> ## 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.

# Image to Structured Output

> Analyze an image and stream a structured `MovieScript` response with `output_schema`.

Analyze an image and return structured output with Pydantic models. Here the agent writes a movie script based on the image content.

## Code

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

from agno.agent import Agent
from agno.media import Image
from agno.models.openai import OpenAIResponses
from pydantic import BaseModel, Field
from rich.pretty import pprint


class MovieScript(BaseModel):
    name: str = Field(..., description="Give a name to this movie")
    setting: str = Field(
        ..., description="Provide a nice setting for a blockbuster 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 = Agent(model=OpenAIResponses(id="gpt-5.2"), output_schema=MovieScript)

response = agent.run(
    "Write a movie about this image",
    images=[
        Image(
            url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
        )
    ],
    stream=True,
)

for event in response:
    pprint(event.content)
```

## Usage

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

**1. Install dependencies**

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

**2. Export your OpenAI API key**

```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"
```

**3. Run Agent**

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


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