Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from transformers import Conversation, pipeline
+from transformers import pipeline
 
 # Example group recommendation database
 GROUP_DB = [
@@ -7,35 +7,40 @@ GROUP_DB = [
     {"group": "TWICE", "style": "pop"},
     {"group": "BLACKPINK", "style": "pop"},
     {"group": "BTS", "style": "pop"},
-    # Add more groups with styles!
 ]
 
-# Conversational model from Hugging Face
-chatbot = pipeline(model="facebook/blenderbot-400M-distill", task="conversational")
+# Use text2text pipeline instead of deprecated conversational task
+chatbot = pipeline("text2text-generation", model="facebook/blenderbot-400M-distill")
 
 def custom_kpop_response(user_input, history):
     user_input_lower = user_input.lower()
-    # Detect greeting and genre hint from the user
+
+    # Greeting detection
+    greeting = ""
     if any(greet in user_input_lower for greet in ["hi", "hello", "hey"]):
         greeting = "Hi there! Welcome to K-pop world! "
-    else:
-        greeting = ""
-    # Custom pop music recommendation logic
+
+    # Custom recommendation
     if ("taylor swift" in user_input_lower or 
         ("pop" in user_input_lower and "kpop" in user_input_lower)):
-        recommendation = ("If you like Taylor Swift's pop style, "
-                          "you might enjoy K-pop groups like Red Velvet, TWICE, or BLACKPINK! "
-                          "They’re known for catchy melodies and energetic choreography.")
-        return greeting + recommendation
-    # Fallback: let chatbot handle other cases
-    conversation = Conversation(user_input)
-    result = chatbot(conversation)
-    # Just return chatbot's generated text
-    return greeting + conversation.generated_responses[-1]
+        recommendation = (
+            "If you like Taylor Swift's pop style, you might enjoy K-pop groups like "
+            "Red Velvet, TWICE, or BLACKPINK! They’re known for catchy melodies and energetic choreography."
+        )
+        history.append((user_input, greeting + recommendation))
+        return "", history
+
+    # Fallback to model
+    result = chatbot(user_input, max_length=100)
+    bot_reply = greeting + result[0]['generated_text']
+
+    history.append((user_input, bot_reply))
+    return "", history
 
 iface = gr.ChatInterface(
-    custom_kpop_response, 
+    fn=custom_kpop_response,
     title="K-Pop Genie Chatbot",
     description="Say hi! Ask for K-pop groups or songs similar to your Western favorites."
 )
+
 iface.launch()