Update app.py

app.py

@@ -1,13 +1,15 @@
-import os
+'''import os
 import gradio as gr
 from transformers import pipeline
+from huggingface_hub import InferenceClient
 
-hf_token = os.getenv("hf_token")
+hf_token = os.getenv("gpt2_token")
 # Initialize the text generation pipeline
-generator = pipeline("text-generation", model="isitcoding/gpt2_120_finetuned", use_auth_token=hf_token)
+client = 
+generator = pipeline("text-generation", )
 
 # Define the response function with additional options for customization
-'''def text_generation(
+def text_generation(
     prompt: str,
     details: bool = False,
     stream: bool = False,
@@ -70,11 +72,35 @@ iface = gr.Interface(
 iface.launch()
 '''
 
-# Test model generation
-def generate_response(prompt):
-    response = generator(prompt, max_length=50)
-    return response[0]["generated_text"]
-
-# Gradio interface
 import gradio as gr
-gr.Interface(fn=generate_response, inputs="text", outputs="text").launch()
+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()