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This example demonstrates how to use reference dependencies by defining them in the team constructor and referencing them directly in team instructions. This approach allows dependencies to be automatically injected into the team’s context and referenced using template variables in instructions.

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Code

cookbook/examples/teams/dependencies/reference_dependencies.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,
    },
    instructions=[
        "You are a personalization team that provides personalized recommendations based on the user's profile and context.",
        "Here is the user profile: {user_profile}",
        "Here is the current context: {current_context}",
    ],
    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)

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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/reference_dependencies.py
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