mirror of
https://github.com/paperless-ngx/paperless-ngx.git
synced 2026-06-29 00:34:17 +00:00
Compare commits
19 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 3a891b38a8 | |||
| f4fa916579 | |||
| 75f0c4c92e | |||
| a020f64d08 | |||
| 11fb09e4f4 | |||
| 8ed4bf2011 | |||
| 92c016ce47 | |||
| fb3816486c | |||
| 4394403beb | |||
| f188d308eb | |||
| a5d6ff5f15 | |||
| 8405f66e38 | |||
| c3459d8f62 | |||
| 6f8e39c2e0 | |||
| eb292baa69 | |||
| 3d0b8343b9 | |||
| a7cec673bb | |||
| 449fd97b1f | |||
| fa0c4368d7 |
@@ -61,7 +61,7 @@ def replace_with_symlinks(
|
||||
total_duplicates = 0
|
||||
space_saved = 0
|
||||
|
||||
for file_list in duplicate_groups.values():
|
||||
for file_hash, file_list in duplicate_groups.items():
|
||||
# Keep the first file as the original, replace others with symlinks
|
||||
original_file = file_list[0]
|
||||
duplicates = file_list[1:]
|
||||
|
||||
+2
-8
@@ -42,7 +42,6 @@ dependencies = [
|
||||
"drf-spectacular~=0.28",
|
||||
"drf-spectacular-sidecar~=2026.5.1",
|
||||
"drf-writable-nested~=0.7.1",
|
||||
"faiss-cpu>=1.10",
|
||||
"filelock~=3.29.0",
|
||||
"flower~=2.0.1",
|
||||
"gotenberg-client~=0.14.0",
|
||||
@@ -57,7 +56,6 @@ dependencies = [
|
||||
"llama-index-embeddings-openai-like>=0.2.2",
|
||||
"llama-index-llms-ollama>=0.9.1",
|
||||
"llama-index-llms-openai-like>=0.7.1",
|
||||
"llama-index-vector-stores-faiss>=0.5.2",
|
||||
"nltk~=3.9.1",
|
||||
"ocrmypdf~=17.4.2",
|
||||
"openai>=2.32",
|
||||
@@ -74,6 +72,7 @@ dependencies = [
|
||||
"scikit-learn~=1.8.0",
|
||||
"sentence-transformers>=5.4.1",
|
||||
"setproctitle~=1.3.4",
|
||||
"sqlite-vec==0.1.9",
|
||||
"tantivy~=0.26.0",
|
||||
"tika-client~=0.11.0",
|
||||
"torch~=2.11.0",
|
||||
@@ -185,16 +184,12 @@ line-ending = "lf"
|
||||
[tool.ruff.lint]
|
||||
# https://docs.astral.sh/ruff/rules/
|
||||
extend-select = [
|
||||
"B", # https://docs.astral.sh/ruff/rules/#flake8-bugbear-b
|
||||
"COM", # https://docs.astral.sh/ruff/rules/#flake8-commas-com
|
||||
"DTZ", # https://docs.astral.sh/ruff/rules/#flake8-datetimez-dtz
|
||||
"PERF", # https://docs.astral.sh/ruff/rules/#perflint-perf
|
||||
"S324", # https://docs.astral.sh/ruff/rules/hashlib-insecure-hash-functions/
|
||||
"DJ", # https://docs.astral.sh/ruff/rules/#flake8-django-dj
|
||||
"EXE", # https://docs.astral.sh/ruff/rules/#flake8-executable-exe
|
||||
"FBT", # https://docs.astral.sh/ruff/rules/#flake8-boolean-trap-fbt
|
||||
"FLY", # https://docs.astral.sh/ruff/rules/#flynt-fly
|
||||
"G", # https://docs.astral.sh/ruff/rules/#flake8-logging-format-g
|
||||
"G201", # https://docs.astral.sh/ruff/rules/#flake8-logging-format-g
|
||||
"I", # https://docs.astral.sh/ruff/rules/#isort-i
|
||||
"ICN", # https://docs.astral.sh/ruff/rules/#flake8-import-conventions-icn
|
||||
"INP", # https://docs.astral.sh/ruff/rules/#flake8-no-pep420-inp
|
||||
@@ -215,7 +210,6 @@ extend-select = [
|
||||
]
|
||||
ignore = [
|
||||
"DJ001",
|
||||
"G004", # f-strings in logging: accepted style in this codebase
|
||||
"PLC0415",
|
||||
"RUF012",
|
||||
"SIM105",
|
||||
|
||||
@@ -11,6 +11,9 @@
|
||||
<button class="btn btn-sm btn-outline-primary me-2" (click)="dismissTasks()" *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.PaperlessTask }" [disabled]="visibleTasks.length === 0">
|
||||
<i-bs name="check2-all" class="me-1"></i-bs>{{dismissButtonText}}
|
||||
</button>
|
||||
<button class="btn btn-sm btn-outline-primary me-2" (click)="dismissAllTasks()" *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.PaperlessTask }" [disabled]="totalTasks === 0">
|
||||
<i-bs name="check2-all" class="me-1"></i-bs><ng-container i18n>Dismiss all</ng-container>
|
||||
</button>
|
||||
<div class="form-check form-switch mb-0 ms-2">
|
||||
<input class="form-check-input" type="checkbox" role="switch" [(ngModel)]="autoRefreshEnabled">
|
||||
<label class="form-check-label" for="autoRefreshSwitch" i18n>Auto refresh</label>
|
||||
@@ -81,7 +84,7 @@
|
||||
<button class="btn btn-sm btn-outline-primary" ngbDropdownToggle>{{filterTargetName}}</button>
|
||||
<div class="dropdown-menu shadow" ngbDropdownMenu>
|
||||
@for (t of filterTargets; track t.id) {
|
||||
<button ngbDropdownItem [class.active]="filterTargetID === t.id" (click)="filterTargetID = t.id">{{t.name}}</button>
|
||||
<button ngbDropdownItem [class.active]="filterTargetID === t.id" (click)="setFilterTarget(t.id)">{{t.name}}</button>
|
||||
}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -11,7 +11,7 @@ import { Router } from '@angular/router'
|
||||
import { RouterTestingModule } from '@angular/router/testing'
|
||||
import { NgbModal, NgbModalRef, NgbModule } from '@ng-bootstrap/ng-bootstrap'
|
||||
import { allIcons, NgxBootstrapIconsModule } from 'ngx-bootstrap-icons'
|
||||
import { throwError } from 'rxjs'
|
||||
import { of, throwError } from 'rxjs'
|
||||
import { routes } from 'src/app/app-routing.module'
|
||||
import {
|
||||
PaperlessTask,
|
||||
@@ -29,7 +29,11 @@ import { ToastService } from 'src/app/services/toast.service'
|
||||
import { environment } from 'src/environments/environment'
|
||||
import { ConfirmDialogComponent } from '../../common/confirm-dialog/confirm-dialog.component'
|
||||
import { PageHeaderComponent } from '../../common/page-header/page-header.component'
|
||||
import { TasksComponent, TaskSection } from './tasks.component'
|
||||
import {
|
||||
TaskFilterTargetID,
|
||||
TasksComponent,
|
||||
TaskSection,
|
||||
} from './tasks.component'
|
||||
|
||||
const tasks: PaperlessTask[] = [
|
||||
{
|
||||
@@ -154,6 +158,13 @@ const paginatedTasks: Results<PaperlessTask> = {
|
||||
results: tasks,
|
||||
}
|
||||
|
||||
const sectionCountResponse = {
|
||||
all: 7,
|
||||
needs_attention: 2,
|
||||
in_progress: 3,
|
||||
completed: 2,
|
||||
}
|
||||
|
||||
describe('TasksComponent', () => {
|
||||
let component: TasksComponent
|
||||
let fixture: ComponentFixture<TasksComponent>
|
||||
@@ -221,6 +232,15 @@ describe('TasksComponent', () => {
|
||||
req.params.get('page') === '1'
|
||||
)
|
||||
.flush(paginatedTasks)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(req) =>
|
||||
req.url === `${environment.apiBaseUrl}tasks/status_counts/` &&
|
||||
req.params.get('acknowledged') === 'false' &&
|
||||
!req.params.has('status')
|
||||
)
|
||||
.flush(sectionCountResponse)
|
||||
})
|
||||
|
||||
it('should display task sections with counts', () => {
|
||||
@@ -295,6 +315,7 @@ describe('TasksComponent', () => {
|
||||
const headerText = header.nativeElement.textContent
|
||||
|
||||
expect(headerText).toContain('Dismiss visible')
|
||||
expect(headerText).toContain('Dismiss all')
|
||||
expect(headerText).toContain('Auto refresh')
|
||||
expect(headerText).not.toContain('All types')
|
||||
expect(headerText).not.toContain('All sources')
|
||||
@@ -327,6 +348,74 @@ describe('TasksComponent', () => {
|
||||
expect(pagination).not.toBeNull()
|
||||
})
|
||||
|
||||
it('should apply the selected section to the server-side task query', () => {
|
||||
component.setSection(TaskSection.NeedsAttention)
|
||||
|
||||
const req = httpTestingController.expectOne(
|
||||
(request) =>
|
||||
request.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
request.params.get('page') === '1' &&
|
||||
request.params.get('page_size') === '25' &&
|
||||
request.params.get('acknowledged') === 'false' &&
|
||||
request.params.getAll('status').includes(PaperlessTaskStatus.Failure) &&
|
||||
request.params.getAll('status').includes(PaperlessTaskStatus.Revoked)
|
||||
)
|
||||
|
||||
req.flush({ count: 2, results: [tasks[0], tasks[1]] })
|
||||
expect(component.totalTasks).toBe(2)
|
||||
})
|
||||
|
||||
it('should apply task type and trigger source filters to the server-side task query', () => {
|
||||
component.setTaskType(PaperlessTaskType.SanityCheck)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(request) =>
|
||||
request.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
request.params.get('page_size') === '25' &&
|
||||
request.params.get('task_type') === PaperlessTaskType.SanityCheck
|
||||
)
|
||||
.flush({ count: 1, results: [tasks[6]] })
|
||||
|
||||
component.setTriggerSource(PaperlessTaskTriggerSource.System)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(request) =>
|
||||
request.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
request.params.get('page_size') === '25' &&
|
||||
request.params.get('task_type') === PaperlessTaskType.SanityCheck &&
|
||||
request.params.get('trigger_source') ===
|
||||
PaperlessTaskTriggerSource.System
|
||||
)
|
||||
.flush({ count: 1, results: [tasks[6]] })
|
||||
})
|
||||
|
||||
it('should apply text filters to the server-side task query', () => {
|
||||
component.filterText = 'invoice'
|
||||
jest.advanceTimersByTime(150)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(request) =>
|
||||
request.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
request.params.get('page_size') === '25' &&
|
||||
request.params.get('name') === 'invoice'
|
||||
)
|
||||
.flush({ count: 1, results: [tasks[0]] })
|
||||
|
||||
component.setFilterTarget(TaskFilterTargetID.Result)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(request) =>
|
||||
request.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
request.params.get('page_size') === '25' &&
|
||||
request.params.get('result') === 'invoice'
|
||||
)
|
||||
.flush({ count: 0, results: [] })
|
||||
})
|
||||
|
||||
it('should load a different task page when pagination changes', () => {
|
||||
component.setPage(2)
|
||||
|
||||
@@ -350,6 +439,27 @@ describe('TasksComponent', () => {
|
||||
expect(component.pagedTasks).toEqual([tasks[0]])
|
||||
})
|
||||
|
||||
it('should not replace section counts with current-page counts', () => {
|
||||
component.setPage(2)
|
||||
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(req) =>
|
||||
req.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
req.params.get('acknowledged') === 'false' &&
|
||||
req.params.get('page_size') === '25' &&
|
||||
req.params.get('page') === '2'
|
||||
)
|
||||
.flush({
|
||||
count: 30,
|
||||
results: [tasks[0]],
|
||||
})
|
||||
|
||||
expect(component.sectionCount(TaskSection.NeedsAttention)).toBe(2)
|
||||
expect(component.sectionCount(TaskSection.InProgress)).toBe(3)
|
||||
expect(component.sectionCount(TaskSection.Completed)).toBe(2)
|
||||
})
|
||||
|
||||
it('should expose stable task type options and disable empty ones', () => {
|
||||
expect(component.taskTypeOptions.map((option) => option.value)).toContain(
|
||||
PaperlessTaskType.TrainClassifier
|
||||
@@ -495,6 +605,46 @@ describe('TasksComponent', () => {
|
||||
expect(dismissSpy).toHaveBeenCalledWith(new Set([467, 466]))
|
||||
})
|
||||
|
||||
it('should support dismiss all tasks', () => {
|
||||
let modal: NgbModalRef
|
||||
modalService.activeInstances.subscribe((m) => (modal = m[m.length - 1]))
|
||||
const dismissSpy = jest
|
||||
.spyOn(tasksService, 'dismissAllTasks')
|
||||
.mockReturnValue(of({}))
|
||||
const reloadPageSpy = jest
|
||||
.spyOn(component as any, 'reloadPage')
|
||||
.mockImplementation(() => undefined)
|
||||
|
||||
component.dismissAllTasks()
|
||||
|
||||
expect(modal).not.toBeUndefined()
|
||||
expect(modal.componentInstance.messageBold).toBe('Dismiss all 7 tasks?')
|
||||
modal.componentInstance.confirmClicked.emit()
|
||||
expect(dismissSpy).toHaveBeenCalled()
|
||||
expect(reloadPageSpy).toHaveBeenCalledWith(false)
|
||||
expect(component.selectedTasks.size).toBe(0)
|
||||
})
|
||||
|
||||
it('should show an error and re-enable modal buttons when dismissing all tasks fails', () => {
|
||||
const error = new Error('dismiss all failed')
|
||||
const toastSpy = jest.spyOn(toastService, 'showError')
|
||||
const dismissSpy = jest
|
||||
.spyOn(tasksService, 'dismissAllTasks')
|
||||
.mockReturnValue(throwError(() => error))
|
||||
|
||||
let modal: NgbModalRef
|
||||
modalService.activeInstances.subscribe((m) => (modal = m[m.length - 1]))
|
||||
|
||||
component.dismissAllTasks()
|
||||
expect(modal).not.toBeUndefined()
|
||||
|
||||
modal.componentInstance.confirmClicked.emit()
|
||||
|
||||
expect(dismissSpy).toHaveBeenCalled()
|
||||
expect(toastSpy).toHaveBeenCalledWith('Error dismissing tasks', error)
|
||||
expect(modal.componentInstance.buttonsEnabled).toBe(true)
|
||||
})
|
||||
|
||||
it('should dismiss the currently visible scoped and filtered tasks', () => {
|
||||
component.setSection(TaskSection.InProgress)
|
||||
component.setTaskType(PaperlessTaskType.SanityCheck)
|
||||
@@ -673,6 +823,9 @@ describe('TasksComponent', () => {
|
||||
})
|
||||
|
||||
it('should keep clearing selection independent from resetting filters', () => {
|
||||
component.resetFilter()
|
||||
expect(component.filterText).toBe('')
|
||||
|
||||
component.setTaskType(PaperlessTaskType.ConsumeFile)
|
||||
component.toggleSelected(tasks[0])
|
||||
expect(component.selectedTasks.size).toBe(1)
|
||||
|
||||
@@ -40,7 +40,7 @@ export enum TaskSection {
|
||||
Completed = 'completed',
|
||||
}
|
||||
|
||||
enum TaskFilterTargetID {
|
||||
export enum TaskFilterTargetID {
|
||||
Name,
|
||||
Result,
|
||||
}
|
||||
@@ -167,6 +167,12 @@ export class TasksComponent
|
||||
public readonly pageSize = 25
|
||||
public page: number = 1
|
||||
public totalTasks: number = 0
|
||||
public sectionCounts: Record<TaskSection, number> = {
|
||||
[TaskSection.All]: 0,
|
||||
[TaskSection.NeedsAttention]: 0,
|
||||
[TaskSection.InProgress]: 0,
|
||||
[TaskSection.Completed]: 0,
|
||||
}
|
||||
public pagedTasks: PaperlessTask[] = []
|
||||
public selectedSection: TaskSection = TaskSection.All
|
||||
public selectedTaskType: PaperlessTaskType | null = null
|
||||
@@ -282,6 +288,7 @@ export class TasksComponent
|
||||
.subscribe((query) => {
|
||||
this._filterText = query
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
})
|
||||
}
|
||||
|
||||
@@ -334,6 +341,30 @@ export class TasksComponent
|
||||
}
|
||||
}
|
||||
|
||||
dismissAllTasks() {
|
||||
let modal = this.modalService.open(ConfirmDialogComponent, {
|
||||
backdrop: 'static',
|
||||
})
|
||||
modal.componentInstance.title = $localize`Confirm Dismiss All`
|
||||
modal.componentInstance.messageBold = $localize`Dismiss all ${this.totalTasks} tasks?`
|
||||
modal.componentInstance.btnClass = 'btn-warning'
|
||||
modal.componentInstance.btnCaption = $localize`Dismiss`
|
||||
modal.componentInstance.confirmClicked.pipe(first()).subscribe(() => {
|
||||
modal.componentInstance.buttonsEnabled = false
|
||||
modal.close()
|
||||
this.tasksService.dismissAllTasks().subscribe({
|
||||
next: () => {
|
||||
this.reloadPage(false)
|
||||
},
|
||||
error: (e) => {
|
||||
this.toastService.showError($localize`Error dismissing tasks`, e)
|
||||
modal.componentInstance.buttonsEnabled = true
|
||||
},
|
||||
})
|
||||
this.clearSelection()
|
||||
})
|
||||
}
|
||||
|
||||
expandTask(task: PaperlessTask) {
|
||||
this.expandedTask = this.expandedTask == task.id ? undefined : task.id
|
||||
}
|
||||
@@ -446,9 +477,7 @@ export class TasksComponent
|
||||
}
|
||||
|
||||
sectionCount(section: TaskSection): number {
|
||||
return this.pagedTasks.filter((task) =>
|
||||
this.taskBelongsToSection(task, section)
|
||||
).length
|
||||
return this.sectionCounts[section]
|
||||
}
|
||||
|
||||
sectionShowsResults(section: TaskSection): boolean {
|
||||
@@ -458,16 +487,27 @@ export class TasksComponent
|
||||
setSection(section: TaskSection) {
|
||||
this.selectedSection = section
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
}
|
||||
|
||||
setTaskType(taskType: PaperlessTaskType | null) {
|
||||
this.selectedTaskType = taskType
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
}
|
||||
|
||||
setTriggerSource(triggerSource: PaperlessTaskTriggerSource | null) {
|
||||
this.selectedTriggerSource = triggerSource
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
}
|
||||
|
||||
setFilterTarget(filterTargetID: TaskFilterTargetID) {
|
||||
this.filterTargetID = filterTargetID
|
||||
if (this._filterText.length) {
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
}
|
||||
}
|
||||
|
||||
taskTypeOptionCount(taskType: PaperlessTaskType | null): number {
|
||||
@@ -505,19 +545,32 @@ export class TasksComponent
|
||||
}
|
||||
|
||||
public resetFilter() {
|
||||
if (!this._filterText.length) {
|
||||
return
|
||||
}
|
||||
|
||||
this._filterText = ''
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
}
|
||||
|
||||
public resetFilters() {
|
||||
const hadFilter = this.isFiltered
|
||||
this.selectedTaskType = null
|
||||
this.selectedTriggerSource = null
|
||||
this.resetFilter()
|
||||
this._filterText = ''
|
||||
this.clearSelection()
|
||||
|
||||
if (hadFilter) {
|
||||
this.reloadPage(true)
|
||||
}
|
||||
}
|
||||
|
||||
filterInputKeyup(event: KeyboardEvent) {
|
||||
if (event.key == 'Enter') {
|
||||
this._filterText = (event.target as HTMLInputElement).value
|
||||
this.clearSelection()
|
||||
this.reloadPage(true)
|
||||
} else if (event.key === 'Escape') {
|
||||
this.resetFilter()
|
||||
}
|
||||
@@ -606,19 +659,86 @@ export class TasksComponent
|
||||
)
|
||||
}
|
||||
|
||||
private reloadSectionCounts() {
|
||||
this.tasksService
|
||||
.statusCounts(this.getParamsForSection(TaskSection.All))
|
||||
.pipe(first(), takeUntil(this.unsubscribeNotifier))
|
||||
.subscribe((counts) => {
|
||||
this.sectionCounts[TaskSection.All] = counts.all
|
||||
this.sectionCounts[TaskSection.NeedsAttention] = counts.needs_attention
|
||||
this.sectionCounts[TaskSection.InProgress] = counts.in_progress
|
||||
this.sectionCounts[TaskSection.Completed] = counts.completed
|
||||
})
|
||||
}
|
||||
|
||||
private getParamsForSection(
|
||||
section: TaskSection
|
||||
): Record<string, string | number | boolean | readonly string[]> {
|
||||
const params: Record<
|
||||
string,
|
||||
string | number | boolean | readonly string[]
|
||||
> = {
|
||||
acknowledged: false,
|
||||
}
|
||||
|
||||
const statuses = this.statusesForSection(section)
|
||||
if (statuses.length) {
|
||||
params.status = statuses
|
||||
}
|
||||
|
||||
if (this.selectedTaskType !== null) {
|
||||
params.task_type = this.selectedTaskType
|
||||
}
|
||||
|
||||
if (this.selectedTriggerSource !== null) {
|
||||
params.trigger_source = this.selectedTriggerSource
|
||||
}
|
||||
|
||||
if (this._filterText.length) {
|
||||
params[
|
||||
this.filterTargetID === TaskFilterTargetID.Name ? 'name' : 'result'
|
||||
] = this._filterText
|
||||
}
|
||||
|
||||
return params
|
||||
}
|
||||
|
||||
private statusesForSection(section: TaskSection): PaperlessTaskStatus[] {
|
||||
switch (section) {
|
||||
case TaskSection.NeedsAttention:
|
||||
return [PaperlessTaskStatus.Failure, PaperlessTaskStatus.Revoked]
|
||||
case TaskSection.InProgress:
|
||||
return [PaperlessTaskStatus.Pending, PaperlessTaskStatus.Started]
|
||||
case TaskSection.Completed:
|
||||
return [PaperlessTaskStatus.Success]
|
||||
default:
|
||||
return []
|
||||
}
|
||||
}
|
||||
|
||||
private reloadPage(resetToFirstPage: boolean = false) {
|
||||
if (resetToFirstPage) {
|
||||
this.page = 1
|
||||
}
|
||||
|
||||
this.reloadSectionCounts()
|
||||
|
||||
this.loading = true
|
||||
this.tasksService
|
||||
.list(this.page, this.pageSize, { acknowledged: false })
|
||||
.list(
|
||||
this.page,
|
||||
this.pageSize,
|
||||
this.getParamsForSection(this.selectedSection)
|
||||
)
|
||||
.pipe(first(), takeUntil(this.unsubscribeNotifier))
|
||||
.subscribe({
|
||||
next: (result) => {
|
||||
this.pagedTasks = result.results
|
||||
this.totalTasks = result.count
|
||||
this.sectionCounts[TaskSection.All] = result.count
|
||||
if (this.selectedSection !== TaskSection.All) {
|
||||
this.sectionCounts[this.selectedSection] = result.count
|
||||
}
|
||||
this.loading = false
|
||||
if (
|
||||
this.page > 1 &&
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
<div class="chat-messages font-monospace small">
|
||||
@for (message of messages; track message) {
|
||||
<div class="message d-flex flex-row small" [class.justify-content-end]="message.role === 'user'">
|
||||
<div class="p-2 m-2" [class.bg-dark]="message.role === 'user'">
|
||||
<div class="p-2 m-2" [class.bg-body]="message.role === 'user'">
|
||||
<span>
|
||||
{{ message.content }}
|
||||
@if (message.isStreaming) { <span class="blinking-cursor">|</span> }
|
||||
|
||||
@@ -188,4 +188,14 @@ describe('ChatComponent', () => {
|
||||
component.searchInputKeyDown(event)
|
||||
expect(component.sendMessage).toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('should not send message on Enter key press while composing with IME', () => {
|
||||
jest.spyOn(component, 'sendMessage')
|
||||
const event = new KeyboardEvent('keydown', {
|
||||
key: 'Enter',
|
||||
isComposing: true,
|
||||
})
|
||||
component.searchInputKeyDown(event)
|
||||
expect(component.sendMessage).not.toHaveBeenCalled()
|
||||
})
|
||||
})
|
||||
|
||||
@@ -155,7 +155,10 @@ export class ChatComponent implements OnInit {
|
||||
}
|
||||
|
||||
public searchInputKeyDown(event: KeyboardEvent) {
|
||||
if (event.key === 'Enter') {
|
||||
if (
|
||||
event.key === 'Enter' &&
|
||||
!(event.isComposing || event.keyCode === 229)
|
||||
) {
|
||||
event.preventDefault()
|
||||
this.sendMessage()
|
||||
}
|
||||
|
||||
@@ -5,10 +5,10 @@
|
||||
</div>
|
||||
<div class="modal-body">
|
||||
@if (messageBold) {
|
||||
<p><b>{{messageBold}}</b></p>
|
||||
<p class="text-break"><b>{{messageBold}}</b></p>
|
||||
}
|
||||
@if (message) {
