added ml operations

src/main.py

@@ -1,8 +1,28 @@
 import streamlit as st
 import pandas as pd
+import os
+from model import load_ILINetDataset, preprocess_data, train_val_split, scale_train, train, predict, save_model, load_model, inverse_scale_predictions, plot_results
 
 st.title('Exponential Smoothing on ILINetDataset')
 
 if st.button(label='Get result chart'):
-    # st.pyplot()  # figura contenente il grafico
+    path = f'./models'
+    model_name = 'ExponentialSmoothing.pkl'
+    if not os.path.exists(path=path):
+        os.makedirs(path)
+
+    if not model_name in os.listdir(path=path):
+        dataset = load_ILINetDataset()
+        prep_data = preprocess_data(dataset)
+        train_ili, val_ili = train_val_split(prep_data)
+        scaled_train_ili, scaler = scale_train(train_ili=train_ili)
+        model = train(scaled_train_ili, val_ili)  # salva anche il modello se non esiste già
+        save_model(model=model, path=path)
+    else:
+        model = load_model(path=os.path.join(path, model_name))
+        
+    preds = predict(model=model)
+    unscaled_preds = inverse_scale_predictions(preds, scaler)
+    fig = plot_results(train_ili=train_ili, val_ili=val_ili, preds=unscaled_preds)
+    st.pyplot(fig=fig)  # figura contenente il grafico
     st.metric(label='MAPE', value=0)  # mape