Structured output

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models/chat/strucured-output/.gitattributes

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+*.cmd text eol=crlf

models/chat/strucured-output/.gitignore

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+HELP.md
+target/
+!.mvn/wrapper/maven-wrapper.jar
+!**/src/main/**/target/
+!**/src/test/**/target/
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+### STS ###
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models/chat/strucured-output/.mvn/wrapper/maven-wrapper.properties

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models/chat/strucured-output/README.md

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+# Spring AI Structured Output Demo
+
+Transform AI responses into type-safe Java objects effortlessly with Spring AI's structured output capabilities. This project demonstrates how to convert natural language responses from Large Language Models (LLMs) into strongly-typed Java objects without writing complex parsing logic.
+
+## Why Structured Output Matters
+
+Working with AI models typically means dealing with unstructured text responses. Converting these responses into usable data structures traditionally requires:
+
+- Writing custom parsing logic
+- Handling edge cases and malformed responses
+- Maintaining complex regex patterns or string manipulation code
+- Implementing error handling for parsing failures
+
+Spring AI eliminates these challenges by providing built-in conversion capabilities that transform AI responses directly into Java objects. This project showcases this functionality through a practical example: converting information about technical authors into structured data.
+
+## Project Overview
+
+This application demonstrates structured output conversion by:
+1. Taking user input for a technical author's name
+2. Querying an AI model for information about the author
+3. Automatically converting the response into a strongly-typed `AuthorInfo` object
+4. Displaying the structured information to the user
+
+## Requirements
+
+- Java 17 or higher
+- OpenAI API key
+- Spring Boot 3.2 or higher
+- Spring AI dependencies
+
+## Project Structure
+
+```
+src/
+├── main/
+│   ├── java/
+│   │   └── io/spring/examples/
+│   │       ├── Application.java       # Main application class
+│   │       └── AuthorInfo.java       # Data structure for author information
+│   └── resources/
+│       └── application.properties    # Configuration properties
+```
+
+## Key Features
+
+### Structured Data Model
+
+The `AuthorInfo` record defines our structured output format:
+
+```java
+public record AuthorInfo(
+    String name,
+    String primaryGenre,
+    List<String> notableBooks,
+    int yearsActive,
+    String specialization
+) {}
+```
+
+### Automatic Conversion
+
+Spring AI handles the conversion from AI response to Java object automatically:
+
+```java
+var authorInfo = chat.prompt()
+    .user(u -> {
+        u.text("Please give me information about ${author}");
+        u.param("author", authorName);
+    })
+    .call()
+    .entity(AuthorInfo.class);  // Automatic conversion to AuthorInfo
+```
+
+## Getting Started
+
+1. Set your OpenAI API key:
+   ```bash
+   export OPENAI_API_KEY=your-api-key-here
+   ```
+
+2. Run the application:
+   ```bash
+   ./mvnw spring-boot:run
+   ```
+
+3. Enter author names when prompted:
+   ```
+   Who is your favorite technical author? (e.g., 'Rod Johnson', or type 'exit' to quit)
+   USER: Rod Johnson
+   ```
+
+## Response Format
+
+The application displays structured information about the author:
+
+```
+=== Author Analysis ===
+Name: Rod Johnson
+Primary Genre: Technical Writing
+Notable Books: Expert One-on-One J2EE Design and Development, Expert One-on-One J2EE Development without EJB
+Years Active: 20
+Specialization: Enterprise Java Development and Spring Framework
+```
+
+## Technical Details
+
+### Configuration
+
+The application uses Spring Boot's configuration properties:
+
+```properties
+spring.application.name=structured-output
+spring.ai.openai.api-key=${OPENAI_API_KEY}
+spring.ai.openai.chat.options.model=gpt-4
+```
+
+### Error Handling
+
+Spring AI's structured output converter handles various edge cases:
+- Malformed AI responses
+- Missing fields in the response
+- Type conversion errors
+
+## Benefits of Using Spring AI's Structured Output
+
+1. **Type Safety**: Get compile-time checking for your AI response structures
+2. **Clean Code**: Eliminate boilerplate parsing code
+3. **Reliability**: Robust handling of edge cases and malformed responses
+4. **Maintainability**: Changes to response structure only require updating the data model
+5. **Integration**: Seamless integration with Spring's ecosystem
+
+## Learn More
+
+For more information about Spring AI and structured output conversion, visit:
+- [Spring AI Documentation](https://docs.spring.io/spring-ai/reference/)
+- [Spring AI GitHub Repository](https://github.com/spring-projects/spring-ai)
+
+---
+
+Built with ❤️ using Spring AI