dikte/filetranscribe.py

"""Transcribe an existing audio/video file with the same models.

ffmpeg converts whatever comes in to 16 kHz mono WAV; long files are cut into
chunks that stay under the API's size limit, then stitched back together with
their timestamps shifted into place.
"""

import contextlib
import os
import re
import shutil
import subprocess
import tempfile
import threading
import wave

from PyQt6.QtCore import QObject, pyqtSignal

import api
from i18n import t

CHUNK_SECONDS = 600          # 10 min ≈ 19 MB at 16 kHz mono s16
CLEANUP_CHUNK_CHARS = 12000  # keep each cleanup call comfortably small
RATE = 16000
MIN_SUBTITLE_SECONDS = 1.5   # how long a cue with no end time of its own stays up

# The [mm:ss] or [h:mm:ss] prefix a timestamped line starts with.
STAMP_RE = re.compile(r"^\[(?:(\d+):)?(\d{1,2}):(\d{2})\]\s*")


class Cancelled(Exception):
    pass


class FileTranscriber(QObject):
    progress = pyqtSignal(str)
    finished = pyqtSignal(str, list)   # text, [(start, end, text)] when timestamped
    failed = pyqtSignal(str)

    def __init__(self, conf, parent=None):
        super().__init__(parent)
        self.conf = conf
        self._thread = None
        self._stop = threading.Event()

    @property
    def busy(self):
        return self._thread is not None and self._thread.is_alive()

    def start(self, path, timestamps, do_cleanup):
        if self.busy:
            return
        self._stop.clear()
        self._thread = threading.Thread(
            target=self._work, args=(path, timestamps, do_cleanup), daemon=True
        )
        self._thread.start()

    def stop(self):
        self._stop.set()

    def _check(self):
        if self._stop.is_set():
            raise Cancelled

    def _work(self, path, timestamps, do_cleanup):
        conf = self.conf
        workdir = None
        try:
            if not shutil.which("ffmpeg"):
                raise api.ApiError(t("ffmpeg not found. Install it to transcribe files."))

            workdir = tempfile.mkdtemp(prefix="dikte-file-")
            self.progress.emit(t("Converting audio…"))
            wav_path = _to_wav(path, workdir)
            self._check()

            chunks = split_wav(wav_path, workdir)
            if len(chunks) > 1:
                self.progress.emit(t("Splitting into {count} chunks…", count=len(chunks)))

            target = conf.transcribe_target()
            pieces = []
            segments = []
            for index, (chunk_path, offset) in enumerate(chunks, start=1):
                self._check()
                self.progress.emit(
                    t("Transcribing chunk {index}/{count}…", index=index, count=len(chunks))
                )
                if timestamps:
                    segments.extend(
                        (start + offset, end + offset, line)
                        for start, end, line in api.transcribe_segments(
                            target,
                            chunk_path,
                            language=conf["language"],
                            prompt=conf["transcribe_prompt"],
                        )
                    )
                    pieces = [f"[{format_timestamp(start)}] {line}"
                              for start, _, line in segments]
                else:
                    pieces.append(api.transcribe(
                        target,
                        chunk_path,
                        language=conf["language"],
                        prompt=conf["transcribe_prompt"],
                    ))

            text = "\n".join(pieces) if timestamps else " ".join(pieces)

            if do_cleanup and text:
                self._check()
                self.progress.emit(t("Cleaning up…"))
                text = self._cleanup(text, timestamps)

            self.finished.emit(text, segments)

        except Cancelled:
            self.progress.emit(t("Stopped."))
        except (api.ApiError, OSError, subprocess.SubprocessError, wave.Error) as exc:
            self.failed.emit(str(exc))
        finally:
            if workdir:
                shutil.rmtree(workdir, ignore_errors=True)

    def _cleanup(self, text, timestamps):
        conf = self.conf
        prompt = conf.cleanup_prompt(with_timestamps=timestamps, subtitles=True)
        target = conf.cleanup_target()
        out = []
        for block in split_text(text, timestamps):
            self._check()
            out.append(api.cleanup(target, block, prompt))
        return ("\n" if timestamps else "\n\n").join(out)


def format_timestamp(seconds):
    seconds = int(seconds)
    hours, rest = divmod(seconds, 3600)
    minutes, secs = divmod(rest, 60)
    return f"{hours}:{minutes:02d}:{secs:02d}" if hours else f"{minutes:02d}:{secs:02d}"


def srt_timestamp(seconds):
    millis = int(round(max(seconds, 0.0) * 1000))
    hours, rest = divmod(millis, 3600000)
    minutes, rest = divmod(rest, 60000)
    secs, millis = divmod(rest, 1000)
    return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"


def to_srt(text, segments):
    """Turn the timestamped transcript into SRT cues.

