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from smolagents import DuckDuckGoSearchTool
from smolagents import Tool
import random
from huggingface_hub import list_models
import requests
from bs4 import BeautifulSoup
import openpyxl
class WikipediaTool(Tool):
name = "wikipedia_api"
description = "Returns the contents of a wikipedia article through a direct API call."
inputs = {
"title": {
"type": "string",
"description": "The title of the wikipedia article to retrieve."
}
}
output_type = "string"
def forward(self, question: str):
search_tool = DuckDuckGoSearchTool()
result = search_tool(question)
return result
class ExcelTool(Tool):
name = "read_excel"
description = "Returns the contents of an Excel file as a Pandas dataframe."
inputs = {
"filename": {
"type": "string",
"description": "The name of the Excel file to read."
}
}
output_type = "string"
def forward(self, question: str):
search_tool = DuckDuckGoSearchTool()
result = search_tool(question)
return result
class WebscraperTool(Tool):
name = "webscraper"
description = "Returns the page's html content from the input url."
inputs = {
"url": {
"type": "string",
"description": "The link of the web page to scrape."
}
}
output_type = "string"
def forward(self, question: str):
search_tool = DuckDuckGoSearchTool()
result = search_tool(question)
return result
# Initialize the DuckDuckGo search tool
class InternetSearchTool(Tool):
name = "internet_search"
description = "Searches the internet for the answer to any question input. Returns a long batch of textual information related to the query."
inputs = {
"question": {
"type": "string",
"description": "The question to retrieve an answer for."
}
}
output_type = "string"
def forward(self, question: str):
search_tool = DuckDuckGoSearchTool()
result = search_tool(question)
return result
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)}"
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