redis-vl-python and RedisVectorXperience
RedisVL is a foundational Python client library that enables vector operations in Redis, while RedisVectorXperience is a demonstration application built on top of Redis capabilities to showcase advanced use cases like semantic caching and RAG—making them complements where the latter depends on capabilities provided by the former or similar Redis vector libraries.
About redis-vl-python
redis/redis-vl-python
Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.
Built on Redis's native vector search, it supports hybrid search combining vector similarity with full-text and complex metadata filtering, while integrating with 8+ embedding providers and reranking frameworks for production RAG pipelines and agentic AI systems. The architecture emphasizes schema-driven index management with YAML/Python configuration, async-first operations for scalability, and semantic caching/routing to optimize LLM interactions. Designed for deployment flexibility across Redis Cloud, Enterprise, Sentinel, and Azure with CLI utilities and vectorizer abstractions that abstract embedding model providers.
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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