Update app.py

app.py

@@ -26,7 +26,8 @@ def transcribe(audio):
 
 client1 = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
-system_instructions1 = "<s>[SYSTEM] Answer as Real Jarvis JARVIS, Made by 'Tony Stark', 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. The request asks you to provide friendly responses as if You are the character Jarvis, made by 'Tony Stark.' The expectation is that I 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_instructions1 = "<s>[SYSTEM] Answer as WATSON, Famous Sherlock Holmes Assistant, Keep conversation short, clear, friendly and concise. The text provided is a request for a specific type of response from you, the virtual assistant. The request asks you to provide friendly responses as if You are the character WATSON From Sherlock Holmes Novels, The expectation is that I 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 a Human and not an AI-powered assistant. [USER]"
+
 
 def model(text):
     generate_kwargs = dict(
@@ -38,7 +39,7 @@ def model(text):
         seed=42,
     )
     
-    formatted_prompt = system_instructions1 + text + "[JARVIS]"
+    formatted_prompt = system_instructions1 + text + "[WATSON]"
     stream = client1.text_generation(
         formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
@@ -71,29 +72,11 @@ async def respond(audio):
         await communicate.save(tmp_path)
     yield tmp_path
 
-DESCRIPTION = """ # <center><b>JARVIS 🤖 🧠 🧬</b></center>
-        ### <center>An Artificial Intelligence Assistant for YOU
-        ### <center>Talk to - JARVIS</center>
-        """
-
-MORE = """ ## TRY Other Models
-        ### Instant Video: Create Amazing Videos in 5 Second -> https://huggingface.co/spaces/KingNish/Instant-Video
-        ### Instant Image: 4k images in 5 Second -> https://huggingface.co/spaces/KingNish/Instant-Image
-        """
-
-BETA = """ ### Voice Chat"""
-
-FAST = """## Fastest Model"""
-
-Complex = """## Best in Complex Question"""
 
-Detail = """## Best for Detailed Generation or Long Answers"""
 
-base_loaded = "mistralai/Mixtral-8x7B-Instruct-v0.1"
-
-client1 = InferenceClient(base_loaded)
+client1 = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
-system_instructions1 = "[SYSTEM] Answer as Real Jarvis male male, Assistant to Tony Stark, 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. The request asks you to provide friendly responses as if You are the character Jarvis, made by 'Tony Stark.' The expectation is that I 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_instructions1 = "[SYSTEM] Answer as Watson with a London accent male voice. You are the character and Assistant Watson, from Sherlock Holmes Novels, 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. The request asks you to provide friendly responses as if You are the character Watson, from Sherlock Holmes Novel. The expectation is that I 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 a Real Person and not an AI-powered assistant. [USER]"
 
 async def generate1(prompt):
     generate_kwargs = dict(
@@ -103,7 +86,7 @@ async def generate1(prompt):
         repetition_penalty=1,
         do_sample=False,
     )
-    formatted_prompt = system_instructions1 + prompt + "[JARVIS]"
+    formatted_prompt = system_instructions1 + prompt + "[WATSON]"
     stream = client1.text_generation(
         formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
     output = ""
@@ -118,10 +101,14 @@ async def generate1(prompt):
     yield tmp_path
 
 with gr.Blocks(css="style.css") as demo:    
-    gr.Markdown(DESCRIPTION)
+    gr.Markdown(""" # <center><b>Watson 🤖 🧠 🧬</b></center>
+        ### <center>An Artificial Intelligence Assistant for YOU
+        ### <center>Talk to - Watson</center>
+        """)
+    
     with gr.Row():
         user_input = gr.Audio(label="Voice Chat", type="filepath")
-        output_audio = gr.Audio(label="JARVIS", type="filepath",
+        output_audio = gr.Audio(label="WATSON", type="filepath",
                         interactive=False,
                         autoplay=True,
                         elem_classes="audio")
@@ -129,11 +116,11 @@ with gr.Blocks(css="style.css") as demo:
         translate_btn = gr.Button("Response")
         translate_btn.click(fn=respond, inputs=user_input,
                             outputs=output_audio, api_name=False)
-    gr.Markdown(FAST)
+    
     with gr.Row():
-        user_input = gr.Textbox(label="Prompt", value="What's a fun science experiment I can do at home?")
+        user_input = gr.Textbox(label="Prompt", value="What's a fun science experiment we can do Watson?")
         input_text = gr.Textbox(label="Input Text", elem_id="important")
-        output_audio = gr.Audio(label="JARVIS", type="filepath",
+        output_audio = gr.Audio(label="WATSON", type="filepath",
                         interactive=False,
                         autoplay=True,
                         elem_classes="audio")
@@ -142,7 +129,7 @@ with gr.Blocks(css="style.css") as demo:
         translate_btn.click(fn=generate1, inputs=user_input,
                             outputs=output_audio, api_name="translate")  
 
-gr.Markdown(MORE)
+
 
 if __name__ == "__main__":
     demo.queue(max_size=200).launch()