import gradio as gr
from pydub import AudioSegment
from faster_whisper import WhisperModel
import os

model = WhisperModel("openai/whisper-large-v3-turbo", compute_type="int8")

def convert_to_wav(file_path):
    audio = AudioSegment.from_file(file_path)
    audio = audio.set_frame_rate(16000).set_channels(1).set_sample_width(2)
    out_path = file_path.replace(".", "_ready.")
    audio.export(out_path, format="wav")
    return out_path

def detect_language(audio_file):
    wav = convert_to_wav(audio_file.name)
    segments, info = model.transcribe(wav)
    transcript = "\n".join([seg.text for seg in segments])
    return f"🌐 Language: {info.language}\n\n📝 Transcript:\n{transcript}"

gr.Interface(fn=detect_language,
             inputs=gr.Audio(type="filepath"),
             outputs="text",
             title="🎧 Audio Language Detector",
             description="Drop any MP3/WAV/FLAC to identify spoken language & get transcript."
).launch()