RedisVL

RedisVL provides a powerful, dedicated Python client library for using Redis as a vector database. Leverage Redis's speed, reliability, and vector-based semantic search capabilities to supercharge your application.

Overview

RedisVL (Redis Vector Library) is a Python client library specifically designed for building AI applications with Redis as a vector database. It provides high-level abstractions for vector search, semantic caching, and AI-powered applications while leveraging Redis's performance and reliability.

Key Features

• Vector Search: High-performance similarity search with multiple distance metrics
• Semantic Caching: Intelligent caching for AI model responses and embeddings
• Schema Management: Declarative schema definition for vector indexes
• Multiple Vectorizers: Built-in support for OpenAI, Hugging Face, and custom embeddings
• Query Filtering: Advanced filtering capabilities for precise search results
• Real-time Updates: Live vector index updates and real-time search
• Python Integration: Native Python API with pandas and NumPy compatibility
• Production Ready: Enterprise-grade performance and reliability with Redis

Getting Started

Refer to the complete [RedisVL documentation]({{< relref "/develop/ai/redisvl/" >}}) for installation, setup, and usage examples.