from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import os import pytz import yaml from tools.final_answer import FinalAnswerTool from Gradio_UI import GradioUI import joblib from sklearn.ensemble import RandomForestClassifier from sklearn.preprocessing import LabelEncoder import pandas as pd os.getenv("HF_TOKEN") @tool def predict_obesity_level(weight:float, age:int, height:float, isMale:bool)-> 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 predicts the obesity level of an individual based on weight, age, height and whether the individual is Male or not. Args: weight: the weight of the individual in kilograms age: the age of the individual in years height: the height of the individual in meters isMale: True if the individual is male, False otherwise """ try: # load model obesity_model = joblib.load("rf_obesity_classifier.joblib") # load Label Encoder label_encoder = joblib.load("le_obesity.joblib") # format data in a dataframe for scoring data = { "Weight":[weight], "Age":[age], "Height":[height], "Gender_Male":[isMale] } X_new = pd.DataFrame(data) prediction = label_encoder.inverse_transform(obesity_model.predict(X_new))[0] result = f"The obesity level is {prediction}" return result except Exception as e: return f"Error predicting the obesity level: {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() # 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, predict_obesity_level, get_current_time_in_timezone], max_steps=6, verbosity_level=1, grammar=None, planning_interval=None, name=None, description=None, prompt_templates=prompt_templates ) GradioUI(agent).launch()