: Contains the code as it appears in the book, built against Spring AI 1.0.3 .
spring: ai: openai: api-key: $OPENAI_API_KEY chat: options: model: gpt-4o-mini temperature: 0.7
If you browse the GitHub repo’s chapter-07 , you will find how to build a pipeline:
spring-ai-action-template/ ├── .github/workflows/ # CI/CD pipelines (Docker builds, Test suites) ├── config/ # Shared infrastructure configuration (Docker Compose) │ └── docker-compose.yml # Local Postgres with pgvector, Redis, and Ollama ├── spring-ai-core/ # Core business domain definitions, entities, interfaces ├── spring-ai-ingestion/ # Batch or streaming jobs to parse PDFs, S3 files, DB records └── spring-ai-api/ # REST Controllers, Security configurations, WebFlux streaming ├── src/main/java/ └── src/main/resources/ └── application.yml Essential Repository Checklists spring ai in action pdf github
The "Spring AI in Action" PDF guide is a comprehensive resource that showcases how to build intelligent applications using Spring AI. The guide covers the following topics:
The full digital version of the book is officially available through .
<!-- Simple Vector Store (In-Memory for testing) --> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-simple-vector-store</artifactId> </dependency> : Contains the code as it appears in
Prompts are structured inputs sent to the AI model. PromptTemplate allows you to create dynamic, reusable text structures using placeholders, similar to view resolution engines like Thymeleaf. EmbeddingModel
habuma/spring-ai-in-action-examples , which features code updated for Spring AI 1.1.0+. How to use the GitHub repo: Clone the Repository: git clone https://github.com
The simplest possible interaction with an AI model in Spring AI is to use the ChatClient . Here’s a basic example: How to use the GitHub repo: Clone the
spring: ai: openai: api-key: $OPENAI_API_KEY chat: options: model: gpt-4o temperature: 0.3 datasource: url: jdbc:postgresql://localhost:5432/ai_db username: postgres password: password Use code with caution. Step 3: The Document Ingestion and Query Service
In a typical "In Action" chapter, we start with a simple synchronous call. However, real-world AI apps need streaming.