# model_handler.py

from gradio_client import Client, handle_file
import threading
import requests

client = Client("ai4bharat/IndicF5")

def call_model_with_timeout(text, ref_audio_path, ref_text="", timeout=120):
    result = {"status": None, "audio_url": None}

    def run():
        try:
            audio_url = client.predict(
                text,
                handle_file(ref_audio_path),
                ref_text,
                api_name="/synthesize_speech"
            )
            result["status"] = "success"
            result["audio_url"] = audio_url
        except Exception as e:
            result["status"] = f"error: {e}"

    thread = threading.Thread(target=run)
    thread.start()
    thread.join(timeout)

    if thread.is_alive():
        return "⛔ Timed out!", None

    if result["status"] == "success":
        audio_url = result["audio_url"]
        try:
            output_path = "output.wav"
            audio_response = requests.get(audio_url)
            with open(output_path, "wb") as f:
                f.write(audio_response.content)
            return "✅ Success", output_path
        except Exception as e:
            return f"⛔ Download error: {e}", None
    else:
        return result["status"], None