| 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=100, | |
| 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() | |