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| # Provides auxiliary tools for agent | |
| from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec | |
| import random | |
| from huggingface_hub import list_models | |
| import aiohttp | |
| import os | |
| import json | |
| from dotenv import load_dotenv | |
| import asyncio | |
| tool_spec = DuckDuckGoSearchToolSpec() | |
| search_tool = tool_spec.duckduckgo_full_search | |
| async def google_search(query: str, num_results: int = 5) -> str: | |
| """ | |
| Args: | |
| query: Search query | |
| num_results: Max results to return | |
| Returns: | |
| dict: JSON response from Google API. | |
| """ | |
| api_key = os.getenv("GOOGLE_API_KEY") | |
| cse_id = os.getenv("GOOGLE_CSE_ID") | |
| if not api_key or not cse_id: | |
| raise ValueError( | |
| "GOOGLE_API_KEY and GOOGLE_CSE_ID must be set in environment variables." | |
| ) | |
| url = "https://www.googleapis.com/customsearch/v1" | |
| params = {"key": api_key, "cx": cse_id, "q": query} | |
| async with aiohttp.ClientSession() as session: | |
| async with session.get(url, params=params) as response: | |
| response.raise_for_status() | |
| data = await response.json() | |
| results = "Web Search results:\n\n" + "\n\n".join( | |
| [ | |
| f"Link:{result['link']}\nTitle:{result['title']}\nSnippet:{result['snippet']}" | |
| for result in data["items"][:num_results] | |
| ] | |
| ) | |
| print(results) | |
| return 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" | |
| 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)}" | |
| async def main(): | |
| response = await google_search("Who's the current President of France 2025?") | |
| print(response) | |
| if __name__ == "__main__": | |
| load_dotenv() | |
| asyncio.run(main()) | |
| # print(get_hub_stats("facebook")) | |