# from smolagents import DuckDuckGoSearchTool
# from smolagents import Tool
# import random
# from huggingface_hub import list_models


# # Initialize the DuckDuckGo search tool
# #search_tool = DuckDuckGoSearchTool()


# class WeatherInfoTool(Tool):
#     name = "weather_info"
#     description = "Fetches dummy weather information for a given location."
#     inputs = {
#         "location": {
#             "type": "string",
#             "description": "The location to get weather information for."
#         }
#     }
#     output_type = "string"

#     def forward(self, location: str):
#         # Dummy weather data
#         weather_conditions = [
#             {"condition": "Rainy", "temp_c": 15},
#             {"condition": "Clear", "temp_c": 25},
#             {"condition": "Windy", "temp_c": 20}
#         ]
#         # Randomly select a weather condition
#         data = random.choice(weather_conditions)
#         return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"

# class HubStatsTool(Tool):
#     name = "hub_stats"
#     description = "Fetches the most downloaded model from a specific author on the Hugging Face Hub."
#     inputs = {
#         "author": {
#             "type": "string",
#             "description": "The username of the model author/organization to find models from."
#         }
#     }
#     output_type = "string"

#     def forward(self, author: str):
#         try:
#             # List models from the specified author, sorted by downloads
#             models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
            
#             if models:
#                 model = models[0]
#                 return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
#             else:
#                 return f"No models found for author {author}."
#         except Exception as e:
#             return f"Error fetching models for {author}: {str(e)}"


from langchain.tools import Tool
from huggingface_hub import list_models
import random

from langchain_community.tools import DuckDuckGoSearchRun

search_tool = DuckDuckGoSearchRun()
results = search_tool.invoke("Who's the current President of France?")
print(results)

def get_weather_info(location: str) -> str:
    """Fetches dummy weather information for a given location."""
    # Dummy weather data
    weather_conditions = [
        {"condition": "Rainy", "temp_c": 15},
        {"condition": "Clear", "temp_c": 25},
        {"condition": "Windy", "temp_c": 20}
    ]
    # Randomly select a weather condition
    data = random.choice(weather_conditions)
    return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"

# Initialize the tool
weather_info_tool = Tool(
    name="get_weather_info",
    func=get_weather_info,
    description="Fetches dummy weather information for a given location."
)

def get_hub_stats(author: str) -> str:
    """Fetches the most downloaded model from a specific author on the Hugging Face Hub."""
    try:
        # List models from the specified author, sorted by downloads
        models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))

        if models:
            model = models[0]
            return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
        else:
            return f"No models found for author {author}."
    except Exception as e:
        return f"Error fetching models for {author}: {str(e)}"

# Initialize the tool
hub_stats_tool = Tool(
    name="get_hub_stats",
    func=get_hub_stats,
    description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
)

# Example usage
print(hub_stats_tool("facebook")) # Example: Get the most downloaded model by Facebook