from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool from Gradio_UI import GradioUI # Below is an example of a tool that does nothing. Amaze us with your creativity ! @tool def summary_of_paper(query: str, max_results: int = 1) -> str: """A tool that searches for a paper on arXiv and summarizes it using a language model. Args: query: The search query for the paper. max_results: The maximum number of search results to return. """ try: # Search for the paper on arXiv search_url = f"http://export.arxiv.org/api/query?search_query={query}&max_results={max_results}" response = requests.get(search_url) if response.status_code != 200: return f"Error fetching paper from arXiv: {response.status_code}" # Parse the response papers = response.text # For simplicity, let's assume we extract the first paper's summary # In a real implementation, you would parse the XML response properly start_idx = papers.find('') + len('') end_idx = papers.find('', start_idx) paper_summary = papers[start_idx:end_idx].strip() # Summarize the paper using a language model summary_prompt = f"Summarize the following paper: {paper_summary}" summary_response = model.generate(summary_prompt) return f"the summary of the paper is: {summary_response}" except Exception as e: return f"Error summarizing paper: {str(e)}" @tool def get_current_time_in_timezone(timezone: str) -> str: """A tool that fetches the current local time in a specified timezone. Args: timezone: A string representing a valid timezone (e.g., 'America/New_York'). """ try: # Create timezone object tz = pytz.timezone(timezone) # Get current time in that timezone local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") return f"The current local time in {timezone} is: {local_time}" except Exception as e: return f"Error fetching time for timezone '{timezone}': {str(e)}" final_answer = FinalAnswerTool() model = HfApiModel( max_tokens=2096, temperature=0.5, model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded custom_role_conversions=None, ) # Import tool from Hub image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) with open("prompts.yaml", 'r') as stream: prompt_templates = yaml.safe_load(stream) agent = CodeAgent( model=model, tools=[summary_of_paper, final_answer], ## add your tools here (don't remove final answer) max_steps=6, verbosity_level=1, grammar=None, planning_interval=None, name=None, description=None, prompt_templates=prompt_templates ) GradioUI(agent).launch()