> ## 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.

# Neosantara Structured Output

> Generate a MovieScript with Neosantara Grok using output_schema and JSON mode.

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

Cookbook example for `neosantara/structured_output.py`.
"""

from typing import List

from agno.agent import Agent
from agno.models.neosantara import Neosantara
from pydantic import BaseModel, Field

# ---------------------------------------------------------------------------
# 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!"
    )


# Agent that uses structured outputs
agent = Agent(
    model=Neosantara(id="grok-4.1-fast-non-reasoning"),
    description="You write movie scripts. Respond ONLY with a valid JSON object matching the provided schema.",
    output_schema=MovieScript,
    use_json_mode=True,
)

# Print the response in the terminal
agent.print_response("New York")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**2. Export your Neosantara API key**

```bash Mac/Linux theme={null}
export NEOSANTARA_API_KEY="your_neosantara_api_key_here"
```

```bash Windows theme={null}
$Env:NEOSANTARA_API_KEY="your_neosantara_api_key_here"
```

**3. 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/neosantara/structured\_output.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/neosantara/structured_output.py)


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