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Pydantic AI Type-Safe Agent Loop
Build a deterministic, type-validated Python agent loop with structured BaseModel output
What it does
Standard architectural pattern for initializing an autonomous Pydantic AI agent that enforces structured validation on all model responses. Uses Python dataclasses or Pydantic BaseModels to guarantee valid output schemas, preventing hallucinated JSON structures in production pipelines.
Installation & Setup
Level: intermediate1. Install package: `pip install pydantic-ai`.
2. Define your output schema using `pydantic.BaseModel`.
3. Instantiate `Agent(model, result_type=YourSchema)`.
4. Call `result = await agent.run('Your prompt')`.
Prerequisites: Python 3.10+, LLM API provider key
Security & Privacy Notes
Open-source library under MIT. Data flows strictly between your Python runtime and your designated AI model endpoint.
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