import gradio as gr
import torch
import scipy.io.wavfile as wavfile
from transformers import AutoProcessor, SeamlessM4TModel

tokenizer = AutoProcessor.from_pretrained("facebook/hf-seamless-m4t-medium")
model = SeamlessM4TModel.from_pretrained("facebook/hf-seamless-m4t-medium")

text = "some example text in the English language"

def greet(text):
    inputs = tokenizer(text, return_tensors="pt")
    with torch.no_grad():
        output = model(**inputs, decoder_input_ids=inputs["input_ids"]).waveform
        out = output[0]
        wavfile.write("tmp.wav", rate=16000, data=out)
        return open("tmp.wav", "rb").read()

iface = gr.Interface(fn=greet, inputs="text", outputs="audio")
iface.launch()