> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-docs-scavio-google-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Output Schema

> Use `output_schema` to return structured data that matches a Pydantic model.

```python output_schema.py theme={null}
"""
Output Schema
=============================

Use `output_schema` to return structured data that matches a Pydantic model.
"""

from typing import List

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


class BreakingNewsSummary(BaseModel):
    topic: str = Field(..., description="The topic or region being summarized")
    summary: str = Field(
        ..., description="A concise summary of the latest developments"
    )
    key_updates: List[str] = Field(
        ..., description="Important updates or headlines related to the topic"
    )
    overall_sentiment: str = Field(
        ..., description="Overall tone of the news coverage, such as positive or mixed"
    )


# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    description="You summarize current events into clean structured outputs.",
    output_schema=BreakingNewsSummary,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    run: RunOutput = agent.run("Latest news from France?")
    pprint(run.content)
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `output_schema.py`, then run:

    ```bash theme={null}
    python output_schema.py
    ```
  </Step>
</Steps>

Full source: [cookbook/02\_agents/02\_input\_output/output\_schema.py](https://github.com/agno-agi/agno/blob/main/cookbook/02_agents/02_input_output/output_schema.py)