feat(redis): Add Redis semantic cache advisor #5072
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…, and HNSW tuning Add new capabilities to Redis Vector Store: - Text search with searchByText() method and configurable scoring algorithms - Range-based vector search with searchByRange() method - Support for multiple distance metrics (COSINE, L2, IP) - Configurable HNSW parameters (M, efConstruction, efRuntime) - Document count queries with count() method - Module-level checkstyle configuration Update Redis documentation with comprehensive coverage of new features including configuration properties, usage examples, and parameter guidelines. Co-authored-by: Brian Sam-Bodden <brian@redis.com> Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
- Add SemanticCacheAdvisor for intelligent response caching - Add DefaultSemanticCache implementation using RedisVectorStore - Add SemanticCache interface for cache abstraction - Add Spring Boot auto-configuration for semantic cache - Include integration tests Note: Checkstyle temporarily skipped - style cleanup needed Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
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Summary
SemanticCacheAdvisorfor intelligent response caching based on semantic similarityDefaultSemanticCacheimplementation usingRedisVectorStoreSemanticCacheinterface for cache abstractionDetails
This PR adds semantic caching capabilities for Spring AI chat responses using Redis Stack's vector search. The implementation provides:
Modules Added
vector-stores/spring-ai-redis-semantic-cache/- Core implementationauto-configurations/vector-stores/spring-ai-autoconfigure-vector-store-redis-semantic-cache/- Auto-configurationTest Plan
Notes
Related