Ollama Structured Output
Request JSON and validate a MovieScript with Pydantic through the native local Ollama API.
The native API receives the Pydantic schema in format. Agno validates the returned content locally.
"""
Ollama Structured Output
========================
Cookbook example for `ollama/chat/structured_output.py`.
"""
from typing import List
from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
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."
)
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.",
)
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 returns a structured output
structured_output_agent = Agent(
model=Ollama(id="llama3.2"),
description="You write movie scripts.",
output_schema=MovieScript,
)
# Get the response in a variable
# json_mode_response: RunOutput = json_mode_agent.run("New York")
# pprint(json_mode_response.content)
# structured_output_response: RunOutput = structured_output_agent.run("New York")
# pprint(structured_output_response.content)
# Run the agent
structured_output_agent.print_response("New York")
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
passoutput_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.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno ollamaSelect the local Ollama server
In the shell used for the pull commands and Python example, clear a previous cloud key and point native clients and embeddings at your local server:
unset OLLAMA_API_KEY
export OLLAMA_HOST="http://localhost:11434"Without this reset, OLLAMA_API_KEY makes Agno's default Ollama model route to https://ollama.com even when OLLAMA_HOST points locally. Keep a local Ollama server running for the following steps.
Prepare Ollama
Install and start Ollama, then pull the model used by this example:
ollama pull llama3.2Run the example
Save the code above as structured_output.py, then run:
python structured_output.pyFull source: cookbook/90_models/ollama/chat/structured_output.py