|
||||
<p class="mb-0" [innerHTML]="message"></p>
|
||||
<p class="mb-0 text-break" [innerHTML]="message"></p>
|
||||
}
|
||||
</div>
|
||||
<div class="modal-footer">
|
||||
|
||||
+5
-1
@@ -9,8 +9,11 @@
|
||||
<label class="form-label" for="metadataDocumentID" i18n>Documents:</label>
|
||||
<ul class="list-group"
|
||||
cdkDropList
|
||||
[cdkDropListData]="documentIDs"
|
||||
(cdkDropListDropped)="onDrop($event)">
|
||||
@for (document of documents; track document.id) {
|
||||
@for (documentID of documentIDs; track documentID) {
|
||||
@let document = getDocument(documentID);
|
||||
@if (document) {
|
||||
<li class="list-group-item d-flex align-items-center" cdkDrag>
|
||||
<i-bs name="grip-vertical" class="me-2"></i-bs>
|
||||
<div class="d-flex flex-column">
|
||||
@@ -27,6 +30,7 @@
|
||||
</small>
|
||||
</div>
|
||||
</li>
|
||||
}
|
||||
}
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
+2
-2
@@ -1,5 +1,5 @@
|
||||
<div class="btn-group">
|
||||
<button type="button" class="btn btn-sm btn-outline-primary" (click)="clickSuggest()" [disabled]="loading || (suggestions && !aiEnabled)">
|
||||
<button type="button" class="btn btn-sm btn-outline-primary" (click)="clickSuggest()" [disabled]="disabled || loading || (suggestions && !aiEnabled)">
|
||||
@if (loading) {
|
||||
<div class="spinner-border spinner-border-sm" role="status"></div>
|
||||
} @else {
|
||||
@@ -13,7 +13,7 @@
|
||||
|
||||
@if (aiEnabled) {
|
||||
<div class="btn-group" ngbDropdown #dropdown="ngbDropdown" [popperOptions]="popperOptions">
|
||||
<button type="button" class="btn btn-sm btn-outline-primary" ngbDropdownToggle [disabled]="loading || !suggestions" aria-expanded="false" aria-controls="suggestionsDropdown" aria-label="Suggestions dropdown">
|
||||
<button type="button" class="btn btn-sm btn-outline-primary" ngbDropdownToggle [disabled]="disabled || loading || !suggestions" aria-expanded="false" aria-controls="suggestionsDropdown" aria-label="Suggestions dropdown">
|
||||
<span class="visually-hidden" i18n>Show suggestions</span>
|
||||
</button>
|
||||
|
||||
|
||||
+12
@@ -37,6 +37,18 @@ describe('SuggestionsDropdownComponent', () => {
|
||||
expect(component.getSuggestions.emit).toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('should not emit getSuggestions when disabled', () => {
|
||||
jest.spyOn(component.getSuggestions, 'emit')
|
||||
component.disabled = true
|
||||
component.suggestions = null
|
||||
fixture.detectChanges()
|
||||
|
||||
component.clickSuggest()
|
||||
|
||||
expect(component.getSuggestions.emit).not.toHaveBeenCalled()
|
||||
expect(fixture.nativeElement.querySelector('button').disabled).toBeTruthy()
|
||||
})
|
||||
|
||||
it('should toggle dropdown when clickSuggest is called and suggestions are not null', () => {
|
||||
component.aiEnabled = true
|
||||
fixture.detectChanges()
|
||||
|
||||
+8
@@ -47,6 +47,14 @@ export class SuggestionsDropdownComponent {
|
||||
addCorrespondent: EventEmitter<string> = new EventEmitter()
|
||||
|
||||
public clickSuggest(): void {
|
||||
if (
|
||||
this.disabled ||
|
||||
this.loading ||
|
||||
(this.suggestions && !this.aiEnabled)
|
||||
) {
|
||||
return
|
||||
}
|
||||
|
||||
if (!this.suggestions) {
|
||||
this.getSuggestions.emit(this)
|
||||
} else {
|
||||
|
||||
+3
-1
@@ -131,7 +131,9 @@
|
||||
@if (status.tasks.celery_status === 'OK') {
|
||||
<i-bs name="check-circle-fill" class="text-primary ms-2 lh-1"></i-bs>
|
||||
} @else {
|
||||
<i-bs name="exclamation-triangle-fill" class="text-danger ms-2 lh-1"></i-bs>
|
||||
<i-bs name="exclamation-triangle-fill" class="ms-2 lh-1"
|
||||
[class.text-danger]="status.tasks.celery_status === SystemStatusItemStatus.ERROR"
|
||||
[class.text-warning]="status.tasks.celery_status === SystemStatusItemStatus.WARNING"></i-bs>
|
||||
}
|
||||
</button>
|
||||
<ng-template #celeryStatus>
|
||||
|
||||
@@ -64,3 +64,10 @@ export interface PaperlessTaskSummary {
|
||||
last_success: Date | null
|
||||
last_failure: Date | null
|
||||
}
|
||||
|
||||
export interface PaperlessTaskStatusCounts {
|
||||
all: number
|
||||
needs_attention: number
|
||||
in_progress: number
|
||||
completed: number
|
||||
}
|
||||
|
||||
@@ -80,6 +80,27 @@ describe('TasksService', () => {
|
||||
.flush({ count: 0, results: [] })
|
||||
})
|
||||
|
||||
it('calls acknowledge_tasks api endpoint on dismiss all and reloads', () => {
|
||||
tasksService.dismissAllTasks().subscribe()
|
||||
const req = httpTestingController.expectOne(
|
||||
`${environment.apiBaseUrl}tasks/acknowledge/`
|
||||
)
|
||||
expect(req.request.method).toEqual('POST')
|
||||
expect(req.request.body).toEqual({
|
||||
all: true,
|
||||
})
|
||||
req.flush([])
|
||||
// reload is then called
|
||||
httpTestingController
|
||||
.expectOne(
|
||||
(req: HttpRequest<unknown>) =>
|
||||
req.url === `${environment.apiBaseUrl}tasks/` &&
|
||||
req.params.get('acknowledged') === 'false' &&
|
||||
req.params.get('page_size') === '1000'
|
||||
)
|
||||
.flush({ count: 0, results: [] })
|
||||
})
|
||||
|
||||
it('groups mixed task types by status when reloading', () => {
|
||||
expect(tasksService.total).toEqual(0)
|
||||
const mockTasks = [
|
||||
@@ -221,4 +242,34 @@ describe('TasksService', () => {
|
||||
task_id: 'abc-123',
|
||||
})
|
||||
})
|
||||
|
||||
it('loads filtered task status counts', () => {
|
||||
tasksService
|
||||
.statusCounts({
|
||||
acknowledged: false,
|
||||
task_type: PaperlessTaskType.ConsumeFile,
|
||||
})
|
||||
.subscribe((res) => {
|
||||
expect(res).toEqual({
|
||||
all: 10,
|
||||
needs_attention: 2,
|
||||
in_progress: 3,
|
||||
completed: 5,
|
||||
})
|
||||
})
|
||||
|
||||
const req = httpTestingController.expectOne(
|
||||
(req: HttpRequest<unknown>) =>
|
||||
req.url === `${environment.apiBaseUrl}tasks/status_counts/` &&
|
||||
req.params.get('acknowledged') === 'false' &&
|
||||
req.params.get('task_type') === PaperlessTaskType.ConsumeFile
|
||||
)
|
||||
expect(req.request.method).toEqual('GET')
|
||||
req.flush({
|
||||
all: 10,
|
||||
needs_attention: 2,
|
||||
in_progress: 3,
|
||||
completed: 5,
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
@@ -5,6 +5,7 @@ import { first, map, takeUntil, tap } from 'rxjs/operators'
|
||||
import {
|
||||
PaperlessTask,
|
||||
PaperlessTaskStatus,
|
||||
PaperlessTaskStatusCounts,
|
||||
PaperlessTaskType,
|
||||
} from 'src/app/data/paperless-task'
|
||||
import { Results } from 'src/app/data/results'
|
||||
@@ -88,7 +89,7 @@ export class TasksService {
|
||||
public list(
|
||||
page: number,
|
||||
pageSize: number,
|
||||
extraParams?: Record<string, string | number | boolean>
|
||||
extraParams?: Record<string, string | number | boolean | readonly string[]>
|
||||
): Observable<Results<PaperlessTask>> {
|
||||
return this.http.get<Results<PaperlessTask>>(
|
||||
`${this.baseUrl}${this.endpoint}/`,
|
||||
@@ -102,6 +103,17 @@ export class TasksService {
|
||||
)
|
||||
}
|
||||
|
||||
public statusCounts(
|
||||
extraParams?: Record<string, string | number | boolean | readonly string[]>
|
||||
): Observable<PaperlessTaskStatusCounts> {
|
||||
return this.http.get<PaperlessTaskStatusCounts>(
|
||||
`${this.baseUrl}${this.endpoint}/status_counts/`,
|
||||
{
|
||||
params: extraParams,
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
public dismissTasks(task_ids: Set<number>): Observable<any> {
|
||||
return this.http
|
||||
.post(`${this.baseUrl}tasks/acknowledge/`, {
|
||||
@@ -116,6 +128,20 @@ export class TasksService {
|
||||
)
|
||||
}
|
||||
|
||||
public dismissAllTasks(): Observable<any> {
|
||||
return this.http
|
||||
.post(`${this.baseUrl}tasks/acknowledge/`, {
|
||||
all: true,
|
||||
})
|
||||
.pipe(
|
||||
first(),
|
||||
takeUntil(this.unsubscribeNotifer),
|
||||
tap(() => {
|
||||
this.reload()
|
||||
})
|
||||
)
|
||||
}
|
||||
|
||||
public cancelPending(): void {
|
||||
this.unsubscribeNotifer.next(true)
|
||||
}
|
||||
|
||||
@@ -904,6 +904,19 @@ def remove_password(
|
||||
doc.id,
|
||||
pair.source_doc.source_path,
|
||||
)
|
||||
try:
|
||||
with pikepdf.open(source_path) as pdf:
|
||||
if not pdf.is_encrypted:
|
||||
logger.info(
|
||||
"Skipping password removal for document %s because the "
|
||||
"source PDF is not encrypted",
|
||||
pair.root_doc.id,
|
||||
)
|
||||
continue
|
||||
except pikepdf.PasswordError:
|
||||
# Password-protected PDFs need the supplied password below.
|
||||
pass
|
||||
|
||||
with pikepdf.open(source_path, password=password) as pdf:
|
||||
filepath: Path = (
|
||||
Path(tempfile.mkdtemp(dir=settings.SCRATCH_DIR))
|
||||
|
||||
@@ -834,9 +834,8 @@ class ConsumerPlugin(
|
||||
self.log.debug(f"Creation date from parse_date: {create_date}")
|
||||
else:
|
||||
stats = Path(self.input_doc.original_file).stat()
|
||||
create_date = datetime.datetime.fromtimestamp(
|
||||
stats.st_mtime,
|
||||
tz=datetime.UTC,
|
||||
create_date = timezone.make_aware(
|
||||
datetime.datetime.fromtimestamp(stats.st_mtime),
|
||||
)
|
||||
self.log.debug(f"Creation date from st_mtime: {create_date}")
|
||||
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import datetime as dt
|
||||
import logging
|
||||
import os
|
||||
import shutil
|
||||
@@ -5,7 +6,6 @@ from pathlib import Path
|
||||
from typing import Final
|
||||
|
||||
from django.conf import settings
|
||||
from django.utils import timezone
|
||||
from pikepdf import Pdf
|
||||
|
||||
from documents.consumer import ConsumerError
|
||||
@@ -78,7 +78,7 @@ class CollatePlugin(NoCleanupPluginMixin, NoSetupPluginMixin, ConsumeTaskPlugin)
|
||||
stats = staging.stat()
|
||||
# if the file is older than the timeout, we don't consider
|
||||
# it valid
|
||||
if (timezone.now().timestamp() - stats.st_mtime) > TIMEOUT_SECONDS:
|
||||
if (dt.datetime.now().timestamp() - stats.st_mtime) > TIMEOUT_SECONDS:
|
||||
logger.warning("Outdated double sided staging file exists, deleting it")
|
||||
staging.unlink()
|
||||
else:
|
||||
@@ -99,7 +99,7 @@ class CollatePlugin(NoCleanupPluginMixin, NoSetupPluginMixin, ConsumeTaskPlugin)
|
||||
"two uploaded files don't belong to the same double-"
|
||||
"sided scan. Please retry, starting with the odd "
|
||||
"numbered pages again.",
|
||||
) from None
|
||||
)
|
||||
# Merged file has the same path, but without the
|
||||
# double-sided subdir. Therefore, it is also in the
|
||||
# consumption dir and will be picked up for processing
|
||||
@@ -134,7 +134,7 @@ class CollatePlugin(NoCleanupPluginMixin, NoSetupPluginMixin, ConsumeTaskPlugin)
|
||||
shutil.move(pdf_file, staging)
|
||||
# update access to modification time so we know if the file
|
||||
# is outdated when another file gets uploaded
|
||||
timestamp = timezone.now().timestamp()
|
||||
timestamp = dt.datetime.now().timestamp()
|
||||
os.utime(staging, (timestamp, timestamp))
|
||||
logger.info(
|
||||
"Got scan with odd numbered pages of double-sided scan, moved it to %s",
|
||||
|
||||
@@ -28,6 +28,7 @@ from django.db.models.functions import Cast
|
||||
from django.utils.translation import gettext_lazy as _
|
||||
from django_filters import DateFilter
|
||||
from django_filters.rest_framework import BooleanFilter
|
||||
from django_filters.rest_framework import CharFilter
|
||||
from django_filters.rest_framework import DateTimeFilter
|
||||
from django_filters.rest_framework import Filter
|
||||
from django_filters.rest_framework import FilterSet
|
||||
@@ -350,7 +351,7 @@ def handle_validation_prefix(func: Callable):
|
||||
try:
|
||||
return func(*args, **kwargs)
|
||||
except serializers.ValidationError as e:
|
||||
raise serializers.ValidationError({validation_prefix: e.detail}) from e
|
||||
raise serializers.ValidationError({validation_prefix: e.detail})
|
||||
|
||||
# Update the signature to include the validation_prefix argument
|
||||
old_sig = inspect.signature(func)
|
||||
@@ -461,7 +462,7 @@ class CustomFieldQueryParser:
|
||||
except json.JSONDecodeError:
|
||||
raise serializers.ValidationError(
|
||||
{self._validation_prefix: [_("Value must be valid JSON.")]},
|
||||
) from None
|
||||
)
|
||||
return (
|
||||
self._parse_expr(expr, validation_prefix=self._validation_prefix),
|
||||
self._annotations,
|
||||
@@ -589,7 +590,7 @@ class CustomFieldQueryParser:
|
||||
except CustomField.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
[_("{name!r} is not a valid custom field.").format(name=id_or_name)],
|
||||
) from None
|
||||
)
|
||||
self._custom_fields[custom_field.id] = custom_field
|
||||
self._custom_fields[custom_field.name] = custom_field
|
||||
return custom_field
|
||||
@@ -900,6 +901,16 @@ class ShareLinkBundleFilterSet(FilterSet):
|
||||
|
||||
|
||||
class PaperlessTaskFilterSet(FilterSet):
|
||||
name = CharFilter(
|
||||
method="filter_name",
|
||||
label="Name",
|
||||
)
|
||||
|
||||
result = CharFilter(
|
||||
method="filter_result",
|
||||
label="Result",
|
||||
)
|
||||
|
||||
task_type = MultipleChoiceFilter(
|
||||
choices=PaperlessTask.TaskType.choices,
|
||||
label="Task Type",
|
||||
@@ -939,7 +950,58 @@ class PaperlessTaskFilterSet(FilterSet):
|
||||
|
||||
class Meta:
|
||||
model = PaperlessTask
|
||||
fields = ["task_type", "trigger_source", "status", "acknowledged", "owner"]
|
||||
fields = [
|
||||
"task_type",
|
||||
"trigger_source",
|
||||
"status",
|
||||
"acknowledged",
|
||||
"owner",
|
||||
"name",
|
||||
"result",
|
||||
]
|
||||
|
||||
def filter_name(self, queryset, name, value):
|
||||
if not value:
|
||||
return queryset
|
||||
|
||||
matching_task_types = [
|
||||
task_type
|
||||
for task_type, label in PaperlessTask.TaskType.choices
|
||||
if value.lower() in str(label).lower()
|
||||
]
|
||||
matching_trigger_sources = [
|
||||
trigger_source
|
||||
for trigger_source, label in PaperlessTask.TriggerSource.choices
|
||||
if value.lower() in str(label).lower()
|
||||
]
|
||||
|
||||
return queryset.filter(
|
||||
Q(input_data__filename__icontains=value)
|
||||
| Q(task_type__in=matching_task_types)
|
||||
| Q(trigger_source__in=matching_trigger_sources),
|
||||
)
|
||||
|
||||
def filter_result(self, queryset, name, value):
|
||||
if not value:
|
||||
return queryset
|
||||
|
||||
query = Q(result_data__reason__icontains=value) | Q(
|
||||
result_data__error_message__icontains=value,
|
||||
)
|
||||
|
||||
try:
|
||||
numeric_value = int(value)
|
||||
except (TypeError, ValueError):
|
||||
pass
|
||||
else:
|
||||
query |= Q(result_data__document_id=numeric_value) | Q(
|
||||
result_data__duplicate_of=numeric_value,
|
||||
)
|
||||
|
||||
if "duplicate" in value.lower():
|
||||
query |= Q(result_data__duplicate_of__isnull=False)
|
||||
|
||||
return queryset.filter(query)
|
||||
|
||||
def filter_is_complete(self, queryset, name, value):
|
||||
if value:
|
||||
@@ -988,7 +1050,7 @@ class DocumentsOrderingFilter(OrderingFilter):
|
||||
except CustomField.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
{self.prefix + str(custom_field_id): [_("Custom field not found")]},
|
||||
) from None
|
||||
)
|
||||
|
||||
annotation = None
|
||||
match field.data_type:
|
||||
|
||||
@@ -480,7 +480,7 @@ class Command(CryptMixin, PaperlessCommand):
|
||||
}
|
||||
|
||||
# 3. Export files from each document
|
||||
for _, document_dict in enumerate(
|
||||
for index, document_dict in enumerate(
|
||||
self.track(
|
||||
document_manifest,
|
||||
description="Exporting documents...",
|
||||
|
||||
@@ -2,6 +2,7 @@ from typing import Any
|
||||
|
||||
from documents.management.commands.base import PaperlessCommand
|
||||
from documents.tasks import llmindex_index
|
||||
from paperless_ai.indexing import llm_index_compact
|
||||
|
||||
|
||||
class Command(PaperlessCommand):
|
||||
@@ -12,9 +13,12 @@ class Command(PaperlessCommand):
|
||||
|
||||
def add_arguments(self, parser: Any) -> None:
|
||||
super().add_arguments(parser)
|
||||
parser.add_argument("command", choices=["rebuild", "update"])
|
||||
parser.add_argument("command", choices=["rebuild", "update", "compact"])
|
||||
|
||||
def handle(self, *args: Any, **options: Any) -> None:
|
||||
if options["command"] == "compact":
|
||||
llm_index_compact()
|
||||
return
|
||||
llmindex_index(
|
||||
rebuild=options["command"] == "rebuild",
|
||||
iter_wrapper=lambda docs: self.track(
|
||||
|
||||
@@ -133,14 +133,11 @@ def _build_suggestion_table(
|
||||
else:
|
||||
doc_cell = Text(f"{doc} [{doc.pk}]")
|
||||
|
||||
tag_parts: list[str] = [
|
||||
f"[green]+{tag.name}[/green]"
|
||||
for tag in sorted(suggestion.tags_to_add, key=lambda t: t.name)
|
||||
]
|
||||
tag_parts.extend(
|
||||
f"[red]-{tag.name}[/red]"
|
||||
for tag in sorted(suggestion.tags_to_remove, key=lambda t: t.name)
|
||||
)
|
||||
tag_parts: list[str] = []
|
||||
for tag in sorted(suggestion.tags_to_add, key=lambda t: t.name):
|
||||
tag_parts.append(f"[green]+{tag.name}[/green]")
|
||||
for tag in sorted(suggestion.tags_to_remove, key=lambda t: t.name):
|
||||
tag_parts.append(f"[red]-{tag.name}[/red]")
|
||||
tag_cell = Text.from_markup(", ".join(tag_parts)) if tag_parts else Text("-")
|
||||
|
||||
table.add_row(
|
||||
|
||||
@@ -369,7 +369,7 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
|
||||
If the queryset already annotated ``effective_content``, that value is used.
|
||||
"""
|
||||
if hasattr(self, "effective_content"):
|
||||
return self.effective_content
|
||||
return getattr(self, "effective_content")
|
||||
|
||||
if self.root_document_id is not None or self.pk is None:
|
||||
return self.content
|
||||
@@ -1204,8 +1204,8 @@ class CustomFieldInstance(SoftDeleteModel):
|
||||
def get_value_field_name(cls, data_type: CustomField.FieldDataType):
|
||||
try:
|
||||
return cls.TYPE_TO_DATA_STORE_NAME_MAP[data_type]
|
||||
except KeyError as exc: # pragma: no cover
|
||||
raise NotImplementedError(data_type) from exc
|
||||
except KeyError: # pragma: no cover
|
||||
raise NotImplementedError(data_type)
|
||||
|
||||
@property
|
||||
def value(self):
|
||||
|
||||
@@ -110,7 +110,7 @@ def run_convert(
|
||||
args += ["-define", "pdf:use-cropbox=true"] if use_cropbox else []
|
||||
args += [str(input_file), str(output_file)]
|
||||
|
||||
logger.debug("Execute: %s", " ".join(args), extra={"group": logging_group})
|
||||
logger.debug("Execute: " + " ".join(args), extra={"group": logging_group})
|
||||
|
||||
try:
|
||||
run_subprocess(args, environment, logger)
|
||||
|
||||
@@ -67,7 +67,8 @@ class DateParserPluginBase(ABC):
|
||||
|
||||
Subclasses can override this to release resources.
|
||||
"""
|
||||
return None
|
||||
# Default implementation does nothing.
|
||||
# Returning None implies exceptions are propagated.
|
||||
|
||||
def _parse_string(
|
||||
self,
|
||||
|
||||
@@ -8,11 +8,15 @@ from documents.search._backend import get_backend
|
||||
from documents.search._backend import reset_backend
|
||||
from documents.search._schema import needs_rebuild
|
||||
from documents.search._schema import wipe_index
|
||||
from documents.search._translate import InvalidDateQuery
|
||||
from documents.search._translate import SearchQueryError
|
||||
|
||||
__all__ = [
|
||||
"InvalidDateQuery",
|
||||
"SearchHit",
|
||||
"SearchIndexLockError",
|
||||
"SearchMode",
|
||||
"SearchQueryError",
|
||||
"TantivyBackend",
|
||||
"TantivyRelevanceList",
|
||||
"WriteBatch",
|
||||
|
||||
@@ -195,12 +195,12 @@ class WriteBatch:
|
||||
try:
|
||||
self._lock.acquire(timeout=self._lock_timeout)
|
||||
break
|
||||
except filelock.Timeout as exc:
|
||||
except filelock.Timeout:
|
||||
if attempt == _LOCK_RETRY_ATTEMPTS - 1:
|
||||
raise SearchIndexLockError(
|
||||
f"Could not acquire index lock after {_LOCK_RETRY_ATTEMPTS} "
|
||||
f"attempts (timeout={self._lock_timeout}s each)",
|
||||
) from exc
|
||||
)
|
||||
sleep_s = random.uniform(
|
||||
0,
|
||||
min(_LOCK_BACKOFF_CAP, _LOCK_BACKOFF_BASE * (2**attempt)),
|
||||
@@ -651,11 +651,7 @@ class TantivyBackend:
|
||||
result_ids = cast("list[int]", searcher.fast_field_values("id", result_addrs))
|
||||
addr_by_id: dict[int, tuple[float, tantivy.DocAddress]] = {
|
||||
doc_id: (score, addr)
|
||||
for (score, addr), doc_id in zip(
|
||||
batch_results.hits,
|
||||
result_ids,
|
||||
strict=False,
|
||||
)
|
||||
for (score, addr), doc_id in zip(batch_results.hits, result_ids)
|
||||
}
|
||||
|
||||
snippet_generator = None
|
||||
|
||||
@@ -0,0 +1,163 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC
|
||||
from datetime import date
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
from typing import TYPE_CHECKING
|
||||
from typing import Final
|
||||
|
||||
from dateutil.relativedelta import relativedelta
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from datetime import tzinfo
|
||||
|
||||
_DATE_ONLY_FIELDS = frozenset({"created"})
|
||||
|
||||
_TODAY: Final[str] = "today"
|
||||
_YESTERDAY: Final[str] = "yesterday"
|
||||
_PREVIOUS_WEEK: Final[str] = "previous week"
|
||||
_THIS_MONTH: Final[str] = "this month"
|
||||
_PREVIOUS_MONTH: Final[str] = "previous month"
|
||||
_THIS_YEAR: Final[str] = "this year"
|
||||
_PREVIOUS_YEAR: Final[str] = "previous year"
|
||||
_PREVIOUS_QUARTER: Final[str] = "previous quarter"
|
||||
|
||||
_DATE_KEYWORDS = frozenset(
|
||||
{
|
||||
_TODAY,
|
||||
_YESTERDAY,
|
||||
_PREVIOUS_WEEK,
|
||||
_THIS_MONTH,
|
||||
_PREVIOUS_MONTH,
|
||||
_THIS_YEAR,
|
||||
_PREVIOUS_YEAR,
|
||||
_PREVIOUS_QUARTER,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def _fmt(dt: datetime) -> str:
|
||||
"""Format a datetime as an ISO 8601 UTC string for use in Tantivy range queries."""
