Redis AI 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.

NotebookCategoryDescription
The place to start if you are brand new to RedisIntroductionGreat for Redis beginners looking for a guided Colab experience.Open in Colab
Implementing hybrid search with RedisHybrid and Vector SearchCombines vector similarity with keyword filters.Open in Colab
Vector search with Redis Python clientHybrid and Vector SearchDemonstrates pure vector search using the Redis Python client.Open in Colab
Vector search with Redis Vector LibraryHybrid and Vector SearchUses RedisVL for advanced vector indexing and querying.Open in Colab
RAG from scratch with Redis Vector LibraryRAGBasic RAG implementation using RedisVL.Open in Colab
RAG using Redis and LangChainRAGShows integration between Redis and LangChain for RAG.Open in Colab
RAG using Redis and LlamaIndexRAGWalkthrough of RAG with Redis and LlamaIndex.Open in Colab
Advanced RAG with RedisVLRAGAdvanced concepts and techniques using RedisVL.Open in Colab
RAG using Redis and NvidiaRAGNVIDIA + Redis for LLM context retrieval.Open in Colab
Utilize RAGAS framework to evaluate RAG performanceRAGEvaluation of RAG apps using the RAGAS framework.Open in Colab
LangGraph and agentsAgentsGetting started with agent workflows.Open in Colab
Movie recommendation systemAgentsCollaborative agent-based movie recommender.Open in Colab
Facial recognitionComputer VisionFace matching using Facenet and RedisVL.Open in Colab
Content filtering with RedisVLRecommendation SystemsIntroduction to content-based filtering.Open in Colab
Collaborative filtering with RedisVLRecommendation SystemsIntro to collaborative filtering with RedisVL.Open in Colab
Advanced RAG exampleBest PracticesDemonstrates mature RAG implementation patterns.Open in Colab

Additional resources

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