tools.py

from langchain_community.tools import DuckDuckGoSearchRun
from langchain_core.tools import Tool
import random
from langchain_core.tools import Tool
from huggingface_hub import list_models

# Initialize the DuckDuckGo search tool
search_tool = DuckDuckGoSearchRun()

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

# Define the hub stats tool
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 hub stats 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."
)



'''
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)}"
'''