In Pydantic AI, the StructuredDict schema acts as a structural constraint that guides LLMs to produce concrete dictionary outputs (like {'name': ..., 'age': ...}) even when prompts are vague or contain no explicit details, demonstrating how schema definitions can 'birth' structured content from emptiness by enforcing required fields and data types.
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Pydantic AI Output Type Patterns - Part 10/19Added:
From Pedantic AI import agent, structured dict.
Human dict equals structured dict.
Type, [music] object.
Properties, name, type, string.
>> [music] >> Age, type, integer.
Required, name, age.
Name equals human.
Description equals a human with a name and age.
Agent equals agent OpenAI GPT-5 [music] 2. Output type equals human dict.
Result equals agent. Run sync create a person.
Name, John Doe, age, 30.
The structured dict births a human with name and age from a prompt that knows nothing.
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