work?"
text3 = "What is the weather?"
emb1 = embedder.embed_query(text1)
emb2 = embedder.embed_query(text2)
emb3 = embedder.embed_query(text3)
# Related queries should be more similar than unrelated
sim_related = embedder.similarity(emb1, emb2)
sim_unrelated = embedder.similarity(emb1, emb3)
assert sim_related > sim_unrelated
assert 0 <= sim_related <= 1
assert 0 <= sim_unrelated <= 1
def test_similarity_threshold_setting(self):
"""Test that similarity threshold is correctly configured."""
assert settings.CACHE_SIMILARITY_THRESHOLD >= 0.85
assert settings.CACHE_SIMILARITY_THRESHOLD <= 1.0
class TestCacheEdgeCases:
"""Test edge cases."""
def test_cache_clear(self):
"""Test clearing cache."""
cache = SemanticCache()
# Store something
cache.store_in_cache(
query="Test",
answer="Answer",
context_tokens_used=50,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages="1"
)
assert len(cache.cached_queries) > 0
# Clear
cache.clear_cache()
assert len(cache.cached_queries) == 0
def test_empty_query_check(self):
"""Test checking empty query."""
cache = SemanticCache()
# Empty or None queries should be handled
result = cache.check_cache("", textbook_id=1)
# Should return None gracefully
assert result is None
def test_very_long_query(self):
"""Test caching very long queries."""
cache = SemanticCache()
long_query = "What is the meaning of life? " * 100
cache_id = cache.store_in_cache(
query=long_query,
answer="42",
context_tokens_used=200,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages="1"
)
assert cache_id > 0
class TestCachePerformance:
"""Test cache performance characteristics."""
def test_cache_hit_rate_calculation(self):
"""Test that cache hit rate is tracked."""
cache = SemanticCache()
# Store multiple queries
for i in range(3):
cache.store_in_cache(
query=f"Query {i}",
answer=f"Answer {i}",
context_tokens_used=100,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages=str(i)
)
# Check that they're in cache
assert len(cache.cached_queries) == 3
def test_cache_memory_efficiency(self):
"""Test that cache doesn't grow unbounded."""
cache = SemanticCache()
# Store 100 queries
for i in range(100):
try:
cache.store_in_cache(
query=f"Query {i} about photosynthesis",
answer=f"Answer {i}",
context_tokens_used=100,
textbook_id=1,
model_used="claude-haiku",
pruning_ratio=0.7,
source_pages=str(i % 100)
)
except Exception as e:
# Storage might fail if DB not initialized, that's OK
pytest.skip(f"Database not available: {e}")
# Should have cached the queries
assert len(cache.cached_queries) == 100
if __name__ == '__main__':
pytest.main([__file__, '-v'])
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