|
||||
return dt.astimezone(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")
|
||||
|
||||
|
||||
def _iso_range(lo: datetime, hi: datetime) -> str:
|
||||
"""Format a [lo TO hi] range string in ISO 8601 for Tantivy query syntax."""
|
||||
return f"[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
|
||||
|
||||
def _quarter_start(d: date) -> date:
|
||||
"""Return the first day of the calendar quarter containing ``d``."""
|
||||
return date(d.year, ((d.month - 1) // 3) * 3 + 1, 1)
|
||||
|
||||
|
||||
def _midnight(d: date, tz: tzinfo) -> datetime:
|
||||
"""Convert a calendar date at local-timezone midnight to a UTC datetime."""
|
||||
return datetime(d.year, d.month, d.day, tzinfo=tz).astimezone(UTC)
|
||||
|
||||
|
||||
def _keyword_bounds(keyword: str, tz: tzinfo) -> tuple[date, date]:
|
||||
"""
|
||||
Map a relative date keyword to ``(start, exclusive_end)`` calendar dates.
|
||||
|
||||
``tz`` only determines what "today" is; the caller decides how the returned
|
||||
dates become UTC datetime boundaries (date-only vs. local-midnight offset).
|
||||
"""
|
||||
today = datetime.now(tz).date()
|
||||
if keyword == _TODAY:
|
||||
return today, today + timedelta(days=1)
|
||||
if keyword == _YESTERDAY:
|
||||
return today - timedelta(days=1), today
|
||||
if keyword == _PREVIOUS_WEEK:
|
||||
this_monday = today - timedelta(days=today.weekday())
|
||||
return this_monday - timedelta(weeks=1), this_monday
|
||||
if keyword == _THIS_MONTH:
|
||||
first = today.replace(day=1)
|
||||
return first, first + relativedelta(months=1)
|
||||
if keyword == _PREVIOUS_MONTH:
|
||||
this_first = today.replace(day=1)
|
||||
return this_first - relativedelta(months=1), this_first
|
||||
if keyword == _THIS_YEAR:
|
||||
return date(today.year, 1, 1), date(today.year + 1, 1, 1)
|
||||
if keyword == _PREVIOUS_YEAR:
|
||||
return date(today.year - 1, 1, 1), date(today.year, 1, 1)
|
||||
if keyword == _PREVIOUS_QUARTER:
|
||||
this_quarter = _quarter_start(today)
|
||||
return this_quarter - relativedelta(months=3), this_quarter
|
||||
raise ValueError(f"Unknown keyword: {keyword}")
|
||||
|
||||
|
||||
def _date_only_range(keyword: str, tz: tzinfo) -> str:
|
||||
"""
|
||||
For `created` (DateField): use the local calendar date, converted to
|
||||
midnight UTC boundaries. No offset arithmetic — date only.
|
||||
"""
|
||||
start, end = _keyword_bounds(keyword, tz)
|
||||
lo = datetime(start.year, start.month, start.day, tzinfo=UTC)
|
||||
hi = datetime(end.year, end.month, end.day, tzinfo=UTC)
|
||||
return _iso_range(lo, hi)
|
||||
|
||||
|
||||
def _datetime_range(keyword: str, tz: tzinfo) -> str:
|
||||
"""
|
||||
For `added` / `modified` (DateTimeField, stored as UTC): convert local day
|
||||
boundaries to UTC — full offset arithmetic required.
|
||||
"""
|
||||
start, end = _keyword_bounds(keyword, tz)
|
||||
return _iso_range(_midnight(start, tz), _midnight(end, tz))
|
||||
|
||||
|
||||
def _precision_bounds(digits: str) -> tuple[date, date] | None:
|
||||
"""
|
||||
Map a 4/6/8-digit date token to (start, exclusive_end) calendar dates.
|
||||
|
||||
YYYY -> whole year, YYYYMM -> whole month, YYYYMMDD -> single day.
|
||||
Returns None for any unparsable or out-of-range value (e.g. month 23),
|
||||
so callers can emit a no-match clause instead of erroring (Whoosh parity).
|
||||
"""
|
||||
try:
|
||||
if len(digits) == 4:
|
||||
year = int(digits)
|
||||
return date(year, 1, 1), date(year + 1, 1, 1)
|
||||
if len(digits) == 6:
|
||||
year, month = int(digits[:4]), int(digits[4:6])
|
||||
start = date(year, month, 1)
|
||||
end = date(year + 1, 1, 1) if month == 12 else date(year, month + 1, 1)
|
||||
return start, end
|
||||
if len(digits) == 8:
|
||||
start = date(int(digits[:4]), int(digits[4:6]), int(digits[6:8]))
|
||||
return start, start + timedelta(days=1)
|
||||
except ValueError:
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _utc_bounds_for_field(
|
||||
field: str,
|
||||
start: date,
|
||||
end: date,
|
||||
tz: tzinfo,
|
||||
) -> tuple[datetime, datetime]:
|
||||
"""
|
||||
Convert calendar-date bounds to UTC datetimes per the field's storage type.
|
||||
|
||||
For DateField (``created``) the bounds are UTC midnight (no offset). For
|
||||
DateTimeField (``added``/``modified``) the bounds are local-tz midnight
|
||||
converted to UTC, matching how each field is indexed.
|
||||
"""
|
||||
if field in _DATE_ONLY_FIELDS:
|
||||
return (
|
||||
datetime(start.year, start.month, start.day, tzinfo=UTC),
|
||||
datetime(end.year, end.month, end.day, tzinfo=UTC),
|
||||
)
|
||||
return (
|
||||
datetime(start.year, start.month, start.day, tzinfo=tz).astimezone(UTC),
|
||||
datetime(end.year, end.month, end.day, tzinfo=tz).astimezone(UTC),
|
||||
)
|
||||
|
||||
|
||||
def _field_range_from_dates(field: str, start: date, end: date, tz: tzinfo) -> str:
|
||||
"""Build a Tantivy ``field:[lo TO hi]`` ISO range from calendar-date bounds."""
|
||||
lo, hi = _utc_bounds_for_field(field, start, end, tz)
|
||||
return f"{field}:{_iso_range(lo, hi)}"
|
||||
+15
-440
@@ -1,88 +1,28 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC
|
||||
from datetime import date
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
import logging
|
||||
from typing import TYPE_CHECKING
|
||||
from typing import Final
|
||||
|
||||
import regex
|
||||
import tantivy
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from django.conf import settings
|
||||
|
||||
from documents.search._tokenizer import simple_search_tokens
|
||||
from documents.search._translate import SearchQueryError
|
||||
from documents.search._translate import translate_query
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from datetime import tzinfo
|
||||
|
||||
from django.contrib.auth.base_user import AbstractBaseUser
|
||||
|
||||
logger = logging.getLogger("paperless.search")
|
||||
|
||||
# Maximum seconds any single regex substitution may run.
|
||||
# Prevents ReDoS on adversarial user-supplied query strings.
|
||||
_REGEX_TIMEOUT: Final[float] = 1.0
|
||||
|
||||
_DATE_ONLY_FIELDS = frozenset({"created"})
|
||||
|
||||
_TODAY: Final[str] = "today"
|
||||
_YESTERDAY: Final[str] = "yesterday"
|
||||
_PREVIOUS_WEEK: Final[str] = "previous week"
|
||||
_THIS_MONTH: Final[str] = "this month"
|
||||
_PREVIOUS_MONTH: Final[str] = "previous month"
|
||||
_THIS_YEAR: Final[str] = "this year"
|
||||
_PREVIOUS_YEAR: Final[str] = "previous year"
|
||||
_PREVIOUS_QUARTER: Final[str] = "previous quarter"
|
||||
|
||||
_DATE_KEYWORDS = frozenset(
|
||||
{
|
||||
_TODAY,
|
||||
_YESTERDAY,
|
||||
_PREVIOUS_WEEK,
|
||||
_THIS_MONTH,
|
||||
_PREVIOUS_MONTH,
|
||||
_THIS_YEAR,
|
||||
_PREVIOUS_YEAR,
|
||||
_PREVIOUS_QUARTER,
|
||||
},
|
||||
)
|
||||
|
||||
_DATE_KEYWORD_PATTERN = "|".join(
|
||||
sorted((regex.escape(k) for k in _DATE_KEYWORDS), key=len, reverse=True),
|
||||
)
|
||||
|
||||
_FIELD_DATE_RE = regex.compile(
|
||||
rf"""(?<!\w)(?P<field>created|modified|added)\s*:\s*(?:
|
||||
(?P<quote>["'])(?P<quoted>{_DATE_KEYWORD_PATTERN})(?P=quote)
|
||||
|
|
||||
(?P<bare>{_DATE_KEYWORD_PATTERN})(?![\w-])
|
||||
)""",
|
||||
regex.IGNORECASE | regex.VERBOSE,
|
||||
)
|
||||
_COMPACT_DATE_RE = regex.compile(r"\b(\d{14})\b")
|
||||
_RELATIVE_RANGE_RE = regex.compile(
|
||||
r"\[now([+-]\d+[dhm])?\s+TO\s+now([+-]\d+[dhm])?\]",
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
# Whoosh-style relative date range: e.g. [-1 week to now], [-7 days to now]
|
||||
_WHOOSH_REL_RANGE_RE = regex.compile(
|
||||
r"\[-(?P<n>\d+)\s+(?P<unit>second|minute|hour|day|week|month|year)s?\s+to\s+now\]",
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
# Whoosh-style 8-digit date: field:YYYYMMDD — field-aware so timezone can be applied correctly.
|
||||
# Scoped to date fields only; numeric fields (asn, id, page_count, ...) must not be rewritten.
|
||||
_DATE8_RE = regex.compile(
|
||||
r"(?<!\w)(?P<field>created|modified|added):(?P<date8>\d{8})\b",
|
||||
)
|
||||
_YEAR_RANGE_RE = regex.compile(
|
||||
r"(?<!\w)(?P<field>created|modified|added):\[(?P<y1>\d{4})\s+TO\s+(?P<y2>\d{4})\]",
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
# Tantivy syntax error: " - " and " + " with spaces on both sides are invalid because
|
||||
# the NOT/MUST operators require no space between the operator and the term.
|
||||
# In natural-language queries (e.g., "H52.1 - Kurzsichtigkeit"), the dash is a separator.
|
||||
_SPACED_OPERATOR_RE = regex.compile(r"\s+[-+]\s+")
|
||||
_TRAILING_OPERATOR_RE = regex.compile(r"\s+[-+]+\s*$")
|
||||
# Matches CJK/Hangul characters so queries can be routed to bigram fields.
|
||||
# Uses Unicode properties to cover all blocks including Extension B+ planes.
|
||||
_CJK_RE: Final = regex.compile(r"[\p{Han}\p{Hiragana}\p{Katakana}\p{Hangul}]+")
|
||||
@@ -117,379 +57,6 @@ def _build_cjk_query(
|
||||
return None
|
||||
|
||||
|
||||
def _fmt(dt: datetime) -> str:
|
||||
"""Format a datetime as an ISO 8601 UTC string for use in Tantivy range queries."""
|
||||
return dt.astimezone(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")
|
||||
|
||||
|
||||
def _iso_range(lo: datetime, hi: datetime) -> str:
|
||||
"""Format a [lo TO hi] range string in ISO 8601 for Tantivy query syntax."""
|
||||
return f"[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
|
||||
|
||||
def _date_only_range(keyword: str, tz: tzinfo) -> str:
|
||||
"""
|
||||
For `created` (DateField): use the local calendar date, converted to
|
||||
midnight UTC boundaries. No offset arithmetic — date only.
|
||||
"""
|
||||
|
||||
today = datetime.now(tz).date()
|
||||
|
||||
def _quarter_start(d: date) -> date:
|
||||
return date(d.year, ((d.month - 1) // 3) * 3 + 1, 1)
|
||||
|
||||
if keyword == _TODAY:
|
||||
lo = datetime(today.year, today.month, today.day, tzinfo=UTC)
|
||||
return _iso_range(lo, lo + timedelta(days=1))
|
||||
if keyword == _YESTERDAY:
|
||||
y = today - timedelta(days=1)
|
||||
lo = datetime(y.year, y.month, y.day, tzinfo=UTC)
|
||||
hi = datetime(today.year, today.month, today.day, tzinfo=UTC)
|
||||
return _iso_range(lo, hi)
|
||||
if keyword == _PREVIOUS_WEEK:
|
||||
this_mon = today - timedelta(days=today.weekday())
|
||||
last_mon = this_mon - timedelta(weeks=1)
|
||||
lo = datetime(last_mon.year, last_mon.month, last_mon.day, tzinfo=UTC)
|
||||
hi = datetime(this_mon.year, this_mon.month, this_mon.day, tzinfo=UTC)
|
||||
return _iso_range(lo, hi)
|
||||
if keyword == _THIS_MONTH:
|
||||
lo = datetime(today.year, today.month, 1, tzinfo=UTC)
|
||||
if today.month == 12:
|
||||
hi = datetime(today.year + 1, 1, 1, tzinfo=UTC)
|
||||
else:
|
||||
hi = datetime(today.year, today.month + 1, 1, tzinfo=UTC)
|
||||
return _iso_range(lo, hi)
|
||||
if keyword == _PREVIOUS_MONTH:
|
||||
if today.month == 1:
|
||||
lo = datetime(today.year - 1, 12, 1, tzinfo=UTC)
|
||||
else:
|
||||
lo = datetime(today.year, today.month - 1, 1, tzinfo=UTC)
|
||||
hi = datetime(today.year, today.month, 1, tzinfo=UTC)
|
||||
return _iso_range(lo, hi)
|
||||
if keyword == _THIS_YEAR:
|
||||
lo = datetime(today.year, 1, 1, tzinfo=UTC)
|
||||
return _iso_range(lo, datetime(today.year + 1, 1, 1, tzinfo=UTC))
|
||||
if keyword == _PREVIOUS_YEAR:
|
||||
lo = datetime(today.year - 1, 1, 1, tzinfo=UTC)
|
||||
return _iso_range(lo, datetime(today.year, 1, 1, tzinfo=UTC))
|
||||
if keyword == _PREVIOUS_QUARTER:
|
||||
this_quarter = _quarter_start(today)
|
||||
last_quarter = this_quarter - relativedelta(months=3)
|
||||
lo = datetime(
|
||||
last_quarter.year,
|
||||
last_quarter.month,
|
||||
last_quarter.day,
|
||||
tzinfo=UTC,
|
||||
)
|
||||
hi = datetime(
|
||||
this_quarter.year,
|
||||
this_quarter.month,
|
||||
this_quarter.day,
|
||||
tzinfo=UTC,
|
||||
)
|
||||
return _iso_range(lo, hi)
|
||||
raise ValueError(f"Unknown keyword: {keyword}")
|
||||
|
||||
|
||||
def _datetime_range(keyword: str, tz: tzinfo) -> str:
|
||||
"""
|
||||
For `added` / `modified` (DateTimeField, stored as UTC): convert local day
|
||||
boundaries to UTC — full offset arithmetic required.
|
||||
"""
|
||||
|
||||
now_local = datetime.now(tz)
|
||||
today = now_local.date()
|
||||
|
||||
def _midnight(d: date) -> datetime:
|
||||
return datetime(d.year, d.month, d.day, tzinfo=tz).astimezone(UTC)
|
||||
|
||||
def _quarter_start(d: date) -> date:
|
||||
return date(d.year, ((d.month - 1) // 3) * 3 + 1, 1)
|
||||
|
||||
if keyword == _TODAY:
|
||||
return _iso_range(_midnight(today), _midnight(today + timedelta(days=1)))
|
||||
if keyword == _YESTERDAY:
|
||||
y = today - timedelta(days=1)
|
||||
return _iso_range(_midnight(y), _midnight(today))
|
||||
if keyword == _PREVIOUS_WEEK:
|
||||
this_mon = today - timedelta(days=today.weekday())
|
||||
last_mon = this_mon - timedelta(weeks=1)
|
||||
return _iso_range(_midnight(last_mon), _midnight(this_mon))
|
||||
if keyword == _THIS_MONTH:
|
||||
first = today.replace(day=1)
|
||||
if today.month == 12:
|
||||
next_first = date(today.year + 1, 1, 1)
|
||||
else:
|
||||
next_first = date(today.year, today.month + 1, 1)
|
||||
return _iso_range(_midnight(first), _midnight(next_first))
|
||||
if keyword == _PREVIOUS_MONTH:
|
||||
this_first = today.replace(day=1)
|
||||
if today.month == 1:
|
||||
last_first = date(today.year - 1, 12, 1)
|
||||
else:
|
||||
last_first = date(today.year, today.month - 1, 1)
|
||||
return _iso_range(_midnight(last_first), _midnight(this_first))
|
||||
if keyword == _THIS_YEAR:
|
||||
return _iso_range(
|
||||
_midnight(date(today.year, 1, 1)),
|
||||
_midnight(date(today.year + 1, 1, 1)),
|
||||
)
|
||||
if keyword == _PREVIOUS_YEAR:
|
||||
return _iso_range(
|
||||
_midnight(date(today.year - 1, 1, 1)),
|
||||
_midnight(date(today.year, 1, 1)),
|
||||
)
|
||||
if keyword == _PREVIOUS_QUARTER:
|
||||
this_quarter = _quarter_start(today)
|
||||
last_quarter = this_quarter - relativedelta(months=3)
|
||||
return _iso_range(_midnight(last_quarter), _midnight(this_quarter))
|
||||
raise ValueError(f"Unknown keyword: {keyword}")
|
||||
|
||||
|
||||
def _rewrite_compact_date(query: str) -> str:
|
||||
"""Rewrite Whoosh compact date tokens (14-digit YYYYMMDDHHmmss) to ISO 8601."""
|
||||
|
||||
def _sub(m: regex.Match[str]) -> str:
|
||||
raw = m.group(1)
|
||||
try:
|
||||
dt = datetime(
|
||||
int(raw[0:4]),
|
||||
int(raw[4:6]),
|
||||
int(raw[6:8]),
|
||||
int(raw[8:10]),
|
||||
int(raw[10:12]),
|
||||
int(raw[12:14]),
|
||||
tzinfo=UTC,
|
||||
)
|
||||
return dt.strftime("%Y-%m-%dT%H:%M:%SZ")
|
||||
except ValueError:
|
||||
return str(m.group(0))
|
||||
|
||||
try:
|
||||
return _COMPACT_DATE_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (compact date rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def _rewrite_relative_range(query: str) -> str:
|
||||
"""Rewrite Whoosh relative ranges ([now-7d TO now]) to concrete ISO 8601 UTC boundaries."""
|
||||
|
||||
def _sub(m: regex.Match[str]) -> str:
|
||||
now = datetime.now(UTC)
|
||||
|
||||
def _offset(s: str | None) -> timedelta:
|
||||
if not s:
|
||||
return timedelta(0)
|
||||
sign = 1 if s[0] == "+" else -1
|
||||
n, unit = int(s[1:-1]), s[-1]
|
||||
return (
|
||||
sign
|
||||
* {
|
||||
"d": timedelta(days=n),
|
||||
"h": timedelta(hours=n),
|
||||
"m": timedelta(minutes=n),
|
||||
}[unit]
|
||||
)
|
||||
|
||||
lo, hi = now + _offset(m.group(1)), now + _offset(m.group(2))
|
||||
if lo > hi:
|
||||
lo, hi = hi, lo
|
||||
return f"[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
|
||||
try:
|
||||
return _RELATIVE_RANGE_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (relative range rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def _rewrite_whoosh_relative_range(query: str) -> str:
|
||||
"""Rewrite Whoosh-style relative date ranges ([-N unit to now]) to ISO 8601.
|
||||
|
||||
Supports: second, minute, hour, day, week, month, year (singular and plural).
|
||||
Example: ``added:[-1 week to now]`` → ``added:[2025-01-01T… TO 2025-01-08T…]``
|
||||
"""
|
||||
now = datetime.now(UTC)
|
||||
|
||||
def _sub(m: regex.Match[str]) -> str:
|
||||
n = int(m.group("n"))
|
||||
unit = m.group("unit").lower()
|
||||
delta_map: dict[str, timedelta | relativedelta] = {
|
||||
"second": timedelta(seconds=n),
|
||||
"minute": timedelta(minutes=n),
|
||||
"hour": timedelta(hours=n),
|
||||
"day": timedelta(days=n),
|
||||
"week": timedelta(weeks=n),
|
||||
"month": relativedelta(months=n),
|
||||
"year": relativedelta(years=n),
|
||||
}
|
||||
lo = now - delta_map[unit]
|
||||
return f"[{_fmt(lo)} TO {_fmt(now)}]"
|
||||
|
||||
try:
|
||||
return _WHOOSH_REL_RANGE_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (Whoosh relative range rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def _rewrite_8digit_date(query: str, tz: tzinfo) -> str:
|
||||
"""Rewrite field:YYYYMMDD date tokens to an ISO 8601 day range.
|
||||
|
||||
Runs after ``_rewrite_compact_date`` so 14-digit timestamps are already
|
||||
converted and won't spuriously match here.
|
||||
|
||||
For DateField fields (e.g. ``created``) uses UTC midnight boundaries.
|
||||
For DateTimeField fields (e.g. ``added``, ``modified``) uses local TZ
|
||||
midnight boundaries converted to UTC — matching the ``_datetime_range``
|
||||
behaviour for keyword dates.
|
||||
"""
|
||||
|
||||
def _sub(m: regex.Match[str]) -> str:
|
||||
field = m.group("field")
|
||||
raw = m.group("date8")
|
||||
try:
|
||||
year, month, day = int(raw[0:4]), int(raw[4:6]), int(raw[6:8])
|
||||
d = date(year, month, day)
|
||||
if field in _DATE_ONLY_FIELDS:
|
||||
lo = datetime(d.year, d.month, d.day, tzinfo=UTC)
|
||||
hi = lo + timedelta(days=1)
|
||||
else:
|
||||
# DateTimeField: use local-timezone midnight → UTC
|
||||
lo = datetime(d.year, d.month, d.day, tzinfo=tz).astimezone(UTC)
|
||||
hi = datetime(
|
||||
(d + timedelta(days=1)).year,
|
||||
(d + timedelta(days=1)).month,
|
||||
(d + timedelta(days=1)).day,
|
||||
tzinfo=tz,
|
||||
).astimezone(UTC)
|
||||
return f"{field}:[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
except ValueError:
|
||||
return m.group(0)
|
||||
|
||||
try:
|
||||
return _DATE8_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (8-digit date rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def _rewrite_year_range(query: str) -> str:
|
||||
"""Rewrite Whoosh-style year-only date ranges to ISO 8601 UTC boundaries.
|
||||
|
||||
Converts ``field:[YYYY TO YYYY]`` to a full ISO 8601 datetime range.
|
||||
The upper bound is the start of the year after the end year (exclusive),
|
||||
matching the Whoosh convention of treating year-only ranges as full-year spans.
