Install torch and torchvision from the CPU-only index before docling
to avoid pulling CUDA/nvidia/triton dependencies. Update documentation
with measured image sizes (270MB remote, 1.9GB local).
Reflect the two Docker targets across README, getting-started,
contributing guides, and .env.example with new configuration
variables (CONVERSION_ENGINE, DOCLING_SERVE_URL, DOCLING_SERVE_API_KEY).
Both root and backend Dockerfiles now use a shared base stage with
two targets: remote (lightweight, ~300MB) and local (full Docling,
~2-3GB). docker-compose uses CONVERSION_MODE to select the target.
Replace generic orange "D" placeholders with the duck mascot logo
in all branding touchpoints: navbar header, home page hero, studio
import view, and browser favicon.
Add document and clock icons above the stat numbers for better visual
context. Accent border and icon color on hover for consistent
interactive feedback across the app.
Reduce toggle width to fit-content with inner padding and individual
border-radius, matching the studio tabs design. Narrower max-width
for a tighter settings layout.
Replace flat rows with rounded cards matching documents page style.
Reduce COMPLETED badge to a green dot so exceptions (FAILED, RUNNING)
stand out visually instead of blending into a wall of green badges.
Add contextual icons (gear, checkmark, grid) to Configure, Verify,
and Prepare tabs. Replace flat white/shadow active state with accent
color background for clearer visual feedback. Use inner padding and
individual border-radius for a modern segmented control look.
Apply the same dimming strategy used in Prepare mode: when an element
is highlighted, reduce stroke and fill opacity of all other bboxes
so the focused element stands out clearly.
Replace hardcoded version strings with build-time injection:
- Frontend: Vite __APP_VERSION__ from env or package.json
- Backend: APP_VERSION env var exposed via /health endpoint
- Docker: build arg propagated through both stages
- CI: release workflow extracts version from git tag
Document branching strategy and release process in CONTRIBUTING.md.
Catch up CHANGELOG with v0.2.0 and Unreleased sections.
Sync package.json version to 0.3.0.
Cover ChunkBbox construction and serialization, ChunkBboxResponse
camelCase output, rechunk endpoint bbox propagation, and frontend
store test data alignment with the new bboxes field.
Extract bounding boxes from chunk doc_items provenance in the chunker,
propagate through domain/service/API layers, and render highlighted
bboxes on canvas when hovering a chunk card. Reset highlights on
mode and page changes to prevent stale visual state.
Filter chunks by current PDF page for consistency with Verify mode.
Add collapsible chunking config section and paginated chunk list.
Show BboxOverlay in Prepare mode so users see element bounding boxes.
Fix scroll containment on prepare panel.
Generic usePagination composable with page navigation, size control,
and auto-reset on data change. PaginationBar renders prev/next with
page size selector. Both support i18n.
AnalysisService gains rechunk() and inline chunking during conversion.
ChunkingOptionsRequest/ChunkResponse schemas, POST rechunk endpoint,
and conditional chunker injection in main.py (local engine only).
LocalChunker implements DocumentChunker port using docling-core chunkers.
LocalConverter now serializes DoclingDocument to JSON for re-chunking support.
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.
Docling Serve expects array fields (to_formats) as repeated multipart
keys (to_formats=md&to_formats=html&to_formats=json), not a JSON
string. Changed _build_form_data to return list[tuple] so httpx sends
repeated keys correctly. Fixes 422 Unprocessable Entity on convert.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove dead get_analysis_service() function in main.py
- Scope file deletion to UPLOAD_DIR to prevent path traversal
- Parse datetime strings back to datetime objects in repos
- Add 10-minute polling timeout in frontend analysis store
- Accept .pdf extension (not just MIME type) on drag-and-drop
- Guard localStorage access for private browsing compatibility
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Wrap store.upload() calls in try-catch in both onFileSelect and onDrop
so thrown errors (e.g. file too large) don't bubble up unhandled.
Display store.error inline below the upload hint so users see why
their upload was rejected.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Bug #1: _on_task_done now receives job_id via functools.partial and
calls _mark_failed when the background task raises or is cancelled,
preventing jobs from being stuck in RUNNING state forever.
Bug #5: _parse_response wraps json.loads in try/except JSONDecodeError
so malformed json_content strings fall back gracefully instead of crashing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Delete domain/parsing.py (broke hexagonal layering by importing infra)
- Migrate all tests to import directly from domain.value_objects and
infra.local_converter
- Rewrite ServeConverter to match real Docling Serve v1 API contract:
options sent as individual form fields (not JSON blob), response
parsed from document.json_content (DoclingDocument), proper bbox
coord_origin handling (TOPLEFT/BOTTOMLEFT)
- Transmit all conversion options including generate_picture_images
- Replace fragile lazy import circular dep with FastAPI Depends() +
app.state for AnalysisService injection
- Add frontend file size validation (50MB) before upload
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implement the HTTP client adapter that delegates document conversion
to a remote Docling Serve instance via its /v1/convert/file endpoint.
Switchable via CONVERSION_ENGINE=remote env var. Includes health check,
API key auth, response parsing, and 30 new tests covering parsing,
type mapping, HTTP calls, and DI wiring.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Extract domain value objects and ports from parsing.py, move Docling-specific
code to infra/local_converter.py, and convert analysis_service to a class
with injected DocumentConverter. This prepares the codebase for plugging in
alternative conversion backends (e.g. Docling Serve) via the Protocol pattern.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
