structured output

A structured output is a model response that adheres to a predefined format, such as a JSON Schema or formal grammar, so that programs can reliably parse and use the results.

This is achieved by constraining generation during decoding, allowing the model to emit only tokens that maintain validity under the target structure.

Structured outputs enhance robustness and reliability for tasks like information extraction, classification, and tool use, compared with free text generation. However, they still require careful schema design, semantic validation, and runtime checks in production systems to ensure correctness beyond syntactic structure.

Related Resources

Tutorial

Pydantic AI: Build Type-Safe LLM Agents in Python

Learn how to use Pydantic AI to build type-safe LLM agents in Python with structured outputs, function calling, and dependency injection patterns.

intermediate ai

For additional information on related topics, take a look at the following resources:

• Building Type-Safe LLM Agents With Pydantic AI (Course)
• Leverage OpenAI's API in Your Python Projects (Course)
• Pydantic AI: Build Type-Safe LLM Agents in Python (Quiz)