Update app.py

app.py

@@ -1,27 +1,60 @@
 import gradio as gr
 from gradio_client import Client, handle_file
 import os
+import smtplib
+from email.message import EmailMessage
 
 BACKEND_SPACE = "CleanSong-AI/Main-tool-backend-main"
 
-def clean_song(file_path):
+# --- Email sender (example with SMTP) ---
+SMTP_SERVER = os.getenv("SMTP_SERVER")      # e.g., smtp.gmail.com
+SMTP_PORT = int(os.getenv("SMTP_PORT", 587))
+SMTP_USER = os.getenv("SMTP_USER")
+SMTP_PASS = os.getenv("SMTP_PASS")
+
+def send_email(to_email, file_path):
+    msg = EmailMessage()
+    msg['Subject'] = "Your CleanSong AI track is ready!"
+    msg['From'] = SMTP_USER
+    msg['To'] = to_email
+    msg.set_content("Hi! Your cleaned track is ready. See the attachment!")
+
+    with open(file_path, 'rb') as f:
+        file_data = f.read()
+        file_name = os.path.basename(file_path)
+
+    msg.add_attachment(file_data, maintype='audio', subtype='mpeg', filename=file_name)
+
+    with smtplib.SMTP(SMTP_SERVER, SMTP_PORT) as server:
+        server.starttls()
+        server.login(SMTP_USER, SMTP_PASS)
+        server.send_message(msg)
+
+# --- Main processing function ---
+def clean_song(file_path, email=None):
     if file_path is None:
         return None
 
+    # Send file to backend
     client = Client(BACKEND_SPACE)
-
     result = client.predict(
-        handle_file(file_path),   # ✅ REQUIRED
+        handle_file(file_path),
         api_name="/predict"
     )
 
-    # Normalize HF return types
+    # Normalize HF return
     if isinstance(result, (list, tuple)):
         result = result[0]
-
     if isinstance(result, dict) and "name" in result:
         result = result["name"]
 
+    # Send email if provided
+    if email:
+        try:
+            send_email(email, result)
+        except Exception as e:
+            print("Failed to send email:", e)
+
     return result
 
 # ------------------------------------------------------------
@@ -29,11 +62,14 @@ def clean_song(file_path):
 # ------------------------------------------------------------
 iface = gr.Interface(
     fn=clean_song,
-    inputs=gr.Audio(type="filepath", label="Upload Song"),
+    inputs=[
+        gr.Audio(type="filepath", label="Upload Song"),
+        gr.Textbox(label="Email (optional)", placeholder="Enter your email to get notified")
+    ],
     outputs=gr.Audio(type="filepath", label="Cleaned Song"),
     title="CleanSong AI - Prototype Frontend",
-    description="Upload a song and get a cleaned version.",
+    description="Upload a song and get a cleaned version. Optionally enter your email to receive the cleaned track."
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()