|
||||
"""
|
||||
|
||||
def _sub(m: regex.Match[str]) -> str:
|
||||
field = m.group("field")
|
||||
y1, y2 = int(m.group("y1")), int(m.group("y2"))
|
||||
# Whoosh swaps a reversed range when both years are explicit
|
||||
# (whoosh.util.times.timespan.disambiguated); match that so a backwards
|
||||
# range spans the intended years instead of matching nothing.
|
||||
lo_year, hi_year = min(y1, y2), max(y1, y2)
|
||||
lo = datetime(lo_year, 1, 1, tzinfo=UTC)
|
||||
hi = datetime(hi_year + 1, 1, 1, tzinfo=UTC)
|
||||
return f"{field}:[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
|
||||
try:
|
||||
return _YEAR_RANGE_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (year range rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def rewrite_natural_date_keywords(query: str, tz: tzinfo) -> str:
|
||||
"""
|
||||
Rewrite natural date syntax to ISO 8601 format for Tantivy compatibility.
|
||||
|
||||
Performs the first stage of query preprocessing, converting various date
|
||||
formats and keywords to ISO 8601 datetime ranges that Tantivy can parse:
|
||||
- Compact 14-digit dates (YYYYMMDDHHmmss)
|
||||
- Whoosh relative ranges ([-7 days to now], [now-1h TO now+2h])
|
||||
- 8-digit dates with field awareness (created:20240115)
|
||||
- Natural keywords (field:today, field:"previous quarter", etc.)
|
||||
|
||||
Args:
|
||||
query: Raw user query string
|
||||
tz: Timezone for converting local date boundaries to UTC
|
||||
|
||||
Returns:
|
||||
Query with date syntax rewritten to ISO 8601 ranges
|
||||
|
||||
Note:
|
||||
Bare keywords without field prefixes pass through unchanged.
|
||||
"""
|
||||
query = _rewrite_compact_date(query)
|
||||
query = _rewrite_whoosh_relative_range(query)
|
||||
query = _rewrite_year_range(query)
|
||||
query = _rewrite_8digit_date(query, tz)
|
||||
query = _rewrite_relative_range(query)
|
||||
|
||||
def _replace(m: regex.Match[str]) -> str:
|
||||
field = m.group("field")
|
||||
keyword = (m.group("quoted") or m.group("bare")).lower()
|
||||
if field in _DATE_ONLY_FIELDS:
|
||||
return f"{field}:{_date_only_range(keyword, tz)}"
|
||||
return f"{field}:{_datetime_range(keyword, tz)}"
|
||||
|
||||
try:
|
||||
return _FIELD_DATE_RE.sub(_replace, query, timeout=_REGEX_TIMEOUT)
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (date keyword rewrite timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def normalize_query(query: str) -> str:
|
||||
"""
|
||||
Normalize query syntax for better search behavior.
|
||||
|
||||
Expands comma-separated field values to explicit AND clauses and
|
||||
collapses excessive whitespace for cleaner parsing:
|
||||
- tag:foo,bar → tag:foo AND tag:bar
|
||||
- multiple spaces → single spaces
|
||||
|
||||
Args:
|
||||
query: Query string after date rewriting
|
||||
|
||||
Returns:
|
||||
Normalized query string ready for Tantivy parsing
|
||||
"""
|
||||
|
||||
def _expand(m: regex.Match[str]) -> str:
|
||||
field = m.group(1)
|
||||
values = [v.strip() for v in m.group(2).split(",") if v.strip()]
|
||||
return " AND ".join(f"{field}:{v}" for v in values)
|
||||
|
||||
try:
|
||||
query = regex.sub(
|
||||
r"(\w+):([^\s\[\]]+(?:,[^\s\[\]]+)+)",
|
||||
_expand,
|
||||
query,
|
||||
timeout=_REGEX_TIMEOUT,
|
||||
)
|
||||
query = regex.sub(r" {2,}", " ", query, timeout=_REGEX_TIMEOUT).strip()
|
||||
# Strip trailing dangling operators before Tantivy sees them.
|
||||
query = _TRAILING_OPERATOR_RE.sub("", query, timeout=_REGEX_TIMEOUT).strip()
|
||||
# Replace " - " / " + " with a space: Tantivy requires no space between
|
||||
# the operator and its operand (-term / +term), so spaces on both sides
|
||||
# means this is a natural-language separator, not a query operator.
|
||||
query = _SPACED_OPERATOR_RE.sub(" ", query, timeout=_REGEX_TIMEOUT).strip()
|
||||
return query
|
||||
except TimeoutError: # pragma: no cover
|
||||
raise ValueError(
|
||||
"Query too complex to process (normalization timed out)",
|
||||
) from None
|
||||
|
||||
|
||||
def build_permission_filter(
|
||||
schema: tantivy.Schema,
|
||||
user: AbstractBaseUser,
|
||||
@@ -607,8 +174,16 @@ def parse_user_query(
|
||||
as a post-search score filter, not during query construction.
|
||||
"""
|
||||
|
||||
query_str = rewrite_natural_date_keywords(raw_query, tz)
|
||||
query_str = normalize_query(query_str)
|
||||
try:
|
||||
query_str = translate_query(raw_query, tz)
|
||||
except SearchQueryError:
|
||||
# Intentional, user-fixable error (e.g. an unparsable date). Propagate so
|
||||
# the view can return a 400 with a helpful message rather than falling
|
||||
# back to the raw (still-invalid) query.
|
||||
raise
|
||||
except Exception: # pragma: no cover - defensive
|
||||
logger.warning("Query translation failed; using raw query", exc_info=True)
|
||||
query_str = raw_query
|
||||
|
||||
exact = index.parse_query(
|
||||
query_str,
|
||||
|
||||
@@ -0,0 +1,566 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from datetime import UTC
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
from typing import TYPE_CHECKING
|
||||
from typing import TypeAlias
|
||||
|
||||
import regex
|
||||
from dateutil.relativedelta import relativedelta
|
||||
|
||||
from documents.search._dates import _DATE_KEYWORDS
|
||||
from documents.search._dates import _DATE_ONLY_FIELDS
|
||||
from documents.search._dates import _date_only_range
|
||||
from documents.search._dates import _datetime_range
|
||||
from documents.search._dates import _field_range_from_dates
|
||||
from documents.search._dates import _fmt
|
||||
from documents.search._dates import _precision_bounds
|
||||
from documents.search._dates import _utc_bounds_for_field
|
||||
|
||||
# Compiled regex that matches any known multi-word (or single-word) date keyword
|
||||
# at the start of a match position, longest alternatives first so "previous week"
|
||||
# wins over a hypothetical shorter "previous".
|
||||
_KEYWORD_VALUE_RE = regex.compile(
|
||||
"|".join(sorted((regex.escape(k) for k in _DATE_KEYWORDS), key=len, reverse=True)),
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from datetime import tzinfo
|
||||
|
||||
# TODO: this module translates date queries into Tantivy *string* syntax, which
|
||||
# forces a workaround for something Tantivy's string parser cannot express on
|
||||
# date fields: open-ended ranges use far-past/far-future string sentinels
|
||||
# (OPEN_LO/OPEN_HI). These can be replaced with a real tantivy.Query object
|
||||
# (Query.range_query(..., None) for open bounds) once tantivy-py accepts Python
|
||||
# datetimes in range_query/term_query on Date fields. That support exists on
|
||||
# tantivy-py master (PRs #655 + #666) but postdates the pinned 0.26.0 wheel, so
|
||||
# it is blocked only on a published release > 0.26.0 and a dependency bump.
|
||||
# (Unparsable dates now raise InvalidDateQuery -> HTTP 400 rather than using a
|
||||
# no-match string sentinel.)
|
||||
|
||||
# Fields that store exact, non-analyzed comma-joined tokens in the index and so
|
||||
# need explicit comma->AND expansion (Whoosh KEYWORD(commas=True) set).
|
||||
MULTI_VALUE_FIELDS = frozenset({"tag", "tag_id", "viewer_id"})
|
||||
|
||||
# Date fields whose values/ranges get rewritten to RFC3339 Tantivy ranges.
|
||||
DATE_FIELDS = frozenset({"created", "modified", "added"})
|
||||
|
||||
# Field aliases: Whoosh (v2) field names that were renamed in the Tantivy schema.
|
||||
# Preserved here so v2 queries using the old names continue to work without 400
|
||||
# errors instead of silently failing. Applied by _render to non-date field tokens.
|
||||
FIELD_ALIASES: dict[str, str] = {
|
||||
"type": "document_type",
|
||||
"type_id": "document_type_id",
|
||||
"path": "storage_path",
|
||||
"path_id": "storage_path_id",
|
||||
}
|
||||
|
||||
# Known schema fields: a comma immediately followed by ``<known>:`` is a clause
|
||||
# separator. Restricting to known fields prevents URL-like ``http:`` misfires.
|
||||
KNOWN_FIELDS = frozenset(
|
||||
{
|
||||
"title",
|
||||
"content",
|
||||
"correspondent",
|
||||
"document_type",
|
||||
"type", # v2 alias -> document_type
|
||||
"storage_path",
|
||||
"path", # v2 alias -> storage_path
|
||||
"tag",
|
||||
"tag_id",
|
||||
"correspondent_id",
|
||||
"document_type_id",
|
||||
"type_id", # v2 alias -> document_type_id
|
||||
"storage_path_id",
|
||||
"path_id", # v2 alias -> storage_path_id
|
||||
"owner_id",
|
||||
"viewer_id",
|
||||
"asn",
|
||||
"page_count",
|
||||
"num_notes",
|
||||
"created",
|
||||
"modified",
|
||||
"added",
|
||||
"original_filename",
|
||||
"checksum",
|
||||
"notes",
|
||||
"custom_fields",
|
||||
},
|
||||
)
|
||||
|
||||
_FIELD_RE = regex.compile(r"(?P<field>\w+):")
|
||||
|
||||
# Matches the TO separator inside a range bracket. Handles three forms:
|
||||
# middle: "lo TO hi" (either lo or hi may be empty)
|
||||
# trailing: "lo TO" (open upper bound)
|
||||
# leading: "TO hi" (open lower bound)
|
||||
# Bounds MAY contain internal spaces (e.g. "-7 days"), so we use .*? / .+?
|
||||
# and split on the whitespace-delimited " TO " / " to " separator.
|
||||
_RANGE_RE = regex.compile(
|
||||
r"^\s*(?P<lo>.*?)\s+[Tt][Oo]\s+(?P<hi>.+?)\s*$"
|
||||
r"|"
|
||||
r"^\s*(?P<lo2>.+?)\s+[Tt][Oo]\s*$"
|
||||
r"|"
|
||||
r"^\s*[Tt][Oo]\s+(?P<hi2>.+?)\s*$",
|
||||
)
|
||||
|
||||
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class FieldValue:
|
||||
field: str
|
||||
value: str
|
||||
|
||||
|
||||
# Produced by the comma-resolution pass (not by scan()).
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class FieldValueList:
|
||||
field: str
|
||||
values: tuple[str, ...]
|
||||
|
||||
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class FieldRange:
|
||||
field: str
|
||||
open: str
|
||||
lo: str
|
||||
hi: str
|
||||
close: str
|
||||
|
||||
|
||||
# Produced by the comma-resolution pass (not by scan()).
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class Comma:
|
||||
pass
|
||||
|
||||
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class Passthrough:
|
||||
raw: str
|
||||
|
||||
|
||||
Token: TypeAlias = FieldValue | FieldValueList | FieldRange | Comma | Passthrough
|
||||
|
||||
_CLOSE: dict[str, str] = {"[": "]", "{": "}"}
|
||||
|
||||
|
||||
def scan(query: str) -> list[Token]:
|
||||
"""
|
||||
Tokenize a raw query into date/comma-aware tokens, leaving everything else
|
||||
as verbatim ``Passthrough`` runs. Non-recursive: finds the first matching
|
||||
close bracket/quote. Nested brackets are not valid Tantivy range syntax and
|
||||
pass through verbatim on mismatch.
|
||||
"""
|
||||
tokens: list[Token] = []
|
||||
buf: list[str] = [] # accumulates passthrough chars
|
||||
i, n = 0, len(query)
|
||||
while i < n:
|
||||
matched = _match_field_token(query, i)
|
||||
if matched is None:
|
||||
buf.append(query[i])
|
||||
i += 1
|
||||
continue
|
||||
token, i = matched
|
||||
_flush(buf, tokens)
|
||||
tokens.append(token)
|
||||
i = _maybe_comma(query, i, tokens)
|
||||
_flush(buf, tokens)
|
||||
return tokens
|
||||
|
||||
|
||||
def _flush(buf: list[str], tokens: list[Token]) -> None:
|
||||
"""Emit any accumulated passthrough characters as a single token."""
|
||||
if buf:
|
||||
tokens.append(Passthrough("".join(buf)))
|
||||
buf.clear()
|
||||
|
||||
|
||||
def _at_word_boundary(query: str, i: int) -> bool:
|
||||
"""A field token may begin only at the start or after a non-word character."""
|
||||
return i == 0 or not (query[i - 1].isalnum() or query[i - 1] == "_")
|
||||
|
||||
|
||||
def _match_field_token(query: str, i: int) -> tuple[Token, int] | None:
|
||||
"""
|
||||
If a known ``field:`` token starts at ``i``, consume it and return
|
||||
``(token, end_index)``; otherwise return None so the caller treats the
|
||||
character as passthrough. Handles both ``field:[range]`` and ``field:value``,
|
||||
and returns None when the range/value cannot be consumed.
|
||||
"""
|
||||
m = _FIELD_RE.match(query, i)
|
||||
if m is None or m.group("field") not in KNOWN_FIELDS:
|
||||
return None
|
||||
if not _at_word_boundary(query, i):
|
||||
return None
|
||||
field = m.group("field")
|
||||
j = m.end()
|
||||
if j < len(query) and query[j] in "[{":
|
||||
return _consume_range(query, j, field)
|
||||
consumed = _consume_field_value(query, field, j)
|
||||
if consumed is None:
|
||||
return None
|
||||
value, end = consumed
|
||||
return FieldValue(field, value), end
|
||||
|
||||
|
||||
def _consume_field_value(query: str, field: str, start: int) -> tuple[str, int] | None:
|
||||
"""
|
||||
Consume a field value starting at ``start``: a multi-word date keyword phrase
|
||||
(date fields only), or a bare/quoted value, then absorb any comma-joined
|
||||
continuation that is not a clause separator. ``resolve_commas`` later splits a
|
||||
multi-value field's joined value into a ``FieldValueList``; for other fields
|
||||
the comma stays literal.
|
||||
"""
|
||||
n = len(query)
|
||||
consumed = None
|
||||
if field in DATE_FIELDS:
|
||||
km = _KEYWORD_VALUE_RE.match(query, start)
|
||||
if km is not None and (km.end() >= n or query[km.end()] in " \t),"):
|
||||
consumed = (km.group(0), km.end())
|
||||
if consumed is None:
|
||||
consumed = _consume_value(query, start)
|
||||
if consumed is None:
|
||||
return None
|
||||
value, k = consumed
|
||||
while k < n and query[k] == ",":
|
||||
if _looks_like_known_field(query, k + 1):
|
||||
break # clause separator: left for _maybe_comma to emit a Comma()
|
||||
more = _consume_value(query, k + 1)
|
||||
if more is None:
|
||||
break
|
||||
value = f"{value},{more[0]}"
|
||||
k = more[1]
|
||||
return value, k
|
||||
|
||||
|
||||
def _consume_range(
|
||||
query: str,
|
||||
start: int,
|
||||
field: str,
|
||||
) -> tuple[FieldRange, int] | None:
|
||||
"""Consume ``[lo TO hi]`` / ``{lo TO hi}`` from ``start`` (the bracket)."""
|
||||
open_br = query[start]
|
||||
close_br = _CLOSE[open_br]
|
||||
end = query.find(close_br, start + 1)
|
||||
if end == -1:
|
||||
return None
|
||||
inner = query[start + 1 : end]
|
||||
m = _RANGE_RE.match(inner)
|
||||
if m is not None:
|
||||
if m.group("lo") is not None or m.group("hi") is not None:
|
||||
# Middle form: "lo TO hi" (either may be empty string)
|
||||
lo = (m.group("lo") or "").strip()
|
||||
hi = (m.group("hi") or "").strip()
|
||||
elif m.group("lo2") is not None:
|
||||
# Trailing form: "lo TO"
|
||||
lo = m.group("lo2").strip()
|
||||
hi = ""
|
||||
else:
|
||||
# Leading form: "TO hi"
|
||||
lo = ""
|
||||
hi = (m.group("hi2") or "").strip()
|
||||
else:
|
||||
lo, hi = inner.strip(), ""
|
||||
return FieldRange(field, open_br, lo, hi, close_br), end + 1
|
||||
|
||||
|
||||
def _consume_value(query: str, start: int) -> tuple[str, int] | None:
|
||||
"""Consume a bare or quoted field value from ``start``, stopping at comma."""
|
||||
n = len(query)
|
||||
if start >= n or query[start] in " \t":
|
||||
return None
|
||||
if query[start] in "\"'":
|
||||
quote = query[start]
|
||||
end = query.find(quote, start + 1)
|
||||
if end == -1:
|
||||
return None
|
||||
return query[start : end + 1], end + 1
|
||||
j = start
|
||||
while j < n and query[j] not in " \t),":
|
||||
j += 1
|
||||
return query[start:j], j
|
||||
|
||||
|
||||
def _looks_like_known_field(query: str, pos: int) -> bool:
|
||||
"""True if a known ``field:`` token starts at ``pos``."""
|
||||
m = _FIELD_RE.match(query, pos)
|
||||
return bool(m and m.group("field") in KNOWN_FIELDS)
|
||||
|
||||
|
||||
def _maybe_comma(query: str, i: int, tokens: list) -> int:
|
||||
"""If a clause-separator comma follows at ``i``, emit ``Comma()`` and advance."""
|
||||
if i < len(query) and query[i] == "," and _looks_like_known_field(query, i + 1):
|
||||
tokens.append(Comma())
|
||||
return i + 1
|
||||
return i
|
||||
|
||||
|
||||
def resolve_commas(tokens: list) -> list:
|
||||
"""
|
||||
Collapse value-list commas into ``FieldValueList`` and keep clause-separator
|
||||
commas as ``Comma``. (Clause-sep commas are already emitted by ``scan`` via
|
||||
the value-stop logic; this pass folds value-lists.)
|
||||
"""
|
||||
out: list = []
|
||||
for tok in tokens:
|
||||
if (
|
||||
isinstance(tok, FieldValue)
|
||||
and tok.field in MULTI_VALUE_FIELDS
|
||||
and "," in tok.value
|
||||
):
|
||||
values = tuple(v for v in tok.value.split(",") if v)
|
||||
out.append(FieldValueList(tok.field, values))
|
||||
else:
|
||||
out.append(tok)
|
||||
return out
|
||||
|
||||
|
||||
class SearchQueryError(ValueError):
|
||||
"""
|
||||
Base for user-fixable search query errors.
|
||||
|
||||
Carries a message safe to surface to the user (no internal details). The view
|
||||
layer catches this and returns an HTTP 400, so any future subclass (unknown
|
||||
field, malformed range, wrapped parser errors) gets the same treatment.
|
||||
"""
|
||||
|
||||
|
||||
class InvalidDateQuery(SearchQueryError):
|
||||
"""Raised when a date field value or range bound cannot be parsed."""
|
||||
|
||||
def __init__(self, field: str, value: str) -> None:
|
||||
self.field = field
|
||||
self.value = value
|
||||
super().__init__(f"Invalid date value {value!r} for field {field!r}.")
|
||||
|
||||
|
||||
_DIGITS_RE = regex.compile(r"^\d{4}(?:\d{2}){0,2}$")
|
||||
_ISO_RE = regex.compile(r"^\d{4}(?:-\d{2}(?:-\d{2})?)?$")
|
||||
|
||||
|
||||
def translate_scalar(field: str, value: str, tz: tzinfo) -> str:
|
||||
"""Translate a bare date-field value to a Tantivy range string."""
|
||||
bare = value.strip("\"'").lower()
|
||||
if bare in _DATE_KEYWORDS:
|
||||
if field in _DATE_ONLY_FIELDS:
|
||||
return f"{field}:{_date_only_range(bare, tz)}"
|
||||
return f"{field}:{_datetime_range(bare, tz)}"
|
||||
digits = value.replace("-", "")
|
||||
if _DIGITS_RE.match(value) or _ISO_RE.match(value):
|
||||
bounds = _precision_bounds(digits)
|
||||
if bounds is None:
|
||||
raise InvalidDateQuery(field, value)
|
||||
return _field_range_from_dates(field, bounds[0], bounds[1], tz)
|
||||
if regex.fullmatch(r"\d{14}", value):
|
||||
try:
|
||||
dt = datetime(
|
||||
int(value[0:4]),
|
||||
int(value[4:6]),
|
||||
int(value[6:8]),
|
||||
int(value[8:10]),
|
||||
int(value[10:12]),
|
||||
int(value[12:14]),
|
||||
tzinfo=UTC,
|
||||
)
|
||||
except ValueError:
|
||||
raise InvalidDateQuery(field, value) from None
|
||||
iso = _fmt(dt)
|
||||
return f"{field}:[{iso} TO {iso}]"
|
||||
# Unrecognized shape -> tell the user their date is malformed rather than
|
||||
# silently matching nothing or emitting invalid Tantivy syntax.
|
||||
raise InvalidDateQuery(field, value)
|
||||
|
||||
|
||||
# Open-bound sentinels for date ranges. These far-past/far-future strings allow
|
||||
# open-ended ranges to be expressed as Tantivy string queries until tantivy-py
|
||||
# exposes Query.range_query(..., None) on Date fields (see module TODO).
|
||||
OPEN_LO = "0001-01-01T00:00:00Z"
|
||||
OPEN_HI = "9999-12-31T23:59:59Z"
|
||||
|
||||
|
||||
# Matches compact now-offset tokens like now-7d, now+1h, now-30m.
|
||||
_NOW_COMPACT_RE = regex.compile(
|
||||
r"^now(?P<sign>[+-])(?P<n>\d+)(?P<unit>[dhm])$",
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
|
||||
# Matches "±N <unit>" Whoosh-style offsets (e.g. -7 days, -1 week, +3 hours)
|
||||
# Unit is singular or plural; sign prefix is mandatory.
|
||||
_NOW_SPACED_RE = regex.compile(
|
||||
r"^(?P<sign>[+-])(?P<n>\d+)\s*"
|
||||
r"(?P<unit>second|minute|hour|day|week|month|year)s?$",
|
||||
regex.IGNORECASE,
|
||||
)
|
||||
|
||||
|
||||
def _resolve_relative_bound(token: str) -> datetime | None:
|
||||
"""
|
||||
Resolve a relative bound token to an exact UTC instant, or return None.
|
||||
|
||||
Supported forms:
|
||||
- ``now`` -> current UTC instant
|
||||
- ``now+/-<n>d/h/m`` -> now +/- timedelta (d=days, h=hours, m=minutes)
|
||||
- ``±N <unit>`` -> now +/- delta; month/year use relativedelta
|
||||
"""
|
||||
stripped = token.strip()
|
||||
low = stripped.lower()
|
||||
now = datetime.now(UTC)
|
||||
|
||||
if low == "now":
|
||||
return now
|
||||
|
||||
m = _NOW_COMPACT_RE.match(stripped)
|
||||
if m:
|
||||
sign = 1 if m.group("sign") == "+" else -1
|
||||
n = int(m.group("n"))
|
||||
unit = m.group("unit").lower()
|
||||
delta = (
|
||||
sign
|
||||
* {
|
||||
"d": timedelta(days=n),
|
||||
"h": timedelta(hours=n),
|
||||
"m": timedelta(minutes=n),
|
||||
}[unit]
|
||||
)
|
||||
return now + delta
|
||||
|
||||
m = _NOW_SPACED_RE.match(stripped)
|
||||
if m:
|
||||
sign = 1 if m.group("sign") == "+" else -1
|
||||
n = int(m.group("n"))
|
||||
unit = m.group("unit").lower()
|
||||
delta_map: dict[str, timedelta | relativedelta] = {
|
||||
"second": timedelta(seconds=n),
|
||||
"minute": timedelta(minutes=n),
|
||||
"hour": timedelta(hours=n),
|
||||
"day": timedelta(days=n),
|
||||
"week": timedelta(weeks=n),
|
||||
"month": relativedelta(months=n),
|
||||
"year": relativedelta(years=n),
|
||||
}
|
||||
return now - delta_map[unit] if sign == -1 else now + delta_map[unit]
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def _bound_datetimes(
|
||||
field: str,
|
||||
token: str,
|
||||
tz: tzinfo,
|
||||
) -> tuple[datetime, datetime] | None:
|
||||
"""
|
||||
Return (floor_dt, ceil_dt) UTC datetimes for a single range bound token, or
|
||||
None if the token is unparsable. ``now`` and relative offsets resolve to the
|
||||
current instant (floor == ceil == that instant; no day-flooring).
