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):
        # I removed the dummy weather data to use wttr.in to find real weather
        try:
            response = requests.get(f"https://wttr.in/{location}?format=3")
            return response.text if response.status_code == 200 else "Weather data unvailable."
        except Exception as e:
            return f"Error: {str(e)}"

# I added the suggested "suggest_gala_outfit" tool
# This should work in theory......
class GalaOutfitTool(Tool):
    name = "suggest_gala_outfit"
    description = "Suggests a gala outfit based on the current weather condition."
    inputs = {"condition": {"type": "string", "descrition": "The current weather (e.g.. rainy, cold, hot)."}}
    output_type = "string"

    def forward(self, condition: str):
        outfits = {
            "rainy": "A sleek waterproof trench coat over a navy blue tuxedo, paired with leather boots.",
            "cold": "A red velvet long gown with a fur coat or wool-blend suit",
            "hot": "A breathable silk dress or a lightweight linen dinner blazer.",
            "clear": "A classic black-tie outfit, tuxedo or evening gown."
        }
        return outfits.get(condition.lower(), "A black-tie formal look is always good")
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)}"