Guardar mis cambios locales

app.py

@@ -1,9 +1,6 @@
 import gradio as gr
 import pandas as pd
-import numpy as np
-import plotly.graph_objects as go
 import joblib  # Para cargar el modelo ARIMA guardado
-from datetime import datetime
 
 # Función para cargar el modelo ARIMA guardado
 def load_arima_model():
@@ -36,12 +33,24 @@ def merge_forecast_data(actual, predicted, future):
         "Forecasted Future Sales": future
     })
 
+# Función para mostrar una alerta si el archivo no es CSV
+def check_file(uploaded_file):
+    if uploaded_file is None:
+        return gr.Error("⚠️ No file uploaded. Please upload a CSV file.")
+
+    if uploaded_file.name.endswith('.csv'):
+        return None  # Si el archivo es CSV, no hay error
+    else:
+        return gr.Error("⚠️ Invalid file format. Please upload a CSV file.")  # Mostrar alerta si no es CSV
+
 # Función principal para la carga de archivo y la predicción
 def upload_and_forecast(uploaded_file, period):
-    if uploaded_file is None:
-        return "⚠️ Please upload a file to proceed."
+    # Verificar si el archivo cargado es CSV
+    error_message = check_file(uploaded_file)
+    if error_message:
+        return error_message
 
-    df = pd.read_csv(uploaded_file)
+    df = pd.read_csv(uploaded_file)  # Leer el archivo CSV
     df = drop(df)
     df = date_format(df)
     series = group_to_three(df)
@@ -77,7 +86,7 @@ def upload_and_forecast(uploaded_file, period):
 def create_sidebar():
     with gr.Column():
         gr.Markdown("### 📂 Upload your sales data (CSV)")
-        uploaded_file = gr.File(label="Choose your file", elem_id="file-uploader")
+        uploaded_file = gr.File(label="Choose your file", elem_id="file-uploader", type="file")
         gr.Markdown("### ⏳ Forecast Period (Days)")
         period = gr.Slider(minimum=30, maximum=90, step=1, label="Forecast period (in days)")
         return uploaded_file, period