|
||||
"""
|
||||
token = token.strip()
|
||||
|
||||
# Try relative/now forms first (before stripping hyphens which would mangle them).
|
||||
rel = _resolve_relative_bound(token)
|
||||
if rel is not None:
|
||||
return rel, rel
|
||||
|
||||
# Full ISO datetime token (contains "T"): parse directly and return an exact
|
||||
# instant (floor == ceil). Python 3.11+ datetime.fromisoformat accepts trailing Z.
|
||||
if "T" in token:
|
||||
try:
|
||||
dt = datetime.fromisoformat(token)
|
||||
# Ensure timezone-aware UTC result.
|
||||
dt = dt.replace(tzinfo=UTC) if dt.tzinfo is None else dt.astimezone(UTC)
|
||||
return dt, dt
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
digits = token.replace("-", "")
|
||||
bounds = _precision_bounds(digits)
|
||||
if bounds is None:
|
||||
return None
|
||||
start, end = bounds
|
||||
return _utc_bounds_for_field(field, start, end, tz)
|
||||
|
||||
|
||||
def _render(tok: Token, tz: tzinfo) -> str:
|
||||
"""Render a single token back to a Tantivy query string fragment."""
|
||||
if isinstance(tok, Passthrough):
|
||||
return tok.raw
|
||||
if isinstance(tok, Comma):
|
||||
return " AND "
|
||||
if isinstance(tok, FieldValueList):
|
||||
field = FIELD_ALIASES.get(tok.field, tok.field)
|
||||
return " AND ".join(f"{field}:{v}" for v in tok.values)
|
||||
if isinstance(tok, FieldValue):
|
||||
field = FIELD_ALIASES.get(tok.field, tok.field)
|
||||
if field in DATE_FIELDS:
|
||||
return translate_scalar(field, tok.value, tz)
|
||||
return f"{field}:{tok.value}"
|
||||
if isinstance(tok, FieldRange):
|
||||
field = FIELD_ALIASES.get(tok.field, tok.field)
|
||||
if field in DATE_FIELDS:
|
||||
return translate_range(field, tok.lo, tok.hi, tz)
|
||||
return f"{field}:{tok.open}{tok.lo} TO {tok.hi}{tok.close}"
|
||||
return "" # pragma: no cover
|
||||
|
||||
|
||||
# Post-render operator normalization patterns: collapse repeated whitespace and
|
||||
# strip spaced/trailing Tantivy boolean operators that would otherwise be invalid.
|
||||
_MULTI_SPACE_RE = regex.compile(r" {2,}")
|
||||
_TRAILING_OP_RE = regex.compile(r"\s+[-+]+\s*$")
|
||||
_SPACED_OP_RE = regex.compile(r"\s+[-+]\s+")
|
||||
|
||||
|
||||
def _normalize_operators(text: str) -> str:
|
||||
"""
|
||||
Collapse multiple spaces, strip trailing dangling operators, and replace
|
||||
spaced operators (`` - `` / `` + ``) with a single space.
|
||||
|
||||
Applied only to Passthrough fragments (the rendered output is scanned for
|
||||
operator artifacts outside bracketed ranges) via a post-render pass on the
|
||||
full rendered string. This preserves date ranges (``[... TO ...]``) verbatim
|
||||
while cleaning natural-language separators in the surrounding text.
|
||||
"""
|
||||
text = _MULTI_SPACE_RE.sub(" ", text)
|
||||
text = _TRAILING_OP_RE.sub("", text).strip()
|
||||
text = _SPACED_OP_RE.sub(" ", text).strip()
|
||||
return text
|
||||
|
||||
|
||||
def translate_query(raw: str, tz: tzinfo) -> str:
|
||||
"""Translate a raw Whoosh-style query into Tantivy-compatible syntax."""
|
||||
tokens = resolve_commas(scan(raw))
|
||||
rendered = "".join(_render(t, tz) for t in tokens)
|
||||
return _normalize_operators(rendered)
|
||||
|
||||
|
||||
def translate_range(field: str, lo: str, hi: str, tz: tzinfo) -> str:
|
||||
"""Translate a date-field ``[lo TO hi]`` range to a Tantivy ISO range string.
|
||||
|
||||
Handles partial-date bounds (YYYY, YYYYMM, YYYYMMDD, ISO dash variants),
|
||||
open bounds (empty string -> OPEN_LO/OPEN_HI), ``now``, and reversed ranges
|
||||
(swaps tokens before computing floor/ceil so the span is always correct).
|
||||
"""
|
||||
lo_s = lo.strip()
|
||||
hi_s = hi.strip()
|
||||
|
||||
# Parse both bounds to (floor, ceil) pairs when present.
|
||||
lo_pair: tuple[datetime, datetime] | None = None
|
||||
hi_pair: tuple[datetime, datetime] | None = None
|
||||
|
||||
if lo_s:
|
||||
lo_pair = _bound_datetimes(field, lo_s, tz)
|
||||
if lo_pair is None:
|
||||
raise InvalidDateQuery(field, lo_s)
|
||||
if hi_s:
|
||||
hi_pair = _bound_datetimes(field, hi_s, tz)
|
||||
if hi_pair is None:
|
||||
raise InvalidDateQuery(field, hi_s)
|
||||
|
||||
# Detect a reversed range: only swap when BOTH bounds are present.
|
||||
if lo_pair is not None and hi_pair is not None and lo_pair[0] > hi_pair[0]:
|
||||
lo_pair, hi_pair = hi_pair, lo_pair
|
||||
|
||||
lo_iso = _fmt(lo_pair[0]) if lo_pair is not None else OPEN_LO
|
||||
hi_iso = _fmt(hi_pair[1]) if hi_pair is not None else OPEN_HI
|
||||
|
||||
return f"{field}:[{lo_iso} TO {hi_iso}]"
|
||||
@@ -48,6 +48,7 @@ from rest_framework import serializers
|
||||
from rest_framework.exceptions import PermissionDenied
|
||||
from rest_framework.fields import SerializerMethodField
|
||||
from rest_framework.filters import OrderingFilter
|
||||
from rest_framework.utils import model_meta
|
||||
|
||||
if settings.AUDIT_LOG_ENABLED:
|
||||
from auditlog.context import set_actor
|
||||
@@ -121,6 +122,45 @@ class DynamicFieldsModelSerializer(serializers.ModelSerializer[Any]):
|
||||
self.fields.pop(field_name)
|
||||
|
||||
|
||||
class DocumentUpdateFieldsModelSerializer(DynamicFieldsModelSerializer):
|
||||
stale_update_excluded_fields = frozenset({"filename", "archive_filename"})
|
||||
|
||||
def _get_update_fields(self, validated_data) -> list[str]:
|
||||
model_fields = {
|
||||
field.name
|
||||
for field in self.Meta.model._meta.concrete_fields
|
||||
if field.name not in self.stale_update_excluded_fields
|
||||
}
|
||||
update_fields = [
|
||||
field_name for field_name in validated_data if field_name in model_fields
|
||||
]
|
||||
if "modified" in model_fields and "modified" not in update_fields:
|
||||
update_fields.append("modified")
|
||||
return update_fields
|
||||
|
||||
def update(self, instance, validated_data):
|
||||
serializers.raise_errors_on_nested_writes("update", self, validated_data)
|
||||
info = model_meta.get_field_info(instance)
|
||||
|
||||
m2m_fields = []
|
||||
for attr, value in validated_data.items():
|
||||
if attr in info.relations and info.relations[attr].to_many:
|
||||
m2m_fields.append((attr, value))
|
||||
else:
|
||||
setattr(instance, attr, value)
|
||||
|
||||
# File names are managed by post-save file handling. Saving only the
|
||||
# serializer-updated fields prevents stale in-memory path values from
|
||||
# overwriting a concurrent move.
|
||||
instance.save(update_fields=self._get_update_fields(validated_data))
|
||||
|
||||
for attr, value in m2m_fields:
|
||||
field = getattr(instance, attr)
|
||||
field.set(value)
|
||||
|
||||
return instance
|
||||
|
||||
|
||||
class MatchingModelSerializer(serializers.ModelSerializer[Any]):
|
||||
document_count = serializers.IntegerField(read_only=True)
|
||||
|
||||
@@ -163,7 +203,7 @@ class MatchingModelSerializer(serializers.ModelSerializer[Any]):
|
||||
logger.debug(f"Invalid regular expression: {e!s}")
|
||||
raise serializers.ValidationError(
|
||||
"Invalid regular expression, see log for details.",
|
||||
) from None
|
||||
)
|
||||
return match
|
||||
|
||||
|
||||
@@ -867,9 +907,7 @@ class CustomFieldInstanceSerializer(serializers.ModelSerializer[CustomFieldInsta
|
||||
try:
|
||||
value_int = int(data["value"])
|
||||
except (TypeError, ValueError):
|
||||
raise serializers.ValidationError(
|
||||
"Enter a valid integer.",
|
||||
) from None
|
||||
raise serializers.ValidationError("Enter a valid integer.")
|
||||
# Keep values within the PostgreSQL integer range
|
||||
MinValueValidator(-2147483648)(value_int)
|
||||
MaxValueValidator(2147483647)(value_int)
|
||||
@@ -901,7 +939,7 @@ class CustomFieldInstanceSerializer(serializers.ModelSerializer[CustomFieldInsta
|
||||
except Exception:
|
||||
raise serializers.ValidationError(
|
||||
f"Value must be an id of an element in {select_options}",
|
||||
) from None
|
||||
)
|
||||
elif field.data_type == CustomField.FieldDataType.DOCUMENTLINK:
|
||||
if not (isinstance(data["value"], list) or data["value"] is None):
|
||||
raise serializers.ValidationError(
|
||||
@@ -991,7 +1029,7 @@ class DocumentVersionInfoSerializer(serializers.Serializer[_DocumentVersionInfo]
|
||||
class DocumentSerializer(
|
||||
OwnedObjectSerializer,
|
||||
NestedUpdateMixin,
|
||||
DynamicFieldsModelSerializer,
|
||||
DocumentUpdateFieldsModelSerializer,
|
||||
):
|
||||
correspondent = CorrespondentField(allow_null=True)
|
||||
tags = TagsField(many=True)
|
||||
@@ -1092,7 +1130,7 @@ class DocumentSerializer(
|
||||
def to_representation(self, instance):
|
||||
doc = super().to_representation(instance)
|
||||
if "content" in self.fields and hasattr(instance, "effective_content"):
|
||||
doc["content"] = instance.effective_content or ""
|
||||
doc["content"] = getattr(instance, "effective_content") or ""
|
||||
if self.truncate_content and "content" in self.fields:
|
||||
doc["content"] = doc.get("content")[0:550]
|
||||
return doc
|
||||
@@ -1130,10 +1168,9 @@ class DocumentSerializer(
|
||||
return super().validate(attrs)
|
||||
|
||||
def update(self, instance: Document, validated_data):
|
||||
if "created_date" in validated_data and "created" not in validated_data:
|
||||
instance.created = validated_data.get("created_date")
|
||||
instance.save()
|
||||
if "created_date" in validated_data:
|
||||
if "created" not in validated_data:
|
||||
validated_data["created"] = validated_data["created_date"]
|
||||
logger.warning(
|
||||
"created_date is deprecated, use created instead",
|
||||
)
|
||||
@@ -1203,11 +1240,13 @@ class DocumentSerializer(
|
||||
for tag in instance.tags.all()
|
||||
if tag not in inbox_tags_not_being_added
|
||||
]
|
||||
|
||||
if settings.AUDIT_LOG_ENABLED:
|
||||
with set_actor(self.user):
|
||||
super().update(instance, validated_data)
|
||||
else:
|
||||
super().update(instance, validated_data)
|
||||
|
||||
# hard delete custom field instances that were soft deleted
|
||||
CustomFieldInstance.deleted_objects.filter(document=instance).delete()
|
||||
return instance
|
||||
@@ -1454,7 +1493,7 @@ class SavedViewSerializer(OwnedObjectSerializer):
|
||||
)
|
||||
)
|
||||
except serializers.ValidationError as exc:
|
||||
raise serializers.ValidationError({field_name: exc.detail}) from exc
|
||||
raise serializers.ValidationError({field_name: exc.detail})
|
||||
del normalized_data[field_name]
|
||||
|
||||
ret = super().to_internal_value(normalized_data)
|
||||
@@ -1758,7 +1797,7 @@ class BulkEditSerializer(
|
||||
logger.exception(f"Error validating custom fields: {e}")
|
||||
raise serializers.ValidationError(
|
||||
f"{name} must be a list of integers or a dict of id:value pairs, see the log for details",
|
||||
) from None
|
||||
)
|
||||
elif not isinstance(custom_fields, list) or not all(
|
||||
isinstance(i, int) for i in ids
|
||||
):
|
||||
@@ -1826,7 +1865,7 @@ class BulkEditSerializer(
|
||||
try:
|
||||
Tag.objects.get(id=tag_id)
|
||||
except Tag.DoesNotExist:
|
||||
raise serializers.ValidationError("Tag does not exist") from None
|
||||
raise serializers.ValidationError("Tag does not exist")
|
||||
else:
|
||||
raise serializers.ValidationError("tag not specified")
|
||||
|
||||
@@ -1839,9 +1878,7 @@ class BulkEditSerializer(
|
||||
try:
|
||||
DocumentType.objects.get(id=document_type_id)
|
||||
except DocumentType.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
"Document type does not exist",
|
||||
) from None
|
||||
raise serializers.ValidationError("Document type does not exist")
|
||||
else:
|
||||
raise serializers.ValidationError("document_type not specified")
|
||||
|
||||
@@ -1853,9 +1890,7 @@ class BulkEditSerializer(
|
||||
try:
|
||||
Correspondent.objects.get(id=correspondent_id)
|
||||
except Correspondent.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
"Correspondent does not exist",
|
||||
) from None
|
||||
raise serializers.ValidationError("Correspondent does not exist")
|
||||
else:
|
||||
raise serializers.ValidationError("correspondent not specified")
|
||||
|
||||
@@ -1869,7 +1904,7 @@ class BulkEditSerializer(
|
||||
except StoragePath.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
"Storage path does not exist",
|
||||
) from None
|
||||
)
|
||||
else:
|
||||
raise serializers.ValidationError("storage path not specified")
|
||||
|
||||
@@ -1924,7 +1959,7 @@ class BulkEditSerializer(
|
||||
):
|
||||
raise serializers.ValidationError("invalid rotation degrees")
|
||||
except ValueError:
|
||||
raise serializers.ValidationError("invalid rotation degrees") from None
|
||||
raise serializers.ValidationError("invalid rotation degrees")
|
||||
|
||||
def _validate_source_mode(self, parameters) -> None:
|
||||
source_mode = parameters.get(
|
||||
@@ -1954,7 +1989,7 @@ class BulkEditSerializer(
|
||||
pages.append([int(doc)])
|
||||
parameters["pages"] = pages
|
||||
except ValueError:
|
||||
raise serializers.ValidationError("invalid pages specified") from None
|
||||
raise serializers.ValidationError("invalid pages specified")
|
||||
|
||||
if "delete_originals" in parameters:
|
||||
if not isinstance(parameters["delete_originals"], bool):
|
||||
@@ -2224,14 +2259,14 @@ class PostDocumentSerializer(serializers.Serializer[dict[str, Any]]):
|
||||
raise serializers.ValidationError(
|
||||
_("Custom field id must be an integer: %(id)s")
|
||||
% {"id": field_id},
|
||||
) from None
|
||||
)
|
||||
try:
|
||||
field = CustomField.objects.get(id=field_id_int)
|
||||
except CustomField.DoesNotExist:
|
||||
raise serializers.ValidationError(
|
||||
_("Custom field with id %(id)s does not exist")
|
||||
% {"id": field_id_int},
|
||||
) from None
|
||||
)
|
||||
custom_field_serializer.validate(
|
||||
{
|
||||
"field": field,
|
||||
@@ -2248,7 +2283,7 @@ class PostDocumentSerializer(serializers.Serializer[dict[str, Any]]):
|
||||
_(
|
||||
"Custom fields must be a list of integers or an object mapping ids to values.",
|
||||
),
|
||||
) from None
|
||||
)
|
||||
if CustomField.objects.filter(id__in=ids).count() != len(set(ids)):
|
||||
raise serializers.ValidationError(
|
||||
_("Some custom fields don't exist or were specified twice."),
|
||||
@@ -2359,9 +2394,7 @@ class EmailSerializer(DocumentListSerializer):
|
||||
for address in address_list:
|
||||
email_validator(address)
|
||||
except ValidationError:
|
||||
raise serializers.ValidationError(
|
||||
f"Invalid email address: {address}",
|
||||
) from None
|
||||
raise serializers.ValidationError(f"Invalid email address: {address}")
|
||||
|
||||
return ",".join(address_list)
|
||||
|
||||
@@ -2640,18 +2673,25 @@ class RunTaskSerializer(serializers.Serializer[dict[str, str]]):
|
||||
|
||||
class AcknowledgeTasksViewSerializer(serializers.Serializer[dict[str, Any]]):
|
||||
tasks = serializers.ListField(
|
||||
required=True,
|
||||
required=False,
|
||||
label="Tasks",
|
||||
write_only=True,
|
||||
child=serializers.IntegerField(),
|
||||
)
|
||||
all = serializers.BooleanField(
|
||||
required=False,
|
||||
default=False,
|
||||
label="All",
|
||||
write_only=True,
|
||||
)
|
||||
|
||||
def _validate_task_id_list(self, tasks, name="tasks") -> None:
|
||||
if not isinstance(tasks, list):
|
||||
raise serializers.ValidationError(f"{name} must be a list")
|
||||
if not all(isinstance(i, int) for i in tasks):
|
||||
raise serializers.ValidationError(f"{name} must be a list of integers")
|
||||
count = PaperlessTask.objects.filter(id__in=tasks).count()
|
||||
queryset = self.context.get("queryset", PaperlessTask.objects.all())
|
||||
count = queryset.filter(id__in=tasks).count()
|
||||
if not count == len(tasks):
|
||||
raise serializers.ValidationError(
|
||||
f"Some tasks in {name} don't exist or were specified twice.",
|
||||
@@ -2661,6 +2701,21 @@ class AcknowledgeTasksViewSerializer(serializers.Serializer[dict[str, Any]]):
|
||||
self._validate_task_id_list(tasks)
|
||||
return tasks
|
||||
|
||||
def validate(self, attrs):
|
||||
acknowledge_all = attrs.get("all", False)
|
||||
task_ids = attrs.get("tasks")
|
||||
|
||||
if acknowledge_all and task_ids is not None:
|
||||
raise serializers.ValidationError(
|
||||
"Set either all or tasks, not both.",
|
||||
)
|
||||
if not acknowledge_all and task_ids is None:
|
||||
raise serializers.ValidationError(
|
||||
"Either all must be true or tasks must be provided.",
|
||||
)
|
||||
|
||||
return attrs
|
||||
|
||||
|
||||
class ShareLinkSerializer(OwnedObjectSerializer):
|
||||
class Meta:
|
||||
@@ -2785,7 +2840,7 @@ class ShareLinkBundleSerializer(OwnedObjectSerializer):
|
||||
return share_link_bundle
|
||||
|
||||
def get_document_count(self, obj: ShareLinkBundle) -> int:
|
||||
return obj.document_total or obj.documents.count()
|
||||
return getattr(obj, "document_total") or obj.documents.count()
|
||||
|
||||
|
||||
class BulkEditObjectsSerializer(SerializerWithPerms, SetPermissionsMixin):
|
||||
@@ -3133,7 +3188,7 @@ class WorkflowActionSerializer(serializers.ModelSerializer[WorkflowAction]):
|
||||
except (ValueError, KeyError) as e:
|
||||
raise serializers.ValidationError(
|
||||
{"assign_title": f'Invalid f-string detected: "{e.args[0]}"'},
|
||||
) from None
|
||||
)
|
||||
|
||||
if (
|
||||
"type" in attrs
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import datetime
|
||||
import hashlib
|
||||
import logging
|
||||
import shutil
|
||||
import traceback as _tb
|
||||
@@ -16,6 +15,7 @@ from celery.signals import task_postrun
|
||||
from celery.signals import task_prerun
|
||||
from celery.signals import task_revoked
|
||||
from celery.signals import worker_process_init
|
||||
from celery.signals import worker_process_shutdown
|
||||
from django.conf import settings
|
||||
from django.contrib.auth.models import Group
|
||||
from django.contrib.auth.models import User
|
||||
@@ -54,6 +54,7 @@ from documents.models import WorkflowTrigger
|
||||
from documents.permissions import get_objects_for_user_owner_aware
|
||||
from documents.plugins.helpers import DocumentsStatusManager
|
||||
from documents.templating.utils import convert_format_str_to_template_format
|
||||
from documents.utils import compute_checksum
|
||||
from documents.workflows.actions import build_workflow_action_context
|
||||
from documents.workflows.actions import execute_email_action
|
||||
from documents.workflows.actions import execute_move_to_trash_action
|
||||
@@ -410,8 +411,7 @@ def _path_matches_checksum(path: Path, checksum: str | None) -> bool:
|
||||
if checksum is None or not path.is_file():
|
||||
return False
|
||||
|
||||
with path.open("rb") as f:
|
||||
return hashlib.md5(f.read(), usedforsecurity=False).hexdigest() == checksum
|
||||
return compute_checksum(path) == checksum
|
||||
|
||||
|
||||
def _filename_template_uses_custom_fields(doc: Document) -> bool:
|
||||
@@ -1340,6 +1340,20 @@ def close_connection_pool_on_worker_init(**kwargs) -> None:
|
||||
conn.close_pool()
|
||||
|
||||
|
||||
@worker_process_shutdown.connect
|
||||
def close_connection_pool_on_worker_shutdown(**kwargs) -> None: # pragma: no cover
|
||||
"""
|
||||
Close the DB connection pool when a Celery child process exits.
|
||||
|
||||
With CELERY_WORKER_MAX_TASKS_PER_CHILD=1 each child is replaced after a
|
||||
single task. Without closing the pool on shutdown, its connections linger
|
||||
on the server until TCP keepalive reaps them, accumulating over time.
|
||||
"""
|
||||
for conn in connections.all(initialized_only=True):
|
||||
if conn.alias == "default" and hasattr(conn, "pool") and conn.pool:
|
||||
conn.close_pool()
|
||||
|
||||
|
||||
def add_or_update_document_in_llm_index(sender, document, **kwargs):
|
||||
"""
|
||||
Add or update a document in the LLM index when it is created or updated.
