This brings users without an embedding backend configured to closer
parity with those who do. Reuse the search backend to locate similar
documents and use them to provide the LLM with the better suggestion pool
to draw from
* Ok! Backend stuff for the remote ocr workflow
* Frotnend workflow stuff
* And docs
* Fix dynamic action fields thing
* Actually, fix the action dropdown thing
* Fix this validation thing, and we have to check existing actions
* Fix migration
* uses_remote_service + allow_remote to allow opt-in / out of remote OCR
* Add to parser dev docs
* remote_ocr_mode config setting
* Checks for remote_ocr_mode and fix import
* Update config.component.spec.ts
* More tests for remote_ocr_mode
* Docs for remote_ocr_mode
* Ok, wire up the remote_ocr_mode with allow_remote for consumer
* Update consumer.py
* Format remote OCR mode check tests
* Use get_choice_from_env
* Backend changes and migration for remote OCR Config
* Backend tests
* Frontend stuff, with sections
* Docs
* Update test_tesseract_parser.py
* Actually we cant use this any more, in case settings are in app config
* Dont mark entire test file for db, use a mock for empty engine settings
AI Suggestions previously invented near-duplicate metadata because the classification
prompt had no knowledge of the installation's own taxonomy. This surfaces
a small, ranked, permission-filtered set of existing tags/document
types/correspondents/storage paths - drawn from the document's RAG
neighbors plus its own already-assigned metadata - so the model prefers
reusing what already exists.
The LLM response schema now returns existing_ids (IDs of reused
candidates) separately from new_names (genuinely new suggestions).
Only new_names goes through localization and fuzzy name-matching;
existing_ids is resolved deterministically and never touched by the
localization pass, so exact matches can no longer be silently
corrupted by translation.
* Feature: Allow configuring the compression type and compression levels during export
Building on the zip export improvements, this now allows users to further configure the
zip to fit their needs. A simple stored zip for speed, or a high compression zstd for
the smallest archive. Full validation of the method and levels at the command line
Co-authored-by: shamoon <4887959+shamoon@users.noreply.github.com>
Added a new --url argument to specify the base URL of the Paperless instance, allowing matched documents to be displayed as clickable links. Updated the logic to fetch document titles based on the presence of the base URL.