Async
Structured Outputs
Examples
- Introduction
- Getting Started
- Agents
- Workflows
- Applications
Agent Concepts
- Multimodal
- RAG
- Knowledge
- Memory
- Teams
- Async
- Hybrid Search
- Storage
- Tools
- Vector Databases
- Embedders
Models
- Anthropic
- AWS Bedrock Claude
- Azure OpenAI
- Cohere
- DeepSeek
- Fireworks
- Gemini
- Groq
- Hugging Face
- Mistral
- NVIDIA
- Ollama
- OpenAI
- Together
- Vertex AI
- xAI
Async
Structured Outputs
Code
cookbook/agent_concepts/async/structured_output.py
import asyncio
from typing import List
from agno.agent import Agent, RunResponse # noqa
from agno.models.openai import OpenAIChat
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
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
json_mode_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
description="You write movie scripts.",
response_model=MovieScript,
)
# Agent that uses structured outputs
structured_output_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"),
description="You write movie scripts.",
response_model=MovieScript,
structured_outputs=True,
)
asyncio.run(json_mode_agent.aprint_response("New York"))
asyncio.run(structured_output_agent.aprint_response("New York"))
Usage
1
Create a virtual environment
Open the Terminal
and create a python virtual environment.
2
Install libraries
pip install -U openai agno
3
Run Agent