Direct Response with Team History

This example demonstrates a team where the team leader routes requests to the appropriate member, and the members respond directly to the user.

In addition, the team has access to the conversation history through add_history_to_context=True.

respond_directly_with_history.py

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.team.team import Team


def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."


weather_agent = Agent(
    name="Weather Agent",
    role="You are a weather agent that can answer questions about the weather.",
    model=OpenAIChat(id="o3-mini"),
    tools=[get_weather],
)


def get_news(topic: str) -> str:
    return f"The news about {topic} is that it is going well!"


news_agent = Agent(
    name="News Agent",
    role="You are a news agent that can answer questions about the news.",
    model=OpenAIChat(id="o3-mini"),
    tools=[get_news],
)


def get_activities(city: str) -> str:
    return f"The activities in {city} are that it is going well!"


activities_agent = Agent(
    name="Activities Agent",
    role="You are a activities agent that can answer questions about the activities.",
    model=OpenAIChat(id="o3-mini"),
    tools=[get_activities],
)


geo_search_team = Team(
    name="Geo Search Team",
    model=OpenAIChat("o3-mini"),
    respond_directly=True,
    members=[
        weather_agent,
        news_agent,
        activities_agent,
    ],
    instructions="You are a geo search agent that can answer questions about the weather, news and activities in a city.",
    db=SqliteDb(
        db_file="tmp/geo_search_team.db"
    ),  # Add a database to store the conversation history
    add_history_to_context=True,  # Ensure that the team leader knows about previous requests
)


geo_search_team.print_response(
    "I am doing research on Tokyo. What is the weather like there?", stream=True
)

geo_search_team.print_response(
    "Is there any current news about that city?", stream=True
)

geo_search_team.print_response("What are the activities in that city?", stream=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 required libraries

   pip install agno openai
   
3. Set environment variables

   export OPENAI_API_KEY=****
   
4. Run the agent

   python respond_directly_with_history.py