Spaces:
Runtime error
Runtime error
| # 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']}Β°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']}Β°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 |