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
import unicodedata
|
||||
from collections.abc import Iterable
|
||||
from pathlib import PurePath
|
||||
|
||||
@@ -36,10 +37,12 @@ class FilePathTemplate(Template):
|
||||
def clean_filepath(value: str) -> str:
|
||||
"""
|
||||
Clean up a filepath by:
|
||||
1. Removing newlines and carriage returns
|
||||
2. Removing extra spaces before and after forward slashes
|
||||
3. Preserving spaces in other parts of the path
|
||||
1. Normalizing Unicode to NFC form to prevent byte-level mismatches
|
||||
2. Removing newlines and carriage returns
|
||||
3. Removing extra spaces before and after forward slashes
|
||||
4. Preserving spaces in other parts of the path
|
||||
"""
|
||||
value = unicodedata.normalize("NFC", value)
|
||||
value = value.replace("\n", "").replace("\r", "")
|
||||
value = re.sub(r"\s*/\s*", "/", value)
|
||||
|
||||
@@ -181,17 +184,17 @@ def get_basic_metadata_context(
|
||||
"""
|
||||
return {
|
||||
"title": pathvalidate.sanitize_filename(
|
||||
document.title,
|
||||
unicodedata.normalize("NFC", document.title),
|
||||
replacement_text="-",
|
||||
),
|
||||
"correspondent": pathvalidate.sanitize_filename(
|
||||
document.correspondent.name,
|
||||
unicodedata.normalize("NFC", document.correspondent.name),
|
||||
replacement_text="-",
|
||||
)
|
||||
if document.correspondent
|
||||
else no_value_default,
|
||||
"document_type": pathvalidate.sanitize_filename(
|
||||
document.document_type.name,
|
||||
unicodedata.normalize("NFC", document.document_type.name),
|
||||
replacement_text="-",
|
||||
)
|
||||
if document.document_type
|
||||
@@ -202,7 +205,10 @@ def get_basic_metadata_context(
|
||||
"owner_username": document.owner.username
|
||||
if document.owner
|
||||
else no_value_default,
|
||||
"original_name": PurePath(document.original_filename).with_suffix("").name
|
||||
"original_name": unicodedata.normalize(
|
||||
"NFC",
|
||||
PurePath(document.original_filename).with_suffix("").name,
|
||||
)
|
||||
if document.original_filename
|
||||
else no_value_default,
|
||||
"doc_pk": f"{document.pk:07}",
|
||||
@@ -269,12 +275,12 @@ def get_tags_context(tags: Iterable[Tag]) -> dict[str, str | list[str]]:
|
||||
return {
|
||||
"tag_list": pathvalidate.sanitize_filename(
|
||||
",".join(
|
||||
sorted(tag.name for tag in tags),
|
||||
sorted(unicodedata.normalize("NFC", 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": [x.name for x in tags],
|
||||
"tag_name_list": [unicodedata.normalize("NFC", x.name) for x in tags],
|
||||
}
|
||||
|
||||
|
||||
@@ -301,7 +307,7 @@ def get_custom_fields_context(
|
||||
CustomField.FieldDataType.LONG_TEXT,
|
||||
}:
|
||||
value = pathvalidate.sanitize_filename(
|
||||
field_instance.value,
|
||||
unicodedata.normalize("NFC", field_instance.value),
|
||||
replacement_text="-",
|
||||
)
|
||||
elif (
|
||||
@@ -310,10 +316,13 @@ def get_custom_fields_context(
|
||||
):
|
||||
options = field_instance.field.extra_data["select_options"]
|
||||
value = pathvalidate.sanitize_filename(
|
||||
next(
|
||||
option["label"]
|
||||
for option in options
|
||||
if option["id"] == field_instance.value
|
||||
unicodedata.normalize(
|
||||
"NFC",
|
||||
next(
|
||||
option["label"]
|
||||
for option in options
|
||||
if option["id"] == field_instance.value
|
||||
),
|
||||
),
|
||||
replacement_text="-",
|
||||
)
|
||||
@@ -321,7 +330,7 @@ def get_custom_fields_context(
|
||||
value = field_instance.value
|
||||
field_data["custom_fields"][
|
||||
pathvalidate.sanitize_filename(
|
||||
field_instance.field.name,
|
||||
unicodedata.normalize("NFC", field_instance.field.name),
|
||||
replacement_text="-",
|
||||
)
|
||||
] = {
|
||||
|
||||
@@ -29,7 +29,9 @@ class SimpleCommand(PaperlessCommand):
|
||||
|
||||
def handle(self, *args, **options):
|
||||
items = list(range(5))
|
||||
results = [item * 2 for item in self.track(items, description="Processing...")]
|
||||
results = []
|
||||
for item in self.track(items, description="Processing..."):
|
||||
results.append(item * 2)
|
||||
self.stdout.write(f"Results: {results}")
|
||||
|
||||
|
||||
@@ -55,13 +57,13 @@ class MultiprocessCommand(PaperlessCommand):
|
||||
|
||||
def handle(self, *args, **options):
|
||||
items = list(range(5))
|
||||
results = list(
|
||||
self.process_parallel(
|
||||
_double_value,
|
||||
items,
|
||||
description="Processing...",
|
||||
),
|
||||
)
|
||||
results = []
|
||||
for result in self.process_parallel(
|
||||
_double_value,
|
||||
items,
|
||||
description="Processing...",
|
||||
):
|
||||
results.append(result)
|
||||
successes = sum(1 for r in results if r.success)
|
||||
self.stdout.write(f"Successes: {successes}")
|
||||
|
||||
|
||||
@@ -0,0 +1,36 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from django.core.management import call_command
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from pytest_mock import MockerFixture
|
||||
|
||||
_COMPACT = "documents.management.commands.document_llmindex.llm_index_compact"
|
||||
_INDEX = "documents.management.commands.document_llmindex.llmindex_index"
|
||||
|
||||
|
||||
class TestDocumentLlmindexCommand:
|
||||
def test_compact_calls_llm_index_compact(self, mocker: MockerFixture) -> None:
|
||||
mock_compact = mocker.patch(_COMPACT)
|
||||
call_command("document_llmindex", "compact")
|
||||
mock_compact.assert_called_once_with()
|
||||
|
||||
def test_rebuild_calls_llmindex_index_with_rebuild_true(
|
||||
self,
|
||||
mocker: MockerFixture,
|
||||
) -> None:
|
||||
mock_index = mocker.patch(_INDEX)
|
||||
call_command("document_llmindex", "rebuild")
|
||||
mock_index.assert_called_once()
|
||||
assert mock_index.call_args.kwargs["rebuild"] is True
|
||||
|
||||
def test_update_calls_llmindex_index_with_rebuild_false(
|
||||
self,
|
||||
mocker: MockerFixture,
|
||||
) -> None:
|
||||
mock_index = mocker.patch(_INDEX)
|
||||
call_command("document_llmindex", "update")
|
||||
mock_index.assert_called_once()
|
||||
assert mock_index.call_args.kwargs["rebuild"] is False
|
||||
@@ -1,11 +1,15 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import tempfile
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
import pytest
|
||||
import tantivy
|
||||
|
||||
from documents.search._backend import TantivyBackend
|
||||
from documents.search._backend import reset_backend
|
||||
from documents.search._schema import build_schema
|
||||
from documents.search._tokenizer import register_tokenizers
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from collections.abc import Generator
|
||||
@@ -31,3 +35,11 @@ def backend() -> Generator[TantivyBackend, None, None]:
|
||||
finally:
|
||||
b.close()
|
||||
reset_backend()
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def index() -> tantivy.Index:
|
||||
"""A real Tantivy index for parse-acceptance tests (module scope for speed)."""
|
||||
idx = tantivy.Index(build_schema(), path=tempfile.mkdtemp())
|
||||
register_tokenizers(idx, "english")
|
||||
return idx
|
||||
|
||||
@@ -11,16 +11,15 @@ import pytest
|
||||
import tantivy
|
||||
import time_machine
|
||||
|
||||
from documents.search._query import _date_only_range
|
||||
from documents.search._query import _datetime_range
|
||||
from documents.search._query import _rewrite_compact_date
|
||||
from documents.search._dates import _date_only_range
|
||||
from documents.search._dates import _datetime_range
|
||||
from documents.search._query import build_permission_filter
|
||||
from documents.search._query import normalize_query
|
||||
from documents.search._query import parse_simple_text_highlight_query
|
||||
from documents.search._query import parse_user_query
|
||||
from documents.search._query import rewrite_natural_date_keywords
|
||||
from documents.search._schema import build_schema
|
||||
from documents.search._tokenizer import register_tokenizers
|
||||
from documents.search._translate import InvalidDateQuery
|
||||
from documents.search._translate import translate_query
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from django.contrib.auth.base_user import AbstractBaseUser
|
||||
@@ -57,7 +56,7 @@ class TestCreatedDateField:
|
||||
)
|
||||
@time_machine.travel(datetime(2026, 3, 28, 15, 30, tzinfo=UTC), tick=False)
|
||||
def test_today(self, tz: tzinfo, expected_lo: str, expected_hi: str) -> None:
|
||||
lo, hi = _range(rewrite_natural_date_keywords("created:today", tz), "created")
|
||||
lo, hi = _range(translate_query("created:today", tz), "created")
|
||||
assert lo == expected_lo
|
||||
assert hi == expected_hi
|
||||
|
||||
@@ -65,7 +64,7 @@ class TestCreatedDateField:
|
||||
def test_today_auckland_ahead_of_utc(self) -> None:
|
||||
# UTC 03:00 -> Auckland (UTC+13) = 16:00 same date; local date = 2026-03-28
|
||||
lo, _ = _range(
|
||||
rewrite_natural_date_keywords("created:today", AUCKLAND),
|
||||
translate_query("created:today", AUCKLAND),
|
||||
"created",
|
||||
)
|
||||
assert lo == "2026-03-28T00:00:00Z"
|
||||
@@ -127,7 +126,7 @@ class TestCreatedDateField:
|
||||
) -> None:
|
||||
# 2026-03-28 is Saturday; Mon-Sun week calculation built into expectations
|
||||
query = f"{field}:{keyword}"
|
||||
lo, hi = _range(rewrite_natural_date_keywords(query, UTC), field)
|
||||
lo, hi = _range(translate_query(query, UTC), field)
|
||||
assert lo == expected_lo
|
||||
assert hi == expected_hi
|
||||
|
||||
@@ -135,7 +134,7 @@ class TestCreatedDateField:
|
||||
def test_this_month_december_wraps_to_next_year(self) -> None:
|
||||
# December: next month must roll over to January 1 of next year
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("created:this month", UTC),
|
||||
translate_query("created:this month", UTC),
|
||||
"created",
|
||||
)
|
||||
assert lo == "2026-12-01T00:00:00Z"
|
||||
@@ -145,7 +144,7 @@ class TestCreatedDateField:
|
||||
def test_last_month_january_wraps_to_previous_year(self) -> None:
|
||||
# January: last month must roll back to December 1 of previous year
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("created:previous month", UTC),
|
||||
translate_query("created:previous month", UTC),
|
||||
"created",
|
||||
)
|
||||
assert lo == "2025-12-01T00:00:00Z"
|
||||
@@ -154,7 +153,7 @@ class TestCreatedDateField:
|
||||
@time_machine.travel(datetime(2026, 7, 15, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_previous_quarter(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords('created:"previous quarter"', UTC),
|
||||
translate_query('created:"previous quarter"', UTC),
|
||||
"created",
|
||||
)
|
||||
assert lo == "2026-04-01T00:00:00Z"
|
||||
@@ -174,7 +173,7 @@ class TestDateTimeFields:
|
||||
@time_machine.travel(datetime(2026, 3, 28, 15, 30, tzinfo=UTC), tick=False)
|
||||
def test_added_today_eastern(self) -> None:
|
||||
# EDT = UTC-4; local midnight 2026-03-28 00:00 EDT = 2026-03-28 04:00 UTC
|
||||
lo, hi = _range(rewrite_natural_date_keywords("added:today", EASTERN), "added")
|
||||
lo, hi = _range(translate_query("added:today", EASTERN), "added")
|
||||
assert lo == "2026-03-28T04:00:00Z"
|
||||
assert hi == "2026-03-29T04:00:00Z"
|
||||
|
||||
@@ -182,14 +181,14 @@ class TestDateTimeFields:
|
||||
def test_added_today_auckland_midnight_crossing(self) -> None:
|
||||
# UTC 02:00 on 2026-03-29 -> Auckland (UTC+13) = 2026-03-29 15:00 local
|
||||
# Auckland midnight = UTC 2026-03-28 11:00
|
||||
lo, hi = _range(rewrite_natural_date_keywords("added:today", AUCKLAND), "added")
|
||||
lo, hi = _range(translate_query("added:today", AUCKLAND), "added")
|
||||
assert lo == "2026-03-28T11:00:00Z"
|
||||
assert hi == "2026-03-29T11:00:00Z"
|
||||
|
||||
@time_machine.travel(datetime(2026, 3, 28, 15, 0, tzinfo=UTC), tick=False)
|
||||
def test_modified_today_utc(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("modified:today", UTC),
|
||||
translate_query("modified:today", UTC),
|
||||
"modified",
|
||||
)
|
||||
assert lo == "2026-03-28T00:00:00Z"
|
||||
@@ -244,14 +243,14 @@ class TestDateTimeFields:
|
||||
expected_hi: str,
|
||||
) -> None:
|
||||
# 2026-03-28 is Saturday; weekday()==5 so Monday=2026-03-23
|
||||
lo, hi = _range(rewrite_natural_date_keywords(f"added:{keyword}", UTC), "added")
|
||||
lo, hi = _range(translate_query(f"added:{keyword}", UTC), "added")
|
||||
assert lo == expected_lo
|
||||
assert hi == expected_hi
|
||||
|
||||
@time_machine.travel(datetime(2026, 12, 15, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_this_month_december_wraps_to_next_year(self) -> None:
|
||||
# December: next month wraps to January of next year
|
||||
lo, hi = _range(rewrite_natural_date_keywords("added:this month", UTC), "added")
|
||||
lo, hi = _range(translate_query("added:this month", UTC), "added")
|
||||
assert lo == "2026-12-01T00:00:00Z"
|
||||
assert hi == "2027-01-01T00:00:00Z"
|
||||
|
||||
@@ -259,7 +258,7 @@ class TestDateTimeFields:
|
||||
def test_last_month_january_wraps_to_previous_year(self) -> None:
|
||||
# January: last month wraps back to December of previous year
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("added:previous month", UTC),
|
||||
translate_query("added:previous month", UTC),
|
||||
"added",
|
||||
)
|
||||
assert lo == "2025-12-01T00:00:00Z"
|
||||
@@ -295,7 +294,7 @@ class TestDateTimeFields:
|
||||
expected_lo: str,
|
||||
expected_hi: str,
|
||||
) -> None:
|
||||
lo, hi = _range(rewrite_natural_date_keywords(query, UTC), "added")
|
||||
lo, hi = _range(translate_query(query, UTC), "added")
|
||||
assert lo == expected_lo
|
||||
assert hi == expected_hi
|
||||
|
||||
@@ -309,20 +308,20 @@ class TestWhooshQueryRewriting:
|
||||
|
||||
@time_machine.travel(datetime(2026, 3, 28, 15, 0, tzinfo=UTC), tick=False)
|
||||
def test_compact_date_shim_rewrites_to_iso(self) -> None:
|
||||
result = rewrite_natural_date_keywords("created:20240115120000", UTC)
|
||||
result = translate_query("created:20240115120000", UTC)
|
||||
assert "2024-01-15" in result
|
||||
assert "20240115120000" not in result
|
||||
|
||||
@time_machine.travel(datetime(2026, 3, 28, 15, 0, tzinfo=UTC), tick=False)
|
||||
def test_relative_range_shim_removes_now(self) -> None:
|
||||
result = rewrite_natural_date_keywords("added:[now-7d TO now]", UTC)
|
||||
result = translate_query("added:[now-7d TO now]", UTC)
|
||||
assert "now" not in result
|
||||
assert "2026-03-" in result
|
||||
|
||||
@time_machine.travel(datetime(2026, 3, 28, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_bracket_minus_7_days(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("added:[-7 days to now]", UTC),
|
||||
translate_query("added:[-7 days to now]", UTC),
|
||||
"added",
|
||||
)
|
||||
assert lo == "2026-03-21T12:00:00Z"
|
||||
@@ -331,7 +330,7 @@ class TestWhooshQueryRewriting:
|
||||
@time_machine.travel(datetime(2026, 3, 28, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_bracket_minus_1_week(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("added:[-1 week to now]", UTC),
|
||||
translate_query("added:[-1 week to now]", UTC),
|
||||
"added",
|
||||
)
|
||||
assert lo == "2026-03-21T12:00:00Z"
|
||||
@@ -341,7 +340,7 @@ class TestWhooshQueryRewriting:
|
||||
def test_bracket_minus_1_month_uses_relativedelta(self) -> None:
|
||||
# relativedelta(months=1) from 2026-03-28 = 2026-02-28 (not 29)
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("created:[-1 month to now]", UTC),
|
||||
translate_query("created:[-1 month to now]", UTC),
|
||||
"created",
|
||||
)
|
||||
assert lo == "2026-02-28T12:00:00Z"
|
||||
@@ -350,7 +349,7 @@ class TestWhooshQueryRewriting:
|
||||
@time_machine.travel(datetime(2026, 3, 28, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_bracket_minus_1_year(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("modified:[-1 year to now]", UTC),
|
||||
translate_query("modified:[-1 year to now]", UTC),
|
||||
"modified",
|
||||
)
|
||||
assert lo == "2025-03-28T12:00:00Z"
|
||||
@@ -359,7 +358,7 @@ class TestWhooshQueryRewriting:
|
||||
@time_machine.travel(datetime(2026, 3, 28, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_bracket_plural_unit_hours(self) -> None:
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("added:[-3 hours to now]", UTC),
|
||||
translate_query("added:[-3 hours to now]", UTC),
|
||||
"added",
|
||||
)
|
||||
assert lo == "2026-03-28T09:00:00Z"
|
||||
@@ -367,7 +366,7 @@ class TestWhooshQueryRewriting:
|
||||
|
||||
@time_machine.travel(datetime(2026, 3, 28, 12, 0, tzinfo=UTC), tick=False)
|
||||
def test_bracket_case_insensitive(self) -> None:
|
||||
result = rewrite_natural_date_keywords("added:[-1 WEEK TO NOW]", UTC)
|
||||
result = translate_query("added:[-1 WEEK TO NOW]", UTC)
|
||||
assert "now" not in result.lower()
|
||||
lo, hi = _range(result, "added")
|
||||
assert lo == "2026-03-21T12:00:00Z"
|
||||
@@ -377,7 +376,7 @@ class TestWhooshQueryRewriting:
|
||||
def test_relative_range_swaps_bounds_when_lo_exceeds_hi(self) -> None:
|
||||
# [now+1h TO now-1h] has lo > hi before substitution; they must be swapped
|
||||
lo, hi = _range(
|
||||
rewrite_natural_date_keywords("added:[now+1h TO now-1h]", UTC),
|
||||
translate_query("added:[now+1h TO now-1h]", UTC),
|
||||
"added",
|
||||
)
|
||||
assert lo == "2026-03-28T11:00:00Z"
|
||||
@@ -385,14 +384,14 @@ class TestWhooshQueryRewriting:
|
||||
|
||||
def test_8digit_created_date_field_always_uses_utc_midnight(self) -> None:
|
||||
# created is a DateField: boundaries are always UTC midnight, no TZ offset
|
||||
result = rewrite_natural_date_keywords("created:20231201", EASTERN)
|
||||
result = translate_query("created:20231201", EASTERN)
|
||||
lo, hi = _range(result, "created")
|
||||
assert lo == "2023-12-01T00:00:00Z"
|
||||
assert hi == "2023-12-02T00:00:00Z"
|
||||
|
||||
def test_8digit_added_datetime_field_converts_local_midnight_to_utc(self) -> None:
|
||||
# added is DateTimeField: midnight Dec 1 Eastern (EST = UTC-5) = 05:00 UTC
|
||||
result = rewrite_natural_date_keywords("added:20231201", EASTERN)
|
||||
result = translate_query("added:20231201", EASTERN)
|
||||
lo, hi = _range(result, "added")
|
||||
assert lo == "2023-12-01T05:00:00Z"
|
||||
assert hi == "2023-12-02T05:00:00Z"
|
||||
@@ -400,17 +399,19 @@ class TestWhooshQueryRewriting:
|
||||
def test_8digit_modified_datetime_field_converts_local_midnight_to_utc(
|
||||
self,
|
||||
) -> None:
|
||||
result = rewrite_natural_date_keywords("modified:20231201", EASTERN)
|
||||
result = translate_query("modified:20231201", EASTERN)
|
||||
lo, hi = _range(result, "modified")
|
||||
assert lo == "2023-12-01T05:00:00Z"
|
||||
assert hi == "2023-12-02T05:00:00Z"
|
||||
|
||||
def test_8digit_invalid_date_passes_through_unchanged(self) -> None:
|
||||
assert rewrite_natural_date_keywords("added:20231340", UTC) == "added:20231340"
|
||||
|
||||
def test_compact_14digit_invalid_date_passes_through_unchanged(self) -> None:
|
||||
# Month=13 makes datetime() raise ValueError; the token must be left as-is
|
||||
assert _rewrite_compact_date("20231300120000") == "20231300120000"
|
||||
def test_8digit_invalid_date_raises(self) -> None:
|
||||
# The translation pipeline raises InvalidDateQuery for unparsable dates
|
||||
# (e.g. month=13) so the API can surface a 400 telling the user the date
|
||||
# is malformed instead of silently returning zero results.
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_query("added:20231340", UTC)
|
||||
assert exc_info.value.field == "added"
|
||||
assert exc_info.value.value == "20231340"
|
||||
|
||||
|
||||
class TestParseUserQuery:
|
||||
@@ -463,6 +464,67 @@ class TestParseUserQuery:
|
||||
) -> None:
|
||||
assert isinstance(parse_user_query(query_index, raw_query, UTC), tantivy.Query)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"raw_query",
|
||||
[
|
||||
# Partial date scalar (year only)
|
||||
pytest.param("created:2020", id="created_year_scalar"),
|
||||
# 8-digit compact date range in brackets
|
||||
pytest.param(
|
||||
"created:[20200101 TO 20201231]",
|
||||
id="created_8digit_bracket_range",
|
||||
),
|
||||
# Comma-separated field + date range (Whoosh v2 multi-clause syntax)
|
||||
pytest.param(
|
||||
"title:x,created:[2020 TO 2021]",
|
||||
id="title_comma_created_range",
|
||||
),
|
||||
# Field alias: type -> document_type
|
||||
pytest.param("type:invoice", id="type_alias"),
|
||||
# Multi-word date keyword
|
||||
pytest.param("created:previous week", id="created_previous_week"),
|
||||
# Full ISO datetime range
|
||||
pytest.param(
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z]",
|
||||
id="created_iso_range",
|
||||
),
|
||||
# Comma-separated ISO ranges (Whoosh v2 syntax)
|
||||
pytest.param(
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z],"
|
||||
"added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]",
|
||||
id="comma_iso_ranges",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_advanced_search_queries_do_not_raise(
|
||||
self,
|
||||
query_index: tantivy.Index,
|
||||
raw_query: str,
|
||||
) -> None:
|
||||
"""
|
||||
End-to-end: queries that the frontend sends must parse without raising.
|
||||
|
||||
This tests the full pipeline: translate_query -> tantivy parse_query.
|
||||
Equivalent to asserting HTTP 200 (not 400) for each query form.
|
||||
"""
|
||||
with time_machine.travel(datetime(2026, 6, 15, 12, 0, tzinfo=UTC), tick=False):
|
||||
assert isinstance(
|
||||
parse_user_query(query_index, raw_query, UTC),
|
||||
tantivy.Query,
|
||||
)
|
||||
|
||||
def test_invalid_date_propagates_not_swallowed(
|
||||
self,
|
||||
query_index: tantivy.Index,
|
||||
) -> None:
|
||||
# parse_user_query falls back to the raw query on unexpected translation
|
||||
# errors, but an InvalidDateQuery is intentional and must propagate so the
|
||||
# view can return a 400 instead of silently parsing the raw (invalid) date.
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
parse_user_query(query_index, "created:202023", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "202023"
|
||||
|
||||
|
||||
class TestYearRangeRewriting:
|
||||
"""Whoosh-style year-only date ranges must be rewritten to ISO 8601."""
|
||||
@@ -514,7 +576,7 @@ class TestYearRangeRewriting:
|
||||
expected_lo: str,
|
||||
expected_hi: str,
|
||||
) -> None:
|
||||
result = rewrite_natural_date_keywords(query, UTC)
|
||||
result = translate_query(query, UTC)
|
||||
lo, hi = _range(result, field)
|
||||
assert lo == expected_lo
|
||||
assert hi == expected_hi
|
||||
@@ -522,14 +584,14 @@ class TestYearRangeRewriting:
|
||||
def test_reversed_year_range_is_swapped(self) -> None:
|
||||
# A reversed range must not yield lo > hi, which Tantivy treats as an
|
||||
# empty range (silently zero results). The bounds are swapped instead.
|
||||
result = rewrite_natural_date_keywords("created:[2025 TO 2020]", UTC)
|
||||
result = translate_query("created:[2025 TO 2020]", UTC)
|
||||
lo, hi = _range(result, "created")
|
||||
assert lo == "2020-01-01T00:00:00Z"
|
||||
assert hi == "2026-01-01T00:00:00Z"
|
||||
|
||||
def test_year_range_in_complex_boolean_query(self) -> None:
|
||||
query = "tag:steuer AND (title:2020 OR (NOT title:2019 AND NOT title:2018 AND created:[2020 TO 2020]))"
|
||||
result = rewrite_natural_date_keywords(query, UTC)
|
||||
result = translate_query(query, UTC)
|
||||
lo, hi = _range(result, "created")
|
||||
assert lo == "2020-01-01T00:00:00Z"
|
||||
assert hi == "2021-01-01T00:00:00Z"
|
||||
@@ -539,14 +601,19 @@ class TestYearRangeRewriting:
|
||||
|
||||
def test_already_iso_date_range_passes_through_unchanged(self) -> None:
|
||||
original = "created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]"
|
||||
assert rewrite_natural_date_keywords(original, UTC) == original
|
||||
assert translate_query(original, UTC) == original
|
||||
|
||||
def test_8digit_in_brackets_not_matched_as_year_range(self) -> None:
|
||||
# [YYYYMMDD TO YYYYMMDD] has 8-digit values - must not be caught by year rewriter
|
||||
# [YYYYMMDD TO YYYYMMDD]: the translation layer converts 8-digit bounds to
|
||||
# ISO day ranges. 20200101 -> 2020-01-01T00:00:00Z (lo of that day);
|
||||
# 20201231 -> the ceil of Dec 31 = 2021-01-01T00:00:00Z (exclusive end).
|
||||
# This is the correct and accepted behavior: old compact form becomes a
|
||||
# proper Tantivy-parseable ISO range.
|
||||
original = "created:[20200101 TO 20201231]"
|
||||
result = rewrite_natural_date_keywords(original, UTC)
|
||||
assert "20200101" in result or "2020-01-01" in result
|
||||
assert "20201231" in result or "2020-12-31" in result
|
||||
result = translate_query(original, UTC)
|
||||
lo, hi = _range(result, "created")
|
||||
assert lo == "2020-01-01T00:00:00Z"
|
||||
assert hi == "2021-01-01T00:00:00Z"
|
||||
|
||||
|
||||
class TestNonDateFieldsNotRewritten:
|
||||
@@ -566,7 +633,7 @@ class TestNonDateFieldsNotRewritten:
|
||||
],
|
||||
)
|
||||
def test_8digit_on_integer_field_passes_through_unchanged(self, query: str) -> None:
|
||||
assert rewrite_natural_date_keywords(query, EASTERN) == query
|
||||
assert translate_query(query, EASTERN) == query
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"query",
|
||||
@@ -580,12 +647,12 @@ class TestNonDateFieldsNotRewritten:
|
||||
self,
|
||||
query: str,
|
||||
) -> None:
|
||||
assert rewrite_natural_date_keywords(query, UTC) == query
|
||||
assert translate_query(query, UTC) == query
|
||||
|
||||
def test_unknown_field_keyword_passes_through_unchanged(self) -> None:
|
||||
# foobar is not a date field: 'foobar:today' must not become a date range,
|
||||
# which Tantivy would otherwise reject as an unknown/typed field.
|
||||
assert rewrite_natural_date_keywords("foobar:today", UTC) == "foobar:today"
|
||||
assert translate_query("foobar:today", UTC) == "foobar:today"
|
||||
|
||||
|
||||
class TestPassthrough:
|
||||
@@ -593,27 +660,39 @@ class TestPassthrough:
|
||||
|
||||
def test_bare_keyword_no_field_prefix_unchanged(self) -> None:
|
||||
# Bare 'today' with no field: prefix passes through unchanged
|
||||
result = rewrite_natural_date_keywords("bank statement today", UTC)
|
||||
result = translate_query("bank statement today", UTC)
|
||||
assert "today" in result
|
||||
|
||||
def test_unrelated_query_unchanged(self) -> None:
|
||||
assert rewrite_natural_date_keywords("title:invoice", UTC) == "title:invoice"
|
||||
assert translate_query("title:invoice", UTC) == "title:invoice"
|
||||
|
||||
|
||||
class TestNormalizeQuery:
|
||||
"""normalize_query expands comma-separated values and collapses whitespace."""
