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Author SHA1 Message Date
stumpylog 1f8cf4cd6e Fix: consolidate and extend unicode NFC normalization for filenames and matching
Consolidates the scattered unicodedata.normalize("NFC", ...) calls introduced
by my earlier filename/path normalization work into a single
documents.utils.normalize_unicode() helper, and closes several gaps where
NFD-normalized filenames could still slip through unnormalized:

- Document.get_public_filename() now normalizes, fixing exported filenames
  built from an NFD title/correspondent name (the default, non-format export
  path was not covered by the earlier fix).
- DocumentViewSet.update_version() now normalizes the uploaded filename,
  matching PostDocumentView's existing behavior.
- ConsumerPlugin normalizes self.filename once at consumption time, covering
  the title fallback and Document.original_filename for every document
  source (consume folder, mail, API, barcode splits).
- Workflow trigger and mail rule filename/path matching (documents/matching.py,
  paperless_mail/mail.py) now normalize the document/attachment side before
  comparing, so an NFD filename matches an NFC-typed filter pattern instead of
  silently failing to match.
- WorkflowTriggerSerializer and MailRuleSerializer normalize filter_filename/
  filter_path and the attachment include/exclude patterns once at write time,
  so the read side isn't re-normalizing an already-canonical value on every
  match.
2026-09-08 16:00:16 -07:00
49 changed files with 1151 additions and 2293 deletions
-9
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@@ -1200,15 +1200,6 @@ still perform some basic text pre-processing before matching.
Defaults to true, enabling the feature.
#### [`PAPERLESS_CLASSIFIER_MATCH_THRESHOLD=<float>`](#PAPERLESS_CLASSIFIER_MATCH_THRESHOLD) {#PAPERLESS_CLASSIFIER_MATCH_THRESHOLD}
: Sets the minimum confidence score (0.0-1.0) required for the automatic
classifier to assign a correspondent, document type, or storage path to a
document. Predictions below this threshold are discarded and the field is
left unassigned, preventing low-confidence guesses from being applied.
Defaults to 0.6.
#### [`PAPERLESS_DATE_PARSER_LANGUAGES=<lang>`](#PAPERLESS_DATE_PARSER_LANGUAGES) {#PAPERLESS_DATE_PARSER_LANGUAGES}
: Specifies which language Paperless should use when parsing dates from documents.
+203 -250
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@@ -112,22 +112,6 @@
<pngx-input-check i18n-title title="Use 'slim' sidebar (icons only)" formControlName="slimSidebarEnabled"></pngx-input-check>
<p class="mb-2 mt-3" i18n>Sidebar items to show:</p>
@for (option of sidebarItemOptions; track option.id) {
<div class="form-check">
<input
class="form-check-input"
type="checkbox"
[id]="'sidebar-item-setting-' + option.id"
[checked]="isSidebarItemShown(option.id)"
(change)="toggleSidebarItem(option.id, $event.target.checked)"
/>
<label class="form-check-label" [for]="'sidebar-item-setting-' + option.id">
{{ option.label }}
</label>
</div>
}
</div>
</div>
@@ -24,7 +24,7 @@ import {
SystemStatus,
SystemStatusItemStatus,
} from 'src/app/data/system-status'
import { HideableSidebarItemID, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfOwnerDirective } from 'src/app/directives/if-owner.directive'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { PermissionsGuard } from 'src/app/guards/permissions.guard'
@@ -209,45 +209,6 @@ describe('SettingsComponent', () => {
fixture.detectChanges()
}
it('supports configuring sidebar items and canceling changes', () => {
completeSetup()
component.toggleSidebarItem(HideableSidebarItemID.Workflows, false)
fixture.detectChanges()
expect(component.settingsForm.value.sidebarHiddenItems).toContain(
HideableSidebarItemID.Workflows
)
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Mail,
false
)
expect(component.settingsForm.value.sidebarHiddenItems).toContain(
HideableSidebarItemID.Mail
)
component.reset()
expect(component.settingsForm.value.sidebarHiddenItems).not.toContain(
HideableSidebarItemID.Workflows
)
expect(component.settingsForm.value.sidebarHiddenItems).not.toContain(
HideableSidebarItemID.Mail
)
})
it('enables sidebar item controls on general settings until destroyed', () => {
completeSetup()
expect(settingsService.organizingSidebarItems()).toBe(true)
component.ngOnDestroy()
expect(settingsService.organizingSidebarItems()).toBe(false)
})
it('should support tabbed settings & change URL, prevent navigation if dirty confirmation rejected', async () => {
completeSetup()
const navigateSpy = jest.spyOn(router, 'navigate')
@@ -288,7 +249,6 @@ describe('SettingsComponent', () => {
it('should support save local settings updating appearance settings and calling API, show error', () => {
completeSetup()
component.toggleSidebarItem(HideableSidebarItemID.Workflows, false)
const toastErrorSpy = jest.spyOn(toastService, 'showError')
const toastSpy = jest.spyOn(toastService, 'show')
const storeSpy = jest.spyOn(settingsService, 'storeSettings')
@@ -307,10 +267,7 @@ describe('SettingsComponent', () => {
expect(toastErrorSpy).toHaveBeenCalled()
expect(storeSpy).toHaveBeenCalled()
expect(appearanceSettingsSpy).not.toHaveBeenCalled()
expect(setSpy).toHaveBeenCalledTimes(34)
expect(setSpy).toHaveBeenCalledWith(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Workflows,
])
expect(setSpy).toHaveBeenCalledTimes(33)
// succeed
storeSpy.mockReturnValueOnce(of(true))
@@ -39,12 +39,7 @@ import {
SystemStatus,
SystemStatusItemStatus,
} from 'src/app/data/system-status'
import {
GlobalSearchType,
HIDEABLE_SIDEBAR_ITEM_IDS,
HideableSidebarItemID,
SETTINGS_KEYS,
} from 'src/app/data/ui-settings'
import { GlobalSearchType, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { User } from 'src/app/data/user'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { CustomDatePipe } from 'src/app/pipes/custom-date.pipe'
@@ -107,14 +102,6 @@ const documentDetailFieldOptions = [
{ id: DocumentDetailFieldID.Tags, label: $localize`Tags` },
]
const sidebarItemLabels: Record<HideableSidebarItemID, string> = {
[HideableSidebarItemID.Dashboard]: $localize`Dashboard`,
[HideableSidebarItemID.SavedViews]: $localize`Saved Views`,
[HideableSidebarItemID.Workflows]: $localize`Workflows`,
[HideableSidebarItemID.Mail]: $localize`Mail`,
[HideableSidebarItemID.Documentation]: $localize`Documentation`,
}
@Component({
selector: 'pngx-settings',
templateUrl: './settings.component.html',
@@ -162,7 +149,6 @@ export class SettingsComponent
bulkEditApplyOnClose: new FormControl(null),
documentListItemPerPage: new FormControl(null),
slimSidebarEnabled: new FormControl(null),
sidebarHiddenItems: new FormControl<HideableSidebarItemID[]>([]),
darkModeUseSystem: new FormControl(null),
darkModeEnabled: new FormControl(null),
darkModeInvertThumbs: new FormControl(null),
@@ -200,7 +186,6 @@ export class SettingsComponent
store: BehaviorSubject<any>
storeSub: Subscription
sidebarItemsSub: Subscription
isDirty$: Observable<boolean>
isDirty: boolean = false
unsubscribeNotifier: Subject<any> = new Subject()
@@ -218,10 +203,6 @@ export class SettingsComponent
public readonly PdfEditorEditMode = PdfEditorEditMode
public readonly documentDetailFieldOptions = documentDetailFieldOptions
public readonly sidebarItemOptions = HIDEABLE_SIDEBAR_ITEM_IDS.map((id) => ({
id,
label: sidebarItemLabels[id],
}))
get systemStatusHasErrors(): boolean {
const status = this.systemStatus()
@@ -249,10 +230,6 @@ export class SettingsComponent
constructor() {
super()
this.sidebarItemsSub =
this.settings.sidebarHiddenItemsEditingChanged.subscribe((hiddenItems) =>
this.settingsForm.controls.sidebarHiddenItems.setValue(hiddenItems)
)
this.settings.settingsSaved.subscribe(() => {
if (!this.savePending) this.initialize()
this.savedViewsService.maybeRefreshDocumentCounts()
@@ -302,21 +279,14 @@ export class SettingsComponent
this.activatedRoute.paramMap.subscribe((paramMap) => {
const section = paramMap.get('section')
let navID = SettingsNavIDs.General
if (section) {
const navIDKey: string = Object.keys(SettingsNavIDs).find(
(navID) => navID.toLowerCase() == section
)
if (navIDKey) {
navID = SettingsNavIDs[navIDKey]
this.activeNavID.set(SettingsNavIDs[navIDKey])
}
}
this.activeNavID.set(navID)
this.settings.sidebarHiddenItemsEditing.set(
navID === SettingsNavIDs.General
? [...this.settingsForm.controls.sidebarHiddenItems.value]
: null
)
})
}
@@ -340,7 +310,6 @@ export class SettingsComponent
SETTINGS_KEYS.DOCUMENT_LIST_SIZE
),
slimSidebarEnabled: this.settings.get(SETTINGS_KEYS.SLIM_SIDEBAR),
sidebarHiddenItems: this.settings.get(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS),
darkModeUseSystem: this.settings.get(SETTINGS_KEYS.DARK_MODE_USE_SYSTEM),
darkModeEnabled: this.settings.get(SETTINGS_KEYS.DARK_MODE_ENABLED),
darkModeInvertThumbs: this.settings.get(
@@ -467,12 +436,6 @@ export class SettingsComponent
this.settingsForm.patchValue(currentFormValue)
}
if (this.settings.organizingSidebarItems()) {
this.settings.sidebarHiddenItemsEditing.set([
...this.settingsForm.controls.sidebarHiddenItems.value,
])
}
if (this.canViewSystemStatus) {
this.systemStatusService.get().subscribe((status) => {
this.systemStatus.set(status)
@@ -481,18 +444,8 @@ export class SettingsComponent
}
ngOnDestroy() {
this.settings.sidebarHiddenItemsEditing.set(null)
if (this.isDirty) this.settings.updateAppearanceSettings() // in case user changed appearance but didn't save
this.storeSub && this.storeSub.unsubscribe()
this.sidebarItemsSub.unsubscribe()
}
isSidebarItemShown(item: HideableSidebarItemID): boolean {
return !(this.settingsForm.value.sidebarHiddenItems || []).includes(item)
}
toggleSidebarItem(item: HideableSidebarItemID, checked: boolean): void {
this.settings.updateSidebarItemVisibility(item, checked)
}
public saveSettings() {
@@ -520,10 +473,6 @@ export class SettingsComponent
SETTINGS_KEYS.SLIM_SIDEBAR,
this.settingsForm.value.slimSidebarEnabled
)
this.settings.set(
SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS,
this.settingsForm.value.sidebarHiddenItems
)
this.settings.set(
SETTINGS_KEYS.DARK_MODE_USE_SYSTEM,
this.settingsForm.value.darkModeUseSystem
@@ -683,11 +632,6 @@ export class SettingsComponent
reset() {
this.settingsForm.patchValue(this.store.getValue())
if (this.settings.organizingSidebarItems()) {
this.settings.sidebarHiddenItemsEditing.set([
...this.settingsForm.controls.sidebarHiddenItems.value,
])
}
}
clearThemeColor() {
@@ -86,15 +86,12 @@
}
<div class="sidebar-sticky pt-3 pb-1 d-flex flex-column justify-space-around">
<ul class="nav flex-column">
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard) && !settingsService.organizingSidebarItems()">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="dashboard" routerLinkActive="active" (click)="closeMenu()"
<li class="nav-item app-link">
<a class="nav-link" routerLink="dashboard" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Dashboard" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="house"></i-bs><span class="nav-link-label"><ng-container i18n>Dashboard</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Dashboard" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Dashboard, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.Document }">
<a class="nav-link" routerLink="documents" routerLinkActive="active"
@@ -240,38 +237,29 @@
</div>
</li>
}
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews) && !settingsService.organizingSidebarItems()" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.SavedView }">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="savedviews" routerLinkActive="active" (click)="closeMenu()"
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.SavedView }">
<a class="nav-link" routerLink="savedviews" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Saved Views" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="window-stack"></i-bs><span class="nav-link-label"><ng-container i18n>Saved Views</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Saved Views" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.SavedViews, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows) && !settingsService.organizingSidebarItems()"
<li class="nav-item app-link"
*pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.Workflow }"
tourAnchor="tour.workflows">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="workflows" routerLinkActive="active" (click)="closeMenu()"
<a class="nav-link" routerLink="workflows" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Workflows" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="boxes"></i-bs><span class="nav-link-label"><ng-container i18n>Workflows</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Workflows" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Workflows, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail) && !settingsService.organizingSidebarItems()" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.MailAccount }"
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.MailAccount }"
tourAnchor="tour.mail">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="mail" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Mail"
<a class="nav-link" routerLink="mail" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Mail"
i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end" container="body"
triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="envelope"></i-bs><span class="nav-link-label"><ng-container i18n>Mail</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Mail" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Mail, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.Delete, type: PermissionType.Document }">
<a class="nav-link" routerLink="trash" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Trash"
@@ -334,16 +322,13 @@
</a>
</li>
}
<li class="nav-item mt-2 position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation) && !settingsService.organizingSidebarItems()" tourAnchor="tour.outro">
<a class="text-muted small d-flex align-items-center flex-wrap text-decoration-none nav-anchor" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()"
