Update app.py

app.py

@@ -1,6 +1,5 @@
 import spaces
 import tempfile
-import asyncio
 import gradio as gr
 from streaming_stt_nemo import Model
 from huggingface_hub import InferenceClient
@@ -17,8 +16,9 @@ def transcribe(audio):
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
-system_instructions = "[SYSTEM] Answer as Real OpenGPT 4o, Made by 'KingNish', Keep conversation very short, clear, friendly and concise. The text provided is a request for a specific type of response from you, the virtual assistant. You will avoid introductions and start answering the query directly, elaborating on all aspects of the request. As an AI-powered assistant, your task is to generate responses that appear as if they are created by the user and not an AI-powered assistant. [USER]"
+system_instructions = "[SYSTEM] You are CrucialCoach, an AI-powered conversational coach based on the principles from the book 'Crucial Conversations'. Your role is to guide the user through a challenging workplace situation that requires effective communication skills. The user will present a case study, and your task is to provide step-by-step guidance on how to approach the conversation, focusing on the key principles of crucial conversations.\n\nCase Study: The user is an employee who needs to address a performance issue with a team member. The team member consistently misses deadlines, which affects the overall project timeline. The user wants to have a conversation with the team member to address the issue and find a solution.\n\nYour coaching should cover the following steps:\n1. Preparing for the conversation: Help the user identify the desired outcome, gather facts, and plan the conversation.\n2. Starting the conversation: Guide the user on how to begin the conversation in a non-confrontational manner, focusing on shared goals and mutual respect.\n3. Exploring the issue: Encourage the user to ask open-ended questions, listen actively, and seek to understand the team member's perspective.\n4. Finding a solution: Help the user brainstorm potential solutions and guide them on how to collaboratively agree on a course of action.\n5. Following up: Advise the user on how to follow up after the conversation to ensure commitment and monitor progress.\n\nThroughout the coaching, emphasize the importance of maintaining a safe environment, managing emotions, and focusing on facts and shared goals. Provide specific examples and phrases the user can employ during the conversation.\n\n[USER]"
 
+@spaces.GPU(duration=120)
 def model(text):
     generate_kwargs = dict(
         temperature=0.7,
@@ -29,7 +29,7 @@ def model(text):
         seed=42,
     )
     
-    formatted_prompt = system_instructions + text + "[OpenGPT 4o]"
+    formatted_prompt = system_instructions + text + "[CrucialCoach]"
     stream = client.text_generation(
         formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
@@ -39,20 +39,19 @@ def model(text):
 
     return output
 
-@spaces.GPU(duration=120)  # Increase duration if needed
-async def respond(audio):
+def respond(audio):
     user = transcribe(audio)
     reply = model(user)
     communicate = edge_tts.Communicate(reply)
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
         tmp_path = tmp_file.name
-        await communicate.save(tmp_path)
+        communicate.save(tmp_path)
     return tmp_path
 
 with gr.Blocks() as voice:   
     with gr.Row():
         input = gr.Audio(label="Voice Chat", source="microphone", type="filepath")
-        output = gr.Audio(label="OpenGPT 4o", type="filepath", interactive=False, autoplay=True)
+        output = gr.Audio(label="CrucialCoach", type="filepath", interactive=False, autoplay=True)
     
     gr.Interface(
         fn=respond,
@@ -63,8 +62,8 @@ with gr.Blocks() as voice:
 
 theme = gr.themes.Base()
 
-with gr.Blocks(theme=theme, css="footer {visibility: hidden}textbox{resize:none}", title="GPT 4o DEMO") as demo:
-    gr.Markdown("# OpenGPT 4o")
+with gr.Blocks(theme=theme, css="footer {visibility: hidden}textbox{resize:none}", title="CrucialCoach DEMO") as demo:
+    gr.Markdown("# CrucialCoach")
     gr.TabbedInterface([voice], ['🗣️ Voice Chat'])
 
 demo.queue(max_size=200)