Update app.py

app.py

@@ -1,8 +1,82 @@
-from datasets import load_dataset
+import gradio as gr
+import pandas as pd
+from datetime import datetime
+import os
 
-# Load the dataset from your Hugging Face Space
-dataset = load_dataset("Abu1998/DataCollection/", split="train")
+# Path for local storage on Hugging Face Space
+STORAGE_PATH = "appointments.csv"
 
-# Convert to pandas DataFrame and save locally
-df = dataset.to_pandas()
-df.to_csv("appointments.csv", index=False)
+# Check if the storage file exists; if not, create it
+if not os.path.exists(STORAGE_PATH):
+    df = pd.DataFrame(columns=[
+        "Date", "Appointment", "Appointment Timing", "Services", "Products",
+        "Contact", "Customer Name", "Rating", "Location", "Key-points", "Price"
+    ])
+    df.to_csv(STORAGE_PATH, index=False)
+
+# Function to save data to CSV
+def save_to_csv(appointment_timing, services, products, contact, customer_name, rating, location, key_points, price):
+    # Load existing data
+    df = pd.read_csv(STORAGE_PATH)
+    
+    # Auto-detect current date and appointment number
+    date = datetime.now().strftime("%Y-%m-%d")
+    appointment = len(df) + 1  # Generate appointment ID
+    
+    # Create a new row as a DataFrame
+    new_row = pd.DataFrame([{
+        "Date": date,
+        "Appointment": appointment,
+        "Appointment Timing": appointment_timing,
+        "Services": services,
+        "Products": products,
+        "Contact": contact,
+        "Customer Name": customer_name,
+        "Rating": rating,
+        "Location": location,
+        "Key-points": key_points,
+        "Price": price
+    }])
+    
+    # Concatenate the new row with the existing DataFrame
+    df = pd.concat([df, new_row], ignore_index=True)
+    df.to_csv(STORAGE_PATH, index=False)  # Save the updated DataFrame to the CSV file
+    return f"Data saved successfully for Appointment {appointment}!"
+
+# Function to provide the download file
+def get_csv_file():
+    return STORAGE_PATH
+
+# Define Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("# Appointment Data Storage Application")
+    appointment_timing = gr.Textbox(label="Appointment Timing")
+    services = gr.Dropdown(
+        label="Services", 
+        choices=["Full arm Rica", "Full leg", "Underarms", "Eyebrow", "Upper lips"],
+        multiselect=True
+    )
+    products = gr.Textbox(label="Products")
+    contact = gr.Textbox(label="Contact")
+    customer_name = gr.Textbox(label="Customer Name")
+    rating = gr.Radio(label="Rating", choices=["Very good", "Good", "Normal", "Bad", "Too bad"])
+    location = gr.Textbox(label="Location")
+    key_points = gr.Textbox(label="Key-points")
+    price = gr.Dropdown(label="Price", choices=["999", "1499", "2499", "3499", "4499"])
+    submit_button = gr.Button("Submit")
+    output = gr.Textbox(label="Output")
+    download_button = gr.File(label="Download Appointments Data", value=STORAGE_PATH)
+
+    submit_button.click(
+        save_to_csv,
+        inputs=[
+            appointment_timing, services, products, contact, customer_name, rating, location, key_points, price
+        ],
+        outputs=output
+    )
+
+    # Add a file download button
+    download_button.render()
+
+# Launch the application
+app.launch(share=True)