Gemini
Agent with Structured Outputs
Examples
- Introduction
- Getting Started
- Agents
- Teams
- Workflows
- Applications
Agent Concepts
- Multimodal
- RAG
- Knowledge
- Memory
- Async
- Hybrid Search
- Storage
- Tools
- Vector Databases
- Embedders
Models
- Anthropic
- AWS Bedrock
- AWS Bedrock Claude
- Azure AI Foundry
- Azure OpenAI
- Cohere
- DeepInfra
- DeepSeek
- Fireworks
- Gemini
- Basic Agent
- Streaming Agent
- Agent with Structured Outputs
- Agent with Tools
- Agent with Storage
- Agent with Knowledge
- Image Agent
- Flash Thinking Agent
- Audio Input (Bytes Content)
- Audio Input (Upload the file)
- Audio Input (Local file)
- Agent with PDF Input (Local file)
- Agent with PDF Input (URL)
- Video Input (Bytes Content)
- Video Input (File Upload)
- Video Input (Local File Upload)
- Groq
- Hugging Face
- Mistral
- NVIDIA
- Ollama
- OpenAI
- Perplexity
- Together
- xAI
- IBM
- LM Studio
- LiteLLM
- LiteLLM OpenAI
Gemini
Agent with Structured Outputs
Code
cookbook/models/google/gemini/structured_output.py
from typing import List
from agno.agent import Agent, RunResponse # noqa
from agno.models.google import Gemini
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!"
)
movie_agent = Agent(
model=Gemini(id="gemini-2.0-flash-exp"),
description="You help people write movie scripts.",
response_model=MovieScript,
)
movie_agent.print_response("New York")
Usage
1
Create a virtual environment
Open the Terminal
and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2
Set your API key
export GOOGLE_API_KEY=xxx
3
Install libraries
pip install -U google-genai agno
4
Run Agent
python cookbook/models/google/gemini/structured_output.py