Add Dependencies to Agent Run

This example demonstrates how to inject dependencies into agent runs, allowing the agent to access dynamic context like user profiles and current time information for personalized responses.

Code

add_dependencies_on_run.py

from agno.agent import Agent
from agno.models.openai import OpenAIChat


def get_user_profile(user_id: str = "john_doe") -> dict:
    """Get user profile information that can be referenced in responses.

    Args:
        user_id: The user ID to get profile for
    Returns:
        Dictionary containing user profile information
    """
    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"),
    }


agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    markdown=True,
)

# Example usage - sync
response = agent.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,
    debug_mode=True,
)

print(response.content)

# ------------------------------------------------------------
# ASYNC EXAMPLE
# ------------------------------------------------------------
# async def test_async():
#     async_response = await agent.arun(
#         "Based on my profile, what should I focus on this week? Include specific recommendations.",
#         dependencies={
#             "user_profile": get_user_profile,
#             "current_context": get_current_context
#         },
#         add_dependencies_to_context=True,
#         debug_mode=True,
#     )

#     print("\n=== Async Run Response ===")
#     print(async_response.content)

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

# ------------------------------------------------------------
# Print response EXAMPLE
# ------------------------------------------------------------
# agent.print_response(
#     "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,
#     debug_mode=True,
# )

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install libraries

   pip install -U agno openai
   
3. Export your OpenAI API key

   Mac/Linux

     export OPENAI_API_KEY="your_openai_api_key_here"
   
4. Create a Python file

   Create a Python file and add the above code.

   touch add_dependencies_on_run.py
   
5. Run Agent

   Mac

   python add_dependencies_on_run.py
   
6. Find All Cookbooks

   Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:

   Agno Cookbooks on GitHub