<li class="nav-item mt-2" tourAnchor="tour.outro">
<a class="text-muted small d-flex align-items-center flex-wrap text-decoration-none nav-anchor"
target="_blank" rel="noopener noreferrer" href="https://docs.paperless-ngx.com" ngbPopover="Documentation"
i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end" container="body"
triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="d-flex me-2" name="question-circle"></i-bs><span><ng-container i18n>Documentation</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Documentation" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Documentation, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item" [class.visually-hidden]="slimSidebarEnabled">
<div class="text-muted small d-flex align-items-center flex-wrap nav-label">
@@ -15,7 +15,7 @@ import { provideUiTour } from 'ngx-ui-tour-ng-bootstrap'
import { of, throwError } from 'rxjs'
import { routes } from 'src/app/app-routing.module'
import { SavedView } from 'src/app/data/saved-view'
import { HideableSidebarItemID, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { PermissionsGuard } from 'src/app/guards/permissions.guard'
import {
@@ -287,82 +287,6 @@ describe('AppFrameComponent', () => {
jest.useRealTimers()
})
it('should hide configured sidebar items', () => {
settingsService.set(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Dashboard,
HideableSidebarItemID.Workflows,
])
fixture.detectChanges()
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]')
.parentElement.classList
).toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="workflows"]')
.parentElement.classList
).toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="mail"]').parentElement
.classList
).not.toContain('d-none')
})
it('should show hidden items and visibility switches while customizing', () => {
settingsService.set(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Dashboard,
])
settingsService.sidebarHiddenItemsEditing.set([
HideableSidebarItemID.Dashboard,
])
fixture.detectChanges()
expect(
fixture.nativeElement.querySelectorAll('pngx-input-switch').length
).toBe(5)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]')
.parentElement.classList
).not.toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).toContain('opacity-50')
settingsService.set(SETTINGS_KEYS.SLIM_SIDEBAR, true)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => toggle.classList.contains('d-none'))
).toBe(true)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).not.toContain('pe-5')
settingsService.set(SETTINGS_KEYS.SLIM_SIDEBAR, false)
component.slimSidebarAnimating.set(true)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => toggle.classList.contains('d-none'))
).toBe(true)
component.slimSidebarAnimating.set(false)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => !toggle.classList.contains('d-none'))
).toBe(true)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).toContain('pe-5')
})
it('should show error on toggle slim sidebar if store settings fails', () => {
jest.spyOn(console, 'warn').mockImplementation(() => {})
const toastSpy = jest.spyOn(toastService, 'showError')
@@ -7,7 +7,6 @@ import {
} from '@angular/cdk/drag-drop'
import { NgClass } from '@angular/common'
import { Component, HostListener, inject, OnInit, signal } from '@angular/core'
import { FormsModule } from '@angular/forms'
import { ActivatedRoute, Router, RouterModule } from '@angular/router'
import {
NgbCollapseModule,
@@ -22,11 +21,7 @@ import { Observable } from 'rxjs'
import { first } from 'rxjs/operators'
import { Document } from 'src/app/data/document'
import { SavedView } from 'src/app/data/saved-view'
import {
CollapsibleSection,
HideableSidebarItemID,
SETTINGS_KEYS,
} from 'src/app/data/ui-settings'
import { CollapsibleSection, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { ComponentCanDeactivate } from 'src/app/guards/dirty-doc.guard'
import { DocumentTitlePipe } from 'src/app/pipes/document-title.pipe'
@@ -53,7 +48,6 @@ import { ChatComponent } from '../chat/chat/chat.component'
import { BrandMarkComponent } from '../common/logo/brand-mark/brand-mark.component'
import { LogoComponent } from '../common/logo/logo.component'
import { ProfileEditDialogComponent } from '../common/profile-edit-dialog/profile-edit-dialog.component'
import { SwitchComponent } from '../common/input/switch/switch.component'
import { DocumentDetailComponent } from '../document-detail/document-detail.component'
import { ComponentWithPermissions } from '../with-permissions/with-permissions.component'
import { GlobalSearchComponent } from './global-search/global-search.component'
@@ -82,8 +76,6 @@ const SCROLL_THRESHOLD = 16
NgxBootstrapIconsModule,
DragDropModule,
TourNgBootstrap,
FormsModule,
SwitchComponent,
],
})
export class AppFrameComponent
@@ -106,7 +98,6 @@ export class AppFrameComponent
readonly isMenuCollapsed = signal(true)
readonly slimSidebarAnimating = signal(false)
readonly mobileSearchHidden = signal(false)
readonly HideableSidebarItemID = HideableSidebarItemID
private readonly versionSetting = this.settingsService.getSignal<string>(
SETTINGS_KEYS.VERSION
)
@@ -204,10 +195,6 @@ export class AppFrameComponent
}, 200) // slightly longer than css animation for slim sidebar
}
toggleSidebarItem(item: HideableSidebarItemID, visible: boolean): void {
this.settingsService.updateSidebarItemVisibility(item, visible)
}
toggleAttributesSections(event?: Event): void {
event?.preventDefault()
event?.stopPropagation()
@@ -1,6 +1,6 @@
<div [class.mb-3]="!compact">
<div [class.row]="!compact">
@if (!horizontal && !compact) {
<div class="mb-3">
<div class="row">
@if (!horizontal) {
<div class="d-flex align-items-center position-relative hidden-button-container col-md-3">
<label class="form-label" [for]="inputId" [ngbTooltip]="showUnsetNote && isUnset ? tipContent: null" placement="end">
{{title}}
@@ -17,8 +17,8 @@
}
<div [ngClass]="{'align-items-center': horizontal, 'd-flex': horizontal}">
<div class="form-check form-switch">
<input #inputField type="checkbox" class="form-check-input" [id]="inputId" [(ngModel)]="value" [ngModelOptions]="{standalone: true}" (change)="onChange(value)" (blur)="onTouched()" [disabled]="disabled" [attr.aria-label]="compact ? title : null">
@if (horizontal && !compact) {
<input #inputField type="checkbox" class="form-check-input" [id]="inputId" [(ngModel)]="value" [ngModelOptions]="{standalone: true}" (change)="onChange(value)" (blur)="onTouched()" [disabled]="disabled">
@if (horizontal) {
<label class="form-check-label" [class.text-muted]="showUnsetNote && isUnset" [for]="inputId" [ngbTooltip]="showUnsetNote && isUnset ? tipContent: null" placement="end">
{{title}}
@if (showUnsetNote && isUnset) {
@@ -48,14 +48,4 @@ describe('SwitchComponent', () => {
component.value = undefined
expect(component.isUnset).toBeTruthy()
})
it('should support a compact layout', () => {
component.compact = true
component.title = 'Test switch'
fixture.detectChanges()
expect(fixture.nativeElement.querySelector('.mb-3')).toBeNull()
expect(fixture.nativeElement.querySelector('.row')).toBeNull()
expect(input.getAttribute('aria-label')).toEqual('Test switch')
})
})
@@ -25,9 +25,6 @@ export class SwitchComponent extends AbstractInputComponent<boolean> {
@Input()
showUnsetNote: boolean = false
@Input()
compact: boolean = false
constructor() {
super()
}
-16
View File
@@ -24,16 +24,6 @@ export enum CollapsibleSection {
ATTRIBUTES = 'attributes',
}
export enum HideableSidebarItemID {
Dashboard = 'dashboard',
SavedViews = 'saved_views',
Workflows = 'workflows',
Mail = 'mail',
Documentation = 'documentation',
}
export const HIDEABLE_SIDEBAR_ITEM_IDS = Object.values(HideableSidebarItemID)
export const PAPERLESS_GREEN_HEX = '#17541f'
export const SETTINGS_KEYS = {
@@ -66,7 +56,6 @@ export const SETTINGS_KEYS = {
NOTES_ENABLED: 'general-settings:notes-enabled',
AUDITLOG_ENABLED: 'general-settings:auditlog-enabled',
SLIM_SIDEBAR: 'general-settings:slim-sidebar',
SIDEBAR_HIDDEN_ITEMS: 'general-settings:sidebar:hidden-items',
ATTRIBUTES_SECTIONS_COLLAPSED:
'general-settings:attributes-sections-collapsed',
UPDATE_CHECKING_ENABLED: 'general-settings:update-checking:enabled',
@@ -138,11 +127,6 @@ export const SETTINGS: UiSetting[] = [
type: 'boolean',
default: false,
},
{
key: SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS,
type: 'array',
default: [],
},
{
key: SETTINGS_KEYS.ATTRIBUTES_SECTIONS_COLLAPSED,
type: 'array',
@@ -14,11 +14,7 @@ import { CustomFieldDataType } from '../data/custom-field'
import { DEFAULT_DISPLAY_FIELDS, DisplayField } from '../data/document'
import { SavedView } from '../data/saved-view'
import { RemoteOCRModeConfig } from '../data/paperless-config'
import {
HideableSidebarItemID,
SETTINGS_KEYS,
UiSettings,
} from '../data/ui-settings'
import { SETTINGS_KEYS, UiSettings } from '../data/ui-settings'
import { PermissionsService } from './permissions.service'
import { CustomFieldsService } from './rest/custom-fields.service'
import { SettingsService } from './settings.service'
@@ -234,35 +230,6 @@ describe('SettingsService', () => {
expect(notesEnabled()).toBeFalsy()
})
it('updates sidebar item visibility', () => {
httpTestingController
.expectOne(`${environment.apiBaseUrl}ui_settings/`)
.flush(ui_settings)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(false)
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Workflows,
false
)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(true)
expect(settingsService.get(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS)).toEqual([])
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Workflows,
true
)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(false)
})
it('updates setting signals when settings are reinitialized', () => {
let req = httpTestingController.expectOne(
`${environment.apiBaseUrl}ui_settings/`
@@ -24,7 +24,6 @@ import { DEFAULT_DISPLAY_FIELDS, DisplayField } from '../data/document'
import { RemoteOCRModeConfig } from '../data/paperless-config'
import { SavedView } from '../data/saved-view'
import {
HideableSidebarItemID,
PAPERLESS_GREEN_HEX,
SETTINGS,
SETTINGS_KEYS,
@@ -314,18 +313,6 @@ export class SettingsService {
readonly globalDropzoneEnabled = signal(true)
readonly globalDropzoneActive = signal(false)
readonly organizingSidebarSavedViews = signal(false)
readonly sidebarHiddenItemsEditing = signal<HideableSidebarItemID[] | null>(
null
)
readonly organizingSidebarItems = computed(
() => this.sidebarHiddenItemsEditing() !== null
)
readonly sidebarHiddenItemsEditingChanged = new EventEmitter<
HideableSidebarItemID[]
>()
readonly hiddenSidebarItems = this.getSignal<HideableSidebarItemID[]>(
SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS
)
readonly allDisplayFields = signal<Array<{ id: DisplayField; name: string }>>(
DEFAULT_DISPLAY_FIELDS
@@ -762,29 +749,6 @@ export class SettingsService {
return this.storeSettings()
}
sidebarItemIsHidden(item: HideableSidebarItemID): boolean {
return (
this.sidebarHiddenItemsEditing() ?? this.hiddenSidebarItems()
).includes(item)
}
updateSidebarItemVisibility(
item: HideableSidebarItemID,
visible: boolean
): void {
const hiddenItems = new Set(
this.sidebarHiddenItemsEditing() ?? this.hiddenSidebarItems()
)
if (visible) {
hiddenItems.delete(item)
} else {
hiddenItems.add(item)
}
const updatedHiddenItems = [...hiddenItems]
this.sidebarHiddenItemsEditing.set(updatedHiddenItems)
this.sidebarHiddenItemsEditingChanged.emit(updatedHiddenItems)
}
updateSavedViewsVisibility(
dashboardVisibleViewIds: number[],
sidebarVisibleViewIds: number[]
+36 -42
View File
@@ -2,7 +2,6 @@ from __future__ import annotations
import logging
import tempfile
import uuid
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Literal
@@ -299,55 +298,53 @@ def modify_custom_fields(
) -> Literal["OK"]:
qs = Document.objects.filter(id__in=doc_ids).only("pk")
affected_docs = list(qs.values_list("pk", flat=True))
# Ensure add_custom_fields is a list of (int, value) tuples, supports old API
# Ensure add_custom_fields is a list of tuples, supports old API
add_custom_fields = (
[(int(field), value) for field, value in add_custom_fields.items()]
add_custom_fields.items()
if isinstance(add_custom_fields, dict)
else [(int(field), None) for field in add_custom_fields]
else [(field, None) for field in add_custom_fields]
)
# Resolved once, instead of re-querying the same field for every document
custom_fields_by_id: dict[int, CustomField] = CustomField.objects.in_bulk(
[field_id for field_id, _ in add_custom_fields],
)
# Passed to update_or_create() below rather than a bare id, so the FK is
# cached on the created instance and auditlog's post_save receiver does
# not reload it per row. Only needed for additions. content is deferred:
# the one field here that is both large and unused.
docs_by_id: dict[int, Document] = (
Document.objects.defer("content").in_bulk(affected_docs)
if add_custom_fields
else {}
)
custom_fields = CustomField.objects.filter(
id__in=[int(field) for field, _ in add_custom_fields],
).distinct()
for field_id, value in add_custom_fields:
custom_field = custom_fields_by_id[field_id]
value_field = CustomFieldInstance.TYPE_TO_DATA_STORE_NAME_MAP[
custom_field.data_type
]
is_doclink = custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK
for doc_id in affected_docs:
if is_doclink and value and doc_id in value:
# Prevent self-linking
continue
defaults = {}
custom_field = custom_fields.get(id=field_id)
if custom_field:
value_field = CustomFieldInstance.TYPE_TO_DATA_STORE_NAME_MAP[
custom_field.data_type
]
defaults[value_field] = value
if (
custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK
and value
and doc_id in value
):
# Prevent self-linking
continue
CustomFieldInstance.objects.update_or_create(
document=docs_by_id[doc_id],
field=custom_field,
defaults={value_field: value},
document_id=doc_id,
field_id=field_id,
defaults=defaults,
)
if is_doclink:
reflect_doclinks(docs_by_id[doc_id], custom_field, value)
if custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK:
doc = Document.objects.get(id=doc_id)
reflect_doclinks(doc, custom_field, value)
