Self-updating translation system for OpenClaw maintains domain glossaries automatically

Core translation system
A Python script wraps the Kimi2.5 API to translate .srt subtitle files while preserving block indices, timestamps, and segmentation. The script loads project profiles from projects/<name>/ folders containing three key files:
glossary.json— locked term mappings for specific spellings of names, competition names, and technical jargonstyle.md— voice guidelines, formatting rules, and cultural notesmemory.jsonl— accumulated context from previous translations
During translation, the script enforces locked terms before delivery. A QA gate validates SRT structure for no overlaps, increasing timecodes, and no stray indices.
Self-updating glossary system
A cron job runs every 6 hours, scanning official source sites in all languages. It extracts new terminology candidates, compares them against existing glossary entries, and appends deltas to glossary_deltas.jsonl. This allows the glossary to grow organically as the domain evolves, capturing official names, emerging terminology, or shifting institutional language without manual review cycles.
The system also maintains a separate knowledge base file with context snapshots—recent news, official communications, and product updates—which feeds back into translation quality by providing current context to the model.
Usage and results
Usage command:
python3 scripts/translate_srt.py \
--input source.srt \
--output output.en.srt \
--to English \
--project clientnameLocked terms get normalized in a post-process pass, then structural QA runs before file delivery. The system runs headless: file in, translated file out, with glossary silently updating in the background.
Results include consistent terminology across 100+ subtitle files, no drift in name spellings or technical vocabulary, and fresh context without manual source monitoring.
📖 Read the full source: r/openclaw
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