|
||||
"""translate_query expands comma-separated values and collapses whitespace."""
|
||||
|
||||
def test_normalize_expands_comma_separated_tags(self) -> None:
|
||||
assert normalize_query("tag:foo,bar") == "tag:foo AND tag:bar"
|
||||
assert translate_query("tag:foo,bar", UTC) == "tag:foo AND tag:bar"
|
||||
|
||||
def test_normalize_comma_between_range_expressions(self) -> None:
|
||||
# Comma-separated field range expressions (Whoosh v2 syntax) must be
|
||||
# converted to AND so Tantivy does not receive an invalid comma.
|
||||
q = "created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z],added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
assert translate_query(q, UTC) == (
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
" AND "
|
||||
"added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
)
|
||||
|
||||
def test_normalize_expands_three_values(self) -> None:
|
||||
assert normalize_query("tag:foo,bar,baz") == "tag:foo AND tag:bar AND tag:baz"
|
||||
assert (
|
||||
translate_query("tag:foo,bar,baz", UTC) == "tag:foo AND tag:bar AND tag:baz"
|
||||
)
|
||||
|
||||
def test_normalize_collapses_whitespace(self) -> None:
|
||||
assert normalize_query("bank statement") == "bank statement"
|
||||
assert translate_query("bank statement", UTC) == "bank statement"
|
||||
|
||||
def test_normalize_no_commas_unchanged(self) -> None:
|
||||
assert normalize_query("bank statement") == "bank statement"
|
||||
assert translate_query("bank statement", UTC) == "bank statement"
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("raw", "expected"),
|
||||
@@ -656,7 +735,7 @@ class TestNormalizeQuery:
|
||||
],
|
||||
)
|
||||
def test_normalize_strips_dangling_operators(self, raw: str, expected: str) -> None:
|
||||
assert normalize_query(raw) == expected
|
||||
assert translate_query(raw, UTC) == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"query",
|
||||
@@ -668,7 +747,7 @@ class TestNormalizeQuery:
|
||||
],
|
||||
)
|
||||
def test_normalize_preserves_valid_operators(self, query: str) -> None:
|
||||
assert normalize_query(query) == query
|
||||
assert translate_query(query, UTC) == query
|
||||
|
||||
|
||||
class TestParseSimpleTextHighlightQuery:
|
||||
|
||||
@@ -0,0 +1,742 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC
|
||||
from datetime import datetime
|
||||
from typing import TYPE_CHECKING
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
import pytest
|
||||
import time_machine
|
||||
|
||||
from documents.search._dates import _precision_bounds
|
||||
|
||||
if TYPE_CHECKING:
|
||||
import tantivy
|
||||
from documents.search._query import _FIELD_BOOSTS
|
||||
from documents.search._query import DEFAULT_SEARCH_FIELDS
|
||||
from documents.search._translate import OPEN_HI
|
||||
from documents.search._translate import OPEN_LO
|
||||
from documents.search._translate import Comma
|
||||
from documents.search._translate import FieldRange
|
||||
from documents.search._translate import FieldValue
|
||||
from documents.search._translate import FieldValueList
|
||||
from documents.search._translate import InvalidDateQuery
|
||||
from documents.search._translate import Passthrough
|
||||
from documents.search._translate import resolve_commas
|
||||
from documents.search._translate import scan
|
||||
from documents.search._translate import translate_query
|
||||
from documents.search._translate import translate_range
|
||||
from documents.search._translate import translate_scalar
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestPrecisionBounds:
|
||||
@pytest.mark.parametrize(
|
||||
("digits", "expected"),
|
||||
[
|
||||
("2020", ((2020, 1, 1), (2021, 1, 1))),
|
||||
("202003", ((2020, 3, 1), (2020, 4, 1))),
|
||||
("202012", ((2020, 12, 1), (2021, 1, 1))),
|
||||
("20200115", ((2020, 1, 15), (2020, 1, 16))),
|
||||
("20201231", ((2020, 12, 31), (2021, 1, 1))),
|
||||
],
|
||||
)
|
||||
def test_valid(self, digits, expected):
|
||||
lo, hi = _precision_bounds(digits)
|
||||
assert (lo.year, lo.month, lo.day) == expected[0]
|
||||
assert (hi.year, hi.month, hi.day) == expected[1]
|
||||
|
||||
@pytest.mark.parametrize("digits", ["202023", "20200230", "20201301", "20", "abcd"])
|
||||
def test_invalid_returns_none(self, digits):
|
||||
assert _precision_bounds(digits) is None
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestScan:
|
||||
def test_plain_words_are_passthrough(self):
|
||||
assert scan("bank statement") == [Passthrough("bank statement")]
|
||||
|
||||
def test_field_value(self):
|
||||
assert scan("created:2020") == [FieldValue("created", "2020")]
|
||||
|
||||
def test_field_value_in_boolean(self):
|
||||
toks = scan("created:2020 OR foo")
|
||||
assert toks == [
|
||||
FieldValue("created", "2020"),
|
||||
Passthrough(" OR foo"),
|
||||
]
|
||||
|
||||
def test_field_value_in_parens(self):
|
||||
toks = scan("(created:2020 OR foo)")
|
||||
assert toks == [
|
||||
Passthrough("("),
|
||||
FieldValue("created", "2020"),
|
||||
Passthrough(" OR foo)"),
|
||||
]
|
||||
|
||||
def test_quoted_value(self):
|
||||
assert scan('correspondent:"A B"') == [FieldValue("correspondent", '"A B"')]
|
||||
|
||||
def test_field_range(self):
|
||||
assert scan("created:[2020 TO 2021]") == [
|
||||
FieldRange("created", "[", "2020", "2021", "]"),
|
||||
]
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("query", "expected"),
|
||||
[
|
||||
pytest.param(
|
||||
"created:[2020 to]",
|
||||
FieldRange("created", "[", "2020", "", "]"),
|
||||
id="open_upper",
|
||||
),
|
||||
pytest.param(
|
||||
"created:[to 2020]",
|
||||
FieldRange("created", "[", "", "2020", "]"),
|
||||
id="open_lower",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_open_range(self, query, expected):
|
||||
assert scan(query) == [expected]
|
||||
|
||||
def test_comma_inside_range_not_split(self):
|
||||
# No depth-0 comma here; the whole thing is one range token.
|
||||
toks = scan("created:[2020 TO 2021]")
|
||||
assert len(toks) == 1
|
||||
|
||||
# --- Edge-case / regression tests (scan must never raise) ---
|
||||
|
||||
def test_url_is_passthrough(self):
|
||||
# "http" is not a known field; the whole URL must pass through verbatim.
|
||||
assert scan("http://example.com") == [Passthrough("http://example.com")]
|
||||
|
||||
def test_unterminated_quote_is_passthrough(self):
|
||||
# title is a known field but the quoted value has no closing quote;
|
||||
# _consume_value returns None so the whole string falls into passthrough.
|
||||
assert scan('title:"abc') == [Passthrough('title:"abc')]
|
||||
|
||||
def test_unterminated_bracket_is_passthrough(self):
|
||||
# created is a known field but the range bracket is never closed;
|
||||
# _consume_range returns None so the whole string falls into passthrough.
|
||||
assert scan("created:[2020") == [Passthrough("created:[2020")]
|
||||
|
||||
def test_empty_value_at_end_is_passthrough(self):
|
||||
# created is a known field but there is no value after the colon
|
||||
# (_consume_value returns None for start >= n), so passthrough.
|
||||
assert scan("created:") == [Passthrough("created:")]
|
||||
|
||||
def test_value_containing_colon(self):
|
||||
# The bare-word value reader stops at whitespace/paren, not at colon,
|
||||
# so "2020:30" is consumed as a single value token.
|
||||
assert scan("created:2020:30") == [FieldValue("created", "2020:30")]
|
||||
|
||||
def test_comma_followed_by_unconsumable_value_stops(self):
|
||||
# A comma followed by whitespace is neither a value-list continuation nor a
|
||||
# clause separator: the value stops and the comma stays as passthrough.
|
||||
assert scan("tag:foo, bar") == [
|
||||
FieldValue("tag", "foo"),
|
||||
Passthrough(", bar"),
|
||||
]
|
||||
|
||||
def test_bracket_without_to_is_open_upper_bound(self):
|
||||
# A bracketed value with no TO falls back to (value, "") -> open upper bound.
|
||||
assert scan("created:[2020]") == [
|
||||
FieldRange("created", "[", "2020", "", "]"),
|
||||
]
|
||||
|
||||
def test_known_field_name_midword_is_passthrough(self):
|
||||
# A known field name embedded mid-word is not a field token (the
|
||||
# word-boundary guard); the whole run stays passthrough.
|
||||
assert scan("xtag:foo") == [Passthrough("xtag:foo")]
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestCommaResolution:
|
||||
def test_value_list_multi_value_field(self):
|
||||
toks = resolve_commas(scan("tag:foo,bar"))
|
||||
assert toks == [FieldValueList("tag", ("foo", "bar"))]
|
||||
|
||||
def test_value_list_three(self):
|
||||
toks = resolve_commas(scan("tag_id:1,2,3"))
|
||||
assert toks == [FieldValueList("tag_id", ("1", "2", "3"))]
|
||||
|
||||
def test_text_field_comma_is_literal(self):
|
||||
# correspondent is not multi-value: comma stays inside the value.
|
||||
toks = resolve_commas(scan("correspondent:foo,bar"))
|
||||
assert toks == [FieldValue("correspondent", "foo,bar")]
|
||||
|
||||
def test_clause_separator_before_known_field(self):
|
||||
toks = resolve_commas(scan("tag:foo,type:bar"))
|
||||
assert toks == [FieldValue("tag", "foo"), Comma(), FieldValue("type", "bar")]
|
||||
|
||||
def test_clause_separator_after_range(self):
|
||||
toks = resolve_commas(scan("created:[2020 TO 2021],added:[2022 TO 2023]"))
|
||||
assert toks == [
|
||||
FieldRange("created", "[", "2020", "2021", "]"),
|
||||
Comma(),
|
||||
FieldRange("added", "[", "2022", "2023", "]"),
|
||||
]
|
||||
|
||||
def test_clause_separator_after_quote(self):
|
||||
toks = resolve_commas(scan('correspondent:"A B",created:[2020 TO 2021]'))
|
||||
assert toks == [
|
||||
FieldValue("correspondent", '"A B"'),
|
||||
Comma(),
|
||||
FieldRange("created", "[", "2020", "2021", "]"),
|
||||
]
|
||||
|
||||
def test_url_comma_is_literal_passthrough(self):
|
||||
toks = resolve_commas(scan("http://example.com/a,b"))
|
||||
assert toks == [Passthrough("http://example.com/a,b")]
|
||||
|
||||
def test_non_multi_value_comma_is_literal(self):
|
||||
# title is not in MULTI_VALUE_FIELDS: comma stays inside the value.
|
||||
toks = resolve_commas(scan("title:10,20"))
|
||||
assert toks == [FieldValue("title", "10,20")]
|
||||
|
||||
def test_clause_separator_before_known_date_field(self):
|
||||
# The comma between a bare value and a known date field acts as a
|
||||
# clause separator; both sides survive as distinct tokens.
|
||||
toks = resolve_commas(scan("correspondent:foo,created:[2020 TO 2021]"))
|
||||
assert toks == [
|
||||
FieldValue("correspondent", "foo"),
|
||||
Comma(),
|
||||
FieldRange("created", "[", "2020", "2021", "]"),
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestTranslateScalar:
|
||||
@pytest.mark.parametrize(
|
||||
("field", "value", "expected"),
|
||||
[
|
||||
(
|
||||
"created",
|
||||
"2020",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"202003",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"20200115",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"2020-01-15",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"2020-03",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z]",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_partial_and_iso_dates(self, field: str, value: str, expected: str) -> None:
|
||||
assert translate_scalar(field, value, UTC) == expected
|
||||
|
||||
def test_invalid_date_raises(self) -> None:
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_scalar("created", "202023", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "202023"
|
||||
|
||||
def test_keyword_delegates(self) -> None:
|
||||
# keyword path produces a range; just assert it is a created range
|
||||
out = translate_scalar("created", "today", UTC)
|
||||
assert out.startswith("created:[") and out.endswith("]")
|
||||
|
||||
def test_14digit_compact_datetime(self) -> None:
|
||||
out = translate_scalar("created", "20240115120000", UTC)
|
||||
assert "20240115120000" not in out
|
||||
assert out.startswith("created:")
|
||||
assert out == "created:[2024-01-15T12:00:00Z TO 2024-01-15T12:00:00Z]"
|
||||
|
||||
def test_14digit_invalid_month_raises(self) -> None:
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_scalar("created", "20231300120000", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "20231300120000"
|
||||
|
||||
def test_unrecognized_value_raises(self) -> None:
|
||||
# A value that is not a keyword, digits, ISO date, or compact timestamp
|
||||
# raises rather than producing invalid Tantivy syntax or silently matching
|
||||
# nothing.
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_scalar("created", "garbage", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "garbage"
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestTranslateRange:
|
||||
@pytest.mark.parametrize(
|
||||
("lo", "hi", "expected"),
|
||||
[
|
||||
("2005", "2009", "created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z]"),
|
||||
(
|
||||
"202001",
|
||||
"202006",
|
||||
"created:[2020-01-01T00:00:00Z TO 2020-07-01T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"20200101",
|
||||
"20201231",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
),
|
||||
(
|
||||
"2020-01-01",
|
||||
"2020-12-31",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_absolute_ranges(self, lo, hi, expected):
|
||||
assert translate_range("created", lo, hi, UTC) == expected
|
||||
|
||||
def test_reversed_swaps(self):
|
||||
assert translate_range("created", "2009", "2005", UTC) == (
|
||||
"created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z]"
|
||||
)
|
||||
|
||||
def test_open_upper(self):
|
||||
out = translate_range("created", "2020", "", UTC)
|
||||
assert out == f"created:[2020-01-01T00:00:00Z TO {OPEN_HI}]"
|
||||
|
||||
def test_open_lower(self):
|
||||
out = translate_range("created", "", "2020", UTC)
|
||||
assert out == f"created:[{OPEN_LO} TO 2021-01-01T00:00:00Z]"
|
||||
|
||||
def test_invalid_bound_raises(self):
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_range("created", "202023", "2025", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "202023"
|
||||
|
||||
def test_invalid_high_bound_raises(self):
|
||||
# Low bound parses, high bound does not -> raise on the high bound.
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_range("created", "2020", "garbage", UTC)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "garbage"
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestTranslateQuery:
|
||||
@pytest.mark.parametrize(
|
||||
("raw", "expected"),
|
||||
[
|
||||
(
|
||||
"created:2020",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
),
|
||||
("tag:foo,bar", "tag:foo AND tag:bar"),
|
||||
# 'type' is a user-facing alias rewritten to 'document_type' (the real schema field)
|
||||
("tag:foo,type:bar", "tag:foo AND document_type:bar"),
|
||||
(
|
||||
"created:[2020 TO 2021],added:[2022 TO 2023]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z]"
|
||||
" AND "
|
||||
"added:[2022-01-01T00:00:00Z TO 2024-01-01T00:00:00Z]",
|
||||
),
|
||||
# correspondent is not multi-value: comma stays literal inside the value
|
||||
("correspondent:foo,bar", "correspondent:foo,bar"),
|
||||
],
|
||||
)
|
||||
def test_golden(self, raw: str, expected: str) -> None:
|
||||
assert translate_query(raw, UTC) == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"raw",
|
||||
[
|
||||
"created:2020",
|
||||
"created:202003",
|
||||
"created:[20200101 TO 20201231]",
|
||||
"created:[2020-01-01 TO 2020-12-31]",
|
||||
"created:[2020 to]",
|
||||
"created:[to 2020]",
|
||||
"title:x,created:[2020 TO 2021]",
|
||||
"created:2020 OR foo",
|
||||
"(created:2020 OR invoice)",
|
||||
"tag:foo,type:bar",
|
||||
"bank statement",
|
||||
],
|
||||
)
|
||||
def test_parse_acceptance(self, index: tantivy.Index, raw: str) -> None:
|
||||
translated = translate_query(raw, UTC)
|
||||
# Must not raise:
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestFieldAliasing:
|
||||
"""Whoosh->Tantivy field-name aliasing (type/path -> document_type/storage_path)."""
|
||||
|
||||
def test_type_alias(self) -> None:
|
||||
assert translate_query("type:invoice", UTC) == "document_type:invoice"
|
||||
|
||||
def test_path_alias(self) -> None:
|
||||
assert translate_query("path:/foo/bar", UTC) == "storage_path:/foo/bar"
|
||||
|
||||
def test_type_id_alias(self) -> None:
|
||||
assert translate_query("type_id:5", UTC) == "document_type_id:5"
|
||||
|
||||
def test_path_id_alias(self) -> None:
|
||||
assert translate_query("path_id:7", UTC) == "storage_path_id:7"
|
||||
|
||||
def test_clause_separator_plus_alias(self) -> None:
|
||||
# Comma between known fields acts as AND separator; alias still applied.
|
||||
assert (
|
||||
translate_query("tag:foo,type:bar", UTC) == "tag:foo AND document_type:bar"
|
||||
)
|
||||
|
||||
def test_type_range_alias(self) -> None:
|
||||
# type is not a date field; range passes through verbatim with alias applied.
|
||||
assert (
|
||||
translate_query("type:[2020 TO 2021]", UTC)
|
||||
== "document_type:[2020 TO 2021]"
|
||||
)
|
||||
|
||||
def test_parse_acceptance_type(self, index: tantivy.Index) -> None:
|
||||
# Translated output must be accepted by the real Tantivy parser.
|
||||
translated = translate_query("type:invoice", UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
def test_parse_acceptance_path(self, index: tantivy.Index) -> None:
|
||||
translated = translate_query("path:foo", UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
|
||||
# Freeze time so relative-date tests are deterministic.
|
||||
_FROZEN_NOW = datetime(2026, 3, 28, 12, 0, 0, tzinfo=UTC)
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestRelativeRanges:
|
||||
"""Relative date-range tokens resolved against a frozen clock."""
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_minus_7_days_to_now(self) -> None:
|
||||
assert translate_query("added:[-7 days to now]", UTC) == (
|
||||
"added:[2026-03-21T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_minus_1_week_to_now(self) -> None:
|
||||
assert translate_query("added:[-1 week to now]", UTC) == (
|
||||
"added:[2026-03-21T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_minus_1_month_to_now(self) -> None:
|
||||
assert translate_query("created:[-1 month to now]", UTC) == (
|
||||
"created:[2026-02-28T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_minus_1_year_to_now(self) -> None:
|
||||
assert translate_query("modified:[-1 year to now]", UTC) == (
|
||||
"modified:[2025-03-28T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_minus_3_hours_to_now(self) -> None:
|
||||
assert translate_query("added:[-3 hours to now]", UTC) == (
|
||||
"added:[2026-03-28T09:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_uppercase_units(self) -> None:
|
||||
assert translate_query("added:[-1 WEEK TO NOW]", UTC) == (
|
||||
"added:[2026-03-21T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_now_minus_7d_compact(self) -> None:
|
||||
assert translate_query("added:[now-7d TO now]", UTC) == (
|
||||
"added:[2026-03-21T12:00:00Z TO 2026-03-28T12:00:00Z]"
|
||||
)
|
||||
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_reversed_range_swapped(self) -> None:
|
||||
# now+1h TO now-1h is reversed; translate_range swaps -> lo=now-1h, hi=now+1h
|
||||
assert translate_query("added:[now+1h TO now-1h]", UTC) == (
|
||||
"added:[2026-03-28T11:00:00Z TO 2026-03-28T13:00:00Z]"
|
||||
)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"raw",
|
||||
[
|
||||
"added:[-7 days to now]",
|
||||
"added:[-1 week to now]",
|
||||
"created:[-1 month to now]",
|
||||
"modified:[-1 year to now]",
|
||||
"added:[-3 hours to now]",
|
||||
"added:[now-7d TO now]",
|
||||
"added:[now+1h TO now-1h]",
|
||||
],
|
||||
)
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_parse_acceptance(self, index: tantivy.Index, raw: str) -> None:
|
||||
translated = translate_query(raw, UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestOperatorNormalization:
|
||||
"""Post-render operator normalization in translate_query."""
|
||||
|
||||
def test_spaced_dash_removed(self) -> None:
|
||||
assert (
|
||||
translate_query("H52.1 - Kurzsichtigkeit", UTC) == "H52.1 Kurzsichtigkeit"
|
||||
)
|
||||
|
||||
def test_spaced_dash_simple(self) -> None:
|
||||
assert translate_query("bar - baz", UTC) == "bar baz"
|
||||
|
||||
def test_trailing_operator_stripped(self) -> None:
|
||||
assert translate_query("foo -", UTC) == "foo"
|
||||
|
||||
def test_date_range_preserved(self) -> None:
|
||||
out = translate_query("created:[2020 TO 2021]", UTC)
|
||||
# Must not corrupt the ISO range
|
||||
assert out == "created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z]"
|
||||
|
||||
def test_date_scalar_with_or(self) -> None:
|
||||
out = translate_query("created:2020 OR foo", UTC)
|
||||
# The created scalar becomes a range; " OR foo" passes through verbatim.
|
||||
assert out.startswith("created:[")
|
||||
assert "OR foo" in out
|
||||
|
||||
def test_parse_acceptance_spaced_dash(self, index: tantivy.Index) -> None:
|
||||
translated = translate_query("H52.1 - Kurzsichtigkeit", UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
def test_parse_acceptance_trailing_op(self, index: tantivy.Index) -> None:
|
||||
translated = translate_query("foo -", UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestMultiWordDateKeywords:
|
||||
"""scan() must consume multi-word date keywords as a single value."""
