from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool import os from tavily import TavilyClient from Gradio_UI import GradioUI import wikipedia import textwrap # Example tool template - can be modified for your needs @tool def my_custom_tool(arg1: str, arg2: int) -> str: # Return type specification is important """A tool that does nothing yet Args: arg1: the first argument arg2: the second argument """ return "What magic will you build?" @tool def wiki_search(query: str, sentences: int = 3) -> str: """Search Wikipedia and return a summary of the topic. Args: query: The topic to search for on Wikipedia sentences: Number of sentences to return in the summary (default: 3) Returns: str: A summary of the Wikipedia article """ try: # Set language to English for consistency wikipedia.set_lang("en") # Search for the page search_results = wikipedia.search(query) if not search_results: return f"No Wikipedia results found for: {query}" try: # Get the page page = wikipedia.page(search_results[0], auto_suggest=False) # Get summary and full URL summary = wikipedia.summary(search_results[0], sentences=sentences, auto_suggest=False) url = page.url # Format the response response = f"Wikipedia article: {page.title}\n" response += f"URL: {url}\n\n" response += f"Summary:\n{textwrap.fill(summary, width=80)}\n" return response except wikipedia.DisambiguationError as e: # Handle disambiguation pages options = e.options[:5] # Show first 5 options response = f"'{query}' may refer to multiple topics. Here are some options:\n\n" for i, option in enumerate(options, 1): response += f"{i}. {option}\n" return response except Exception as e: return f"Error searching Wikipedia: {str(e)}" # @tool # def tavily_search(query: str) -> str: # """A tool that performs web search using Tavily API and formats the results. # Args: # query: The search query to look up # Returns: # str: A formatted summary of search results # """ # try: # client = TavilyClient(api_key=os.environ["TAVILY_API_KEY"]) # search_result = client.search(query=query, search_depth="advanced") # # Format the results in a user-friendly way # summary = f"Here are the search results for: {query}\n\n" # for result in search_result['results'][:5]: # Top 5 results # summary += f"• {result['title']}\n" # summary += f" Summary: {result['description'][:200]}...\n\n" # return summary # except Exception as e: # return f"Error performing search: {str(e)}" @tool def get_current_time_in_timezone(timezone: str) -> str: """A tool that fetches and formats the current local time in a specified timezone. Args: timezone: A string representing a valid timezone (e.g., 'America/New_York', 'Asia/Tokyo') Returns: str: A formatted string containing the timezone and current time """ try: tz = pytz.timezone(timezone) local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") # Return a more descriptive string with cleaned timezone name city = timezone.split('/')[-1].replace('_', ' ') return f"The current time in {city} is: {local_time}" except Exception as e: return f"Error fetching time for timezone '{timezone}': {str(e)}" # Initialize tools final_answer = FinalAnswerTool() image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) # If the agent does not answer, the model is overloaded, please use another model or # the following Hugging Face Endpoint that also contains qwen2.5 coder: # Model configuration model_id = 'https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' model = HfApiModel( max_tokens=2096, temperature=0.3, # Lower temperature for more consistent responses model_id=model_id, # 'Qwen/Qwen2.5-Coder-32B-Instruct', custom_role_conversions=None, ) # Load prompt templates with open("prompts.yaml", 'r') as stream: prompt_templates = yaml.safe_load(stream) # Initialize agent with tools agent = CodeAgent( model=model, tools=[final_answer, wiki_search, get_current_time_in_timezone, image_generation_tool], # tavily_search, max_steps=6, verbosity_level=1, grammar=None, planning_interval=None, name=None, description=None, prompt_templates=prompt_templates ) # Launch the Gradio interface GradioUI(agent).launch()