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Title: Redis AI notebooks collection
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alwaysopen: false
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categories:
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- docs
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- operate
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- rs
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- rc
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description: 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.
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linkTitle: AI notebooks collection
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weight: 40
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---
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| Notebook | Category | Description | |
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|----------|----------|-------------|--|
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| The place to start if you are brand new to Redis | Introduction | Great for Redis beginners looking for a guided Colab experience. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/redis-intro/00_redis_intro.ipynb) |
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| Implementing hybrid search with Redis | Hybrid and Vector Search | Combines vector similarity with keyword filters. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/02_hybrid_search.ipynb) |
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| Vector search with Redis Python client | Hybrid and Vector Search | Demonstrates pure vector search using the Redis Python client. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) |
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| Vector search with Redis Vector Library | Hybrid and Vector Search | Uses RedisVL for advanced vector indexing and querying. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/01_redisvl.ipynb) |
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| RAG from scratch with Redis Vector Library | RAG | Basic RAG implementation using RedisVL. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/01_redisvl.ipynb) |
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| RAG using Redis and LangChain | RAG | Shows integration between Redis and LangChain for RAG. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/02_langchain.ipynb) |
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| RAG using Redis and LlamaIndex | RAG | Walkthrough of RAG with Redis and LlamaIndex. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/03_llamaindex.ipynb) |
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| Advanced RAG with redisvl | RAG | Advanced concepts and techniques using RedisVL. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) |
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| RAG using Redis and Nvidia | RAG | NVIDIA + Redis for LLM context retrieval. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/05_nvidia_ai_rag_redis.ipynb) |
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| Utilize RAGAS framework to evaluate RAG performance | RAG | Evaluation of RAG apps using the RAGAS framework. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/06_ragas_evaluation.ipynb) |
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| Vector search with Azure | RAG | Example with Azure Cache for Redis. | [<button>Get Started</button>](https://techcommunity.microsoft.com/blog/azuredevcommunityblog/vector-similarity-search-with-azure-cache-for-redis-enterprise/3822059) |
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| RAG with Spring AI | RAG | Blog article on integrating Redis with Spring AI. | [<button>Get Started</button>](https://redis.io/blog/building-a-rag-application-with-redis-and-spring-ai/) |
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| RAG with Vertex AI | RAG | Guide to use Redis in GCP stack with Vertex AI. | [<button>Get Started</button>](https://github.com/redis-developer/gcp-redis-llm-stack/tree/main) |
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| LangGraph and agents | Agents | Getting started with agent workflows. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/00_langgraph_redis_agentic_rag.ipynb) |
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| Movie recommendation system | Agents | Collaborative agent-based movie recommender. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/01_crewai_langgraph_redis.ipynb) |
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| LLM session manager with semantic similarity | LLM Memory | Tracks conversation sessions using Redis and similarity. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/00_llm_session_manager.ipynb) |
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| Multiple simultaneous chat sessions | LLM Memory | Supports handling multiple chat threads. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/01_multiple_sessions.ipynb) |
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| Semantic cache with Llama3.1 | Semantic Caching | Uses Doc2Cache framework with Llama3.1. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/doc2cache_llama3_1.ipynb) |
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| Semantic cache with Gemini | Semantic Caching | Gemini-based semantic caching demo. | [<button>Get Started</button>](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/semantic_caching_gemini.ipynb) |
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| Facial recognition | Computer Vision | Face matching using Facenet and RedisVL. | [<button>Get Started</button>](https://github.com/redis-developer/redis-ai-resources/blob/main/python-recipes/computer-vision/00_facial_recognition_facenet.ipynb) |
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| Content filtering with redisvl | Recommendation Systems | Introduction to content-based filtering. | [<button>Get Started</button>](https://github.com/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/00_content_filtering.ipynb) |
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| Collaborative filtering with redisvl | Recommendation Systems | Intro to collaborative filtering with RedisVL. | [<button>Get Started</button>](https://github.com/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/01_collaborative_filtering.ipynb) |
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| Advanced RAG example | Best Practices | Demonstrates mature RAG implementation patterns. | [<button>Get Started</button>](https://github.com/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) |
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