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

# Agent with Structured Outputs

> Get structured Pydantic output from an AWS Claude agent.

## Code

```python structured_output.py theme={null}
from typing import List

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

class MovieScript(BaseModel):
    setting: str = Field(
        ..., description="Provide a nice setting for a blockbuster movie."
    )
    ending: str = Field(
        ...,
        description="Ending of the movie. If not available, provide a happy ending.",
    )
    genre: str = Field(
        ...,
        description="Genre of the movie. If not available, select action, thriller or romantic comedy.",
    )
    name: str = Field(..., description="Give a name to this movie")
    characters: List[str] = Field(..., description="Name of characters for this movie.")
    storyline: str = Field(
        ..., description="3 sentence storyline for the movie. Make it exciting!"
    )

movie_agent = Agent(
    model=Claude(id="global.anthropic.claude-sonnet-4-5-20250929-v1:0"),
    description="You help people write movie scripts.",
    output_schema=MovieScript,
)

# Get the response in a variable
# run_response: RunOutput = movie_agent.run("New York")
# pprint(run_response.content)

movie_agent.print_response("New York")
```

## Usage

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

**1. Set your AWS Credentials**

```bash theme={null}
export AWS_ACCESS_KEY_ID=***
export AWS_SECRET_ACCESS_KEY=***
export AWS_REGION=***
```

**2. Install dependencies**

```bash theme={null}
uv pip install -U 'anthropic[bedrock]' agno
```

**3. Run Agent**

```bash theme={null}
python structured_output.py
```


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