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| 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") | |
| 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)}" | |
| 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() |