> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Team Streaming

> Stream responses from a team in real-time.

Stream responses from a team with `stream=True` for real-time output as the team works.

**1. Create a Python file**

```python streaming_team.py theme={null}
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,
)
```

<Snippet file="create-venv-step.mdx" />

**2. Install dependencies**

```bash theme={null}
uv pip install -U agno openai yfinance
```

**3. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```powershell Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

**4. Run Team**

```bash theme={null}
python streaming_team.py
```


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