from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool, Tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool from Gradio_UI import GradioUI class HFModelDownloadsTool(Tool): name = "model_download_counter" description = """ This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub. It returns the name of the checkpoint.""" inputs = { "task": { "type": "string", "description": "the task category (such as text-classification, depth-estimation, etc)", } } output_type = "string" def forward(self, task: str): from huggingface_hub import list_models model = next(iter(list_models(filter=task, sort="downloads", direction=-1))) return model.id # Below is an example of a tool that does nothing. Amaze us with your creativity ! @tool def calculator_multiply(num1:int, num2:int)-> int: """A tool that multiplies the two provided numbers. Args: num1: the first argument num2: the second argument """ return num1 * num2 @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 search_wikipedia(query: str) -> str: """ Fetches a summary of a Wikipedia page for a given query. Args: query: The search term to look up on Wikipedia. Returns: str: A summary of the Wikipedia page if successful, or an error message if the request fails. Raises: requests.exceptions.RequestException: If there is an issue with the HTTP request. """ url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{query}" try: response = requests.get(url) response.raise_for_status() data = response.json() title = data["title"] extract = data["extract"] return f"Summary for {title}: {extract}" except requests.exceptions.RequestException as e: return f"Error fetching Wikipedia data: {str(e)}" final_answer = FinalAnswerTool() model = HfApiModel( max_tokens=2096, temperature=0.5, model_id='Qwen/Qwen2.5-Coder-32B-Instruct', custom_role_conversions=None, ) # Import tool from Hub image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) web_search_tool = DuckDuckGoSearchTool() model_downloads_tool = HFModelDownloadsTool() object_detection_tool = Tool.from_space( space_id="kadirnar/Yolov10", name="object-detector", description="Detect objects within an image" ) with open("prompts.yaml", 'r') as stream: prompt_templates = yaml.safe_load(stream) agent = CodeAgent( model=model, tools=[final_answer, image_generation_tool, web_search_tool, model_downloads_tool, object_detection_tool, search_wikipedia], ## 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()