Pydantic 模型

使用 PydanticAI 从文本输入构建 Pydantic 模型的简单示例。

演示了

• 结构化的 result_type

运行示例

在安装依赖项并设置环境变量后，运行

pipuv

python -m pydantic_ai_examples.pydantic_model

uv run -m pydantic_ai_examples.pydantic_model

此示例默认使用 openai:gpt-4o，但它也适用于其他模型，例如，您可以使用 Gemini 运行它，通过

pipuv

PYDANTIC_AI_MODEL=gemini-1.5-pro python -m pydantic_ai_examples.pydantic_model

PYDANTIC_AI_MODEL=gemini-1.5-pro uv run -m pydantic_ai_examples.pydantic_model

(或 PYDANTIC_AI_MODEL=gemini-1.5-flash ...)

示例代码

pydantic_model.py

import os
from typing import cast

import logfire
from pydantic import BaseModel

from pydantic_ai import Agent
from pydantic_ai.models import KnownModelName

# 'if-token-present' means nothing will be sent (and the example will work) if you don't have logfire configured
logfire.configure(send_to_logfire='if-token-present')


class MyModel(BaseModel):
    city: str
    country: str


model = cast(KnownModelName, os.getenv('PYDANTIC_AI_MODEL', 'openai:gpt-4o'))
print(f'Using model: {model}')
agent = Agent(model, result_type=MyModel, instrument=True)

if __name__ == '__main__':
    result = agent.run_sync('The windy city in the US of A.')
    print(result.data)
    print(result.usage())