> ## 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.

# Vertex AI Structured Output

> Return a typed MovieScript from Claude on Vertex AI with a Pydantic output schema.

```python structured_output.py theme={null}
"""
Vertexai Structured Output
==========================

Cookbook example for `vertexai/claude/structured_output.py`.
"""

from typing import List

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

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


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="claude-sonnet-4@20250514"),
    description="You help people write movie scripts.",
    output_schema=MovieScript,
)

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

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    # --- Sync + Streaming ---
    movie_agent.print_response("New York", stream=True)
```

## Run the Example

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

**1. Install dependencies**

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

**2. Export environment variables**

```bash Mac/Linux theme={null}
export ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
export CLOUD_ML_REGION="your_cloud_ml_region_here"
```

```bash Windows theme={null}
$Env:ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
$Env:CLOUD_ML_REGION="your_cloud_ml_region_here"
```

**3. Authenticate with Google Cloud**

Sign in with Application Default Credentials:

```bash theme={null}
gcloud auth application-default login
```

**4. Run the example**

Save the code above as `structured_output.py`, then run:

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

Full source: [cookbook/90\_models/vertexai/claude/structured\_output.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/vertexai/claude/structured_output.py)


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