import gradio as gr
from transformers import pipeline
import torch

# Load model Whisper medium fine-tuned Indonesia (paling direkomendasikan untuk bahasa Indo)
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipeline(
    "automatic-speech-recognition",
    model="cahya/whisper-medium-id",
    device=device,
    torch_dtype=torch.float16 if device == "cuda" else torch.float32,
)

# Force bahasa Indonesia biar lebih akurat
pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language="id", task="transcribe")

def transcribe(audio):
    if audio is None:
        return "Silakan rekam suara atau upload file audio dulu ya!"
    try:
        text = pipe(audio, chunk_length_s=30, max_new_tokens=256)["text"]
        return text.strip().capitalize() + "."
    except Exception as e:
        return f"Error: {str(e)} (coba audio lebih pendek)"

# Interface Gradio yang bagus
with gr.Blocks(title="Transkripsi Suara Bahasa Indonesia 🇮🇩") as demo:
    gr.Markdown("# Demo Transkripsi Suara ke Teks Bahasa Indonesia")
    gr.Markdown("Rekam via mikrofon atau upload audio (.wav/.mp3) → langsung jadi teks akurat! Model: [cahya/whisper-medium-id](https://huggingface.co/cahya/whisper-medium-id) – fine-tuned khusus Indo.")

    with gr.Row():
        with gr.Column(scale=1):
            audio_input = gr.Audio(
                sources=["microphone", "upload"],
                type="filepath",
                label="Rekam atau Upload Audio"
            )
        with gr.Column(scale=2):
            text_output = gr.Textbox(label="Hasil Transkripsi", lines=10, placeholder="Hasil akan muncul di sini...")

    btn = gr.Button("Transkripsi Sekarang!", variant="primary", size="lg")
    btn.click(fn=transcribe, inputs=audio_input, outputs=text_output)

    gr.Markdown("### Tips biar akurat:")
    gr.Markdown("- Audio pendek (<60 detik) lebih cepat & bagus hasilnya.")
    gr.Markdown("- Bicara jelas, coba contoh: 'Halo, apa kabar? Hari ini saya mau ke pasar beli sayuran segar.'")
    gr.Markdown("- Kalau Space lambat, tunggu build selesai atau upgrade ke ZeroGPU (gratis).")

demo.launch()