> ## 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.

# AI Foundry Structured Output

> Use Azure OpenAI for supported Pydantic structured output because the v2.7.2 Azure AI Foundry source fails before sending a request.

Use Azure OpenAI for the supported Pydantic structured-output pattern. The v2.7.2 Azure AI Foundry source below fails before sending a request.

<Warning>
  Agno v2.7.2's `AzureAIFoundry.get_request_params()` constructs `response_format` as a tuple, so both agents fail before sending a request. The adapter also depends on Microsoft's retired `azure-ai-inference` SDK. Do not run this source as written.
</Warning>

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

Cookbook example for `azure/ai_foundry/structured_output.py`.
"""

from typing import List

from agno.agent import Agent, RunOutput  # noqa
from agno.models.azure import AzureAIFoundry
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!"
    )


# Agent that uses structured outputs with strict_output=True (default)
structured_output_agent = Agent(
    model=AzureAIFoundry(id="gpt-4o"),
    description="You write movie scripts.",
    output_schema=MovieScript,
)

# Agent with strict_output=False (guided mode)
# strict_output=False: Attempts to follow the schema as a guide but may occasionally deviate
guided_output_agent = Agent(
    model=AzureAIFoundry(id="gpt-4o", strict_output=False),
    description="You write movie scripts.",
    output_schema=MovieScript,
)

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

structured_output_agent.print_response("New York")
guided_output_agent.print_response("New York")

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

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

## Current Alternative

Use [Azure OpenAI Structured Output](/models/providers/cloud/azure-openai/usage/structured-output) for a supported Pydantic output-schema example.

Full source: [cookbook/90\_models/azure/ai\_foundry/structured\_output.py](https://github.com/agno-agi/agno/blob/main/cookbook/90_models/azure/ai_foundry/structured_output.py)