Spaces:
Sleeping
Sleeping
| import os | |
| import numpy as np | |
| import gradio as gr | |
| import requests | |
| from genai_chat_ai import AI,create_chat_session | |
| api_key = os.environ.get("Id_mode_vits") | |
| headers = {"Authorization": f"Bearer {api_key}"} | |
| from transformers import AutoTokenizer,VitsModel | |
| import torch | |
| models= {} | |
| tokenizer = AutoTokenizer.from_pretrained("asg2024/vits-ar-sa-huba",token=api_key) | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| def get_model(name_model): | |
| global models | |
| if name_model in models: | |
| return models[name_model] | |
| models[name_model]=VitsModel.from_pretrained(name_model,token=api_key).to(device) | |
| return models[name_model] | |
| def genrate_speech(text,name_model): | |
| inputs=tokenizer(text,return_tensors="pt") | |
| model=get_model(name_model) | |
| with torch.no_grad(): | |
| wav=model( | |
| input_ids= input_ids.input_ids.to(device), | |
| attention_mask=input_ids.attention_mask.to(device), | |
| speaker_id=0 | |
| ).waveform.cpu().numpy().reshape(-1) | |
| return model.config.sampling_rate,wav | |
| def remove_extra_spaces(text): | |
| """ | |
| Removes extra spaces between words in a string. | |
| Args: | |
| text: The string to process. | |
| Returns: | |
| The string with extra spaces removed. | |
| """ | |
| return ' '.join(text.split()) | |
| def query(text,API_URL): | |
| payload={"inputs": text} | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.content | |
| def get_answer_ai(text): | |
| global AI | |
| try: | |
| response = AI.send_message(text) | |
| return response.text | |
| except : | |
| AI=create_chat_session() | |
| response = AI.send_message(text) | |
| return response.text | |
| with gr.Blocks() as demo: # Use gr.Blocks to wrap the entire interface | |
| with gr.Tab("محادثة صوتية بالذكاء الاصطناعي باللهجة السعودية"): | |
| with gr.Row(): # Arrange input/output components side-by-side | |
| with gr.Column(): | |
| text_input = gr.Textbox(label="أدخل أي نص") | |
| user_audio = gr.Audio(label="صوتك") | |
| with gr.Row(): | |
| btn = gr.Button("إرسال") | |
| btn_ai_only = gr.Button("توليد رد الذكاء الاصطناعي فقط") | |
| with gr.Column(): | |
| model_choices = gr.Dropdown( | |
| choices=[ | |
| "asg2024/vits-ar-sa", | |
| "asg2024/vits-ar-sa-huba", | |
| "asg2024/vits-ar-sa-ms", | |
| "asg2024/vits-ar-sa-magd", | |
| "asg2024/vits-ar-sa-fahd", | |
| ], | |
| label="اختر النموذج", | |
| value="asg2024/vits-ar-sa", | |
| ) | |
| ai_audio = gr.Audio(label="رد الذكاء الاصطناعي الصوتي") | |
| ai_text = gr.Textbox(label="رد الذكاء الاصطناعي النصي") | |
| # Use a single button to trigger both functionalities | |
| def process_audio(text, model_choice, generate_user_audio=True): | |
| API_URL = f"https://api-inference.huggingface.co/models/{model_choice}" | |
| text_answer = get_answer_ai(text) | |
| text_answer = remove_extra_spaces(text_answer) | |
| data_ai = genrate_speech(text_answer,model_choice)#query(text_answer, API_URL) | |
| if generate_user_audio: # Generate user audio if needed | |
| data_user =genrate_speech(text_answer,model_choice)# query(text, API_URL) | |
| return data_user, data_ai, text_answer | |
| else: | |
| return data_ai # Return None for user_audio | |
| btn.click( | |
| process_audio, # Call the combined function | |
| inputs=[text_input, model_choices], | |
| outputs=[user_audio, ai_audio, ai_text], | |
| ) | |
| # Additional button to generate only AI audio | |
| btn_ai_only.click( | |
| lambda text, model_choice: process_audio(text, model_choice, False), | |
| inputs=[text_input, model_choices], | |
| outputs=[ai_audio], | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |