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| import os | |
| import re | |
| import requests | |
| from smolagents import CodeAgent, ToolCallingAgent, WebSearchTool, tool | |
| from smolagents.models.huggingface import HuggingFaceModel | |
| from dotenv import load_dotenv | |
| from markdownify import markdownify | |
| from requests.exceptions import RequestException | |
| def initialize_agent(): | |
| # Load environment variables from .env file | |
| load_dotenv() | |
| # 1. Load the model | |
| # Make sure to set HF_TOKEN in your Hugging Face Space secrets | |
| model_name = "HuggingFaceH4/zephyr-7b-beta" | |
| try: | |
| model = HuggingFaceModel(model=model_name, token=os.environ.get("HF_TOKEN")) | |
| except Exception as e: | |
| print(f"Error loading model: {e}") | |
| model = None | |
| # 2. Define the tools | |
| def visit_webpage(url: str) -> str: | |
| """Visits a webpage at the given URL and returns its content as a markdown string. | |
| Args: | |
| url: The URL of the webpage to visit. | |
| Returns: | |
| The content of the webpage converted to Markdown, or an error message if the request fails. | |
| """ | |
| try: | |
| # Send a GET request to the URL | |
| response = requests.get(url) | |
| response.raise_for_status() # Raise an exception for bad status codes | |
| # Convert the HTML content to Markdown | |
| markdown_content = markdownify(response.text).strip() | |
| # Remove multiple line breaks | |
| markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content) | |
| return markdown_content | |
| except RequestException as e: | |
| return f"Error fetching the webpage: {str(e)}" | |
| except Exception as e: | |
| return f"An unexpected error occurred: {str(e)}" | |
| # 3. Define the agents | |
| if model: | |
| web_agent = ToolCallingAgent( | |
| tools=[WebSearchTool(), visit_webpage], | |
| model=model, | |
| max_steps=10, | |
| name="web_search_agent", | |
| description="Runs web searches for you.", | |
| ) | |
| manager_agent = CodeAgent( | |
| tools=[], | |
| model=model, | |
| managed_agents=[web_agent], | |
| additional_authorized_imports=["time", "numpy", "pandas"], | |
| ) | |
| return manager_agent | |
| else: | |
| return None | |