# For doc link fields that are being removed, remove symmetrical links.
# select_related avoids a per-instance reload of the document and field.
# For doc link fields that are being removed, remove symmetrical links
for doclink_being_removed_instance in CustomFieldInstance.objects.filter(
document_id__in=affected_docs,
field__id__in=remove_custom_fields,
field__data_type=CustomField.FieldDataType.DOCUMENTLINK,
value_document_ids__isnull=False,
).select_related("field", "document"):
):
for target_doc_id in doclink_being_removed_instance.value:
remove_doclink(
document=doclink_being_removed_instance.document,
document=Document.objects.get(
id=doclink_being_removed_instance.document.id,
),
field=doclink_being_removed_instance.field,
target_doc_id=target_doc_id,
)
@@ -382,7 +379,7 @@ def delete(doc_ids: list[int]) -> Literal["OK"]:
)
delete_ids = list({*doc_ids, *version_ids})
Document.objects.filter(id__in=delete_ids).delete(transaction_id=uuid.uuid4())
Document.objects.filter(id__in=delete_ids).delete()
from documents.search import get_backend
@@ -1180,13 +1177,10 @@ def remove_doclink(
"""
Removes a 'symmetrical' link to `document` from the target document's existing custom field instance
"""
# select_related: a signal receiver (auditlog) touches .document/.field on
# the save() below, without this that is a per-call reload query
target_doc_field_instance = (
CustomFieldInstance.objects.filter(document_id=target_doc_id, field=field)
.select_related("document", "field")
.first()
)
target_doc_field_instance = CustomFieldInstance.objects.filter(
document_id=target_doc_id,
field=field,
).first()
if (
target_doc_field_instance is not None
and document.id in target_doc_field_instance.value
+28 -66
View File
@@ -34,27 +34,6 @@ from paperless.signed_pickle import signed_pickle_loads
logger = logging.getLogger("paperless.classifier")
def _predict_with_threshold(classifier, X, threshold: float) -> int | None:
"""
Return the predicted class id, or None if:
- the prediction is -1 (no match), or
- the winning class probability is below the configured threshold.
Using predict_proba() instead of predict() lets us apply a minimum-confidence
cutoff so that uncertain predictions are discarded rather than assigned.
"""
probas = classifier.predict_proba(X)[0]
best_idx = int(probas.argmax())
best_class = int(classifier.classes_[best_idx])
if best_class == -1:
return None
if threshold > 0.0 and probas[best_idx] < threshold:
return None
return best_class
ADVANCED_TEXT_PROCESSING_ENABLED = (
settings.NLTK_LANGUAGE is not None and settings.NLTK_ENABLED
)
@@ -123,8 +102,7 @@ class DocumentClassifier:
# v8 - Added storage path classifier
# v9 - Changed from hashing to time/ids for re-train check
# v10 - HMAC-signed model file
# v11 - Use sample_weight for balanced training; predict_proba with threshold
FORMAT_VERSION = 11
FORMAT_VERSION = 10
HMAC_SIZE = 32 # SHA-256 digest length
@@ -346,13 +324,6 @@ class DocumentClassifier:
from sklearn.preprocessing import LabelBinarizer
from sklearn.preprocessing import MultiLabelBinarizer
# MLPClassifier does not support class_weight directly
# (https://github.com/scikit-learn/scikit-learn/issues/9113), so we use
# compute_sample_weight to balance classes during training and prevent
# over-represented correspondents from dominating predictions.
# https://scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_sample_weight.html
from sklearn.utils.class_weight import compute_sample_weight
# Step 2: vectorize data
logger.debug("Vectorizing data...")
notify("Vectorizing document content...")
@@ -398,7 +369,7 @@ class DocumentClassifier:
self.tags_binarizer = MultiLabelBinarizer()
labels_tags_vectorized = self.tags_binarizer.fit_transform(labels_tags)
self.tags_classifier = MLPClassifier(tol=0.01, random_state=0)
self.tags_classifier = MLPClassifier(tol=0.01)
self.tags_classifier.fit(data_vectorized, labels_tags_vectorized)
else:
self.tags_classifier = None
@@ -409,12 +380,8 @@ class DocumentClassifier:
notify(
f"Training correspondent classifier ({num_correspondents} correspondent(s))...",
)
self.correspondent_classifier = MLPClassifier(tol=0.01, random_state=0)
self.correspondent_classifier.fit(
data_vectorized,
labels_correspondent,
sample_weight=compute_sample_weight("balanced", labels_correspondent),
)
self.correspondent_classifier = MLPClassifier(tol=0.01)
self.correspondent_classifier.fit(data_vectorized, labels_correspondent)
else:
self.correspondent_classifier = None
logger.debug(
@@ -426,12 +393,8 @@ class DocumentClassifier:
notify(
f"Training document type classifier ({num_document_types} type(s))...",
)
self.document_type_classifier = MLPClassifier(tol=0.01, random_state=0)
self.document_type_classifier.fit(
data_vectorized,
labels_document_type,
sample_weight=compute_sample_weight("balanced", labels_document_type),
)
self.document_type_classifier = MLPClassifier(tol=0.01)
self.document_type_classifier.fit(data_vectorized, labels_document_type)
else:
self.document_type_classifier = None
logger.debug(
@@ -443,11 +406,10 @@ class DocumentClassifier:
"Training storage paths classifier...",
)
notify(f"Training storage path classifier ({num_storage_paths} path(s))...")
self.storage_path_classifier = MLPClassifier(tol=0.01, random_state=0)
self.storage_path_classifier = MLPClassifier(tol=0.01)
self.storage_path_classifier.fit(
data_vectorized,
labels_storage_path,
sample_weight=compute_sample_weight("balanced", labels_storage_path),
)
else:
self.storage_path_classifier = None
@@ -584,24 +546,24 @@ class DocumentClassifier:
def predict_correspondent(self, content: str) -> int | None:
if self.correspondent_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.correspondent_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
correspondent_id = self.correspondent_classifier.predict(X)
if correspondent_id != -1:
return correspondent_id
else:
return None
else:
return None
def predict_document_type(self, content: str) -> int | None:
if self.document_type_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.document_type_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
document_type_id = self.document_type_classifier.predict(X)
if document_type_id != -1:
return document_type_id
else:
return None
else:
return None
def predict_tags(self, content: str) -> list[int]:
from sklearn.utils.multiclass import type_of_target
@@ -627,10 +589,10 @@ class DocumentClassifier:
def predict_storage_path(self, content: str) -> int | None:
if self.storage_path_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.storage_path_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
storage_path_id = self.storage_path_classifier.predict(X)
if storage_path_id != -1:
return storage_path_id
else:
return None
else:
return None
+4 -1
View File
@@ -52,6 +52,7 @@ from documents.templating.workflows import parse_w_workflow_placeholders
from documents.utils import compute_checksum
from documents.utils import copy_basic_file_stats
from documents.utils import copy_file_with_basic_stats
from documents.utils import normalize_unicode
from documents.utils import run_subprocess
from paperless.config import OcrConfig
from paperless.config import RemoteOCRConfig
@@ -201,7 +202,9 @@ class ConsumerPluginMixin:
self.renew_logging_group()
self.filename = self.metadata.filename or self.input_doc.original_file.name
self.filename = normalize_unicode(
self.metadata.filename or self.input_doc.original_file.name,
)
def _send_progress(
self,
@@ -156,15 +156,6 @@ class FileStabilityTracker:
logger.debug(f"File disappeared during stability check: {path}")
continue
# Stable, but empty: some scanners create a zero byte placeholder
# and only write the page some time later. Consuming it now can
# only fail so drop it and let the writer's next event
# (or the periodic rescan) bring it back once it has content
if not tracked.last_size:
to_remove.append(path)
logger.debug("Ignoring stable but empty file: %s", path)
continue
# File is stable, we can return it
to_yield.append(path)
logger.info(f"File is stable: {path}")
+10 -6
View File
@@ -21,6 +21,7 @@ from documents.models import Workflow
from documents.models import WorkflowTrigger
from documents.permissions import permitted_object_ids
from documents.regex import safe_regex_search
from documents.utils import normalize_unicode
if TYPE_CHECKING:
from django.db.models import QuerySet
@@ -311,11 +312,12 @@ def consumable_document_matches_workflow(
trigger_matched = False
# Document filename vs trigger filename
document_filename = normalize_unicode(document.original_file.name)
if (
trigger.filter_filename is not None
and len(trigger.filter_filename) > 0
and not fnmatch(
document.original_file.name.lower(),
document_filename.lower(),
trigger.filter_filename.lower(),
)
):
@@ -328,10 +330,12 @@ def consumable_document_matches_workflow(
# Document path vs trigger path
# Use the original_path if set, else us the original_file
match_against = (
document.original_path
if document.original_path is not None
else document.original_file
match_against = normalize_unicode(
str(
document.original_path
if document.original_path is not None
else document.original_file,
),
)
if (
@@ -536,7 +540,7 @@ def existing_document_matches_workflow(
and len(trigger.filter_filename) > 0
and document.original_filename is not None
and not fnmatch(
document.original_filename.lower(),
normalize_unicode(document.original_filename).lower(),
trigger.filter_filename.lower(),
)
):
+4 -11
View File
@@ -1,5 +1,4 @@
import datetime
import uuid
from pathlib import Path
from typing import Final
@@ -28,6 +27,7 @@ from django_softdelete.models import SoftDeleteModel
from documents.data_models import DocumentSource
from documents.parsers import get_default_file_extension
from documents.utils import normalize_unicode
class ModelWithOwner(models.Model):
@@ -468,7 +468,7 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
context_document = (
self.root_document if self.root_document_id is not None else self
)
result = str(context_document)
result = normalize_unicode(str(context_document))
if counter:
result += f"_{counter:02}"
@@ -515,20 +515,13 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
def delete(
self,
*args,
transaction_id=None,
**kwargs,
):
# Versions must share the root's transaction ID so they are restored
# together by django-softdelete.
if transaction_id is None:
transaction_id = uuid.uuid4()
