model_training/train.py

import os
import joblib
import pandas as pd
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier

# Set up directories
MODEL_DIR = "models"
os.makedirs(MODEL_DIR, exist_ok=True)
MODEL_PATH = os.path.join(MODEL_DIR, "iris_model.joblib")

def train_model():
    print("Loading Iris dataset...")
    iris = load_iris()
    X, y = iris.data, iris.target

    print("Training Random Forest Classifier...")
    clf = RandomForestClassifier(n_estimators=100, random_state=42)
    clf.fit(X, y)

    print(f"Saving model to {MODEL_PATH}...")
    joblib.dump(clf, MODEL_PATH)
    print("Model saved successfully!")

if __name__ == "__main__":
    train_model()