🤖 LangChain4j ChatModel: Structured Output

This repository demonstrates how to reliably get JSON responses from LLMs using LangChain4j ChatModel Structured Output, enforce strict JSON schemas, and safely handle AI responses in production systems.

📖 Complete Guide: For detailed explanations and a full code walkthrough, read our comprehensive tutorial.
👉 LangChain4j ChatModel Structured Output

🎥 Video Tutorial: Prefer hands-on learning? Watch our step-by-step implementation guide.
👉 YouTube Tutorial - LangChain4j Structured Output: Stop Getting Broken JSON from AI Models!

▶️ Watch on YouTube

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✨ What This Project Demonstrates

This application serves as a deep dive into Structured Outputs, covering different strategies to extract data:

• Text Fallback - Handling scenarios where models do not support structured output natively.
• Generic JSON Mode - Getting loose JSON data without a pre-defined schema.
• Strict Schema Enforcement - Using JSON Schema to force the model to adhere to shared structure.
• Raw JSON Schemas - Generating structured output by passing raw JSON Schema strings directly to the model.

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🛠️ Prerequisites

To run this application, you will need the following:

1. OpenRouter API Key: This project uses OpenRouter to access free AI models (DeepSeek, Llama, etc.) via OpenAI-compatible endpoints.
   • Sign up at OpenRouter.ai to generate your key.
2. Setup Environment Variables: Set your API key as an environment variable:

# Set your OpenRouter API Key
export OPENROUTER_API_KEY=your_api_key_here

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🚀 How to Run and Test

For detailed instructions on how to set up, configure, and test the application, kindly go through our comprehensive article:
👉 Click here for Setup & Testing Instructions

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