RedisVL is an AI-native Python client for Redis, designed to simplify the integration of vector search and AI capabilities into applications. It targets AI/ML engineers and data scientists building real-time RAG pipelines, agentic memory structures, and recommendation engines, enabling fast information retrieval and semantic search using Redis.

How It Works

RedisVL leverages Redis Stack's vector search capabilities, allowing users to define schemas with vector fields and metadata. It provides a Pythonic interface for creating and querying these indexes, supporting various vector algorithms and distance metrics. The library also integrates with popular vectorization services and offers extensions for LLM caching, session management, and semantic routing, all powered by Redis.

Quick Start & Requirements

• Install via pip: pip install redisvl
• Requires Python >= 3.8.
• Redis Stack (Docker recommended: docker run -d --name redis-stack -p 6379:6379 -p 8001:8001 redis/redis-stack:latest).
• Official documentation: https://redisvl.readthedocs.io/en/latest/

Highlighted Details

• Schema definition for index management using YAML or Python dictionaries.
• Flexible query capabilities including vector search, metadata filtering, and range queries.
• Built-in vectorizers for OpenAI, Cohere, HuggingFace, and more.
• Extensions for LLM semantic caching, session management, and semantic routing.
• Command-line interface (rvl) for index management.

Maintenance & Community

• Supported by Redis, Inc.
• Contribution welcome via GitHub issues and PRs.

Licensing & Compatibility

• MIT License.
• Compatible with commercial and closed-source applications.

Limitations & Caveats

• Threshold optimization utility requires Python > 3.9.