Both files exercise documents.search._schema exclusively (build_schema,
schema_fingerprint, needs_rebuild, open_or_rebuild_index) with no
dependency on whoosh-compat query routing, so they belong with the
schema/field-registry work rather than PR2's query rewrite.
Collapse the TEXT/KEYWORD/U64/DATE/DATETIME if/elif chain into a
FieldKind -> (schema kind, tokenizer) lookup table. JSON stays an
explicit branch since it can emit a second, synthetic notes_text
descriptor.
* fix(search): resolve index-write permissions and effective content in bulk
Add WriteBatch.add_or_update_ids() and use it in bulk_update_documents
and trash restore, cutting index writes from ~8 queries per document
to a constant handful per batch
* Always these new ones with xdist, try a better condition
* Fix: skip vector store document id filter for unrestricted chat users
ChatStreamingView built an IN filter from every permitted document id
for the "chat over all documents" case, which exceeds the vector
store's SQLite bound-parameter safety limit on installs with more
than ~32700 documents, silently returning no context. For a user who
can see every document (an active superuser), that filter never
narrows anything, so skip it and let the retriever search the whole
index instead.
* Minor improvements from a Claude review
* When a user is unrestricted chatting, still exclude trashed documents using a 'NOT IN' SQL statement. Wire that up where we need it
* Update src/paperless_ai/chat.py
Co-authored-by: shamoon <4887959+shamoon@users.noreply.github.com>
* Security: validate remote OCR endpoint against internal SSRF
Adds PAPERLESS_REMOTE_OCR_ALLOW_INTERNAL_ENDPOINTS (default true)
and validates remote_ocr_endpoint via validate_outbound_http_url
on the config serializer, matching the existing LLM endpoint handling.
* Validates te outbound url again right before use
* cover empty-value branch of validate_remote_ocr_endpoint because coverage
* re-validate remote OCR endpoint on every outbound request
* 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.
In tracemalloc based profiling, not materializing the whole Document list
reduced memory to approximately 20% of the baseline, with a peak memory
that scaled with the library size. Now, the lazt queryset is used and only
the needed pk value is actually contributing to memory
stumpylog
shamoon
dependabot[bot]andTrenton Holmes
Max Truxa
Jayden