Description
LLMs can be unpredictable, fragile, and tricky to scale responsibly. In this talk, you’ll learn how to use Pydantic to transform that chaos into clean, typed, validated Python objects you can safely rely on in production.Based on our own real world experience with it, we'll explore how to define schemas, coerce LLM output into those schemas, and add guardrails through validation and structured prompting.
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