Add TOON (Token-Oriented Object Notation) Support

Expected Behavior

Spring AI should support the TOON format as a serialization option when sending structured data to LLM models.

Example usage:

ExampleObject exampleObject = new ExampleObject();

String response = chatClient.prompt()
    .mapper(toonMapper) // <-- the TOON mapper bean
    .user(exampleObject)
    .call()
    .content();

This would allow applications to use TOON instead of JSON/YAML for model inputs, improving efficiency and reducing token count.

Current Behavior

Spring AI currently supports JSON and YAML (via built-in or user-provided serializers), but there’s no native TOON support.
Developers must manually serialize/deserialize TOON data and integrate it into prompts or function-calling logic.

Context

• TOON (Token-Oriented Object Notation) is a compact, token-efficient format designed for LLM input/output.
• Article reference:
  • https://codefarm0.medium.com/toon-a-token-friendly-data-format-for-the-llm-era-with-java-code-examples-4dcafbfb03ce
  • https://blog.arun.im/toon4j-slash-your-llm-token-costs-by-50-with-this-java-library-1e16578ff9eb
• Benefits of adding TOON support:
  • Reduces token usage and improves prompt window efficiency.
  • Provides native serialization/deserialization similar to JSON/YAML.
  • Makes it easier to handle structured POJO exchanges with LLMs.
• Workarounds exist (manual TOON serialization), but a built-in module would provide first-class support aligned with Spring AI’s extensibility model.

The issue does not name files, tests, or an existing entry point; start by locating Spring AI's JSON/YAML serialization integration and prompt mapper support. Review the referenced TOON libraries and define the module boundaries and compatibility expectations before implementation. Done means applications can use native TOON serialization and deserialization for structured model inputs.