# If deleting a root document, move all its versions to trash as well.
if self.root_document_id is None:
Document.objects.filter(root_document=self).delete(
transaction_id=transaction_id,
)
Document.objects.filter(root_document=self).delete()
return super().delete(
*args,
transaction_id=transaction_id,
**kwargs,
)
+8
View File
@@ -87,6 +87,7 @@ from documents.regex import validate_regex_pattern
from documents.templating.filepath import validate_filepath_template_and_render
from documents.templating.utils import convert_format_str_to_template_format
from documents.templating.workflows import validate_workflow_template
from documents.utils import normalize_unicode
from documents.validators import uri_validator
from documents.validators import url_validator
from documents.versioning import sort_versions_newest_first
@@ -3120,6 +3121,13 @@ class WorkflowTriggerSerializer(serializers.ModelSerializer[WorkflowTrigger]):
):
attrs["filter_path"] = None
# Normalize once at write time, since these are matched against many
# documents but edited rarely
if attrs.get("filter_filename") is not None:
attrs["filter_filename"] = normalize_unicode(attrs["filter_filename"])
if attrs.get("filter_path") is not None:
attrs["filter_path"] = normalize_unicode(attrs["filter_path"])
if (
"filter_custom_field_query" in attrs
and attrs["filter_custom_field_query"] is not None
+11 -13
View File
@@ -1,7 +1,6 @@
import logging
import os
import re
import unicodedata
from collections.abc import Iterable
from pathlib import PurePath
@@ -26,6 +25,7 @@ from documents.templating.environment import _template_environment
from documents.templating.filters import format_datetime
from documents.templating.filters import get_cf_value
from documents.templating.filters import localize_date
from documents.utils import normalize_unicode
logger = logging.getLogger("paperless.templating")
@@ -42,7 +42,7 @@ class FilePathTemplate(Template):
3. Removing extra spaces before and after forward slashes
4. Preserving spaces in other parts of the path
"""
value = unicodedata.normalize("NFC", value)
value = normalize_unicode(value)
value = value.replace("\n", "").replace("\r", "")
value = re.sub(r"\s*/\s*", "/", value)
@@ -184,17 +184,17 @@ def get_basic_metadata_context(
"""
return {
"title": pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", document.title),
normalize_unicode(document.title),
replacement_text="-",
),
"correspondent": pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", document.correspondent.name),
normalize_unicode(document.correspondent.name),
replacement_text="-",
)
if document.correspondent
else no_value_default,
"document_type": pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", document.document_type.name),
normalize_unicode(document.document_type.name),
replacement_text="-",
)
if document.document_type
@@ -205,8 +205,7 @@ def get_basic_metadata_context(
"owner_username": document.owner.username
if document.owner
else no_value_default,
"original_name": unicodedata.normalize(
"NFC",
"original_name": normalize_unicode(
PurePath(document.original_filename).with_suffix("").name,
)
if document.original_filename
@@ -275,12 +274,12 @@ def get_tags_context(tags: Iterable[Tag]) -> dict[str, str | list[str]]:
return {
"tag_list": pathvalidate.sanitize_filename(
",".join(
sorted(unicodedata.normalize("NFC", tag.name) for tag in tags),
sorted(normalize_unicode(tag.name) for tag in tags),
),
replacement_text="-",
),
# Assumed to be ordered, but a template could loop through to find what they want
"tag_name_list": [unicodedata.normalize("NFC", x.name) for x in tags],
"tag_name_list": [normalize_unicode(x.name) for x in tags],
}
@@ -307,7 +306,7 @@ def get_custom_fields_context(
CustomField.FieldDataType.LONG_TEXT,
}:
value = pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", field_instance.value),
normalize_unicode(field_instance.value),
replacement_text="-",
)
elif (
@@ -316,8 +315,7 @@ def get_custom_fields_context(
):
options = field_instance.field.extra_data["select_options"]
value = pathvalidate.sanitize_filename(
unicodedata.normalize(
"NFC",
normalize_unicode(
next(
option["label"]
for option in options
@@ -330,7 +328,7 @@ def get_custom_fields_context(
value = field_instance.value
field_data["custom_fields"][
pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", field_instance.field.name),
normalize_unicode(field_instance.field.name),
replacement_text="-",
)
] = {
-62
View File
@@ -207,65 +207,3 @@ class TestTrashAPI(DirectoriesMixin, APITestCase):
)
self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
self.assertIn("have not yet been deleted", resp.data["documents"][0])
def _make_versioned_document(self) -> tuple[Document, list[Document]]:
root = Document.objects.create(
title="root",
content="root-content",
checksum="root",
mime_type="application/pdf",
)
versions = [
Document.objects.create(
title=f"v{index}",
content=f"v{index}-content",
checksum=f"v{index}",
mime_type="application/pdf",
root_document=root,
version_index=index,
)
for index in range(1, 3)
]
return root, versions
def test_api_trash_restore_document_restores_its_versions(self) -> None:
"""
GIVEN:
- Existing document with two versions
WHEN:
- API request to delete the document
- API request to restore it from the trash
THEN:
- Only the document itself is listed in the trash
- A version cannot be restored without its root
- The document is restored together with all of its versions
"""
root, versions = self._make_versioned_document()
self.client.force_login(user=self.user)
self.client.delete(f"/api/documents/{root.pk}/")
self.assertEqual(Document.deleted_objects.count(), 3)
resp = self.client.get("/api/trash/")
self.assertEqual(resp.status_code, status.HTTP_200_OK)
self.assertEqual(resp.data["count"], 1)
self.assertEqual(resp.data["results"][0]["id"], root.pk)
# A version cannot be restored while its root remains in the trash.
resp = self.client.post(
"/api/trash/",
{"action": "restore", "documents": [versions[0].pk]},
)
self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
self.assertIn("Restore the root document", resp.data["documents"][0])
resp = self.client.post(
"/api/trash/",
{"action": "restore", "documents": [root.pk]},
)
self.assertEqual(resp.status_code, status.HTTP_200_OK)
self.assertEqual(Document.deleted_objects.count(), 0)
self.assertCountEqual(
Document.objects.filter(root_document=root).values_list("id", flat=True),
[version.pk for version in versions],
)
@@ -0,0 +1,69 @@
import unicodedata
from typing import TYPE_CHECKING
from unittest import mock
import celery.result
import pytest
from django.core.files.uploadedfile import SimpleUploadedFile
from documents.models import Document
if TYPE_CHECKING:
from documents.data_models import ConsumableDocument
@pytest.fixture()
def consume_file_mock():
with mock.patch("documents.tasks.consume_file.apply_async") as m:
m.return_value = celery.result.AsyncResult(id="test-task-id")
yield m
@pytest.fixture()
def directories(tmp_path, settings, _media_settings):
scratch = tmp_path / "scratch"
scratch.mkdir()
settings.SCRATCH_DIR = scratch
return scratch
@pytest.mark.django_db
class TestUpdateVersionNFCNormalization:
def test_nfd_filename_normalized_to_nfc(
self,
admin_client,
consume_file_mock: mock.MagicMock,
directories,
):
"""Uploaded new-version file with NFD filename must have its temp name stored as NFC."""
document = Document.objects.create(
title="Test",
content="content",
checksum="checksum",
mime_type="application/pdf",
)
nfd = unicodedata.normalize("NFD", "Rechnung März.pdf")
nfc = unicodedata.normalize("NFC", "Rechnung März.pdf")
assert nfd != nfc
uploaded = SimpleUploadedFile(
nfd,
b"%PDF-1.4 test",
content_type="application/pdf",
)
response = admin_client.post(
f"/api/documents/{document.pk}/update_version/",
{"document": uploaded},
)
assert response.status_code == 200
task_kwargs = consume_file_mock.call_args.kwargs["kwargs"]
input_doc: ConsumableDocument = task_kwargs["input_doc"]
assert input_doc.original_file.name == nfc, (
f"Expected NFC filename {nfc!r}, got {input_doc.original_file.name!r}"
)
assert unicodedata.is_normalized("NFC", input_doc.original_file.name)
-5
View File
@@ -392,11 +392,6 @@ class TestBulkEdit(DirectoriesMixin, TestCase):
self.assertFalse(Document.objects.filter(id=self.doc1.id).exists())
self.assertFalse(Document.objects.filter(id=version.id).exists())
Document.deleted_objects.get(id=self.doc1.id).restore(strict=False)
self.assertTrue(Document.objects.filter(id=self.doc1.id).exists())
self.assertTrue(Document.objects.filter(id=version.id).exists())
def test_delete_version_document_keeps_root(self) -> None:
version = Document.objects.create(
checksum="A-v1",
-145
View File
@@ -3,7 +3,6 @@ import warnings
from pathlib import Path
from unittest import mock
import numpy as np
import pytest
from django.conf import settings
from django.test import TestCase
@@ -12,7 +11,6 @@ from django.test import override_settings
from documents.classifier import ClassifierModelCorruptError
from documents.classifier import DocumentClassifier
from documents.classifier import IncompatibleClassifierVersionError
from documents.classifier import _predict_with_threshold
from documents.classifier import load_classifier
from documents.models import Correspondent
from documents.models import Document
@@ -627,103 +625,6 @@ class TestClassifier(DirectoriesMixin, TestCase):
self.assertEqual(self.classifier.predict_storage_path(doc1.content), sp.pk)
self.assertIsNone(self.classifier.predict_storage_path(doc2.content))
def test_predict_rejects_prediction_below_match_threshold(self) -> None:
"""
GIVEN:
- Classifiers trained against test data with confident predictions
WHEN:
- CLASSIFIER_MATCH_THRESHOLD exceeds the model's confidence
THEN:
- Every predict_* method discards the match in favor of no match
"""
c1 = Correspondent.objects.create(
name="c1",
matching_algorithm=Correspondent.MATCH_AUTO,
)
dt1 = DocumentType.objects.create(
name="dt1",
matching_algorithm=DocumentType.MATCH_AUTO,
)
sp1 = StoragePath.objects.create(
name="sp1",
matching_algorithm=StoragePath.MATCH_AUTO,
)
doc1 = Document.objects.create(
title="doc1",
content="this is a document from c1",
correspondent=c1,
document_type=dt1,
storage_path=sp1,
checksum="A",
)
Document.objects.create(
title="doc2",
content="this is a document from no one",
checksum="B",
)
self.classifier.train()
predictors = {
"correspondent": self.classifier.predict_correspondent,
"document_type": self.classifier.predict_document_type,
"storage_path": self.classifier.predict_storage_path,
}
# No real prediction can reach a confidence this high, so this
# isolates the threshold check from the model's actual output.
with override_settings(CLASSIFIER_MATCH_THRESHOLD=0.999999):
for name, predict in predictors.items():
with self.subTest(field=name):
self.assertIsNone(predict(doc1.content))
def test_train_uses_balanced_sample_weight(self) -> None:
"""
GIVEN:
- A training set with correspondents, document types and storage paths
WHEN:
- The classifier is trained
THEN:
- Each MLP classifier is fit with balanced sample weights, so that
over-represented classes don't dominate predictions
"""
c1 = Correspondent.objects.create(
name="c1",
matching_algorithm=Correspondent.MATCH_AUTO,
)
dt1 = DocumentType.objects.create(
name="dt1",
matching_algorithm=DocumentType.MATCH_AUTO,
)
sp1 = StoragePath.objects.create(
name="sp1",
matching_algorithm=StoragePath.MATCH_AUTO,
)
Document.objects.create(
title="doc1",
content="this is a document from c1",
correspondent=c1,
document_type=dt1,
storage_path=sp1,
checksum="A",
)
Document.objects.create(
title="doc2",
content="this is a document from no one",
checksum="B",
)
with mock.patch(
"sklearn.utils.class_weight.compute_sample_weight",
return_value=None,
) as mocked_compute_sample_weight:
self.classifier.train()
self.assertEqual(mocked_compute_sample_weight.call_count, 3)
for call in mocked_compute_sample_weight.call_args_list:
self.assertEqual(call.args[0], "balanced")
def test_one_tag_predict(self) -> None:
t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
@@ -909,52 +810,6 @@ class TestClassifier(DirectoriesMixin, TestCase):
load_classifier(raise_exception=True)
class _StubProbaClassifier:
"""
A fake scikit-learn classifier exposing just enough of the API for
`_predict_with_threshold`: `classes_` and `predict_proba`.
"""
def __init__(self, classes: list[int], probabilities: list[float]) -> None:
self.classes_ = np.array(classes)
self._probabilities = np.array([probabilities])
def predict_proba(self, X) -> np.ndarray:
return self._probabilities
@pytest.mark.parametrize(
("classes", "probabilities", "threshold", "expected"),
[
# confident prediction above the threshold is returned
([-1, 3], [0.1, 0.9], 0.6, 3),
# prediction below the threshold is discarded
([-1, 3], [0.45, 0.55], 0.6, None),
# boundary: exactly at the threshold is accepted, not discarded
([-1, 3], [0.4, 0.6], 0.6, 3),
# the winning class is the "no match" pseudo-class, regardless of its
# own confidence
([-1, 3], [0.99, 0.01], 0.0, None),
# threshold of 0.0 disables the confidence check entirely
([-1, 3], [0.45, 0.55], 0.0, 3),
],
)
def test_predict_with_threshold(classes, probabilities, threshold, expected) -> None:
classifier = _StubProbaClassifier(classes, probabilities)
result = _predict_with_threshold(classifier, X=None, threshold=threshold)
assert result == expected
def test_classifier_match_threshold_default() -> None:
"""
GIVEN:
- No PAPERLESS_CLASSIFIER_MATCH_THRESHOLD environment variable is set
THEN:
- The classifier match threshold defaults to 0.6
"""
assert settings.CLASSIFIER_MATCH_THRESHOLD == 0.6
def test_preprocess_content() -> None:
"""
GIVEN:
+1 -5
View File
@@ -110,7 +110,7 @@ class TestDocument(TestCase):
checksum="checksum",
mime_type="application/pdf",
)
version = Document.objects.create(
Document.objects.create(
root_document=root,
correspondent=root.correspondent,
title="Version",
@@ -124,10 +124,6 @@ class TestDocument(TestCase):
self.assertEqual(Document.objects.count(), 0)
self.assertEqual(Document.deleted_objects.count(), 2)
root.restore(strict=False)
self.assertTrue(Document.objects.filter(pk=version.pk).exists())
def test_file_name(self) -> None:
doc = Document(
mime_type="application/pdf",
@@ -0,0 +1,48 @@
import unicodedata
from datetime import date
import pytest
from documents.models import Correspondent
from documents.models import Document
@pytest.mark.django_db
class TestGetPublicFilenameNfc:
def test_normalizes_nfd_title_to_nfc(self) -> None:
nfd_title = unicodedata.normalize("NFD", "Gehaltserhöhung")
assert not unicodedata.is_normalized("NFC", nfd_title)
doc = Document(
mime_type="application/pdf",
title=nfd_title,
created=date(2025, 10, 17),
)
result = doc.get_public_filename()
assert unicodedata.is_normalized("NFC", result)
assert (
result
== "2025-10-17 "
+ unicodedata.normalize(
"NFC",
nfd_title,
)
+ ".pdf"
)
def test_normalizes_nfd_correspondent_name_to_nfc(self) -> None:
nfd_name = unicodedata.normalize("NFD", "Müller GmbH")
correspondent = Correspondent.objects.create(name=nfd_name)
doc = Document.objects.create(
mime_type="application/pdf",
title="Rechnung",
created=date(2025, 10, 17),
correspondent=correspondent,
)
result = doc.get_public_filename()
assert unicodedata.is_normalized("NFC", result)
@@ -136,23 +136,6 @@ def wait_for_mock_call(
return False
def sleep_past_stability(
owner: FileStabilityTracker | ConsumerThread,
*,
windows: float = 1.5,
) -> None:
"""
Block until a tracked file's stability window has certainly elapsed.
