Update app.py

app.py

@@ -1,51 +1,17 @@
-import gradio as gr
-import torch
-from transformers import AutoProcessor, AutoModelForTextToSpeech, pipeline
-from huggingface_hub import list_models
-from iso639 import Lang
-import re
+from transformers import pipeline
 
-# Lấy danh sách các model MMS-TTS
-def get_mms_tts_languages():
-    models = list_models(author="facebook", search="mms-tts-")
-    lang_map = {}
-    for model in models:
-        match = re.search(r"mms-tts-([a-z0-9]{3})$", model.modelId)
-        if match:
-            iso = match.group(1)
-            try:
-                lang = Lang(iso)
-                lang_map[lang.name.title()] = iso
-            except:
-                lang_map[iso.upper()] = iso
-    return dict(sorted(lang_map.items()))
+def main():
+    # Dùng model Facebook MMS TTS đa ngôn ngữ
+    model_name = "facebook/mms-tts-1b"
+    tts = pipeline("text-to-speech", model=model_name)
 
-LANG_MAP = get_mms_tts_languages()
-LANGUAGE_NAMES = list(LANG_MAP.keys())
+    text = "Hello world, this is a multi-language TTS test."
+    audio = tts(text)
 
-# Sinh âm thanh từ văn bản
-@torch.inference_mode()
-def generate_tts(text, language_name):
-    iso_code = LANG_MAP[language_name]
-    model_id = f"facebook/mms-tts-{iso_code}"
+    with open("output.wav", "wb") as f:
+        f.write(audio["wav"])
 
-    processor = AutoProcessor.from_pretrained(model_id)
-    model = AutoModelForTextToSpeech.from_pretrained(model_id).to("cpu")
-
-    tts_pipeline = pipeline("text-to-speech", model=model, tokenizer=processor, feature_extractor=processor)
-    output = tts_pipeline(text)
-    return output["audio"]
-
-# Giao diện Gradio
-with gr.Blocks() as demo:
-    gr.Markdown("## 🌍 MMS-TTS: 1100+ Ngôn ngữ TTS từ Meta")
-    with gr.Row():
-        language = gr.Dropdown(label="Chọn ngôn ngữ", choices=LANGUAGE_NAMES, value="Vietnamese")
-        text = gr.Textbox(label="Nhập văn bản", placeholder="Xin chào thế giới")
-    output = gr.Audio(label="Giọng nói")
-
-    btn = gr.Button("Phát")
-    btn.click(generate_tts, inputs=[text, language], outputs=output)
+    print("TTS thành công, file output.wav đã lưu")
 
 if __name__ == "__main__":
-    demo.launch()
+    main()