# app.py – ZeroGPU SAFE – 3 mín hljóð án "GPU task aborted"
import os
import gradio as gr
import spaces
from transformers import pipeline
import numpy as np
import librosa

MODEL_NAME = "palli23/whisper-small-sam_spjall"

@spaces.GPU(duration=60)   # ← MEST 60 sek – ZeroGPU leyfir
def transcribe_safe(audio_path):
    if not audio_path:
        return "Hladdu upp hljóðskrá"
    
    # Hlaða hljóð og klippa í 20 sek chunkar (mjög öruggt)
    audio, sr = librosa.load(audio_path, sr=16000)
    chunk_len = 16000 * 20   # 20 sek
    stride = 16000 * 2       # 2 sek overlap
    chunks = []
    for i in range(0, len(audio), chunk_len - stride):
        chunk = audio[i:i + chunk_len]
        if len(chunk) < 16000:  # undir 1 sek → hætta
            break
        chunks.append(chunk)
    
    # Hlaða ASR á GPU (cached)
    pipe = pipeline(
        "automatic-speech-recognition",
        model=MODEL_NAME,
        device=0,
        token=os.getenv("HF_TOKEN")
    )
    
    full_text = ""
    for idx, chunk in enumerate(chunks):
        result = pipe(chunk, batch_size=8)
        full_text += result["text"] + " "
    
    return full_text.strip() or "Ekkert heyrt"

# Gradio – fallegt og tilbúið fyrir 3 mín
with gr.Blocks(title="Íslenskt ASR – 3 mín ZeroGPU") as demo:
    gr.Markdown("# Íslenskt ASR – 3 mín hljóð")
    gr.Markdown("**~4 % WER · 25–45 sek · ZeroGPU (PRO)**")
    
    audio = gr.Audio(type="filepath", label="Hladdu upp .mp3 / .wav (allt að 3 mín)")
    btn = gr.Button("Transcribe (25–45 sek)", variant="primary", size="lg")
    out = gr.Textbox(lines=30, label="Útskrift")
    
    btn.click(transcribe_safe, inputs=audio, outputs=out)

demo.launch(auth=("beta", "beta2025"))