Args:
owner: The tracker, or the consumer thread running one, whose
configured stability delay sets the wait.
windows: How many stability windows to wait, giving slop for a slow
or loaded test runner.
"""
sleep(owner.stability_delay * windows)
class TestTrackedFile:
"""Tests for the TrackedFile dataclass."""
@@ -278,56 +261,6 @@ class TestFileStabilityTracker:
assert len(stable) == 0
assert stability_tracker.pending_count == 1
def test_get_stable_files_skips_empty_file(
self,
stability_tracker: FileStabilityTracker,
tmp_path: Path,
) -> None:
"""
GIVEN:
- A zero byte file, tracked and past its stability delay
WHEN:
- Stable files are collected
THEN:
- The file is not yielded for consumption
- The file is dropped from tracking rather than held, so an
abandoned placeholder does not keep the watch loop awake
"""
empty = tmp_path / "scan.pdf"
empty.write_bytes(b"")
stability_tracker.track(empty, Change.added)
sleep_past_stability(stability_tracker)
stable = list(stability_tracker.get_stable_files())
assert stable == []
assert stability_tracker.pending_count == 0
def test_empty_file_is_yielded_once_content_arrives(
self,
stability_tracker: FileStabilityTracker,
tmp_path: Path,
) -> None:
"""
GIVEN:
- A zero byte file which was dropped from tracking while empty
WHEN:
- The writer fills the file and a new event re-tracks it
THEN:
- The file is yielded for consumption once it is stable
"""
target = tmp_path / "scan.pdf"
target.write_bytes(b"")
stability_tracker.track(target, Change.added)
sleep_past_stability(stability_tracker)
assert list(stability_tracker.get_stable_files()) == []
target.write_bytes(b"%PDF-1.4 content")
stability_tracker.track(target, Change.modified)
sleep_past_stability(stability_tracker)
assert list(stability_tracker.get_stable_files()) == [target]
def test_get_stable_files_deleted_during_check(self, temp_file: Path) -> None:
"""Test deleted file is not returned during stability check."""
tracker = FileStabilityTracker(stability_delay=0.1)
@@ -946,51 +879,6 @@ class TestCommandWatch:
mock_consume_file_delay.apply_async.assert_called()
def test_scanner_placeholder_is_not_consumed_while_empty(
self,
consumption_dir: Path,
sample_pdf: Path,
mock_consume_file_delay: MagicMock,
start_consumer: Callable[..., ConsumerThread],
) -> None:
"""
GIVEN:
- A scanner which creates a zero byte placeholder and only writes
the page some time later (GH discussion #13969)
WHEN:
- The placeholder sits untouched well past the stability delay
- The scanner then writes the real content
THEN:
- The empty placeholder is never queued, as it could only fail
with "Unsupported mime type inode/x-empty"
- The file is queued exactly once, when the content lands
"""
thread = start_consumer(stability_delay=0.2)
target = consumption_dir / "scan.pdf"
target.write_bytes(b"") # the scanner's placeholder
# Well past the stability delay: the old behaviour queued it here.
sleep_past_stability(thread, windows=5)
if thread.exception:
raise thread.exception
assert mock_consume_file_delay.apply_async.call_count == 0
shutil.copy(sample_pdf, target) # the scanner finishes the page
assert wait_for_mock_call(
mock_consume_file_delay.apply_async,
timeout_s=5.0,
)
if thread.exception:
raise thread.exception
assert mock_consume_file_delay.apply_async.call_count == 1
queued_doc = mock_consume_file_delay.apply_async.call_args.kwargs["kwargs"][
"input_doc"
]
assert queued_doc.original_file.name == "scan.pdf"
def test_ignores_macos_files(
self,
consumption_dir: Path,
+80
View File
@@ -0,0 +1,80 @@
import unicodedata
import pytest
from documents.data_models import ConsumableDocument
from documents.data_models import DocumentSource
from documents.matching import consumable_document_matches_workflow
from documents.matching import existing_document_matches_workflow
from documents.models import Document
from documents.models import Workflow
from documents.models import WorkflowTrigger
@pytest.mark.django_db
class TestMatchingNfcNormalization:
def test_consumable_document_filename_nfd_matches_nfc_pattern(
self,
tmp_path,
) -> None:
"""
GIVEN:
- A file on disk whose name is NFD-normalized
- A workflow trigger filename filter typed as NFC
WHEN:
- The consumable document is checked against the trigger
THEN:
- It matches, because both sides are normalized before comparing
"""
nfd_name = unicodedata.normalize("NFD", "Gehaltserhöhung.pdf")
nfc_pattern = unicodedata.normalize("NFC", "*Gehaltserhöhung*")
assert nfd_name != unicodedata.normalize("NFC", nfd_name)
file_path = tmp_path / nfd_name
file_path.write_bytes(b"%PDF-1.4 test")
document = ConsumableDocument(
source=DocumentSource.ConsumeFolder,
original_file=file_path,
)
trigger = WorkflowTrigger(
type=WorkflowTrigger.WorkflowTriggerType.CONSUMPTION,
filter_filename=nfc_pattern,
sources=[],
)
matched, reason = consumable_document_matches_workflow(document, trigger)
assert matched, reason
def test_existing_document_filename_nfd_matches_nfc_pattern(self) -> None:
"""
GIVEN:
- A Document whose original_filename is NFD-normalized (e.g. from
before normalization was applied at consumption time)
- A workflow trigger filename filter typed as NFC
WHEN:
- The document is checked against the trigger
THEN:
- It matches, because both sides are normalized before comparing
"""
nfd_name = unicodedata.normalize("NFD", "Gehaltserhöhung.pdf")
nfc_pattern = unicodedata.normalize("NFC", "*Gehaltserhöhung*")
document = Document.objects.create(
title="Test",
content="content",
checksum="checksum",
mime_type="application/pdf",
original_filename=nfd_name,
)
workflow = Workflow.objects.create(name="Test workflow", order=0)
trigger = WorkflowTrigger.objects.create(
type=WorkflowTrigger.WorkflowTriggerType.DOCUMENT_ADDED,
filter_filename=nfc_pattern,
)
workflow.triggers.add(trigger)
matched, reason = existing_document_matches_workflow(document, trigger)
assert matched, reason
@@ -0,0 +1,6 @@
from documents.utils import normalize_unicode
class TestNormalizeUnicode:
def test_none_passes_through(self) -> None:
assert normalize_unicode(None) is None
-33
View File
@@ -32,7 +32,6 @@ from documents.signals.handlers import update_llm_suggestions_cache
from documents.tests.utils import DirectoriesMixin
from documents.tests.utils import read_streaming_response
from paperless.models import ApplicationConfiguration
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
@@ -738,38 +737,6 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="openai-like",
)
def test_ai_suggestions_with_llm_provider_error(
self,
mock_get_ai_classification,
) -> None:
mock_get_ai_classification.side_effect = LLMProviderError(
"confidential provider response",
)
self.client.force_login(user=self.user)
response = self.client.get(
f"/api/documents/{self.document.pk}/ai_suggestions/",
)
self.assertEqual(response.status_code, status.HTTP_502_BAD_GATEWAY)
self.assertEqual(
response.json(),
{
"ai": [
"AI backend rejected the request. Check logs for details.",
],
},
)
self.assertNotIn("confidential provider response", response.content.decode())
self.assertIsNone(
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
+20
View File
@@ -1,6 +1,7 @@
import hashlib
import logging
import shutil
import unicodedata
from collections.abc import Callable
from collections.abc import Iterable
from collections.abc import Iterator
@@ -31,6 +32,25 @@ def identity(iterable: Iterable[_T]) -> Iterable[_T]:
return iterable
def normalize_unicode(value: str | None) -> str | None:
"""
Normalize a string to Unicode NFC form, or return None unchanged.
This is the single normalization pass for any user- or filesystem-supplied
text that ends up in a filename, path, or is compared/matched against one
(titles, correspondent/tag/type names, uploaded filenames, workflow and
mail rule filename/path filters). Composed (NFC) and decomposed (NFD)
forms of the same visible text are different byte sequences, which breaks
exact comparisons and filesystem lookups even though the text looks
identical. Always normalize through this function rather than calling
unicodedata.normalize() directly, so every call site agrees on the same
form.
"""
if value is None:
return None
return unicodedata.normalize("NFC", value)
class QuerySetStream(Generic[_M]):
"""Stream a QuerySet via .iterator(chunk_size=...) instead of
materializing it (plus any prefetch caches) all at once, while still
+5 -31
View File
@@ -231,6 +231,7 @@ from documents.tasks import sanity_check
from documents.tasks import train_classifier
from documents.tasks import update_document_parent_tags
from documents.utils import get_boolean
from documents.utils import normalize_unicode
from documents.versioning import VersionResolutionError
from documents.versioning import annotate_effective_content
from documents.versioning import get_latest_version_for_root
@@ -252,7 +253,6 @@ from paperless.views import StandardPagination
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.ai_classifier import get_llm_output_language
from paperless_ai.chat import stream_chat_with_documents
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
from paperless_ai.matching import extract_unmatched_names
from paperless_ai.matching import match_correspondents_by_name
@@ -1604,22 +1604,6 @@ class DocumentViewSet(
{"ai": [_("AI backend request timed out.")]},
status=status.HTTP_503_SERVICE_UNAVAILABLE,
)
except LLMProviderError:
logger.exception(
"AI backend rejected the request for document %s",
doc.pk,
)
return Response(
{
"ai": [
_(
"AI backend rejected the request. "
"Check logs for details.",
),
],
},
status=status.HTTP_502_BAD_GATEWAY,
)
set_llm_suggestions_cache(
doc.pk,
llm_suggestions,
@@ -2085,6 +2069,7 @@ class DocumentViewSet(
try:
doc_name, doc_data = serializer.validated_data.get("document")
doc_name = normalize_unicode(doc_name)
version_label = serializer.validated_data.get("version_label")
t = int(mktime(datetime.now().timetuple()))
@@ -3351,7 +3336,7 @@ class PostDocumentView(GenericAPIView[Any]):
serializer.is_valid(raise_exception=True)
doc_name, doc_data = serializer.validated_data.get("document")
doc_name = normalize("NFC", doc_name)
doc_name = normalize_unicode(doc_name)
correspondent_id = serializer.validated_data.get("correspondent")
document_type_id = serializer.validated_data.get("document_type")
storage_path_id = serializer.validated_data.get("storage_path")
@@ -5454,10 +5439,7 @@ class TrashView(ListModelMixin, PassUserMixin):
model = Document
# A version is listed separately only when its root is not in the trash.
queryset = Document.deleted_objects.exclude(
root_document_id__in=Document.deleted_objects.values("id"),
)
queryset = Document.deleted_objects.all()
def get(self, request: Request, format: str | None = None) -> Response:
self.serializer_class = DocumentSerializer
@@ -5488,15 +5470,7 @@ class TrashView(ListModelMixin, PassUserMixin):
return HttpResponseForbidden("Insufficient permissions")
action = serializer.validated_data.get("action")
if action == "restore":
restored = list(self.get_queryset().filter(id__in=doc_ids))
if len(restored) != len(doc_ids):
raise ValidationError(
{
"documents": [
"Restore the root document instead of one of its versions.",
],
},
)
restored = list(Document.deleted_objects.filter(id__in=doc_ids))
for doc in restored:
doc.restore(strict=False)
if restored:
File diff suppressed because it is too large Load Diff
-7
View File
@@ -96,13 +96,6 @@ MODEL_FILE = get_path_from_env(
"PAPERLESS_MODEL_FILE",
DATA_DIR / "classification_model.pickle",
)
