agentic_chat.py
"""
Agentic Chat — Dojo Demo
========================
Frontend tool: change_background (external_execution)
Backend tool: get_weather (renders as card via useRenderTool)
Dojo expects:
- change_background(background: str) -> changes CSS background
- get_weather(location: str) -> dict with city, temperature, humidity, wind_speed, conditions
"""
from agno.agent.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.tools import tool
@tool(external_execution=True, external_execution_silent=True)
def change_background(background: str) -> str:
"""Change the background color of the chat. Can be anything that the CSS background attribute accepts. Regular colors, linear or radial gradients etc."""
return f"Background changed to {background}"
@tool
def get_weather(location: str) -> dict:
"""Get the current weather for a location."""
data = {
"San Francisco": {
"city": "San Francisco",
"temperature": 18,
"humidity": 65,
"wind_speed": 12,
"conditions": "Sunny",
},
"New York": {
"city": "New York",
"temperature": 22,
"humidity": 55,
"wind_speed": 8,
"conditions": "Cloudy",
},
"Tokyo": {
"city": "Tokyo",
"temperature": 26,
"humidity": 70,
"wind_speed": 5,
"conditions": "Rainy",
},
"London": {
"city": "London",
"temperature": 15,
"humidity": 80,
"wind_speed": 15,
"conditions": "Overcast",
},
"Paris": {
"city": "Paris",
"temperature": 20,
"humidity": 60,
"wind_speed": 10,
"conditions": "Partly cloudy",
},
}
return data.get(
location,
{
"city": location,
"temperature": 20,
"humidity": 60,
"wind_speed": 10,
"conditions": "Partly cloudy",
},
)
agentic_chat_agent = Agent(
name="agentic_chat",
model=OpenAIResponses(id="gpt-5.5"),
db=SqliteDb(db_file="/tmp/agentic_chat.db"),
tools=[change_background, get_weather],
instructions="""You are a helpful assistant with frontend and backend capabilities.
Tools available:
- change_background: Changes the page background. Accepts CSS values (colors, gradients). Only use when explicitly asked.
- get_weather: Gets weather for a location. Returns temperature, humidity, wind speed, and conditions.
Be helpful and use tools when appropriate.""",
markdown=True,
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U "agno[agui,os]" ddgs google-genai openai requests
3
Export your API keys
export GOOGLE_API_KEY="your_google_api_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:GOOGLE_API_KEY="your_google_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Clone Agno
Clone the repository and run the remaining commands from its root:
git clone https://github.com/agno-agi/agno.git
cd agno
5
Run the example
Run the example from the repository root:
python cookbook/05_agent_os/interfaces/agui/showcase.py