Update app.py

app.py

@@ -1,56 +1,56 @@
-import os
-import re
-import gradio as gr
-import edge_tts
-import asyncio
-import time
-import tempfile
-from huggingface_hub import InferenceClient
-
-DESCRIPTION = """ # <center><b>JARVIS⚡</b></center>
-        ### <center>A personal Assistant of Tony Stark for YOU
-        ### <center>Currently It supports text input, But If this space completes 1k hearts than I starts working on Audio Input.</center>
-        """
-
-client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
-
-system_instructions = "[INST] Answer as Real Jarvis JARVIS, Made by 'Tony Stark', Keep conversation very short, clear, friendly and concise."
-
-async def generate(prompt):
-    generate_kwargs = dict(
-        temperature=0.6,
-        max_new_tokens=256,
-        top_p=0.95,
-        repetition_penalty=1,
-        do_sample=True,
-        seed=42,
-    )
-    formatted_prompt = system_instructions + prompt + "[/INST]"
-    stream = client.text_generation(
-        formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
-    output = ""
-    for response in stream:
-        output += response.token.text
-
-    communicate = edge_tts.Communicate(output)
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
-        tmp_path = tmp_file.name
-        await communicate.save(tmp_path)
-    yield tmp_path
-
-with gr.Blocks(css="style.css") as demo:    
-    gr.Markdown(DESCRIPTION)
-    with gr.Row():
-        user_input = gr.Textbox(label="Prompt")
-        input_text = gr.Textbox(label="Input Text", elem_id="important")
-        output_audio = gr.Audio(label="Audio", type="filepath",
-                        interactive=False,
-                        autoplay=True,
-                        elem_classes="audio")
-    with gr.Row():
-        translate_btn = gr.Button("Response")
-        translate_btn.click(fn=generate, inputs=user_input,
-                            outputs=output_audio, api_name="translate")        
-
-if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+import os
+import re
+import gradio as gr
+import edge_tts
+import asyncio
+import time
+import tempfile
+from huggingface_hub import InferenceClient
+
+DESCRIPTION = """ # <center><b>Rabbit R1 🐰</b></center>
+        ### <center>Rabbit’s Little Walkie-Talkie 🥤
+        ### <center>Voice 2 Voice Coming Soon 🚧 </center>
+        """
+
+client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+
+system_instructions = "[INST] Answers by 🐰🚀, Keep conversation very short, clear, friendly and concise."
+
+async def generate(prompt):
+    generate_kwargs = dict(
+        temperature=0.6,
+        max_new_tokens=256,
+        top_p=0.95,
+        repetition_penalty=1,
+        do_sample=True,
+        seed=42,
+    )
+    formatted_prompt = system_instructions + prompt + "[/INST]"
+    stream = client.text_generation(
+        formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
+    output = ""
+    for response in stream:
+        output += response.token.text
+
+    communicate = edge_tts.Communicate(output)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
+        tmp_path = tmp_file.name
+        await communicate.save(tmp_path)
+    yield tmp_path
+
+with gr.Blocks(css="style.css") as demo:    
+    gr.Markdown(DESCRIPTION)
+    with gr.Row():
+        user_input = gr.Textbox(label="Prompt")
+        input_text = gr.Textbox(label="Input Text", elem_id="important")
+        output_audio = gr.Audio(label="Audio", type="filepath",
+                        interactive=False,
+                        autoplay=True,
+                        elem_classes="audio")
+    with gr.Row():
+        translate_btn = gr.Button("Response")
+        translate_btn.click(fn=generate, inputs=user_input,
+                            outputs=output_audio, api_name="translate")        
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()