Frontend decoupling:
- Create shared/appConfig.ts as reactive bridge (locale, maxFileSizeMb,
maxPageCount) eliminating shared→features and feature→feature imports
- Give history feature its own Pinia store and API layer (was re-export
of analysis store)
- Give chunking feature its own Pinia store and API layer (was importing
from analysis)
- ChunkPanel receives analysis data via props instead of cross-feature
store import
- document/store reads maxFileSizeMb from shared config instead of
importing feature-flags store
- shared/i18n reads locale from shared config instead of importing
settings store
Backend:
- Add HealthResponse Pydantic schema for /api/health endpoint
Closes#140, closes#141, closes#142, closes#143
Read version from the backend /api/health endpoint instead of
hardcoding from package.json at build time. Add About section
in Settings with link to the DZone design article.
Replace hardcoded 5 MB upload limit with a configurable setting.
Backend exposes the value via /api/health, frontend reads it
dynamically for validation and UI messages.
Closes#48
Prevents PyTorch/Docling pipeline crashes on HF Spaces CPU by:
- Reducing max file size from 50 MB to 5 MB
- Adding configurable MAX_PAGE_COUNT setting (env var, default unlimited)
- Increasing conversion timeout from 600s to 900s
- Adding frontend upload validation with explicit error messages
- Exposing maxPageCount via /api/health for dynamic UI hints
Move /health to /api/health on backend and update the frontend
feature flag store to match. Without this, the combined Docker
image nginx proxy could not reach the endpoint and feature flags
(chunking/prepare mode) failed to load.
Introduce a feature-flags module in the frontend that detects
the backend conversion engine via /health and exposes typed
feature flags. Chunking is enabled only in local engine mode.
