Update app.py

app.py

@@ -1,94 +1,69 @@
 import gradio as gr
 
-# Placeholder for model loading (adjust as needed for your specific models)
 def load_model(model_name):
-    # Replace this function with actual model loading code if needed
     return lambda input_text: f"Response from {model_name}: {input_text}"
 
-# Load the models (placeholder functions here)
 deepseek_r1_distill = load_model("DeepSeek-R1-Distill-Qwen-32B")
 deepseek_r1 = load_model("DeepSeek-R1")
 deepseek_r1_zero = load_model("DeepSeek-R1-Zero")
 
-# Define the optional parameters section
 def create_optional_parameters():
-    with gr.Accordion("Optional Parameters (Click to Expand)", open=False):
+    with gr.Accordion("Optional Parameters", open=False):
         system_message = gr.Textbox(
             label="System Message", 
             value="You are a friendly Chatbot created by ruslanmv.com",
-            lines=2,
-            interactive=True
+            lines=2
         )
-        max_new_tokens = gr.Slider(minimum=1, maximum=4000, value=200, label="Max New Tokens", interactive=True)
-        temperature = gr.Slider(minimum=0.10, maximum=4.00, value=0.70, label="Temperature", interactive=True)
-        top_p = gr.Slider(minimum=0.10, maximum=1.00, value=0.90, label="Top-p (nucleus sampling)", interactive=True)
+        max_new_tokens = gr.Slider(minimum=1, maximum=4000, value=200, label="Max New Tokens")
+        temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, label="Temperature")
+        top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, label="Top-p (nucleus sampling)")
     return system_message, max_new_tokens, temperature, top_p
 
-# Define the main interface
 def chat_interface(user_input, system_message, max_new_tokens, temperature, top_p):
-    # Placeholder response - integrate with actual model here
     response = f"""**System Message**: {system_message}
 **Your Input**: {user_input}
 **Parameters Used**:
 - Max New Tokens: {max_new_tokens}
 - Temperature: {temperature}
 - Top-p: {top_p}
-
 *Note: Actual model integration required for real responses*"""
     return response
 
-# Create the Gradio interface
 with gr.Blocks(css="""
-    .gradio-container {
-        font-family: Arial, sans-serif;
-        background-color: #f9f9f9;
-        color: #333;
-        padding: 20px;
-    }
-    .gr-button.primary {
-        background-color: #4caf50;
-        color: white;
-        border: none;
-        padding: 10px 20px;
-        font-size: 16px;
-        border-radius: 5px;
-        cursor: pointer;
-    }
-    .gr-button.primary:hover {
-        background-color: #45a049;
-    }
-    .gr-textbox textarea {
-        font-size: 16px;
-    }
+    .chat-container { max-width: 700px; margin: auto; }
+    .chat-input { margin-top: 20px; }
+    .chat-output { margin-top: 10px; padding: 10px; border: 1px solid #ccc; border-radius: 10px; background-color: #f9f9f9; }
 """) as demo:
-    gr.Markdown("""
-    # DeepSeek Chatbot
-    Welcome to the **DeepSeek Chatbot**! This AI-powered chatbot is designed to provide insightful responses.
-    Created by [ruslanmv.com](https://ruslanmv.com/).
-    """)
-    
-    with gr.Row():
-        with gr.Column(scale=3):
+    with gr.Row(variant="panel"):
+        gr.Markdown(
+            """# DeepSeek Chatbot  
+            Created by [ruslanmv.com](https://ruslanmv.com/)  
+            A friendly chatbot interface. Start a conversation below!
+            """,
+            elem_id="header"
+        )
+
+    with gr.Row(elem_classes="chat-container"):
+        with gr.Column():
             user_input = gr.Textbox(
                 label="Your Message",
                 placeholder="Type your message here...",
-                lines=4,
-                interactive=True
+                lines=3,
+                elem_classes="chat-input"
             )
-            submit_button = gr.Button("Send", variant="primary")
-        with gr.Column(scale=5):
-            output = gr.Markdown(label="Chatbot Response")
-    
-    # Add the optional parameters section
-    system_message, max_new_tokens, temperature, top_p = create_optional_parameters()
-    
-    # Link the submit button to the chat interface
+            submit_button = gr.Button("Submit", variant="primary")
+            system_message, max_new_tokens, temperature, top_p = create_optional_parameters()
+        with gr.Column():
+            output = gr.Markdown(
+                label="Chatbot Response", 
+                elem_classes="chat-output"
+            )
+
     submit_button.click(
         chat_interface,
         inputs=[user_input, system_message, max_new_tokens, temperature, top_p],
         outputs=output
     )
 
-# Launch the demo
 if __name__ == "__main__":
     demo.launch()