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 find_product(num1:int, num2:int)-> int: #it's import to specify the return type # #Keep this format for the description / args / args description but feel free to modify the tool # """A tool that multiplies num1 and num2 # Args: # num1: the first number # num2: the second number # """ # return num1*num2 @tool def greet(name: str)-> str: #it's import to specify the return type #Keep this format for the description / args / args description but feel free to modify the tool """A tool that greets user when the name is specified Args: name: a string representing name of the user """ return f"Hello {name}, Have a nice day!!" @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)}" @tool def get_latest_ai_agent_arxiv_papers(num_papers:int = 5) -> list: """ Searches arXiv for the latest research papers on AI agents and retrieves the specified number of results. Args: num_papers: The number of papers to retrieve (default: 5). Returns: A list of dictionaries, where each dictionary represents a paper and contains its title, authors, and URL. Returns an empty list if any errors occur. Prints informative messages to the console during the search. """ import arxiv try: search = arxiv.Search( query="AI agents", # Your search term max_results=num_papers, sort_by=arxiv.SortCriterion.SubmittedDate # Sort by submission date for latest ) papers = [] for result in search.results(): paper_info = { "title": result.title, "authors": ", ".join([author.name for author in result.authors]), # Nicer author format "url": result.pdf_url, "date": result.published.date(), # Get the date part of the datetime object "abstract": result.summary } papers.append(paper_info) return papers except Exception as e: print(f"An error occurred during the arXiv search: {e}") return [] final_answer = FinalAnswerTool() # 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_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 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 model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud', 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=[final_answer,greet,get_latest_ai_agent_arxiv_papers], ## 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()