Pydantic AI
Leverage Pydantic to build reliable, predictable AI agents with type-safe development. Define structured outputs and robust tool calling schemas to ensure data integrity and reduce runtime errors in complex AI applications.
3 Steps
- 1
Install Pydantic: Ensure Pydantic is installed in your Python environment to begin defining structured data.
- 2
Define Agent Output Structure: Use Pydantic `BaseModel` to define the expected structure for your agent's decisions or outputs. This ensures predictable and parsable responses from the agent.
- 3
Define Tool Input Schemas: For each external tool or API your agent can interact with, define a Pydantic `BaseModel` to represent its input parameters. This guarantees that tool arguments are correctly typed and validated before execution.
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