# Minimum confidence (0.0-1.0) for the ML classifier to assign a correspondent,
# document type, or storage path. 0.0 disables the threshold.
CLASSIFIER_MATCH_THRESHOLD: Final[float] = get_float_from_env(
"PAPERLESS_CLASSIFIER_MATCH_THRESHOLD",
0.6,
)
LLM_INDEX_DIR = DATA_DIR / "llm_index"
LLM_INDEX_LOCK = LLM_INDEX_DIR / "index.lock"
# Cross-process read/write lock guarding the LLM index compaction/migration
+47 -97
View File
@@ -4,24 +4,21 @@ from django.conf import settings
from django.contrib.auth.models import User
from documents.models import Document
from documents.permissions import permitted_object_ids
from documents.permissions import restrict_queryset_to_visible
from documents.permissions import user_is_unrestricted
from documents.permissions import get_objects_for_user_owner_aware
from paperless.config import AIConfig
from paperless_ai.base_model import ClassificationSuggestions
from paperless_ai.base_model import TaxonomyChoiceDict
from paperless_ai.base_model import classification_suggestions_to_model
from paperless_ai.client import AIClient
from paperless_ai.db import db_connection_released
from paperless_ai.indexing import _node_document_ids
from paperless_ai.indexing import retrieve_similar_nodes
from paperless_ai.indexing import truncate_content
from paperless_ai.prompts.context import ClassificationPromptContext
from paperless_ai.prompts.context import LocalizationPromptContext
from paperless_ai.prompts.context import RagContextPromptContext
from paperless_ai.prompts.render import render_prompt
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidates
from paperless_ai.taxonomy import _node_document_weights
from paperless_ai.taxonomy import build_taxonomy_candidates
from paperless_ai.taxonomy import empty_taxonomy_candidates
from paperless_ai.taxonomy import format_taxonomy_for_prompt
@@ -40,48 +37,6 @@ logger = logging.getLogger("paperless_ai.rag_classifier")
TAXONOMY_CANDIDATE_TOP_K = 15
def _fulltext_similar_documents(
document: Document,
user: User | None,
top_k: int,
) -> list[SimilarDocument]:
"""Rank-based fallback when no embedding backend is configured. Uses
Tantivy's "More Like This" (term-overlap similarity) instead of vector
similarity - cruder, but far better than no candidates at all.
more_like_this_ids returns only a ranked ID list, no scores, so weight is
synthesized from rank (descending from top_k) rather than claiming a
similarity magnitude that doesn't exist. An unrestricted user (none, or an
active superuser - see user_is_unrestricted) is normalized to ``None``
before calling, since the backend's permission filter has no superuser
short-circuit of its own. Results are re-checked with
restrict_queryset_to_visible() since Tantivy's indexed permission fields
lag the DB via async reindexing.
"""
from documents.search import get_backend
unrestricted = user_is_unrestricted(user)
search_user = None if unrestricted else user
backend = get_backend()
similar_ids = backend.more_like_this_ids(
document.pk,
user=search_user,
limit=top_k,
)
if not unrestricted:
allowed_ids = set(
restrict_queryset_to_visible(
Document.objects.filter(pk__in=similar_ids),
user,
"view_document",
).values_list("pk", flat=True),
)
similar_ids = [doc_id for doc_id in similar_ids if doc_id in allowed_ids]
return [
SimilarDocument(document_id=doc_id, weight=float(top_k - rank))
for rank, doc_id in enumerate(similar_ids)
]
def get_language_name(language_code: str) -> str:
normalized_language_code = language_code.lower()
for code, name in settings.LANGUAGES:
@@ -181,52 +136,43 @@ def get_taxonomy_context(
user: User | None = None,
max_docs: int = 5,
) -> tuple[TaxonomyCandidates, str]:
"""One retrieval feeds both taxonomy candidates and RAG text context. Uses
vector similarity when an embedding backend is configured, otherwise
falls back to Tantivy full-text "More Like This" similarity - see
_fulltext_similar_documents. On any retrieval failure, degrades to empty
candidates/context rather than propagating the exception - neither a
vector-store outage nor a search-index issue should block classification,
only its context-assisted enrichment.
"""One retrieval feeds both taxonomy candidates and RAG text context.
On any retrieval failure, degrades to empty candidates/context rather than
propagating the exception - a vector-store outage should not block
classification, only its RAG-assisted enrichment.
"""
ai_config = AIConfig()
try:
if ai_config.llm_embedding_backend:
# None means "no restriction" to retrieve_similar_nodes. An
# unrestricted user (no user at all, or an active superuser -- see
# user_is_unrestricted) can see every document, so skip
# materializing every visible pk into a Python list and passing it
# through as an IN filter: for a large library that is a wasted
# quadratic scan in the vector store at best, and past ~32,763
# documents a hard sqlite3.OperationalError (SQLite's
# bound-parameter limit) at worst.
# permitted_object_ids() has its own superuser shortcut that would
# return every Document's id anyway, so this changes nothing about
# which documents are considered -- only how we get there.
visible_document_ids = (
None
if user_is_unrestricted(user)
else list(permitted_object_ids(user, Document, "view_document"))
)
nodes = retrieve_similar_nodes(
document,
top_k=TAXONOMY_CANDIDATE_TOP_K,
document_ids=visible_document_ids,
)
similar_documents = _node_document_weights(nodes)
else:
# See _fulltext_similar_documents: it applies its own permission
# filter via `user`, so no visible-document-id list is needed here.
similar_documents = _fulltext_similar_documents(
document,
user,
top_k=TAXONOMY_CANDIDATE_TOP_K,
# None means "no restriction" to retrieve_similar_nodes. A superuser
# (like no user at all) can see every document, so skip materializing
# every visible pk into a Python list and passing it through as an IN
# filter: for a large library that is a wasted quadratic scan in the
# vector store at best, and past ~32,763 documents a hard
# sqlite3.OperationalError (SQLite's bound-parameter limit) at worst.
# get_objects_for_user_owner_aware() would return every Document for a
# superuser anyway (guardian's own with_superuser shortcut), so this
# changes nothing about which documents are considered -- only how we
# get there.
visible_document_ids = (
None
if user is None or user.is_superuser
else list(
get_objects_for_user_owner_aware(
user,
"view_document",
Document,
).values_list("pk", flat=True),
)
)
nodes = retrieve_similar_nodes(
document,
top_k=TAXONOMY_CANDIDATE_TOP_K,
document_ids=visible_document_ids,
)
candidates = build_taxonomy_candidates(similar_documents, user)
candidates = build_taxonomy_candidates(nodes, user)
# similar_documents is already ordered by descending weight; don't lose it.
similar_document_ids = [s["document_id"] for s in similar_documents]
# ``nodes`` are already ordered by descending vector similarity; don't lose it.
similar_document_ids = list(dict.fromkeys(_node_document_ids(nodes)))
similar_documents_by_id = Document.objects.in_bulk(similar_document_ids)
similar_docs = [
similar_documents_by_id[document_id]
@@ -240,8 +186,8 @@ def get_taxonomy_context(
context_blocks.append(f"TITLE: {title}\n{text}")
except Exception:
logger.exception(
"Failed to retrieve similar-document context for document %s; "
"continuing without taxonomy candidates or similar-document context.",
"Failed to retrieve RAG neighbours for document %s; continuing "
"without taxonomy candidates or similar-document context.",
document.pk,
)
return empty_taxonomy_candidates(), ""
@@ -295,13 +241,17 @@ def get_ai_document_classification(
) -> ClassificationSuggestions:
ai_config = AIConfig()
candidates, context = get_taxonomy_context(document, user)
prompt = build_prompt_with_rag(
document,
ai_config,
candidates=candidates,
context=context,
)
if ai_config.llm_embedding_backend:
candidates, context = get_taxonomy_context(document, user)
prompt = build_prompt_with_rag(
document,
ai_config,
candidates=candidates,
context=context,
)
else:
candidates = empty_taxonomy_candidates()
prompt = build_prompt_without_rag(document, ai_config, candidates=candidates)
client = AIClient()
# Hand the pooled DB connection back while the (slow) LLM query runs so it
+3 -19
View File
@@ -22,7 +22,6 @@ from paperless.network import validate_outbound_http_url
from paperless_ai.base_model import ClassificationSuggestions
from paperless_ai.base_model import DocumentClassifierSchema
from paperless_ai.base_model import model_to_classification_suggestions
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
logger = logging.getLogger("paperless_ai.client")
@@ -133,7 +132,7 @@ class AIClient:
from llama_index.core.llms import ChatMessage
if self.settings.llm_backend == LLMBackend.OLLAMA:
with self._normalize_errors():
with self._normalize_timeouts():
result = self.llm.chat(
[ChatMessage(role="user", content=prompt)],
format=DocumentClassifierSchema.model_json_schema(),
@@ -154,7 +153,7 @@ class AIClient:
content=f"{prompt}\n\n"
f"Answer by calling the {tool.metadata.name} tool. Do not write the answer as text.",
)
with self._normalize_errors():
with self._normalize_timeouts():
result = self.llm.chat_with_tools(
tools=[tool],
user_msg=user_msg,
@@ -174,7 +173,7 @@ class AIClient:
)
@contextmanager
def _normalize_errors(self) -> Iterator[None]:
def _normalize_timeouts(self) -> Iterator[None]:
try:
yield
except httpx.TimeoutException as exc:
@@ -182,23 +181,8 @@ class AIClient:
except Exception as exc:
if self._is_openai_timeout(exc):
raise LLMTimeoutError from exc
if self._is_provider_error(exc):
raise LLMProviderError from exc
raise
def _is_provider_error(self, exc: Exception) -> bool:
if self.settings.llm_backend == LLMBackend.OLLAMA:
from ollama import ResponseError
return isinstance(exc, ResponseError)
if self.settings.llm_backend == LLMBackend.OPENAI_LIKE:
from openai import APIStatusError
return isinstance(exc, APIStatusError)
return False
def _is_openai_timeout(self, exc: Exception) -> bool:
if self.settings.llm_backend != LLMBackend.OPENAI_LIKE:
return False
-4
View File
@@ -1,6 +1,2 @@
class LLMTimeoutError(Exception):
pass
class LLMProviderError(Exception):
"""The LLM backend rejected the request."""
+17
View File
@@ -721,3 +721,20 @@ def retrieve_similar_nodes(
continue
filtered.append(node)
return filtered
def _node_document_ids(nodes: list["NodeWithScore"]) -> list[int]:
document_ids: list[int] = []
for node in nodes:
document_id = node.metadata.get("document_id")
if document_id is None: # pragma: no cover
# See the matching guard in retrieve_similar_nodes() above.
continue
try:
document_ids.append(int(document_id))
except ValueError: # pragma: no cover
logger.warning(
"Skipping LLM index result with invalid document_id %r.",
document_id,
)
return document_ids
+14 -31
View File
@@ -31,11 +31,6 @@ class TaxonomyCandidate(TypedDict):
weight: float
class SimilarDocument(TypedDict):
document_id: int
weight: float
class TaxonomyCandidates(TypedDict):
tags: list[TaxonomyCandidate]
document_types: list[TaxonomyCandidate]
@@ -54,10 +49,10 @@ def empty_taxonomy_candidates() -> TaxonomyCandidates:
)
def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument]:
"""Sum each node's similarity score into its document_id (a document can
appear via multiple chunks/nodes) and return one SimilarDocument per
distinct document_id."""
def _node_document_weights(nodes: list["NodeWithScore"]) -> dict[int, float]:
"""document_id -> that node's similarity score, summed if a document_id
appears more than once across the retrieved nodes (e.g. multiple chunks
of the same source document)."""
weights: dict[int, float] = defaultdict(float)
for node in nodes:
document_id = node.metadata.get("document_id")
@@ -70,14 +65,7 @@ def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument
weights[int(document_id)] += float(node.score or 0.0)
except (TypeError, ValueError): # pragma: no cover
continue
return sorted(
(
SimilarDocument(document_id=document_id, weight=weight)
for document_id, weight in weights.items()
),
key=lambda similar: similar["weight"],
reverse=True,
)
return weights
def _visible_ranked_candidates(
@@ -113,25 +101,20 @@ def _visible_ranked_candidates(
def build_taxonomy_candidates(
similar_documents: list[SimilarDocument],
nodes: list["NodeWithScore"],
user: User | None,
) -> TaxonomyCandidates:
"""Resolve each similar document's id to a live Document, read its
*current* tags/type/correspondent/storage_path via the ORM (never any
possibly-stale names an adapter's source might have cached), weight each
distinct taxonomy object by aggregate similarity weight, permission-filter
"""Resolve each neighbour node's document_id to a live Document, read its
*current* tags/type/correspondent/storage_path via the ORM (never the
possibly-stale names cached in vector-index node metadata), weight each
distinct taxonomy object by aggregate neighbour similarity, permission-filter
against what ``user`` can see, and return each category ranked by weight
and capped. ``similar_documents`` may come from either the vector-RAG
adapter or the full-text fallback adapter - both produce this same shape.
and capped.
