Smolagents Integration

Colab Notebook

Weather Agent Example

The snippet below shows a minimal agent that exposes a get_weather_api tool, wraps it in a sub‑agent, and lets a manager agent answer user questions. Paste this MDX file anywhere in your docs (e.g., content/docs/weather-agent.mdx) to embed the example with syntax highlighting.

import patronus
from openinference.instrumentation.smolagents import SmolagentsInstrumentor
from opentelemetry.instrumentation.threading import ThreadingInstrumentor
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from datetime import datetime
from smolagents import LiteLLMModel, ToolCallingAgent, tool
 
patronus.init(integrations=[SmolagentsInstrumentor(), ThreadingInstrumentor()])
 
@tool
def get_weather_api(location: str, date_time: str) -> str:
    """
    Returns the weather report.
 
    Args:
        location: the name of the place that you want the weather for. Should be a place name, followed by possibly a city name, then a country, like "Anchor Point, Taghazout, Morocco".
        date_time: the date and time for which you want the report, formatted as '%m/%d/%y %H:%M:%S'.
    """
    try:
        date_time = datetime.strptime(date_time, '%m/%d/%y %H:%M:%S')
    except Exception as e:
        raise ValueError("Conversion of `date_time` to datetime format failed, make sure to provide a string in format '%m/%d/%y %H:%M:%S'. Full trace:" + str(e))
    temperature_celsius, risk_of_rain, wave_height = 10, 0.5, 4  # mock outputs
    return (
        f"Weather report for {location}, {date_time}: "
        f"Temperature will be {temperature_celsius}°C, "
        f"risk of rain is {risk_of_rain*100:.0f}%, wave height is {wave_height}m."
    )
 
def create_agent(model_id):
    # Create weather agent
    weather_model = LiteLLMModel(model_id, temperature=0.0, top_p=1.0)
    weather_subagent = ToolCallingAgent(
        tools=[get_weather_api],
        model=weather_model,
        max_steps=10,
        name="weather_agent",
        description="This agent can provide information about the weather at a certain location",
    )
 
    # Create manager agent and add weather agent as subordinate
    manager_model = LiteLLMModel(model_id, temperature=0.0, top_p=1.0)
    agent = ToolCallingAgent(
        model=manager_model,
        managed_agents=[weather_subagent],
        tools=[],
        add_base_tools=False,
    )
    return agent
 
@patronus.traced()
def main():
    agent = create_agent("openai/gpt-4o")
    agent.run("What is the weather in Paris, France?")
 
if __name__ == "__main__":
    main()

Remember to export OPENAI_API_KEY (or configure LiteLLM with your own provider credentials) before running this example locally.

Smolagents Integration

Colab Notebook

Weather Agent Example

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