app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torchaudio
from torchaudio.transforms import Resample
import torch

# สร้างโมเดล TTS
model_name = "facebook/tts-crdnn-baker-softmax"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# ฟังก์ชันสำหรับแปลงข้อความเป็นเสียง
def text_to_speech(text, output_path="generated_audio.wav"):
    input_ids = tokenizer.encode(text, return_tensors="pt", max_length=150, truncation=True)
    with torch.no_grad():
        audio = model.generate(input_ids)
    waveform = torchaudio.transforms.Resample(48_000, 24_000)(audio.squeeze().numpy())
    torchaudio.save(output_path, waveform, 24_000)

def play_audio(audio_path):
    gr.audio(audio_path, type="player")

# สร้าง Gradio interface ที่ใช้ image input, textbox output, button และ audio player
demo = gr.Interface(
    fn=text_to_speech, 
    inputs=gr.Textbox(label="Enter Text"), 
    outputs=[
        gr.Audio("audio", type="player"), 
        gr.Button("Convert to Audio", play_audio),
    ],
    live=True  # ทำให้ Gradio ทำงานแบบไม่บล็อก
)
demo.launch(share=True)