import sys
from pathlib import Path
import sherpa_onnx, soundfile as sf
from core import args_parser as ap

def stt_run(args):

    print("Recognize...")
    recognizer = sherpa_onnx.OfflineRecognizer.from_qwen3_asr( # qwen3 asr
        conv_frontend   = args.conv_frontend,
        encoder         = args.encoder,
        decoder         = args.decoder,
        tokenizer       = args.tokenizer,
        hotwords        = args.hotwords,
        num_threads     = args.num_threads,
        sample_rate     = 16000,
        feature_dim     = 128,
        provider        = args.provider,
        max_total_len   = args.max_total_len,
        max_new_tokens  = args.max_new_tokens,
    )
    print("Recognizer ready!")

    for f in args.sounds: # Multi-file
        if not Path(f).is_file():
            print(f"Skip. file not found: {f}", file=sys.stderr)
            continue

        audio, sr  = sf.read(f, dtype="float32", always_2d=True)
        audio      = audio[:, 0]

        stream     = recognizer.create_stream()
        
        if args.language:
            stream.set_option("language", args.language)
        stream.accept_waveform(sr, audio)

        recognizer.decode_stream(stream) # Inference execution for `stream.result`
        
        text       = stream.result.text

        if "<asr_text>" in text: # qwen3 asr format
            text = text.split("<asr_text>", 1)[1]

        print()
        print(f"File      : {f}")
        print(f"Duration  : {len(audio) / sr:.2f} s")
        print(f"Result    : {text}")
        print()

if __name__ == "__main__":
    stt_run( ap.parser.parse_args() )