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This example demonstrates how to add dependencies directly to the team context. Unlike adding dependencies per run, this approach makes the dependency functions available to all team runs by default, providing consistent access to contextual information across all interactions.

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Code

cookbook/examples/teams/dependencies/add_dependencies_to_context.py
from agno.agent import Agent
from agno.models.openai import OpenAIChat
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."""
    from datetime import datetime

    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=OpenAIChat(id="gpt-5-mini"),
    instructions="You analyze user profiles and provide personalized recommendations.",
)

context_agent = Agent(
    name="ContextAnalyst",
    model=OpenAIChat(id="gpt-5-mini"),
    instructions="You analyze current context and timing to provide relevant insights.",
)

team = Team(
    name="PersonalizationTeam",
    model=OpenAIChat(id="gpt-5-mini"),
    members=[profile_agent, context_agent],
    dependencies={
        "user_profile": get_user_profile,
        "current_context": get_current_context,
    },
    add_dependencies_to_context=True,
    debug_mode=True,
    markdown=True,
)

response = team.run(
    "Please provide me with a personalized summary of today's priorities based on my profile and interests.",
)

print(response.content)

# ------------------------------------------------------------
# ASYNC EXAMPLE
# ------------------------------------------------------------
# async def test_async():
#     async_response = await team.arun(
#         "Based on my profile, what should I focus on this week? Include specific recommendations.",
#     )
#
#     print("\n=== Async Run Response ===")
#     print(async_response.content)

# # Run the async test
# import asyncio
# asyncio.run(test_async())

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Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install required libraries

pip install agno openai
3

Set environment variables

export OPENAI_API_KEY=****
4

Run the agent

python cookbook/examples/teams/dependencies/add_dependencies_to_context.py
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