Fireworks Structured Output

This example uses a Llama 3.1 405B model that requires an on-demand deployment. Replace it with the serverless accounts/fireworks/models/gpt-oss-120b model before running. See Fireworks GPT OSS 120B.

structured_output.py

"""
Fireworks Structured Output
===========================

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

from typing import List

from agno.agent import Agent, RunOutput  # noqa
from agno.models.fireworks import Fireworks
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 JSON mode
agent = Agent(
    model=Fireworks(id="accounts/fireworks/models/llama-v3p1-405b-instruct"),
    description="You write movie scripts.",
    output_schema=MovieScript,
)

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

# agent.print_response("New York")

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

if __name__ == "__main__":
    pass

The current Fireworks adapter sends a JSON Schema request for this source, despite its historical JSON-mode comment. Apply the model substitution below and use a model that supports the requested format.

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.

Run the Example

Set up your virtual environment

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

Install dependencies

uv pip install -U agno openai

Export your Fireworks API key

export FIREWORKS_API_KEY="your_fireworks_api_key_here"

Use the current Fireworks model

Replace accounts/fireworks/models/llama-v3p1-405b-instruct with accounts/fireworks/models/gpt-oss-120b in the saved file.

Run the example

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

python structured_output.py

Full source: cookbook/90_models/fireworks/structured_output.py