Backend: - TranslationRun model: add cache_hits Integer column (default 0) - TranslationRunResponse schema: add cache_hits field - _helpers.py/_run_list_routes.py/orchestrator_aggregator.py: include cache_hits in all run API responses - _batch_proc.py: count pre_rows served from translation cache per batch, return cache_hits in batch result - executor.py: accumulate cache_hits across batches, persist to run - Alembic migration: dabc9709 — add cache_hits column to translation_runs Frontend: - translationRun.svelte.ts: add cacheHits to store state, WS handler, polling handler - TranslationRunProgress.svelte: 5-col stats grid with purple Cache card - TranslationRunGlobalIndicator.svelte: 5-col stats with Cache - TranslationRunResult.svelte: 5-col detail stats with Cache card - History page: cache_hits shown in run list row + detail panel Visual: cache hits shown in purple alongside green/yellow/red metrics (total/success/failed/skipped). Visible during run + in history. Tests: backend 69/69 translate tests ✅, frontend 698/698 tests ✅, frontend build ✅
Superset Tools Frontend (SvelteKit)
This is the frontend for the Superset Tools application, built with SvelteKit in SPA mode.
Development
-
Install dependencies:
npm install -
Run development server:
npm run devThe frontend will be available at
http://localhost:5173. It is configured to proxy API requests tohttp://localhost:8000.
Production Build
-
Build the static SPA:
npm run buildThis generates a static SPA in the
build/directory. -
Serve with Backend: The Python backend is configured to serve the files from
frontend/build/. Ensure the backend is running:cd ../backend python src/app.py
Architecture
- Routing: File-based routing in
src/routes/. - Layouts: Shared UI in
src/routes/+layout.svelte. - Data Loading:
loadfunctions in+page.tsfor efficient data fetching. - API Client: Centralized API logic in
src/lib/api.js. - Styling: Tailwind CSS.