"""
if not similar_documents:
return empty_taxonomy_candidates()
# Both adapters guarantee at most one SimilarDocument per document_id, so
# this never silently drops a duplicate's weight.
document_weights: dict[int, float] = {
s["document_id"]: s["weight"] for s in similar_documents
}
document_weights = _node_document_weights(nodes)
if not document_weights:
return empty_taxonomy_candidates()
# Only .tags.all() needs prefetching (a reverse M2M, one extra query for
# the whole batch). document_type/correspondent/storage_path are read
+22 -306
View File
@@ -1,5 +1,4 @@
import datetime
from collections.abc import Generator
from types import SimpleNamespace
from unittest.mock import MagicMock
from unittest.mock import patch
@@ -7,24 +6,18 @@ from unittest.mock import patch
import pytest
import pytest_mock
from django.test import override_settings
from guardian.shortcuts import assign_perm
from guardian.shortcuts import remove_perm
from documents.models import Document
from documents.search import TantivyBackend
from documents.tests.factories import DocumentFactory
from documents.tests.factories import TagFactory
from documents.tests.factories import UserFactory
from paperless.config import AIConfig
from paperless_ai.ai_classifier import TAXONOMY_CANDIDATE_TOP_K
from paperless_ai.ai_classifier import _fulltext_similar_documents
from paperless_ai.ai_classifier import build_localization_prompt
from paperless_ai.ai_classifier import build_prompt_with_rag
from paperless_ai.ai_classifier import build_prompt_without_rag
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.ai_classifier import get_language_name
from paperless_ai.ai_classifier import get_taxonomy_context
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidate
from paperless_ai.taxonomy import TaxonomyCandidates
@@ -227,10 +220,12 @@ def test_use_rag_if_configured(
@pytest.mark.django_db
@patch("paperless_ai.client.AIClient.run_llm_query")
@patch("paperless_ai.ai_classifier.build_prompt_with_rag")
@patch("paperless_ai.ai_classifier.build_prompt_without_rag")
@patch("paperless_ai.ai_classifier.AIConfig")
@override_settings(LLM_BACKEND="ollama", LLM_MODEL="some_model")
def test_use_rag_prompt_even_without_embedding_backend(
mock_build_prompt_with_rag,
def test_use_without_rag_if_not_configured(
mock_ai_config,
mock_build_prompt_without_rag,
mock_run_llm_query,
mock_document,
):
@@ -240,13 +235,13 @@ def test_use_rag_prompt_even_without_embedding_backend(
WHEN:
- get_ai_document_classification() is called
THEN:
- The RAG-context prompt builder is still used (fed by the full-text
fallback's context/candidates instead of the vector store's)
- The non-RAG prompt builder is used
"""
mock_build_prompt_with_rag.return_value = "Prompt with RAG"
mock_ai_config.return_value.llm_embedding_backend = None
mock_build_prompt_without_rag.return_value = "Prompt without RAG"
mock_run_llm_query.return_value = NESTED_SUGGESTIONS
get_ai_document_classification(mock_document)
mock_build_prompt_with_rag.assert_called_once()
mock_build_prompt_without_rag.assert_called_once()
@pytest.mark.django_db
@@ -325,7 +320,6 @@ def test_build_localization_prompt_preserves_unicode_characters():
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_assembles_rag_text_and_candidates():
"""
GIVEN:
@@ -360,7 +354,6 @@ def test_get_taxonomy_context_assembles_rag_text_and_candidates():
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents():
"""
GIVEN:
@@ -431,7 +424,6 @@ def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents(
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_no_similar_docs():
"""
GIVEN:
@@ -455,67 +447,6 @@ def test_get_taxonomy_context_no_similar_docs():
}
@pytest.mark.django_db
def test_get_taxonomy_context_uses_fulltext_fallback_when_no_embedding_backend(
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- No LLM embedding backend is configured (the default test settings)
WHEN:
- get_taxonomy_context() is called
THEN:
- _fulltext_similar_documents() is called with the document, the user
and TAXONOMY_CANDIDATE_TOP_K
- retrieve_similar_nodes() (the vector path) is never called
"""
document = DocumentFactory.create(content="Some content")
mock_fulltext = mocker.patch(
"paperless_ai.ai_classifier._fulltext_similar_documents",
return_value=[],
)
mock_retrieve = mocker.patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
get_taxonomy_context(document, user=None)
mock_fulltext.assert_called_once_with(
document,
None,
top_k=TAXONOMY_CANDIDATE_TOP_K,
)
mock_retrieve.assert_not_called()
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_uses_vector_path_when_embedding_backend_configured(
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An LLM embedding backend is configured
WHEN:
- get_taxonomy_context() is called
THEN:
- retrieve_similar_nodes() (the vector path) is called
- _fulltext_similar_documents() (the no-embedding-backend fallback)
is never called
"""
document = DocumentFactory.create(content="Some content")
mock_retrieve = mocker.patch(
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_fulltext = mocker.patch(
"paperless_ai.ai_classifier._fulltext_similar_documents",
)
get_taxonomy_context(document, user=None)
mock_retrieve.assert_called_once()
mock_fulltext.assert_not_called()
class TestGetTaxonomyContextVisibility:
"""get_taxonomy_context must not materialize every visible document id
for a user who can already see the whole library: a superuser (like no
@@ -528,7 +459,6 @@ class TestGetTaxonomyContextVisibility:
"""
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_skips_permission_lookup_for_superuser(
self,
mocker: pytest_mock.MockerFixture,
@@ -547,18 +477,17 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
)
user = UserFactory.create(is_superuser=True)
get_taxonomy_context(document, user)
mock_permitted.assert_not_called()
mock_get_objects.assert_not_called()
assert mock_retrieve.call_args.kwargs["document_ids"] is None
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_skips_permission_lookup_when_no_user(
self,
mocker: pytest_mock.MockerFixture,
@@ -577,17 +506,16 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
)
get_taxonomy_context(document, None)
mock_permitted.assert_not_called()
mock_get_objects.assert_not_called()
assert mock_retrieve.call_args.kwargs["document_ids"] is None
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_restricts_to_visible_documents_for_non_superuser(
self,
mocker: pytest_mock.MockerFixture,
@@ -598,7 +526,7 @@ class TestGetTaxonomyContextVisibility:
WHEN:
- get_taxonomy_context() is called
THEN:
- The user's permitted document ids are looked up and passed to
- The user's visible document ids are looked up and passed to
retrieve_similar_nodes() as a restriction
"""
document = DocumentFactory.create(content="Some content")
@@ -606,232 +534,21 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
return_value=[1, 2, 3],
mock_queryset = mocker.MagicMock()
mock_queryset.values_list.return_value = [1, 2, 3]
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
return_value=mock_queryset,
)
user = UserFactory.create(is_superuser=False)
get_taxonomy_context(document, user)
mock_permitted.assert_called_once_with(user, Document, "view_document")
mock_get_objects.assert_called_once_with(user, "view_document", Document)
assert mock_retrieve.call_args.kwargs["document_ids"] == [1, 2, 3]
@pytest.mark.django_db
class TestFulltextSimilarDocuments:
"""_fulltext_similar_documents is the no-embedding-backend fallback: it
asks the Tantivy full-text index for "More Like This" neighbours instead
of the vector store, and synthesizes a rank-based weight since Tantivy's
more_like_this_ids returns only an ordered id list, no scores.
"""
@pytest.fixture
def fulltext_backend(
self,
mocker: pytest_mock.MockerFixture,
) -> Generator[TantivyBackend, None, None]:
"""An in-memory Tantivy backend, wired up as the module-level
singleton _fulltext_similar_documents resolves via get_backend()."""
backend = TantivyBackend(path=None)
backend.open()
mocker.patch("documents.search.get_backend", return_value=backend)
try:
yield backend
finally:
backend.close()
def test_ranks_by_rank_based_weight_descending(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and two similar documents indexed in Tantivy
WHEN:
- _fulltext_similar_documents() is called
THEN:
- Each result's weight reflects its rank (first result weighted
higher than the second), not a raw similarity score
"""
source = DocumentFactory.create(content="quarterly financial report details")
first = DocumentFactory.create(content="quarterly financial report details")
second = DocumentFactory.create(content="financial report")
for doc in (source, first, second):
fulltext_backend.add_or_update(doc)
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert len(result) == 2
weight_by_id = {s["document_id"]: s["weight"] for s in result}
assert weight_by_id[first.pk] > weight_by_id[second.pk]
def test_excludes_source_document(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document indexed in Tantivy with no other documents
WHEN:
- _fulltext_similar_documents() is called
THEN:
- An empty list is returned - the source document is never its
own similar document
"""
source = DocumentFactory.create(content="unique unrelated content")
fulltext_backend.add_or_update(source)
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert result == []
def test_empty_index_returns_empty_list(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A document that has never been indexed (fresh/empty Tantivy index)
WHEN:
- _fulltext_similar_documents() is called
THEN:
- An empty list is returned rather than raising
"""
source = DocumentFactory.create(content="never indexed")
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert result == []
def test_respects_top_k_limit(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and four similar documents indexed
WHEN:
- _fulltext_similar_documents() is called with top_k=2
THEN:
- At most 2 results are returned
"""
source = DocumentFactory.create(content="shared overlapping keyword text")
fulltext_backend.add_or_update(source)
for _ in range(4):
fulltext_backend.add_or_update(
DocumentFactory.create(content="shared overlapping keyword text"),
)
result = _fulltext_similar_documents(source, user=None, top_k=2)
assert len(result) == 2
def test_result_shape_is_similar_document(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and one similar document indexed
WHEN:
- _fulltext_similar_documents() is called
THEN:
- Each result is a SimilarDocument (document_id + weight only)
"""
source = DocumentFactory.create(content="shared content phrase")
other = DocumentFactory.create(content="shared content phrase")
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(other)
result = _fulltext_similar_documents(source, user=None, top_k=5)
# rank 0 (the only/best result) with top_k=5 -> weight = top_k - rank = 5.0,
# per the "first result gets top_k, the last gets 1" formula.
assert result == [SimilarDocument(document_id=other.pk, weight=5.0)]
def test_superuser_sees_other_users_documents(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document owned by one user and a similar document
owned by a different user, with no sharing between them
WHEN:
- _fulltext_similar_documents() is called with a superuser
THEN:
- The other user's document is still returned as a similar
document - a superuser must not be narrowed by the backend's
owner-based permission filter
"""
owner = UserFactory.create()
other_owner = UserFactory.create()
superuser = UserFactory.create(is_superuser=True)
source = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
other = DocumentFactory.create(
content="shared content phrase",
owner=other_owner,
)
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(other)
result = _fulltext_similar_documents(source, user=superuser, top_k=5)
assert [s["document_id"] for s in result] == [other.pk]
def test_excludes_stale_permitted_document_for_regular_user(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A regular (non-superuser) user
- A similar document the user is permitted to view, and another
similar document indexed while the user still had view
permission but which has since had that permission revoked in
the database, i.e. the Tantivy index has stale permission data
WHEN:
- _fulltext_similar_documents() is called with that user
THEN:
- Only the still-permitted document is returned - the DB
re-check via restrict_queryset_to_visible() must catch the
document Tantivy's stale index still thinks is visible
"""
owner = UserFactory.create()
viewer = UserFactory.create(is_superuser=False)
source = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
permitted = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
now_private = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
assign_perm("view_document", viewer, permitted)
assign_perm("view_document", viewer, now_private)
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(permitted)
fulltext_backend.add_or_update(now_private)
