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

# Adding Dependencies to Team Run

> This example demonstrates how to add dependencies to a specific team run. Dependencies are functions that provide contextual information (like user profiles and current context) that get passed to the team during execution for personalized responses.

<Steps>
  <Step title="Create a Python file">
    ```python add_dependencies_on_run.py theme={null}
    from datetime import datetime

    from agno.agent import Agent
    from agno.models.openai import OpenAIResponses
    from agno.team import Team


    def get_user_profile(user_id: str = "john_doe") -> dict:
        """Get user profile information that can be referenced in responses."""
        profiles = {
            "john_doe": {
                "name": "John Doe",
                "preferences": {
                    "communication_style": "professional",
                    "topics_of_interest": ["AI/ML", "Software Engineering", "Finance"],
                    "experience_level": "senior",
                },
                "location": "San Francisco, CA",
                "role": "Senior Software Engineer",
            }
        }

        return profiles.get(user_id, {"name": "Unknown User"})


    def get_current_context() -> dict:
        """Get current contextual information like time, weather, etc."""
        return {
            "current_time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
            "timezone": "PST",
            "day_of_week": datetime.now().strftime("%A"),
        }


    profile_agent = Agent(
        name="ProfileAnalyst",
        model=OpenAIResponses(id="gpt-5.2"),
        instructions="You analyze user profiles and provide personalized recommendations.",
    )

    context_agent = Agent(
        name="ContextAnalyst",
        model=OpenAIResponses(id="gpt-5.2"),
        instructions="You analyze current context and timing to provide relevant insights.",
    )

    team = Team(
        name="PersonalizationTeam",
        model=OpenAIResponses(id="gpt-5.2"),
        members=[profile_agent, context_agent],
        markdown=True,
    )

    response = team.run(
        "Please provide me with a personalized summary of today's priorities based on my profile and interests.",
        dependencies={
            "user_profile": get_user_profile,
            "current_context": get_current_context,
        },
        add_dependencies_to_context=True,
    )

    print(response.content)
    ```
  </Step>

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

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

  <Step title="Export your OpenAI API key">
    ```bash theme={null}
    export OPENAI_API_KEY=your_openai_api_key_here
    ```
  </Step>

  <Step title="Run Team">
    ```bash theme={null}
    python add_dependencies_on_run.py
    ```
  </Step>
</Steps>