RediSearch and RedisVectorXperience
One project offers a query and indexing engine for Redis (including vector similarity search) while the other provides an example of using those Redis capabilities for various AI/ML use cases like vector similarity search, semantic caching, and RAG models.
About RediSearch
RediSearch/RediSearch
A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.
Implements compressed inverted indexes for memory-efficient indexing and supports distributed clustering across Redis Enterprise for billion-scale datasets. Built as a Redis module providing a dedicated query language with BM25 ranking, phonetic matching, multi-language stemming, and geospatial/vector KNN search capabilities beyond basic secondary indexes.
About RedisVectorXperience
mar1boroman/RedisVectorXperience
Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.
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