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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")) | |