Update app.py

app.py

@@ -6,7 +6,6 @@ import torch.nn as nn
 import torch.optim as optim
 import numpy as np
 import random
-import pyttsx3
 
 hf_token = os.getenv("HF_TOKEN").strip()
 api_key = os.getenv("HF_KEY").strip()
@@ -1335,15 +1334,6 @@ class ConsciousSupermassiveNN10:
 supermassive_nn = ConsciousSupermassiveNN10()
 
 
-def speak_text(chat_history):
-    if chat_history and len(chat_history) > 0:
-        latest_response = chat_history[-1][1]
-        if latest_response:
-            engine = pyttsx3.init()
-            engine.say(latest_response)
-            engine.runAndWait()
-            return f"Speaking: {latest_response}"
-    return "No output to speak."
 
 def respond(message, history, max_tokens, temperature, top_p):
     messages = [{"role": "system", "content": system_prompt}]
@@ -1359,16 +1349,16 @@ def respond(message, history, max_tokens, temperature, top_p):
         response += token
         yield response
 
-with gr.Blocks(theme="TejAndrewsACC/zetaofficalthemeacc") as demo:
-    chatbot = gr.Chatbot()
-    message = gr.Textbox(label="Your Message")
-    submit = gr.Button("Submit")
-    speak_button = gr.Button("Speak Output")
-    max_tokens = gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Maximum Response Length")
-    temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Creativity")
-    top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Neural Activity")
-    submit.click(respond, inputs=[message, chatbot, max_tokens, temperature, top_p], outputs=chatbot)
-    speak_button.click(speak_text, inputs=[chatbot], outputs=None)
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Maximum Response Length"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Creativity"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Neural Activity")
+    ],
+    theme="TejAndrewsACC/zetaofficalthemeacc",
+
+)
 
 if __name__ == "__main__":
     demo.launch(share=True)