Update app.py

app.py

@@ -1,3 +1,7 @@
+from transformers import pipeline
+generator = pipeline('text-generation', model = 'isitcoding/gpt2_120_finetuned')
+generator("", max_length = 1028, num_return_sequences=3)
+
 '''import os
 import gradio as gr
 from transformers import pipeline
@@ -72,35 +76,4 @@ iface = gr.Interface(
 iface.launch()
 '''
 
-import gradio as gr
-from transformers import pipeline
-
-# Load a text generation model (e.g., GPT-2 or a model of your choice)
-generator = pipeline("text-generation", model="isitcoding/gpt2_120_finetuned", tokenizer="isitcoding/gpt2_120_finetuned")
 
-# Function to generate assistant's response based on user input
-def generate_response(messages):
-    # Extract the user message from the input format
-    user_message = messages[-1]["content"]
-    
-    # Generate a response based on the user's input
-    response = generator(user_message, max_length=100, num_return_sequences=1)
-    
-    # Get the assistant's message from the generated output
-    assistant_message = response[0]["generated_text"]
-    
-    # Return the updated conversation with user and assistant messages
-    messages.append({"role": "assistant", "content": assistant_message})
-    return messages
-
-# Set up the Gradio interface
-iface = gr.Interface(
-    fn=generate_response,
-    inputs=gr.Textbox(placeholder="Type your message..."),  # User input
-    outputs=gr.JSON(),  # JSON format output to display the conversation
-    live=True,  # Ensure real-time updates
-    title="Text Generation Pipeline",
-    description="Enter a message to get a response from the assistant."
-)
-
-iface.launch()