> ## Documentation Index
> Fetch the complete documentation index at: https://ikun.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 结构化输出

## 代码

```python cookbook/agent_concepts/async/structured_output.py theme={null}
import asyncio
from typing import List

from agno.agent import Agent, RunResponse  # noqa
from agno.models.openai import OpenAIChat
from pydantic import BaseModel, Field
from rich.pretty import pprint  # noqa


class MovieScript(BaseModel):
    setting: str = Field(
        ..., description="为一部大片提供一个不错的场景。"
    )
    ending: str = Field(
        ...,
        description="电影的结局。如果不可用，请提供一个大团圆结局。",
    )
    genre: str = Field(
        ...,
        description="电影的类型。如果不可用，请选择动作、惊悚或浪漫喜剧。",
    )
    name: str = Field(..., description="为这部电影起一个名字")
    characters: List[str] = Field(..., description="这部电影的角色名字。")
    storyline: str = Field(
        ..., description="电影的 3 句故事情节。要激动人心！"
    )


# 使用 JSON 模式的 Agent
json_mode_agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    description="你写电影剧本。",
    response_model=MovieScript,
)

# 使用结构化输出的 Agent
structured_output_agent = Agent(
    model=OpenAIChat(id="gpt-4o-2024-08-06"),
    description="你写电影剧本。",
    response_model=MovieScript,
)


asyncio.run(json_mode_agent.aprint_response("New York"))
asyncio.run(structured_output_agent.aprint_response("New York"))
```

## 用法

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="安装库">
    ```bash theme={null}
    pip install -U openai agno
    ```
  </Step>

  <Step title="运行 Agent">
    <CodeGroup>
      ```bash Mac theme={null}
      python cookbook/agent_concepts/async/structured_output.py
      ```

      ```bash Windows theme={null}
      python cookbook/agent_concepts/async/structured_output.py
      ```
    </CodeGroup>
  </Step>
</Steps>