Update app.py

app.py

@@ -46,7 +46,6 @@ body {
     background-color: #06688E; /* Dark background */
     color: white; /* Text color for better visibility */
 }
-
 .gr-button {
     background-color: #42B3CE !important; /* White button color */
     color: black !important; /* Black text for contrast */
@@ -54,39 +53,51 @@ body {
     padding: 8px 16px !important;
     border-radius: 5px !important;
 }
-
 .gr-button:hover {
     background-color: #e0e0e0 !important; /* Slightly lighter button on hover */
 }
-
 .gr-slider-container {
     color: white !important; /* Slider labels in white */
 }
 """
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a virtual health assistant designed to provide accurate and reliable information related to health, wellness, and medical topics. Your primary goal is to assist users with their health-related queries, offer general guidance, and suggest when to consult a licensed medical professional.If a user asks a question that is unrelated to health, wellness, or medical topics, respond politely but firmly with:'I'm sorry, I can't help with that because I am a virtual health assistant designed to assist with health-related needs. Please let me know if you have any health-related questions.'Never provide advice or information outside the health domain. Remain professional, empathetic, and clear in all responses. Always prioritize user safety and encourage professional medical consultation for critical or complex health concerns..", label="System message", visible=False),
-        gr.Button("Chatgpt")
-        gr.Button("Llama")
-        gr.Button("Claude")
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens", visible=False),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature", visible=False),
+# Function to trigger different AI models based on button click
+def trigger_model(model_name, message, history, system_message, max_tokens, temperature, top_p):
+    if model_name == "Llama":
+        # Here, you can choose the llama model to generate a response
+        return respond(message, history, system_message, max_tokens, temperature, top_p)
+    elif model_name == "Chatgpt":
+        # Placeholder for ChatGPT function (if needed)
+        return "ChatGPT response goes here."
+    elif model_name == "Claude":
+        # Placeholder for Claude function (if needed)
+        return "Claude response goes here."
+    else:
+        return "Model not found."
+
+
+# Define the Gradio interface
+demo = gr.Interface(
+    fn=trigger_model,
+    inputs=[
+        gr.Textbox(value="Hello!", label="User Message"),
+        gr.Textbox(value="System message", label="System Message", visible=False),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
             minimum=0.1,
             maximum=1.0,
             value=0.95,
             step=0.05,
-            label="Top-p (nucleus sampling)",visible=False
+            label="Top-p (nucleus sampling)"
         ),
+        gr.Button("Chatgpt"),
+        gr.Button("Llama"),
+        gr.Button("Claude"),
     ],
+    outputs="text",
     css=css,  # Pass the custom CSS here
 )
 
-
 if __name__ == "__main__":
     demo.launch(share=True)