from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool from tools.final_answer import FinalAnswerTool from Gradio_UI import GradioUI import os, sys, datetime, requests, pytz, yaml from dotenv import load_dotenv final_answer = FinalAnswerTool() # ============================================================================================ # Uncomment when runnng locally. Leave commented when running atop HuggingFace Hub. # ============================================================================================ # load_dotenv(f"{os.path.expanduser("~")}/WORKSPACES.d/AGENTIC.GEN.AI.d/.env") # ============================================================================================ # ============================================================================================ # Here's an example of a tool that does nothing, but it shows the structure you should follow. # - Reuse this format for the DESCRIPTION, the ARGS, and the ARGS DESCRIPTIONS. # - However, copy template and feel free to modify the tool. # - Important: It's important to always specify the function's return type. # ============================================================================================ @tool def my_custom_tool(arg1:str, arg2:int) -> str: """An example custom tool that does nothing. Args: arg1: The first argument. arg2: The second argument. """ return "Hello, World!" # ============================================================================================ @tool def get_current_time_in_timezone(timezone: str) -> str: """A tool that retrieves the current local time in a specified timezone. Args: timezone: A string representing a valid timezone (e.g., 'America/New_York'). """ try: tz = pytz.timezone(timezone) # Create timezone object. local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") # Get current time in that TZ. 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)}" # ================================================================================ # If the agent does not answer, the model is likely overloaded. Please use a different model, # or use the following HuggingFace Inference 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', # Change if overloaded. #token = os.environ['HF_TOKEN'], # Uncomment when run locally; Comment when run on HF Hub. custom_role_conversions=None,) # ================================================================================ # ================================================================================ # Use load_tool() from the 'smolagents' library to get ready-made tools available # in HuggingFace Hub. # ================================================================================ image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) # ================================================================================ with open("prompts.yaml", 'r') as stream: # yaml.safe_load() permits only built-in prompt_templates = yaml.safe_load(stream) # Python datastructures to be instantiated. agent = CodeAgent( model=model, tools=[final_answer, image_generation_tool], # Append 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()