tts_txt.py reads a plain text file aloud with the lektor voice. The pipeline is
built around subtitles — every clip is placed at a timestamp — so prose needs
the one piece that is genuinely missing, a chunker that splits text into
sentence-sized pieces (240 chars, on sentence boundaries, long sentences split
at clause breaks). Everything else is lektor_ai_comfy's: the dictionary, the
Polish number normalizer, the ComfyUI call with its truncation retries and
crash recovery, the per-clip trim and speed-up. Clips land in
output/clips/<stem>/ like a film's, so --resume-from and re-assembly work the
same way, and --dry-run prints the chunks without generating anything.
tmp2srt.py converts TMPlayer subtitles (HH:MM:SS:text, '|' for a line break)
to SRT. TMPlayer stores only a start time, so an end is inferred: the next
cue's start less a small gap, or sooner when 16 chars/second says the line can
be read in less. The separator after the timestamp is optional in the wild —
some files use ':', some a space, some nothing — so all three parse.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NkWDx9dVB7xBpqntvjvm6A
