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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 | |
import wikipedia | |
import pandas as pd | |
class MediaTool(Tool): | |
name = "media_tool" | |
description = "Used for deciphering video and audio files." | |
inputs = { | |
"filename": { | |
"type": "string", | |
"description": "The name of the media file to transcribe." | |
} | |
} | |
output_type = "string" | |
def forward(self, filename: str): | |
print(f"called MediaTool with {filename}") | |
return "This tool hasn't been implemented yet. Please return 0 if the task cannot be solved without knowing the contents of this file." | |
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, title: str): | |
print(f"called WikipediaTool with {title}") | |
try: | |
page = wikipedia.page(title) | |
content = page.content[:3000] | |
return content | |
except Exception as e: | |
return f"ERROR: {e}" | |
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, filename: str): | |
print(f"called ExcelTool with {filename}") | |
try: | |
df = pd.read_excel(filename, engine = "openpyxl") | |
return df | |
except Exception as e: | |
return f"ERROR: {e}" | |
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, url: str): | |
print(f"called WebscraperTool with {url}") | |
try: | |
response = requests.get(url, stream=True) | |
if response.status_code == 200: | |
soup = BeautifulSoup(response.content, 'html.parser') | |
html_text = soup.get_text() | |
return html_text | |
else: | |
return "Website cannot be reached." | |
except Exception as e: | |
return f"ERROR: {e}" | |
# 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): | |
print(f"called InternetSearchTool with {question}") | |
try: | |
search_tool = DuckDuckGoSearchTool() | |
result = search_tool(question) | |
return result | |
except Exception as e: | |
return f"ERROR: {e}" | |
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)}" | |