- Spring AI Basics
- Getting Started
- Prerequisites
- Spring Boot Application
- Use Model Service
- Consolidate Local and Production Environment
- Chat Completion
- Model
- ChatModel
- Create Prompts
- Chat Response
- ChatClient
- Use Custom Chat Options
- Prompt Template
- Advisor
- Streaming Chat Completion
- StreamingChatModel
- Streaming Web Application
- Streaming JSON Events
- Structured Output Converter
- StructuredOutputConverter
- ListOutputConverter
- MapOutputConverter
- BeanOutputConverter
- Use ChatClient
- Multimodal Input
- Media
- Image Understanding
- RAG Introduction
- Reduce Hallucinations
- Naive RAG
- Embedding Model
EmbeddingModel
EmbeddingOptions
BatchingStrategy
- Use
EmbeddingModel
- Documents
- Create Documents
- Document Reader
- Document Transformer
- Document Writer
- Vector Store
- VectorStore
- Create
VectorStore
- Add Documents
- Delete Documents
- Similarity Search
- VectorStore REST API
- SimpleVectorStore
- Pgvector
- Vector Store Cloud Services
- RAG
- Simple RAG
- Modular RAG
- Query
- Pre-Retrieval
- Retrieval
- Post-Retrieval
- Generation
- RetrievalAugmentationAdvisor
- RAG Examples
- Text-to-SQL
- PDF Q&A
- MCP Introduction
- Quick Start
- Java Development Basics
- stdio Server
- HTTP SSE Server
- MCP Client
- Spring Integration
- Spring AI Integration
- MCP Server
- Shared Models
- ServerExchange
- Prompt Templates
- Resources
- Tools
- Completions
- Logging
- Pagination
- MCP Client
- Roots
- Sampling
- MCP Examples
- File System MCP Server
- Agent Introduction
- Cooking Suggestion Agent
- Agent Components
- Profile
- Persona
- Tools
- Knowledge and memory
- Reasoning and evaluation
- Planning and feedback
- Agentic Patterns
- Task Execution
- Evaluator-Optimizer
- Parallelization Workflow
- Routing Workflow
- Chain Workflow
- Agent as Tool
- Tool as Agent
- Orchestrator-Workers Workflow
- Agent Development
- Persona
- Knowledge
- Tools
- Reasoning
- Task
- Getting Started
Build AI Applications with Spring AI
RAG, MCP and Agents
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Create AI applications using Spring AI, RAG, MCP and Agents
About
About the Book
Create AI applications using Spring AI
This book uses Spring AI 1.0.3.
Spring AI Basics
- Chat Completion
- Streaming Chat Completion
- Structured Output Converter
- Multimodal Input
RAG
- Vector store
- Embedding model
- Simple RAG
- Modular RAG
MCP
- Quick start
- MCP server
- MCP client
- MCP examples
Agent
- Agent Components
- Agentic Patterns and Workflow
- Build Agents
I’m also maintaining the website JavaAIDev.com. Some content will be published freely on that website. If you find the content useful, please support me by purchasing a copy of this book.
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Author
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Contents
Table of Contents
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