Update app.py

app.py

@@ -2,21 +2,14 @@ import gradio as gr
 import pandas as pd
 from datetime import datetime
 import os
-from huggingface_hub import HfApi, HfFolder, Repository
+from huggingface_hub import Repository
 
-# Authenticate with Hugging Face using the secret token
-api = HfApi()
-HfFolder.save_token(HF_TOKEN)
+# Constants
+HF_TOKEN = os.getenv("HF_TOKEN")  # Retrieve token from environment variables
+STORAGE_PATH = "appointments.csv"  # Local CSV file path
+REPO_ID = "Abu1998/DataCollection"  # Your Hugging Face dataset repo
 
-# Use the token to access or modify your repository
-repo = Repository(local_dir="temp_repo", clone_from="Abu1998/DataCollection", use_auth_token=HF_TOKEN)
-
-
-# Authenticate with Hugging Face Hub
-api = HfApi()
-HfFolder.save_token(HF_TOKEN)
-
-# Ensure the CSV file exists
+# Ensure the CSV file exists locally
 if not os.path.exists(STORAGE_PATH):
     df = pd.DataFrame(columns=[
         "Date", "Appointment", "Appointment Timing", "Services", "Products",
@@ -24,59 +17,63 @@ if not os.path.exists(STORAGE_PATH):
     ])
     df.to_csv(STORAGE_PATH, index=False)
 
-# Function to upload CSV to Hugging Face Hub
+# Function to upload the CSV to Hugging Face Hub
 def upload_to_huggingface():
-    repo = Repository(local_dir="temp_repo", clone_from=REPO_ID, use_auth_token=HF_TOKEN)
-    repo.git_pull()  # Ensure the latest version
-    os.makedirs("temp_repo", exist_ok=True)
-    df = pd.read_csv(STORAGE_PATH)
-    df.to_csv(os.path.join("temp_repo", "appointments.csv"), index=False)
-    repo.git_add("appointments.csv")
-    repo.git_commit("Updated appointments data")
-    repo.git_push()
-    return "Data uploaded to Hugging Face successfully!"
+    try:
+        repo = Repository(local_dir="temp_repo", clone_from=REPO_ID, use_auth_token=HF_TOKEN)
+        repo.git_pull()  # Pull the latest changes
+        os.makedirs("temp_repo", exist_ok=True)
+        df = pd.read_csv(STORAGE_PATH)
+        df.to_csv(os.path.join("temp_repo", "appointments.csv"), index=False)
+        repo.git_add("appointments.csv")
+        repo.git_commit("Updated appointments data")
+        repo.git_push()
+        return "Data uploaded to Hugging Face successfully!"
+    except Exception as e:
+        return f"Error uploading data: {e}"
 
-# Function to save data locally and upload to Hugging Face
+# Function to save data locally and upload it
 def save_and_upload_to_csv(appointment_timing, services, products, contact, customer_name, rating, location, key_points, price):
-    # Load existing data
-    df = pd.read_csv(STORAGE_PATH)
+    try:
+        # Load existing data
+        df = pd.read_csv(STORAGE_PATH)
 
-    # Auto-detect date and appointment ID
-    date = datetime.now().strftime("%Y-%m-%d")
-    appointment = len(df) + 1
+        # Auto-detect date and appointment ID
+        date = datetime.now().strftime("%Y-%m-%d")
+        appointment = len(df) + 1
 
-    # Add a new row
-    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
-    }])
-
-    # Append and save locally
-    df = pd.concat([df, new_row], ignore_index=True)
-    df.to_csv(STORAGE_PATH, index=False)
+        # Add a new row
+        new_row = pd.DataFrame([{
+            "Date": date,
+            "Appointment": appointment,
+            "Appointment Timing": appointment_timing,
+            "Services": ', '.join(services) if isinstance(services, list) else services,
+            "Products": products,
+            "Contact": contact,
+            "Customer Name": customer_name,
+            "Rating": rating,
+            "Location": location,
+            "Key-points": key_points,
+            "Price": price
+        }])
 
-    # Upload to Hugging Face
-    upload_to_huggingface()
+        # Append and save locally
+        df = pd.concat([df, new_row], ignore_index=True)
+        df.to_csv(STORAGE_PATH, index=False)
 
-    return f"Appointment {appointment} saved and uploaded successfully!"
+        # Upload to Hugging Face
+        upload_message = upload_to_huggingface()
+        return f"Appointment {appointment} saved locally and uploaded! {upload_message}"
+    except Exception as e:
+        return f"Error saving data: {e}"
 
 # Gradio Interface
 with gr.Blocks() as app:
     gr.Markdown("# Appointment Data Storage Application")
     appointment_timing = gr.Textbox(label="Appointment Timing")
-    services = gr.Dropdown(
+    services = gr.CheckboxGroup(
         label="Services", 
-        choices=["Full arm Rica", "Full leg", "Underarms", "Eyebrow", "Upper lips"],
-        multiselect=True
+        choices=["Full arm Rica", "Full leg", "Underarms", "Eyebrow", "Upper lips"]
     )
     products = gr.Textbox(label="Products")
     contact = gr.Textbox(label="Contact")