stream=True for real-time output as the team works.
1
Create a Python file
streaming_team.py
2
Set up your virtual environment
3
Install dependencies
4
Export your OpenAI API key
5
Run Team
Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Stream responses from a team in real-time.
stream=True for real-time output as the team works.
Create a Python file
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.yfinance import YFinanceTools
news_agent = Agent(
name="News Agent",
model=OpenAIResponses(id="gpt-5.2"),
role="Gets trending tech stories from HackerNews.",
tools=[HackerNewsTools()],
)
finance_agent = Agent(
name="Finance Agent",
model=OpenAIResponses(id="gpt-5.2"),
role="Gets stock prices and financial data.",
tools=[YFinanceTools()],
)
team = Team(
name="Research Team",
model=OpenAIResponses(id="gpt-5.2"),
members=[news_agent, finance_agent],
markdown=True,
show_members_responses=True,
)
# Stream the response
team.print_response(
"What are the trending AI stories and how is NVDA stock doing?",
stream=True,
)
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Install dependencies
uv pip install -U agno openai yfinance
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
Run Team
python streaming_team.py
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