Building AI Agents with smolagents and a Gaia Node

from smolagents.agents import ToolCallingAgent from smolagents import tool, LiteLLMModel from typing import Optional import requests # Configure the model with Gaia's tooling node model = LiteLLMModel( model_id="openai/llama", # Using OpenAI format for Gaia compatibility  api_base="https://llama3b.gaia.domains/v1", # Gaia's tooling node  api_key="gaia-" # API key for Gaia node ) @tool def get_weather(location: str, celsius: Optional[bool] = True) -> str: """ Get current weather conditions for a location using wttr.in service. This function fetches weather data in a human-readable format without requiring any API keys. It provides comprehensive weather information including temperature, conditions, and forecast. Args: location: The city name or location to get weather for celsius: Whether to return temperature in Celsius (True) or Fahrenheit (False) Returns: A formatted string containing current weather conditions """ try: # Construct the wttr.in URL with proper formatting  # We use format=3 for a concise output and add language specification  # The 'u' or 'm' parameter controls the unit (metric or USCS)  unit = 'm' if celsius else 'u' url = f"https://wttr.in/{location}?format=3&{unit}" # Make the request to wttr.in  response = requests.get(url, headers={'User-Agent': 'curl'}, timeout=10) response.raise_for_status() # Raise an exception for bad responses  # Get the weather data and clean it up  weather_data = response.text.strip() # Create a more detailed response using the weather data  detailed_response = ( f"Weather Report for {location}:\n" f"{weather_data}\n\n" f"Temperature is shown in {'Celsius' if celsius else 'Fahrenheit'}" ) return detailed_response except requests.exceptions.RequestException as e: # Handle any network or service errors gracefully  return f"I apologize, but I couldn't fetch the weather data: {str(e)}" # Create our weather-capable agent agent = ToolCallingAgent(tools=[get_weather], model=model) def demonstrate_weather_queries(): """ Demonstrate various weather queries to show the agent's capabilities. This function shows how the agent can handle different types of weather requests. """ print("Weather Agent Demonstration\n" + "="*25 + "\n") # Test various types of queries to show versatility  test_queries = [ "What's the weather like in London?", "Tell me the current conditions in Tokyo", "How's the weather in New York City with temperatures in Fahrenheit?", "What's the weather like in Paris, France?" ] for query in test_queries: print(f"\nQuery: {query}") try: response = agent.run(query) print(f"Response: {response}") except Exception as e: print(f"Error processing query: {str(e)}") print("-" * 50) if __name__ == "__main__": # Run our demonstration  demonstrate_weather_queries()