Spring Ai In Action Pdf Github -

Getting started with Spring AI, submitting prompts, and evaluating generated responses.

Which you intend to use (OpenAI, Anthropic, Ollama, etc.)?

Search for repositories featuring Docker Compose setups ( docker-compose.yml ) containing PostgreSQL with pgvector , Ollama, and LocalStack. This ensures you can run local end-to-end RAG workflows without spending money on cloud API tokens.

The "Spring AI in Action" PDF and GitHub repository cover the following key features: spring ai in action pdf github

The best GitHub repos reveal advanced tricks you won't find in the introductory PDFs.

: Early readers have awarded it a 5.0 out of 5 stars rating, citing it as the "perfect book" for bridging the gap between Java and AI engineering. GitHub & PDF Resources Spring AI in Action - Craig Walls - Manning Publications

public record MovieReview(String title, String director, int rating, String summary) {} @GetMapping("/review") public MovieReview getStructuredReview(@RequestParam String movieName) return this.chatClient.prompt() .user("Give me a review of the movie: " + movieName) .call() .entity(MovieReview.class); // Automatically maps JSON string to Java Record Use code with caution. 4. Advanced RAG (Retrieval-Augmented Generation) Getting started with Spring AI, submitting prompts, and

The author maintains two main repositories for the book's example code:

Configure your API keys and default models in src/main/resources/application.properties : properties

: Submitting prompts, using prompt templates, and managing response metadata. This ensures you can run local end-to-end RAG

@GetMapping("/rag/ask") public String askPrivateData(@RequestParam String question) // Search vector store for documents similar to the user's question List similarDocuments = this.vectorStore.similaritySearch( SearchRequest.query(question).withTopK(3) ); // Extract contents from documents String contentContext = similarDocuments.stream() .map(Document::getContent) .collect(Collectors.joining(System.lineSeparator())); // Execute prompt containing context and original question return this.chatClient.prompt() .system("Use the following context to answer the user question. If you do not know, say 'I do not know'.") .user(u -> u.text("Context: context \n Question: question") .param("context", contentContext) .param("question", question)) .call() .content(); Use code with caution. 5. Harnessing AI Functions (Tool Calling)

To maximize your learning from the repository: Clone the Repo: Clone habuma/spring-ai-in-action-samples.

The ChatModel interface is the central abstraction for interacting with text-based LLMs. It handles the request-response lifecycle, streaming responses, and configuration overrides. 2. Prompts and Prompt Templates

Quick starter checklist