from rastrik.proto.callrecord_pb2 import CallRecord
import gzip
from pydub import AudioSegment
from .utils import ui_dump_manifest_writer, strip_silence

import typer
from itertools import chain
from io import BytesIO
from pathlib import Path

app = typer.Typer()


@app.command()
def extract_manifest(
    call_log_dir: Path = Path("./data/call_audio"),
    output_dir: Path = Path("./data"),
    dataset_name: str = "grassroot_pizzahut_v1",
    caller_name: str = "grassroot",
    verbose: bool = False,
):
    call_asr_data: Path = output_dir / Path("asr_data")
    call_asr_data.mkdir(exist_ok=True, parents=True)

    def wav_pb2_generator(log_dir):
        for wav_path in log_dir.glob("**/*.wav"):
            if verbose:
                typer.echo(f"loading events for file {wav_path}")
            call_wav = AudioSegment.from_file_using_temporary_files(wav_path)
            meta_path = wav_path.with_suffix(".pb2.gz")
            yield call_wav, wav_path, meta_path

    def read_event(call_wav, log_file):
        call_wav_0, call_wav_1 = call_wav.split_to_mono()
        with gzip.open(log_file, "rb") as log_h:
            record_data = log_h.read()
        cr = CallRecord()
        cr.ParseFromString(record_data)

        first_audio_event_timestamp = next(
            (
                i
                for i in cr.events
                if i.WhichOneof("event_type") == "call_event"
                and i.call_event.WhichOneof("event_type") == "call_audio"
            )
        ).timestamp.ToDatetime()

        speech_events = [
            i
            for i in cr.events
            if i.WhichOneof("event_type") == "speech_event"
            and i.speech_event.WhichOneof("event_type") == "asr_final"
        ]
        previous_event_timestamp = (
            first_audio_event_timestamp - first_audio_event_timestamp
        )
        for index, each_speech_events in enumerate(speech_events):
            asr_final = each_speech_events.speech_event.asr_final
            speech_timestamp = each_speech_events.timestamp.ToDatetime()
            actual_timestamp = speech_timestamp - first_audio_event_timestamp
            start_time = previous_event_timestamp.total_seconds() * 1000
            end_time = actual_timestamp.total_seconds() * 1000
            audio_segment = strip_silence(call_wav_1[start_time:end_time])

            code_fb = BytesIO()
            audio_segment.export(code_fb, format="wav")
            wav_data = code_fb.getvalue()
            previous_event_timestamp = actual_timestamp
            duration = (end_time - start_time) / 1000
            yield asr_final, duration, wav_data, "grassroot", audio_segment

    def generate_call_asr_data():
        full_data = []
        total_duration = 0
        for wav, wav_path, pb2_path in wav_pb2_generator(call_log_dir):
            asr_data = read_event(wav, pb2_path)
            total_duration += wav.duration_seconds
            full_data.append(asr_data)
        n_calls = len(full_data)
        typer.echo(f"loaded {n_calls} calls of duration {total_duration}s")
        n_dps = ui_dump_manifest_writer(call_asr_data, dataset_name, chain(*full_data))
        typer.echo(f"written {n_dps} data points")

    generate_call_asr_data()


def main():
    app()


if __name__ == "__main__":
    main()