feat: per-client glossary — hybrid exact/vector retrieval + AI injection
Adds full glossary system so Gemini uses client-approved terminology
when generating subtitles and translations (critical for 3M brand names
and product codes across 16 target locales).
Backend:
- lib/locales.py: BCP-47 locale registry, normalises xlsx fr_fr → fr-FR
- models/glossary.py: Glossary / GlossaryVersion / GlossaryTerm + enums
- services/glossary_service.py: xlsx parse (openpyxl), ingest to Mongo,
hybrid retrieval (Aho-Corasick exact + Atlas Vector Search), prompt block
- services/embedding_service.py: Gemini text-embedding-004, batch 100, retry
- tasks/embed_glossary.py: Celery background task for async embedding
- api/v1/routes_glossaries.py: CRUD endpoints under /clients/{id}/glossaries
- gemini.py: _build_glossary_block(), {GLOSSARY} injection in all 4 call sites
- tts.py / gemini_tts.py: pass full locale codes (no split("-")[0] truncation)
- tasks/translate_and_synthesize.py: glossary lookup + injection per language
- prompts: {GLOSSARY} placeholder in ingestion, targeted, transcreation prompts
- pyproject.toml: +openpyxl, +pyahocorasick
Frontend:
- routes/admin/glossaries/: GlossaryList, GlossaryUpload, GlossaryDetail
- App.tsx: 3 new routes under /admin/clients/:clientId/glossaries
- ClientDetail.tsx: Glossaries card with count + quick links
- types/api.ts: Glossary, GlossaryVersion, GlossaryDetail, GlossaryTerm types
- lib/api.ts: 7 new API methods (upload, list, detail, terms, versions, activate, archive)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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