# Revoke access after indexing, without reindexing: the index still
# carries viewer as a permitted viewer for `now_private`.
remove_perm("view_document", viewer, now_private)
result = _fulltext_similar_documents(source, user=viewer, top_k=5)
assert [s["document_id"] for s in result] == [permitted.pk]
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrieve):
"""
@@ -858,7 +575,6 @@ def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrie
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
@patch("paperless_ai.ai_classifier.build_taxonomy_candidates")
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
def test_get_taxonomy_context_candidate_building_failure_degrades_to_no_hints(
+5 -3
View File
@@ -1188,7 +1188,9 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, document_ids=[b.id])
assert all(int(node.metadata["document_id"]) == b.id for node in nodes)
assert all(
document_id == b.id for document_id in indexing._node_document_ids(nodes)
)
def test_excludes_self(
self,
@@ -1210,7 +1212,7 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, top_k=5)
assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}
assert set(indexing._node_document_ids(nodes)) == {b.id}
def test_excludes_self_with_multiple_chunks(
self,
@@ -1233,4 +1235,4 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, top_k=3)
assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}
assert set(indexing._node_document_ids(nodes)) == {b.id}
-48
View File
@@ -4,7 +4,6 @@ from unittest.mock import MagicMock
from unittest.mock import patch
import httpx
import ollama
import openai
import pytest
from llama_index.core.llms.llm import ToolSelection
@@ -12,7 +11,6 @@ from llama_index.core.llms.llm import ToolSelection
from paperless_ai.client import LLM_SYSTEM_PROMPT
from paperless_ai.client import PLACEHOLDER_API_KEY
from paperless_ai.client import AIClient
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
@@ -216,52 +214,6 @@ def test_run_llm_query_openai_timeout_raises_local_error(
client.run_llm_query("test_prompt")
def test_run_llm_query_openai_status_error_raises_provider_error(
mock_ai_config,
mock_openai_llm,
):
mock_ai_config.llm_backend = "openai-like"
mock_ai_config.llm_model = "test_model"
mock_ai_config.llm_endpoint = "http://test-url"
request = httpx.Request("POST", "http://test-url/v1/chat/completions")
body = {"error": {"message": "Thinking mode does not support this tool_choice"}}
mock_openai_llm.return_value.chat_with_tools.side_effect = openai.BadRequestError(
"Error code: 400",
response=httpx.Response(400, request=request, json=body),
body=body,
)
client = AIClient()
with pytest.raises(LLMProviderError) as exc_info:
client.run_llm_query("test_prompt")
assert str(exc_info.value) == ""
assert isinstance(exc_info.value.__cause__, openai.BadRequestError)
def test_run_llm_query_ollama_response_error_raises_provider_error(
mock_ai_config,
mock_ollama_llm,
):
mock_ai_config.llm_backend = "ollama"
mock_ai_config.llm_model = "test_model"
mock_ai_config.llm_endpoint = "http://test-url"
response_error = ollama.ResponseError(
"confidential provider response",
status_code=400,
)
mock_ollama_llm.return_value.chat.side_effect = response_error
client = AIClient()
with pytest.raises(LLMProviderError) as exc_info:
client.run_llm_query("test_prompt")
assert str(exc_info.value) == ""
assert exc_info.value.__cause__ is response_error
def test_run_llm_query_httpx_timeout_raises_local_error(
mock_ai_config,
mock_ollama_llm,
+31 -33
View File
@@ -1,4 +1,5 @@
import json
from types import SimpleNamespace
import pytest
import pytest_mock
@@ -9,14 +10,14 @@ from documents.tests.factories import DocumentTypeFactory
from documents.tests.factories import StoragePathFactory
from documents.tests.factories import TagFactory
from documents.tests.factories import UserFactory
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidates
from paperless_ai.taxonomy import build_taxonomy_candidates
from paperless_ai.taxonomy import format_taxonomy_for_prompt
def make_similar(document_id: int, weight: float) -> SimilarDocument:
return SimilarDocument(document_id=document_id, weight=weight)
def make_node(document_id: int, score: float) -> SimpleNamespace:
"""A stand-in for NodeWithScore: only ``.metadata``/``.score`` are read."""
return SimpleNamespace(metadata={"document_id": str(document_id)}, score=score)
@pytest.mark.django_db
@@ -52,9 +53,9 @@ class TestBuildTaxonomyCandidates:
doc_a.tags.add(tag)
doc_b = DocumentFactory.create()
doc_b.tags.add(tag)
similar_documents = [make_similar(doc_a.pk, 0.9), make_similar(doc_b.pk, 0.4)]
nodes = [make_node(doc_a.pk, 0.9), make_node(doc_b.pk, 0.4)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["tags"]) == 1
assert result["tags"][0]["id"] == tag.pk
@@ -79,9 +80,9 @@ class TestBuildTaxonomyCandidates:
document.tags.add(tag)
tag.name = "New Name"
tag.save()
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"][0]["name"] == "New Name"
@@ -101,9 +102,9 @@ class TestBuildTaxonomyCandidates:
document = DocumentFactory.create()
document.tags.add(tag)
tag.delete()
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"] == []
@@ -122,12 +123,9 @@ class TestBuildTaxonomyCandidates:
strong_doc.tags.add(strong_tag)
weak_doc = DocumentFactory.create()
weak_doc.tags.add(weak_tag)
similar_documents = [
make_similar(strong_doc.pk, 0.9),
make_similar(weak_doc.pk, 0.1),
]
nodes = [make_node(strong_doc.pk, 0.9), make_node(weak_doc.pk, 0.1)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert [c["name"] for c in result["tags"]] == ["Strong", "Weak"]
@@ -143,9 +141,9 @@ class TestBuildTaxonomyCandidates:
document = DocumentFactory.create()
for i in range(15):
document.tags.add(TagFactory.create(name=f"Tag{i}"))
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["tags"]) == 10
@@ -159,12 +157,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 correspondents are returned
"""
correspondents = CorrespondentFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(correspondent=c).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(correspondent=c).pk, 0.5)
for c in correspondents
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["correspondents"]) == 5
@@ -179,9 +177,9 @@ class TestBuildTaxonomyCandidates:
"""
document_type = DocumentTypeFactory.create(name="Invoice")
document = DocumentFactory.create(document_type=document_type)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["document_types"]) == 1
assert result["document_types"][0]["id"] == document_type.pk
@@ -197,12 +195,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 document_types are returned
"""
document_types = DocumentTypeFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(document_type=dt).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(document_type=dt).pk, 0.5)
for dt in document_types
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["document_types"]) == 5
@@ -217,9 +215,9 @@ class TestBuildTaxonomyCandidates:
"""
storage_path = StoragePathFactory.create(name="Invoices")
document = DocumentFactory.create(storage_path=storage_path)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["storage_paths"]) == 1
assert result["storage_paths"][0]["id"] == storage_path.pk
@@ -235,12 +233,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 storage_paths are returned
"""
storage_paths = StoragePathFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(storage_path=sp).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(storage_path=sp).pk, 0.5)
for sp in storage_paths
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["storage_paths"]) == 5
@@ -260,14 +258,14 @@ class TestBuildTaxonomyCandidates:
tag = TagFactory.create(name="Restricted")
document = DocumentFactory.create()
document.tags.add(tag)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
user = UserFactory.create()
mocker.patch(
"documents.permissions.permitted_object_ids",
return_value=[], # user cannot see this tag
)
result = build_taxonomy_candidates(similar_documents, user=user)
result = build_taxonomy_candidates(nodes, user=user)
assert result["tags"] == []
@@ -297,10 +295,10 @@ class TestBuildTaxonomyCandidates:
tag.save()
document = DocumentFactory.create()
document.tags.add(tag)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
spy = mocker.patch("documents.permissions.permitted_object_ids")
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"][0]["name"] == "Owned"
spy.assert_not_called()
+9 -7
View File
@@ -6,7 +6,6 @@ import socket
import ssl
import tempfile
import traceback
import unicodedata
from datetime import date
from datetime import timedelta
from fnmatch import fnmatch
@@ -45,6 +44,7 @@ from documents.models import Correspondent
from documents.models import PaperlessTask
from documents.parsers import is_mime_type_supported
from documents.tasks import consume_file
from documents.utils import normalize_unicode
from paperless.network import is_public_ip
from paperless.network import resolve_hostname_ips
from paperless_mail.models import MailAccount
@@ -617,10 +617,10 @@ class MailAccountHandler(LoggingMixin):
rule: MailRule,
) -> str | None:
if rule.assign_title_from == MailRule.TitleSource.FROM_SUBJECT:
return unicodedata.normalize("NFC", message.subject)
return normalize_unicode(message.subject)
elif rule.assign_title_from == MailRule.TitleSource.FROM_FILENAME:
return unicodedata.normalize("NFC", Path(att.filename).stem)
return normalize_unicode(Path(att.filename).stem)
elif rule.assign_title_from == MailRule.TitleSource.NONE:
return None
@@ -1004,6 +1004,8 @@ class MailAccountHandler(LoggingMixin):
consume_tasks = []
for att in message.attachments:
attachment_filename = normalize_unicode(att.filename)
if (
att.content_disposition != "attachment"
and rule.attachment_type
@@ -1018,7 +1020,7 @@ class MailAccountHandler(LoggingMixin):
if not self.filename_inclusion_matches(
rule.filter_attachment_filename_include,
att.filename,
attachment_filename,
):
# Force the filename and pattern to the lowercase
# as this is system dependent otherwise
@@ -1030,7 +1032,7 @@ class MailAccountHandler(LoggingMixin):
continue
elif self.filename_exclusion_matches(
rule.filter_attachment_filename_exclude,
att.filename,
attachment_filename,
):
self.log.debug(
f"Rule {rule}: "
@@ -1064,7 +1066,7 @@ class MailAccountHandler(LoggingMixin):
)
attachment_name = pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", att.filename),
attachment_filename,
)
if attachment_name:
temp_filename = temp_dir / attachment_name
@@ -1175,7 +1177,7 @@ class MailAccountHandler(LoggingMixin):
doc_overrides = DocumentMetadataOverrides(
title=message.subject,
filename=pathvalidate.sanitize_filename(
unicodedata.normalize("NFC", f"{message.subject}.eml"),
normalize_unicode(f"{message.subject}.eml"),
),
correspondent_id=correspondent.id if correspondent else None,
document_type_id=doc_type.id if doc_type else None,
+7
View File
@@ -8,6 +8,7 @@ from documents.serialisers import CorrespondentField
from documents.serialisers import DocumentTypeField
from documents.serialisers import OwnedObjectSerializer
from documents.serialisers import TagsField
from documents.utils import normalize_unicode
from paperless_mail.models import MailAccount
from paperless_mail.models import MailRule
from paperless_mail.models import ProcessedMail
@@ -161,6 +162,12 @@ class MailRuleSerializer(OwnedObjectSerializer):
raise serializers.ValidationError("Maximum mail age is unreasonably large.")
return value
def validate_filter_attachment_filename_include(self, value):
return normalize_unicode(value)
def validate_filter_attachment_filename_exclude(self, value):
return normalize_unicode(value)
class ProcessedMailSerializer(OwnedObjectSerializer):
class Meta:
+2 -22
View File
@@ -1,9 +1,7 @@
import logging
from celery import Task
from celery import shared_task
from documents.models import PaperlessTask
from paperless_mail.mail import MailAccountHandler
from paperless_mail.mail import MailError
from paperless_mail.models import MailAccount
@@ -12,26 +10,8 @@ from paperless_mail.models import MailRule
logger = logging.getLogger("paperless.mail.tasks")
@shared_task(bind=True)
def process_mail_accounts(self: Task, account_ids: list[int] | None = None) -> str:
# A scheduled check can still be running (or queued) when the next one
# ProcessedMail dedup only records a message once its
# handling has finished, so an overlapping run can still pick up the same
# not-yet-recorded message. Skip outright rather than race it.
other_mail_fetch_running = (
PaperlessTask.objects.filter(
task_type=PaperlessTask.TaskType.MAIL_FETCH,
status__in=[PaperlessTask.Status.PENDING, PaperlessTask.Status.STARTED],
)
.exclude(task_id=self.request.id)
.exists()
)
if other_mail_fetch_running:
logger.info(
"Mail account processing is already running; skipping this run.",
)
return "Skipped: mail account processing already in progress."
@shared_task
def process_mail_accounts(account_ids: list[int] | None = None) -> str:
total_new_documents = 0
accounts = (
MailAccount.objects.filter(pk__in=account_ids)
@@ -1,134 +0,0 @@
from typing import Final
import pytest
import pytest_mock
from documents.models import PaperlessTask
from documents.tests.factories import PaperlessTaskFactory
from paperless_mail import tasks
from paperless_mail.tests.factories import MailAccountFactory
from paperless_mail.tests.factories import MailRuleFactory
NO_DOCUMENTS_ADDED: Final = "No new documents were added."
SKIPPED: Final = "Skipped: mail account processing already in progress."
@pytest.mark.django_db
@pytest.mark.usefixtures("account_with_rule")
class TestProcessMailAccountsOverlap:
@pytest.fixture
def account_with_rule(self) -> None:
"""An enabled mail account with a single enabled rule."""
account = MailAccountFactory.create()
MailRuleFactory.create(account=account, enabled=True)
@pytest.mark.parametrize(
("status", "expected_result", "expected_call_count"),
[
pytest.param(
PaperlessTask.Status.PENDING,
SKIPPED,
0,
id="pending-task-blocks",
),
pytest.param(
PaperlessTask.Status.STARTED,
SKIPPED,
0,
id="started-task-blocks",
),
pytest.param(
PaperlessTask.Status.SUCCESS,
NO_DOCUMENTS_ADDED,
1,
id="finished-task-does-not-block",
),
],
)
def test_skips_only_while_another_mail_fetch_task_runs(
self,
mocker: pytest_mock.MockerFixture,
status: PaperlessTask.Status,
expected_result: str,
expected_call_count: int,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- Another mail fetch task row in the given status
WHEN:
- Mail accounts are processed
THEN:
- Processing is skipped only if that other task is pending or running
"""
PaperlessTaskFactory.create(
task_type=PaperlessTask.TaskType.MAIL_FETCH,
trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
status=status,
)
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts()
assert mocked_handle.call_count == expected_call_count
assert result == expected_result
def test_runs_when_no_other_mail_fetch_task_exists(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- No other mail fetch task rows
WHEN:
- Mail accounts are processed
THEN:
- The account is handled
"""
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts()
mocked_handle.assert_called_once()
assert result == NO_DOCUMENTS_ADDED
def test_does_not_skip_due_to_its_own_task_row(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- A running mail fetch task row belonging to this very task
WHEN:
- Mail accounts are processed under that task id
THEN:
- The task does not skip itself and handles the account
"""
PaperlessTaskFactory.create(
task_id="self-task-id",
task_type=PaperlessTask.TaskType.MAIL_FETCH,
trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
status=PaperlessTask.Status.STARTED,
)
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts.apply(task_id="self-task-id").result
mocked_handle.assert_called_once()
assert result == NO_DOCUMENTS_ADDED