Update app.py

app.py

@@ -1,22 +1,28 @@
 import gradio as gr
 import pandas as pd
+from datetime import datetime
+import pytz  # This library is used for timezone conversions
 
-def display_csv(file, supplier):
+def display_csv(file, supplier, order_number):
     df = pd.read_csv(file.name)
-    
+
     # Define supplier-specific filters
     vendor_filters = {
-        "Supplier 1": lambda df: df[~df['Vendor'].isin(["Seed", "EverColor", "Candy Magic", "OLENS", "Fairy", "Shobido", "Geo Medical", "Ann365"])],
+        "Supplier 1": lambda df: df[~df['Vendor'].isin(["Seed", "EverColor", "Candy Magic", "OLENS", "Fairy", "Shobido", "Geo Medical", "Ann365", "Lenstown", "LensVery"])],
         "Supplier 2": lambda df: df[df['Vendor'].isin(["Candy Magic", "OLENS", "Fairy", "Shobido"])],
         "Supplier 3": lambda df: df[df['Vendor'].isin(["Seed", "EverColor"])],
-        "Supplier 4": lambda df: df[df['Vendor'] == "Geo Medical"],
-        "Supplier 5": lambda df: df[df['Vendor'] == "Ann365"]
+        "Supplier 4": lambda df: df[df['Vendor'] == "Geo Medical", "Lenstown"],
+        "Supplier 5": lambda df: df[df['Vendor'] == "Ann365", "LensVery"]
     }
-    
-    # Apply filter based on selected supplier
+
+    # Apply supplier filter if selected
     if supplier and supplier in vendor_filters:
         df = vendor_filters[supplier](df)
-    
+
+    # Filter based on order number
+    if order_number:
+        df = df[df['Order Number'] >= int(order_number)]
+
     # Specify columns for output
     columns_to_include = [
         'Order Number', 'Quantity', 'Product Title', 'Product Option Name',
@@ -25,27 +31,36 @@ def display_csv(file, supplier):
         'Order Line item Properties 3 Value'
     ]
     download_df = df[columns_to_include]
-    
-    # Save filtered DataFrame as CSV file
-    output_file = "filtered_output.csv"
-    download_df.to_csv(output_file, index=False)
+
+    # Get the current date in Hong Kong Time
+    hk_timezone = pytz.timezone("Asia/Hong_Kong")
+    current_date_hk = datetime.now(hk_timezone).strftime("%y%m%d")
+
+    # Set output file name based on the selected supplier
+    if supplier == "Supplier 1":
+        output_file = f"Leading Bridge Order {current_date_hk}.xlsx"
+    elif supplier == "Supplier 2":
+        output_file = f"Leading Bridge Order {current_date_hk}-Ammu.xlsx"
+    else:
+        output_file = "filtered_output.xlsx"  # Default file name for other cases
+
+    # Save filtered DataFrame as Excel file
+    download_df.to_excel(output_file, index=False)
     return df, output_file
 
 # Define the main block for the interface
 with gr.Blocks() as demo:
-    with gr.Tab("CSV Viewer"):
-        with gr.Row():
-            file_input = gr.File(label="Upload CSV")
-            supplier_input = gr.Dropdown(choices=["", "Supplier 1", "Supplier 2", "Supplier 3", "Supplier 4", "Supplier 5"], label="Select Supplier")
-            load_button = gr.Button("Load Data")
-        with gr.Row():
-            output_df = gr.DataFrame()
-            output_file = gr.File(label="Download Filtered CSV")
-
-        # Bind the function to inputs and outputs using the button
-        load_button.click(fn=display_csv, inputs=[file_input, supplier_input], outputs=[output_df, output_file])
-
-    # You can add more tabs here with different functions
+    with gr.Row():
+        file_input = gr.File(label="Upload CSV")
+        supplier_input = gr.Dropdown(choices=["", "Supplier 1", "Supplier 2", "Supplier 3", "Supplier 4", "Supplier 5"], label="Select Supplier")
+        order_number_input = gr.Number(label="Minimum Order Number", precision=0)
+        load_button = gr.Button("Load Data")
+    with gr.Row():
+        output_df = gr.DataFrame()
+        output_file = gr.File(label="Download Filtered CSV")
+
+    # Bind the function to inputs and outputs using the button
+    load_button.click(fn=display_csv, inputs=[file_input, supplier_input, order_number_input], outputs=[output_df, output_file])
 
 # Run the interface
 demo.launch()