Update app.py

app.py

@@ -7,19 +7,22 @@ from transformers import pipeline
 api_key = os.getenv("LLAMA")
 login(api_key)
 
-# Load the Llama model
+# Load the model using the Hugging Face Hub
 llama_model = gr.load("models/meta-llama/Llama-3.1-8B-Instruct")
 
-# Function to handle inputs and outputs
+# Function to handle input and output
 def chat_with_llama(user_input):
-    # Generate response using the pipeline
-    response = llama_model(user_input)
-    return response
-
-# Customize Gradio interface
+    # Ensure user_input is correctly formatted as a string
+    if isinstance(user_input, str):
+        response = llama_model([user_input])  # Pass input as a list
+        return response[0]  # Return the first element of the output list
+    else:
+        return "Invalid input. Please provide a valid text."
+
+# Customize the Gradio interface
 with gr.Blocks(css=".title {font-size: 3em; font-weight: bold; text-align: center; color: #4A90E2;}") as demo:
     
-    # Header section
+    # Header
     gr.Markdown(
         """
         <div class="title">🦙 Llama 3.1 Chatbot 🦙</div>
@@ -28,20 +31,20 @@ with gr.Blocks(css=".title {font-size: 3em; font-weight: bold; text-align: cente
         elem_classes="header"
     )
     
-    # Main input/output section
+    # Main Input/Output Section
     with gr.Row():
         with gr.Column(scale=1):
             user_input = gr.Textbox(label="Your question", placeholder="Type your question here...", lines=4)
         with gr.Column(scale=1):
             response_output = gr.Textbox(label="Llama's response", lines=4)
 
-    # Button to submit the input
+    # Button to submit input
     submit_button = gr.Button("Submit", variant="primary")
 
     # Link the input and output
     submit_button.click(fn=chat_with_llama, inputs=user_input, outputs=response_output)
 
-    # Footer section
+    # Footer
     gr.Markdown(
         """
         <div style="text-align:center; font-size:0.8em; color:gray;">Developed with ❤️ using Llama 3.1 and Gradio</div>