Redis Spring Boot Recipes is a comprehensive collection of practical examples and patterns demonstrating how to leverage Redis with Spring Boot for various common application needs. This repository serves as a reference implementation for developers looking to integrate Redis into their Spring Boot applications.
This repository contains several modules demonstrating different Redis capabilities with Spring Boot:
| Module | Description | Link |
|---|---|---|
| Agent Memory with Spring AI | Demonstrates how to implement AI agent memory using Redis and Spring AI | agent-memory-with-spring-ai |
| RAG with Spring AI | Shows how to implement Retrieval-Augmented Generation (RAG) using Redis and Spring AI | rag-with-spring-ai |
| Semantic Caching with Spring AI | Illustrates how to implement semantic caching for LLM responses using Redis and Spring AI | semantic-caching-with-spring-ai |
| Vector Search with Redis OM Spring | Shows how to implement vector similarity search using Redis OM Spring | vector-search |
| Vector Search with Spring AI | Illustrates how to implement vector similarity search using Spring AI and Redis | vector-search-spring-ai |
| Module | Description | Link |
|---|---|---|
| Full-Text Search and Autocomplete with Redis OM Spring | Demonstrates how to implement full-text search and autocomplete using Redis OM Spring | full-text-search-and-autocomplete |
| Vector Search with Redis OM Spring | Shows how to implement vector similarity search using Redis OM Spring | vector-search |
| Vector Search with Spring AI | Illustrates how to implement vector similarity search using Spring AI and Redis | vector-search-spring-ai |
| Module | Description | Link |
|---|---|---|
| Distributed Session Management | Demonstrates how to implement distributed session management in Spring Boot using Redis | distributed-session-management |
Each module contains one or more complete Spring Boot applications that demonstrate the respective Redis capabilities.
Each recipe is contained in its own directory with specific instructions on how to run and use the example.
Contributions are welcome! If you have a recipe or improvement you'd like to share, please feel free to submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.