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 creative tool that generates emojis based on mood @tool def my_custom_tool(mood: str) -> str: # it's important to specify the return type """A tool that returns a fun emoji sequence based on the given mood. Args: mood: A mood like 'happy', 'sad', 'angry', or 'love'. """ emoji_dict = { "happy": "😊🎉🌈✨😄", "sad": "😢🌧️💔😭🕯️", "angry": "😠🔥💢👿⚡", "love": "😍❤️💌💘😘", "tired": "😴💤☕😩🛌", "excited": "🤩🚀🎊🥳💥", } return f"Mood: {mood}\nEmojis: {emoji_dict.get(mood.lower(), '🤖❓ Unknown mood ❓🤖')}" @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() # 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 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, my_custom_tool, get_current_time_in_timezone, image_generation_tool], # all tools listed max_steps=6, verbosity_level=1, grammar=None, planning_interval=None, name=None, description=None, prompt_templates=prompt_templates ) GradioUI(agent).launch()