Update app.py

app.py

@@ -1,34 +1,33 @@
 import gradio as gr
-from transformers import pipeline, AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Create a conversational pipeline with DialoGPT-medium
-chatbot = pipeline("conversational", model="microsoft/DialoGPT-medium")
+# Initialize the DialoGPT model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
 
-# Initialize the GPT-2 tokenizer
-gpt2_tokenizer = AutoTokenizer.from_pretrained("gpt2")
+chat_history = None
 
-def chat(message, history):
-    # Use the GPT-2 tokenizer for user input
-    user_input = gpt2_tokenizer.encode(message, return_tensors="pt")
-
-    # Prepare conversation history as a list of dictionaries
-    conversation = [{"role": "system", "content": "You are a helpful assistant."},
-                    {"role": "user", "content": message}]
+def chat(message):
+    global chat_history
+    
+    # Encode the user's message with the GPT-2 tokenizer
+    input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors="pt")
     
-    if history:
-        conversation.append({"role": "assistant", "content": history})
-
     # Generate a response from DialoGPT-medium
-    response = chatbot(conversation)
-    bot_response = response[0]['message']['content']
-
+    response_ids = model.generate(input_ids, max_length=150, pad_token_id=tokenizer.eos_token_id, num_return_sequences=1)
+    
+    # Decode and return the bot's response
+    bot_response = tokenizer.decode(response_ids[0], skip_special_tokens=True)
+    
+    chat_history = bot_response  # Store the bot's response for reference
+    
     return bot_response
 
 # Create and launch the Gradio interface
-iface = gr.ChatInterface(
-    chat,
+iface = gr.Interface(
+    fn=chat,
     title="UrFriendly Chatbot",
-    description="UrFriendly Chatbot is a conversational assistant based on DialoGPT-medium and GPT-2 tokenizer. Type or click on one of the examples to get started. Please note that UrFriendly Chatbot is not 100% accurate, so incorrect information may generate. 💬🤗",
+    description="UrFriendly Chatbot is a conversational assistant based on DialoGPT-medium with GPT-2 tokenization. Type or click on one of the examples to get started. Please note that UrFriendly Chatbot is not 100% accurate, so incorrect information may generate. 💬🤗",
     examples=[
         "Howdy!",
         "Tell me a joke.", 
@@ -37,10 +36,9 @@ iface = gr.ChatInterface(
         "What is an exponent in mathematics?",
         "Does money buy happiness?"
     ],
-    retry_btn=None,
-    undo_btn="Undo",
-    clear_btn="Clear conversation"
+    inputs="text",
+    outputs="text",
+    live=True  # Set to True to allow continuous conversation
 )
 
-iface.queue()
 iface.launch()