> ## 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.

# In-Memory Storage for Team

> HackerNews research team stores sessions in an in-memory database with a structured Article output.

```python in_memory_storage_for_team.py theme={null}
"""
1. Run: `uv pip install openai ddgs newspaper4k lxml_html_clean agno` to install the dependencies
2. Run: `python cookbook/06_storage/in_memory/in_memory_storage_for_team.py` to run the team
"""

from typing import List

from agno.agent import Agent
from agno.db.in_memory import InMemoryDb
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from pydantic import BaseModel

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
db = InMemoryDb()


# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
class Article(BaseModel):
    title: str
    summary: str
    reference_links: List[str]


hn_researcher = Agent(
    name="HackerNews Researcher",
    model=OpenAIChat("gpt-5.6-luna"),
    role="Gets top stories from hackernews.",
    tools=[HackerNewsTools()],
)

web_searcher = Agent(
    name="Web Searcher",
    model=OpenAIChat("gpt-5.6-luna"),
    role="Searches the web for information on a topic",
    tools=[WebSearchTools()],
)

hn_team = Team(
    name="HackerNews Team",
    model=OpenAIChat("gpt-5.6-luna"),
    members=[hn_researcher, web_searcher],
    db=db,
    instructions=[
        "First, search hackernews for what the user is asking about.",
        "Then, ask the web searcher to search for each story to get more information.",
        "Finally, provide a thoughtful and engaging summary.",
    ],
    output_schema=Article,
    markdown=True,
    show_members_responses=True,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    hn_team.print_response("Write an article about the top 2 stories on hackernews")
```

## Run the Example

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

**1. Install dependencies**

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

**2. Export your OpenAI API key**

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

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

**3. Run the example**

Save the code above as `in_memory_storage_for_team.py`, then run:

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

Full source: [cookbook/06\_storage/in\_memory/in\_memory\_storage\_for\_team.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/06_storage/in_memory/in_memory_storage_for_team.py)


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