Pydantic Input
Demonstrates passing validated Pydantic models as team inputs.
"""
Pydantic Input
==============
Demonstrates passing validated Pydantic models as team inputs.
"""
from typing import List
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from pydantic import BaseModel, Field
class ResearchTopic(BaseModel):
"""Structured research topic with specific requirements."""
topic: str = Field(description="The main research topic")
focus_areas: List[str] = Field(description="Specific areas to focus on")
target_audience: str = Field(description="Who this research is for")
sources_required: int = Field(description="Number of sources needed", default=5)
# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
hackernews_agent = Agent(
name="Hackernews Agent",
model=OpenAIResponses(id="gpt-5-mini"),
tools=[HackerNewsTools()],
role="Extract key insights and content from Hackernews posts",
instructions=[
"Search Hacker News for relevant articles and discussions",
"Extract key insights and summarize findings",
"Focus on high-quality, well-discussed posts",
],
)
# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
team = Team(
name="Hackernews Research Team",
model=OpenAIResponses(id="gpt-5-mini"),
members=[hackernews_agent],
determine_input_for_members=False,
instructions=[
"Conduct thorough research based on the structured input",
"Address all focus areas mentioned in the research topic",
"Tailor the research to the specified target audience",
"Provide the requested number of sources",
],
show_members_responses=True,
)
# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
research_request = ResearchTopic(
topic="AI Agent Frameworks",
focus_areas=[
"AI Agents",
"Framework Design",
"Developer Tools",
"Open Source",
],
target_audience="Software Developers and AI Engineers",
sources_required=7,
)
team.print_response(input=research_request)
alternative_research = ResearchTopic(
topic="Distributed Systems",
focus_areas=["Microservices", "Event-Driven Architecture", "Scalability"],
target_audience="Backend Engineers",
sources_required=5,
)
team.print_response(input=alternative_research)Validation and delegation
Pydantic validates ResearchTopic when you construct it. determine_input_for_members=False passes the original structured request to the selected member instead of the leader's rewritten task. The schema has no lower bound on sources_required, and the requested source count is not checked against the answer.
HackerNewsTools reads top stories and user profiles. Add a search tool if your task requires finding arbitrary topics beyond those stories.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno openaiExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Run the example
Save the code above as pydantic_input.py, then run:
python pydantic_input.pyFull source: cookbook/03_teams/04_structured_input_output/pydantic_input.py