app.py

import torch
import torchaudio
import tempfile
import requests
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
import gradio as gr

model_name = "ibm-granite/granite-speech-3.3-8b"
device = "cuda" if torch.cuda.is_available() else "cpu"

processor = AutoProcessor.from_pretrained(model_name)
model = AutoModelForSpeechSeq2Seq.from_pretrained(model_name).to(device)

def download_audio_from_url(url):
    response = requests.get(url)
    if response.status_code != 200:
        raise Exception("Failed to download file from URL.")
    tmp = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
    tmp.write(response.content)
    tmp.close()
    waveform, sr = torchaudio.load(tmp.name)
    return waveform, sr

def transcribe_from_url(audio_url, translate_to=None):
    waveform, sr = download_audio_from_url(audio_url)
    # Resample if needed
    if sr != 16000:
        waveform = torchaudio.functional.resample(waveform, sr, 16000)

    inputs = processor(waveform, sampling_rate=16000, return_tensors="pt").to(device)
    outputs = model.generate(**inputs, num_beams=5, max_new_tokens=512)
    text = processor.tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]

    if translate_to:
        text = f"<|translate_to={translate_to}|> " + text
        inputs2 = processor(text, return_tensors="pt").to(device)
        outputs2 = model.generate(**inputs2, num_beams=5)
        text = processor.tokenizer.batch_decode(outputs2, skip_special_tokens=True)[0]

    return text

gr.Interface(
    fn=transcribe_from_url,
    inputs=[
        gr.Textbox(label="🎧 Audio File URL (.mp3, .wav)", placeholder="Paste Google Drive direct link or other audio URL"),
        gr.Dropdown(choices=[None, "fr", "es", "it", "de", "pt", "ja", "zh"], label="Translate to (optional)")
    ],
    outputs=gr.Textbox(label="📝 Transcription / Translation"),
    title="Granite Speech 3.3-8B - Audio from URL",
    description="Paste a direct URL to an audio file (Google Drive with 'uc?export=download' format or any MP3/WAV link)"
).launch()