Notebooks collection
This collection showcases how Redis can be integrated into AI workflows to enhance performance, reduce latency, and enable real-time AI applications. Each notebook comes with complete code examples, explanations, and integration guides.
| Notebook | Category | Description | |
|---|---|---|---|
| The place to start if you are brand new to Redis | Introduction | Great for Redis beginners looking for a guided Colab experience. | Open in Colab |
| Implementing hybrid search with Redis | Hybrid and Vector Search | Combines vector similarity with keyword filters. | Open in Colab |
| Vector search with Redis Python client | Hybrid and Vector Search | Demonstrates pure vector search using the Redis Python client. | Open in Colab |
| Vector search with Redis Vector Library | Hybrid and Vector Search | Uses RedisVL for advanced vector indexing and querying. | Open in Colab |
| Shows how to convert a float32 index to float16 or integer data types | Hybrid and Vector Search | Demonstrates data type optimization for vector indices. | Open in Colab |
| RAG from scratch with Redis Vector Library | RAG | Basic RAG implementation using RedisVL. | Open in Colab |
| RAG using Redis and LangChain | RAG | Shows integration between Redis and LangChain for RAG. | Open in Colab |
| RAG using Redis and LlamaIndex | RAG | Walkthrough of RAG with Redis and LlamaIndex. | Open in Colab |
| Advanced RAG with RedisVL | RAG | Advanced concepts and techniques using RedisVL. | Open in Colab |
| RAG using Redis and Nvidia | RAG | NVIDIA + Redis for LLM context retrieval. | Open in Colab |
| Utilize RAGAS framework to evaluate RAG performance | RAG | Evaluation of RAG apps using the RAGAS framework. | Open in Colab |
| Implement a simple RBAC policy with vector search using Redis | RAG | Role-based access control implementation for RAG systems. | Open in Colab |
| LangGraph and agents | Agents | Getting started with agent workflows. | Open in Colab |
| Movie recommendation system | Agents | Collaborative agent-based movie recommender. | Open in Colab |
| Full-Featured Agent Architecture | Agents | Comprehensive agent implementation with advanced features. | Open in Colab |
| Optimize semantic cache threshold with RedisVL | Semantic Cache | Performance optimization for semantic caching systems. | Open in Colab |
| Simple examples of how to build an allow/block list router in addition to a multi-topic router | Semantic Router | Basic routing patterns and access control mechanisms. | Open in Colab |
Use RouterThresholdOptimizer from RedisVL to setup best router config |
Semantic Router | Router configuration optimization using RedisVL. | Open in Colab |
| Facial recognition | Computer Vision | Face matching using Facenet and RedisVL. | Open in Colab |
| Content filtering with RedisVL | Recommendation Systems | Introduction to content-based filtering. | Open in Colab |
| Collaborative filtering with RedisVL | Recommendation Systems | Intro to collaborative filtering with RedisVL. | Open in Colab |
| Intro deep learning two tower example with RedisVL | Recommendation Systems | Deep learning approach to recommendation systems. | Open in Colab |
| Credit scoring system using Feast with Redis as the online store | Feature Store | Feature store implementation for ML model serving. | Open in Colab |
Additional resources
Looking for more ways to learn about Redis for AI? Check out our:
- AI video collection - Video tutorials and demonstrations covering Redis AI concepts
- Ecosystem integrations - Learn how Redis works with popular AI frameworks and tools