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| from langchain_core.tools import tool | |
| from langchain_community.tools import DuckDuckGoSearchRun | |
| import random | |
| from huggingface_hub import list_models | |
| search = DuckDuckGoSearchRun() | |
| def web_search_tool(query: str) -> str: | |
| """Search the web for information about unfamiliar guests.""" | |
| return search.run(query) | |
| def latest_news_tool(topic: str) -> str: | |
| """ | |
| Get the latest news about a specific topic. | |
| """ | |
| query = f"latest news about {topic}" | |
| results = search.run(query) | |
| return results | |
| def get_weather_tool(location:str)-> str: | |
| """Fetches weather information for a given location.""" | |
| weather_condition =[ | |
| {"condition": "Rainy", "temp_c": 15}, | |
| {"condition": "Clear", "temp_c": 25}, | |
| {"condition": "Windy", "temp_c": 20} | |
| ] | |
| data = random.choice(weather_condition) | |
| return f"Wrather in {location} is {data['condition']} with temp : {data['temp_c']}c" | |
| def hub_stats_tool(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)}" | |