    The text is the authority on wording, so cleanup edits survive; the segments
    are the authority on timing. They meet at the [mm:ss] prefix, which cleanup
    is told to leave alone: a line's whole-second stamp finds the segment it came
    from, and with it the fractional start and the end time whisper reported. A
    line whose stamp finds nothing runs until the next line starts.
    """
    cues = []
    for line in text.splitlines():
        line = line.strip()
        if not line:
            continue
        match = STAMP_RE.match(line)
        body = line[match.end():].strip() if match else line
        if not match:
            if cues and body:      # a wrapped line belongs to the cue above it
                cues[-1][2] += " " + body
            continue
        if not body:
            continue
        hours, minutes, secs = (int(g or 0) for g in match.groups())
        cues.append([hours * 3600 + minutes * 60 + secs, None, body])

    timing = {}
    for start, end, _ in segments:
        timing.setdefault(int(start), (start, end))
    for cue in cues:
        cue[0], cue[1] = timing.get(cue[0], (float(cue[0]), 0.0))
    for index, cue in enumerate(cues):
        following = cues[index + 1][0] if index + 1 < len(cues) else 0.0
        if following > cue[0]:
            cue[1] = min(cue[1], following) if cue[1] > cue[0] else following
        elif cue[1] <= cue[0]:
            cue[1] = cue[0] + MIN_SUBTITLE_SECONDS

    blocks = [
        f"{number}\n{srt_timestamp(start)} --> {srt_timestamp(end)}\n{body}"
        for number, (start, end, body) in enumerate(cues, start=1)
    ]
    return "\n\n".join(blocks) + "\n" if blocks else ""


def _to_wav(path, workdir):
    out = os.path.join(workdir, "audio.wav")
    res = subprocess.run(
        ["ffmpeg", "-nostdin", "-y", "-i", path, "-vn",
         "-ac", "1", "-ar", str(RATE), "-c:a", "pcm_s16le", out],
        capture_output=True, text=True,
    )
    if res.returncode != 0 or not os.path.exists(out):
        tail = (res.stderr or "").strip().splitlines()
        raise api.ApiError(t("Could not read the file: {error}",
                             error=tail[-1] if tail else res.returncode))
    return out


def split_wav(wav_path, workdir):
    """[(chunk path, offset in seconds)], a single entry for short files."""
    with contextlib.closing(wave.open(wav_path, "rb")) as src:
        rate = src.getframerate()
        total = src.getnframes()
        per_chunk = CHUNK_SECONDS * rate
        if total <= per_chunk:
            return [(wav_path, 0.0)]

        chunks = []
        index = 0
        while True:
            frames = src.readframes(per_chunk)
            if not frames:
                break
            path = os.path.join(workdir, f"chunk-{index:03d}.wav")
            with contextlib.closing(wave.open(path, "wb")) as dst:
                dst.setnchannels(src.getnchannels())
                dst.setsampwidth(src.getsampwidth())
                dst.setframerate(rate)
                dst.writeframes(frames)
            chunks.append((path, index * CHUNK_SECONDS))
            index += 1
        return chunks


def split_text(text, timestamps):
    """Break long text into cleanup-sized blocks, never mid-line."""
    if len(text) <= CLEANUP_CHUNK_CHARS:
        return [text]
    separator = "\n" if timestamps else " "
    blocks, current = [], ""
    for part in text.split(separator):
        candidate = f"{current}{separator}{part}" if current else part
        if len(candidate) > CLEANUP_CHUNK_CHARS and current:
            blocks.append(current)
            current = part
        else:
            current = candidate
    if current:
        blocks.append(current)
    return blocks