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

# Team With Knowledge

> Demonstrates a team that combines knowledge-base retrieval with web search support.

```python team_with_knowledge.py theme={null}
"""
Team With Knowledge
=============================

Demonstrates a team that combines knowledge-base retrieval with web search support.
"""

from pathlib import Path

from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.websearch import WebSearchTools
from agno.vectordb.lancedb import LanceDb, SearchType

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
cwd = Path(__file__).parent
tmp_dir = cwd.joinpath("tmp")
tmp_dir.mkdir(parents=True, exist_ok=True)

agno_docs_knowledge = Knowledge(
    vector_db=LanceDb(
        uri=str(tmp_dir.joinpath("lancedb")),
        table_name="agno_docs",
        search_type=SearchType.hybrid,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

agno_docs_knowledge.insert(url="https://docs.agno.com/llms-full.txt")

# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
web_agent = Agent(
    name="Web Search Agent",
    role="Handle web search requests",
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[WebSearchTools()],
    instructions=["Always include sources"],
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
team_with_knowledge = Team(
    name="Team with Knowledge",
    members=[web_agent],
    model=OpenAIResponses(id="gpt-5-mini"),
    knowledge=agno_docs_knowledge,
    show_members_responses=True,
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    team_with_knowledge.print_response("Tell me about the Agno framework", stream=True)
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno beautifulsoup4 ddgs lancedb openai pyarrow
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```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"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `team_with_knowledge.py`, then run:

    ```bash theme={null}
    python team_with_knowledge.py
    ```
  </Step>
</Steps>

Full source: [cookbook/03\_teams/05\_knowledge/01\_team\_with\_knowledge.py](https://github.com/agno-agi/agno/blob/main/cookbook/03_teams/05_knowledge/01_team_with_knowledge.py)