Agent with Structured Output

Get typed Pydantic responses instead of free-form text.

Use output_schema to get structured, typed responses you can trust. The agent returns a Pydantic model instead of free-form text.

1. Create a Python file

   structured_output.py

   from typing import List, Optional
   
   from agno.agent import Agent
   from agno.models.openai import OpenAIResponses
   from agno.tools.yfinance import YFinanceTools
   from pydantic import BaseModel, Field
   
   
   class StockAnalysis(BaseModel):
       ticker: str = Field(..., description="Stock ticker symbol")
       company_name: str = Field(..., description="Full company name")
       current_price: float = Field(..., description="Current price in USD")
       pe_ratio: Optional[float] = Field(None, description="P/E ratio")
       summary: str = Field(..., description="One-line summary")
       key_drivers: List[str] = Field(..., description="2-3 key growth drivers")
       key_risks: List[str] = Field(..., description="2-3 key risks")
   
   
   agent = Agent(
       model=OpenAIResponses(id="gpt-5.2"),
       tools=[YFinanceTools()],
       output_schema=StockAnalysis,
   )
   
   response = agent.run("Analyze NVIDIA stock")
   
   # Access typed data directly
   analysis: StockAnalysis = response.content
   print(f"{analysis.company_name} ({analysis.ticker})")
   print(f"Price: ${analysis.current_price}")
   print(f"P/E Ratio: {analysis.pe_ratio or 'N/A'}")
   print(f"Summary: {analysis.summary}")
   print("Key Drivers:")
   for driver in analysis.key_drivers:
       print(f"  - {driver}")
   print("Key Risks:")
   for risk in analysis.key_risks:
       print(f"  - {risk}")
   
2. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
3. Install dependencies

   uv pip install -U agno openai yfinance
   
4. Export your OpenAI API key

   Mac/Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   
5. Run Agent

   python structured_output.py