Agent with Structured Outputs

output_schema describes the expected type. If parsing or validation fails, result.content can remain a string. Before accessing schema fields in a run result, use isinstance(result.content, YourSchema), replacing YourSchema with the class you passed as output_schema.

MiMo uses JSON object mode. Agno adds the expected schema to the prompt and attempts local Pydantic parsing; the provider does not enforce the field structure.

Code

from typing import List

from agno.agent import Agent
from agno.models.xiaomi import MiMo
from pydantic import BaseModel, Field


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!"
    )


# The adapter sends JSON object mode; Agno supplies the schema in the prompt.
agent = Agent(
    model=MiMo(id="mimo-v2.5-pro"),
    description="You help people write movie scripts.",
    output_schema=MovieScript,
    use_json_mode=True,
)

if __name__ == "__main__":
    agent.print_response("New York")

Usage

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Set your API key

export MIMO_API_KEY=xxx

Install dependencies

uv pip install -U openai agno

Run Agent

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

python structured_output.py