|
||||
|
||||
def test_scan_previous_week_as_single_token(self) -> None:
|
||||
# "created:previous week" must produce one FieldValue with value "previous week",
|
||||
# not FieldValue("created","previous") + Passthrough(" week").
|
||||
toks = scan("created:previous week")
|
||||
assert toks == [FieldValue("created", "previous week")]
|
||||
|
||||
def test_scan_this_month_as_single_token(self) -> None:
|
||||
toks = scan("added:this month")
|
||||
assert toks == [FieldValue("added", "this month")]
|
||||
|
||||
def test_scan_previous_month_as_single_token(self) -> None:
|
||||
toks = scan("created:previous month")
|
||||
assert toks == [FieldValue("created", "previous month")]
|
||||
|
||||
def test_scan_this_year_as_single_token(self) -> None:
|
||||
toks = scan("added:this year")
|
||||
assert toks == [FieldValue("added", "this year")]
|
||||
|
||||
def test_scan_previous_year_as_single_token(self) -> None:
|
||||
toks = scan("created:previous year")
|
||||
assert toks == [FieldValue("created", "previous year")]
|
||||
|
||||
def test_scan_previous_quarter_as_single_token(self) -> None:
|
||||
toks = scan("created:previous quarter")
|
||||
assert toks == [FieldValue("created", "previous quarter")]
|
||||
|
||||
def test_quoted_multi_word_keyword_still_works(self) -> None:
|
||||
# The quoted form must continue to work as before.
|
||||
toks = scan('created:"previous week"')
|
||||
assert toks == [FieldValue("created", '"previous week"')]
|
||||
|
||||
def test_non_date_field_not_affected(self) -> None:
|
||||
# "previous" stops at the space for non-date fields; " week" passes through.
|
||||
toks = scan("correspondent:previous week")
|
||||
assert toks == [
|
||||
FieldValue("correspondent", "previous"),
|
||||
Passthrough(" week"),
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestKeywordDateResolution:
|
||||
"""Relative date keywords resolve to exact ISO ranges against a frozen clock.
|
||||
|
||||
Frozen at 2026-03-28 12:00 UTC (a Saturday in Q1) so the week, month,
|
||||
quarter and year rollovers are all exercised by a single anchor.
|
||||
"""
|
||||
|
||||
# created is a DateField: bounds are UTC midnight, no timezone offset.
|
||||
@pytest.mark.parametrize(
|
||||
("keyword", "expected"),
|
||||
[
|
||||
pytest.param(
|
||||
"today",
|
||||
"created:[2026-03-28T00:00:00Z TO 2026-03-29T00:00:00Z]",
|
||||
id="today",
|
||||
),
|
||||
pytest.param(
|
||||
"yesterday",
|
||||
"created:[2026-03-27T00:00:00Z TO 2026-03-28T00:00:00Z]",
|
||||
id="yesterday",
|
||||
),
|
||||
pytest.param(
|
||||
"previous week",
|
||||
"created:[2026-03-16T00:00:00Z TO 2026-03-23T00:00:00Z]",
|
||||
id="previous-week",
|
||||
),
|
||||
pytest.param(
|
||||
"this month",
|
||||
"created:[2026-03-01T00:00:00Z TO 2026-04-01T00:00:00Z]",
|
||||
id="this-month",
|
||||
),
|
||||
pytest.param(
|
||||
"previous month",
|
||||
"created:[2026-02-01T00:00:00Z TO 2026-03-01T00:00:00Z]",
|
||||
id="previous-month",
|
||||
),
|
||||
pytest.param(
|
||||
"this year",
|
||||
"created:[2026-01-01T00:00:00Z TO 2027-01-01T00:00:00Z]",
|
||||
id="this-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous year",
|
||||
"created:[2025-01-01T00:00:00Z TO 2026-01-01T00:00:00Z]",
|
||||
id="previous-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous quarter",
|
||||
"created:[2025-10-01T00:00:00Z TO 2026-01-01T00:00:00Z]",
|
||||
id="previous-quarter",
|
||||
),
|
||||
],
|
||||
)
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_date_only_field_keyword_ranges(
|
||||
self,
|
||||
keyword: str,
|
||||
expected: str,
|
||||
) -> None:
|
||||
assert translate_query(f"created:{keyword}", UTC) == expected
|
||||
|
||||
# added is a DateTimeField: local-tz midnight converted to UTC. Tokyo
|
||||
# (+09:00, no DST) shifts each midnight boundary back to 15:00Z the day
|
||||
# before, so this also exercises the local-midnight offset path.
|
||||
@pytest.mark.parametrize(
|
||||
("keyword", "expected"),
|
||||
[
|
||||
pytest.param(
|
||||
"today",
|
||||
"added:[2026-03-27T15:00:00Z TO 2026-03-28T15:00:00Z]",
|
||||
id="today",
|
||||
),
|
||||
pytest.param(
|
||||
"yesterday",
|
||||
"added:[2026-03-26T15:00:00Z TO 2026-03-27T15:00:00Z]",
|
||||
id="yesterday",
|
||||
),
|
||||
pytest.param(
|
||||
"previous week",
|
||||
"added:[2026-03-15T15:00:00Z TO 2026-03-22T15:00:00Z]",
|
||||
id="previous-week",
|
||||
),
|
||||
pytest.param(
|
||||
"this month",
|
||||
"added:[2026-02-28T15:00:00Z TO 2026-03-31T15:00:00Z]",
|
||||
id="this-month",
|
||||
),
|
||||
pytest.param(
|
||||
"previous month",
|
||||
"added:[2026-01-31T15:00:00Z TO 2026-02-28T15:00:00Z]",
|
||||
id="previous-month",
|
||||
),
|
||||
pytest.param(
|
||||
"this year",
|
||||
"added:[2025-12-31T15:00:00Z TO 2026-12-31T15:00:00Z]",
|
||||
id="this-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous year",
|
||||
"added:[2024-12-31T15:00:00Z TO 2025-12-31T15:00:00Z]",
|
||||
id="previous-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous quarter",
|
||||
"added:[2025-09-30T15:00:00Z TO 2025-12-31T15:00:00Z]",
|
||||
id="previous-quarter",
|
||||
),
|
||||
],
|
||||
)
|
||||
@time_machine.travel(_FROZEN_NOW, tick=False)
|
||||
def test_datetime_field_keyword_ranges_local_tz(
|
||||
self,
|
||||
keyword: str,
|
||||
expected: str,
|
||||
) -> None:
|
||||
assert translate_query(f"added:{keyword}", ZoneInfo("Asia/Tokyo")) == expected
|
||||
|
||||
|
||||
@pytest.mark.search
|
||||
class TestISODatetimeBounds:
|
||||
"""Full ISO datetime tokens in range bounds must be parsed directly."""
|
||||
|
||||
def test_translate_range_iso_bounds_passthrough(self) -> None:
|
||||
# Already-ISO datetime bounds must pass through as-is (exact instant).
|
||||
result = translate_range(
|
||||
"created",
|
||||
"2020-01-01T00:00:00Z",
|
||||
"2021-01-01T00:00:00Z",
|
||||
UTC,
|
||||
)
|
||||
assert result == "created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]"
|
||||
|
||||
def test_translate_query_iso_range_preserved(self) -> None:
|
||||
q = "created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
assert translate_query(q, UTC) == q
|
||||
|
||||
def test_translate_query_comma_separated_iso_ranges(self) -> None:
|
||||
q = (
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z],"
|
||||
"added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
)
|
||||
result = translate_query(q, UTC)
|
||||
assert result == (
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
" AND "
|
||||
"added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
)
|
||||
|
||||
def test_invalid_iso_datetime_raises(self) -> None:
|
||||
# A token with "T" that is not valid ISO datetime -> raise.
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
translate_range(
|
||||
"created",
|
||||
"2020-01-01T99:00:00Z",
|
||||
"2021-01-01T00:00:00Z",
|
||||
UTC,
|
||||
)
|
||||
assert exc_info.value.field == "created"
|
||||
assert exc_info.value.value == "2020-01-01T99:00:00Z"
|
||||
|
||||
def test_parse_acceptance_iso_bounds(self, index: tantivy.Index) -> None:
|
||||
q = "created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
translated = translate_query(q, UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
|
||||
def test_parse_acceptance_comma_iso_ranges(self, index: tantivy.Index) -> None:
|
||||
q = (
|
||||
"created:[2026-01-01T00:00:00Z TO 2026-06-01T00:00:00Z],"
|
||||
"added:[2026-05-01T00:00:00Z TO 2026-06-01T00:00:00Z]"
|
||||
)
|
||||
translated = translate_query(q, UTC)
|
||||
index.parse_query(translated, DEFAULT_SEARCH_FIELDS, field_boosts=_FIELD_BOOSTS)
|
||||
@@ -844,7 +844,7 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
|
||||
|
||||
with (
|
||||
patch("documents.tasks.llmindex_index.apply_async") as mock_update,
|
||||
patch("paperless.views.vector_store_file_exists") as mock_exists,
|
||||
patch("paperless.views.llm_index_exists") as mock_exists,
|
||||
):
|
||||
mock_exists.return_value = False
|
||||
self.client.patch(
|
||||
@@ -869,7 +869,7 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
|
||||
|
||||
with (
|
||||
patch("documents.tasks.llmindex_index.apply_async") as mock_update,
|
||||
patch("paperless.views.vector_store_file_exists") as mock_exists,
|
||||
patch("paperless.views.llm_index_exists") as mock_exists,
|
||||
):
|
||||
mock_exists.return_value = True
|
||||
self.client.patch(
|
||||
@@ -890,7 +890,7 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
|
||||
|
||||
with (
|
||||
patch("documents.tasks.llmindex_index.apply_async") as mock_update,
|
||||
patch("paperless.views.vector_store_file_exists") as mock_exists,
|
||||
patch("paperless.views.llm_index_exists") as mock_exists,
|
||||
):
|
||||
mock_exists.return_value = True
|
||||
self.client.patch(
|
||||
@@ -928,7 +928,7 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
|
||||
|
||||
with (
|
||||
patch("documents.tasks.llmindex_index.apply_async") as mock_update,
|
||||
patch("paperless.views.vector_store_file_exists") as mock_exists,
|
||||
patch("paperless.views.llm_index_exists") as mock_exists,
|
||||
):
|
||||
mock_exists.return_value = True
|
||||
self.client.patch(
|
||||
|
||||
@@ -6,6 +6,7 @@ import zipfile
|
||||
|
||||
from django.contrib.auth.models import User
|
||||
from django.test import override_settings
|
||||
from django.utils import timezone
|
||||
from rest_framework import status
|
||||
from rest_framework.test import APITestCase
|
||||
|
||||
@@ -32,21 +33,21 @@ class TestBulkDownload(DirectoriesMixin, SampleDirMixin, APITestCase):
|
||||
filename="docA.pdf",
|
||||
mime_type="application/pdf",
|
||||
checksum="B",
|
||||
created=datetime.datetime(2021, 1, 1, tzinfo=datetime.UTC),
|
||||
created=timezone.make_aware(datetime.datetime(2021, 1, 1)),
|
||||
)
|
||||
self.doc2b = Document.objects.create(
|
||||
title="document A",
|
||||
filename="docA2.pdf",
|
||||
mime_type="application/pdf",
|
||||
checksum="D",
|
||||
created=datetime.datetime(2021, 1, 1, tzinfo=datetime.UTC),
|
||||
created=timezone.make_aware(datetime.datetime(2021, 1, 1)),
|
||||
)
|
||||
self.doc3 = Document.objects.create(
|
||||
title="document B",
|
||||
filename="docB.jpg",
|
||||
mime_type="image/jpeg",
|
||||
checksum="C",
|
||||
created=datetime.datetime(2020, 3, 21, tzinfo=datetime.UTC),
|
||||
created=timezone.make_aware(datetime.datetime(2020, 3, 21)),
|
||||
archive_filename="docB.pdf",
|
||||
archive_checksum="D",
|
||||
)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import datetime
|
||||
import json
|
||||
from datetime import date
|
||||
from unittest import mock
|
||||
from unittest.mock import ANY
|
||||
|
||||
@@ -456,7 +456,7 @@ class TestCustomFieldsAPI(DirectoriesMixin, APITestCase):
|
||||
},
|
||||
)
|
||||
|
||||
date_value = datetime.datetime.now(tz=datetime.UTC).date()
|
||||
date_value = date.today()
|
||||
|
||||
resp = self.client.patch(
|
||||
f"/api/documents/{doc.id}/",
|
||||
@@ -618,7 +618,7 @@ class TestCustomFieldsAPI(DirectoriesMixin, APITestCase):
|
||||
data_type=CustomField.FieldDataType.DATE,
|
||||
)
|
||||
|
||||
date_value = datetime.datetime.now(tz=datetime.UTC).date()
|
||||
date_value = date.today()
|
||||
|
||||
resp = self.client.patch(
|
||||
f"/api/documents/{doc.id}/",
|
||||
|
||||
@@ -265,7 +265,7 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
|
||||
created=date(2023, 1, 1),
|
||||
)
|
||||
|
||||
created_datetime = datetime.datetime(2023, 2, 1, 12, 0, 0, tzinfo=datetime.UTC)
|
||||
created_datetime = datetime.datetime(2023, 2, 1, 12, 0, 0)
|
||||
response = self.client.patch(
|
||||
f"/api/documents/{doc.pk}/",
|
||||
{"created": created_datetime},
|
||||
|
||||
@@ -0,0 +1,95 @@
|
||||
import unicodedata
|
||||
from typing import TYPE_CHECKING
|
||||
from unittest import mock
|
||||
|
||||
import celery.result
|
||||
import pytest
|
||||
from django.core.files.uploadedfile import SimpleUploadedFile
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from documents.data_models import ConsumableDocument
|
||||
from documents.data_models import DocumentMetadataOverrides
|
||||
|
||||
|
||||
@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 TestPostDocumentNFCNormalization:
|
||||
def test_nfd_filename_normalized_to_nfc(
|
||||
self,
|
||||
admin_client,
|
||||
consume_file_mock: mock.MagicMock,
|
||||
directories,
|
||||
):
|
||||
"""Uploaded file with NFD filename must have its name stored as NFC."""
|
||||
nfd = unicodedata.normalize("NFD", "Rechnung März.pdf")
|
||||
nfc = unicodedata.normalize("NFC", "Rechnung März.pdf")
|
||||
|
||||
# Verify our test strings actually differ at the byte level
|
||||
assert nfd != nfc
|
||||
|
||||
uploaded = SimpleUploadedFile(
|
||||
nfd,
|
||||
b"%PDF-1.4 test",
|
||||
content_type="application/pdf",
|
||||
)
|
||||
response = admin_client.post(
|
||||
"/api/documents/post_document/",
|
||||
{"document": uploaded},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
task_kwargs = consume_file_mock.call_args.kwargs["kwargs"]
|
||||
input_doc: ConsumableDocument = task_kwargs["input_doc"]
|
||||
overrides: DocumentMetadataOverrides = task_kwargs["overrides"]
|
||||
|
||||
# The temp file on disk must have an NFC name
|
||||
assert input_doc.original_file.name == nfc, (
|
||||
f"Expected NFC filename {nfc!r}, got {input_doc.original_file.name!r}"
|
||||
)
|
||||
# The override filename stored for later use must also be NFC
|
||||
assert overrides.filename == nfc, (
|
||||
f"Expected NFC override filename {nfc!r}, got {overrides.filename!r}"
|
||||
)
|
||||
assert unicodedata.is_normalized("NFC", overrides.filename)
|
||||
|
||||
def test_already_nfc_filename_unchanged(
|
||||
self,
|
||||
admin_client,
|
||||
consume_file_mock: mock.MagicMock,
|
||||
directories,
|
||||
):
|
||||
"""Uploaded file with already-NFC filename must pass through unchanged."""
|
||||
nfc = unicodedata.normalize("NFC", "Invoice_2024.pdf")
|
||||
|
||||
uploaded = SimpleUploadedFile(
|
||||
nfc,
|
||||
b"%PDF-1.4 test",
|
||||
content_type="application/pdf",
|
||||
)
|
||||
response = admin_client.post(
|
||||
"/api/documents/post_document/",
|
||||
{"document": uploaded},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
task_kwargs = consume_file_mock.call_args.kwargs["kwargs"]
|
||||
overrides: DocumentMetadataOverrides = task_kwargs["overrides"]
|
||||
|
||||
assert overrides.filename == nfc
|
||||
assert unicodedata.is_normalized("NFC", overrides.filename)
|
||||
@@ -700,7 +700,7 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
pk=3,
|
||||
checksum="C",
|
||||
# specific time zone aware date
|
||||
added=datetime.datetime(2023, 12, 1, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2023, 12, 1)),
|
||||
)
|
||||
# refresh doc instance to ensure we operate on date objects that Django uses
|
||||
# Django converts dates to UTC
|
||||
@@ -725,9 +725,11 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
GIVEN:
|
||||
- One document added right now
|
||||
WHEN:
|
||||
- Query with invalid added date
|
||||
- Query with an invalid added date
|
||||
THEN:
|
||||
- 400 Bad Request returned (Tantivy rejects invalid date field syntax)
|
||||
- 400 Bad Request with a message naming the malformed date, so the
|
||||
user knows their date is invalid rather than silently getting zero
|
||||
results
|
||||
"""
|
||||
d1 = Document.objects.create(
|
||||
title="invoice",
|
||||
@@ -740,8 +742,9 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
|
||||
response = self.client.get("/api/documents/?query=added:invalid-date")
|
||||
|
||||
# Tantivy rejects unparsable field queries with a 400
|
||||
# An unparsable date is reported as a malformed query, not silently empty.
|
||||
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
|
||||
self.assertIn("invalid-date", str(response.data["query"]))
|
||||
|
||||
@override_settings(
|
||||
TIME_ZONE="UTC",
|
||||
@@ -994,25 +997,25 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
title="invoice",
|
||||
content="the thing i bought at a shop and paid with bank account",
|
||||
created=datetime.date(2018, 1, 1),
|
||||
added=datetime.datetime(2018, 1, 1, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2018, 1, 1)),
|
||||
)
|
||||
d2 = DocumentFactory(
|
||||
title="bank statement 1",
|
||||
content="things i paid for in august",
|
||||
created=datetime.date(2019, 3, 4),
|
||||
added=datetime.datetime(2019, 3, 4, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2019, 3, 4)),
|
||||
)
|
||||
d3 = DocumentFactory(
|
||||
title="bank statement 3",
|
||||
content="things i paid for in september",
|
||||
created=datetime.date(2020, 7, 9),
|
||||
added=datetime.datetime(2020, 7, 9, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2020, 7, 9)),
|
||||
)
|
||||
d4 = DocumentFactory(
|
||||
title="Quarterly Report",
|
||||
content="quarterly revenue profit margin earnings growth",
|
||||
created=datetime.date(2021, 11, 30),
|
||||
added=datetime.datetime(2021, 11, 30, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2021, 11, 30)),
|
||||
)
|
||||
backend = get_backend()
|
||||
backend.add_or_update(d1)
|
||||
@@ -1131,7 +1134,7 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d4.tags.add(t2)
|
||||
d5 = Document.objects.create(
|
||||
checksum="5",
|
||||
added=datetime.datetime(2020, 7, 13, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2020, 7, 13)),
|
||||
content="test",
|
||||
original_filename="doc5.pdf",
|
||||
)
|
||||
@@ -1241,18 +1244,14 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d4.id,
|
||||
search_query(
|
||||
"&created__date__lt="
|
||||
+ datetime.datetime(2020, 9, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 9, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
self.assertNotIn(
|
||||
d4.id,
|
||||
search_query(
|
||||
"&created__date__gt="
|
||||
+ datetime.datetime(2020, 9, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 9, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
|
||||
@@ -1260,18 +1259,14 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d4.id,
|
||||
search_query(
|
||||
"&created__date__lt="
|
||||
+ datetime.datetime(2020, 1, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 1, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
self.assertIn(
|
||||
d4.id,
|
||||
search_query(
|
||||
"&created__date__gt="
|
||||
+ datetime.datetime(2020, 1, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 1, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
|
||||
@@ -1279,18 +1274,14 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d5.id,
|
||||
search_query(
|
||||
"&added__date__lt="
|
||||
+ datetime.datetime(2020, 9, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 9, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
self.assertNotIn(
|
||||
d5.id,
|
||||
search_query(
|
||||
"&added__date__gt="
|
||||
+ datetime.datetime(2020, 9, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 9, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
|
||||
@@ -1298,9 +1289,7 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d5.id,
|
||||
search_query(
|
||||
"&added__date__lt="
|
||||
+ datetime.datetime(2020, 1, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 1, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
|
||||
@@ -1308,9 +1297,7 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
d5.id,
|
||||
search_query(
|
||||
"&added__date__gt="
|
||||
+ datetime.datetime(2020, 1, 2, tzinfo=datetime.UTC).strftime(
|
||||
"%Y-%m-%d",
|
||||
),
|
||||
+ datetime.datetime(2020, 1, 2).strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@@ -216,6 +216,77 @@ class TestSystemStatus(APITestCase):
|
||||
self.assertEqual(response.status_code, status.HTTP_200_OK)
|
||||
self.assertEqual(response.data["tasks"]["celery_status"], "OK")
|
||||
|
||||
@mock.patch("celery.app.control.Inspect.ping")
|
||||
def test_system_status_celery_ping_none(self, mock_ping) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- Celery ping returns no worker responses
|
||||
WHEN:
|
||||
- The user requests the system status
|
||||
THEN:
|
||||
- The response contains a warning celery status
|
||||
"""
|
||||
mock_ping.return_value = None
|
||||
self.client.force_login(self.user)
|
||||
response = self.client.get(self.ENDPOINT)
|
||||
self.assertEqual(response.status_code, status.HTTP_200_OK)
|
||||
self.assertEqual(response.data["tasks"]["celery_status"], "WARNING")
|
||||
self.assertEqual(
|
||||
response.data["tasks"]["celery_error"],
|
||||
"No celery workers responded to ping. This may be temporary.",
|
||||
)
|
||||
|
||||
@mock.patch("celery.app.control.Inspect.ping")
|
||||
def test_system_status_celery_ping_unexpected_responses(self, mock_ping) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- Celery ping returns an unexpected worker response
|
||||
WHEN:
|
||||
- The user requests the system status
|
||||
THEN:
|
||||
- The response contains a warning celery status
|
||||
"""
|
||||
self.client.force_login(self.user)
|
||||
for ping_response in (
|
||||
{"hostname": {"ok": "not-pong"}},
|
||||
{"hostname": {}},
|
||||
{"hostname": "pong"},
|
||||
):
|
||||
with self.subTest(ping_response=ping_response):
|
||||
mock_ping.return_value = ping_response
|
||||
response = self.client.get(self.ENDPOINT)
|
||||
self.assertEqual(response.status_code, status.HTTP_200_OK)
|
||||
self.assertEqual(response.data["tasks"]["celery_status"], "WARNING")
|
||||
self.assertEqual(response.data["tasks"]["celery_url"], "hostname")
|
||||
self.assertEqual(
|
||||
response.data["tasks"]["celery_error"],
|
||||
"Celery worker responded unexpectedly.",
|
||||
)
|
||||
|
||||
@mock.patch("documents.views.sleep")
|
||||
@mock.patch("celery.app.control.Inspect.ping")
|
||||
def test_system_status_celery_ping_retry_success(
|
||||
self,
|
||||
mock_ping,
|
||||
mock_sleep,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- Celery ping fails once but succeeds on retry
|
||||
WHEN:
|
||||
- The user requests the system status
|
||||
THEN:
|
||||
- The response contains an OK celery status
|
||||
"""
|
||||
mock_ping.side_effect = [None, {"hostname": {"ok": "pong"}}]
|
||||
self.client.force_login(self.user)
|
||||
response = self.client.get(self.ENDPOINT)
|
||||
self.assertEqual(response.status_code, status.HTTP_200_OK)
|
||||
self.assertEqual(response.data["tasks"]["celery_status"], "OK")
|
||||
self.assertIsNone(response.data["tasks"]["celery_error"])
|
||||
self.assertEqual(mock_ping.call_count, 2)
|
||||
mock_sleep.assert_called_once_with(0.25)
|
||||
|
||||
@mock.patch("documents.search.get_backend")
|
||||
def test_system_status_index_ok(self, mock_get_backend) -> None:
|
||||
"""
|
||||
|
||||
@@ -18,6 +18,7 @@ from guardian.shortcuts import assign_perm
|
||||
from rest_framework import status
|
||||
from rest_framework.test import APIClient
|
||||
|
||||
from documents.filters import PaperlessTaskFilterSet
|
||||
from documents.models import PaperlessTask
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.factories import PaperlessTaskFactory
|
||||
@@ -169,6 +170,165 @@ class TestGetTasksV10:
|
||||
PaperlessTask.Status.STARTED,
|
||||
}
|
||||
|
||||
def test_filter_by_task_name(self, admin_client: APIClient) -> None:
|
||||
"""?name= searches task filenames, task types, and trigger sources."""
|
||||
filename_task = PaperlessTaskFactory(input_data={"filename": "invoice-123.pdf"})
|
||||
type_task = PaperlessTaskFactory(task_type=PaperlessTask.TaskType.SANITY_CHECK)
|
||||
source_task = PaperlessTaskFactory(
|
||||
trigger_source=PaperlessTask.TriggerSource.EMAIL_CONSUME,
|
||||
)
|
||||
PaperlessTaskFactory(input_data={"filename": "unrelated.pdf"})
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"name": "invoice"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data["count"] == 1
|
||||
assert response.data["results"][0]["task_id"] == filename_task.task_id
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"name": "sanity"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data["count"] == 1
|
||||
assert response.data["results"][0]["task_id"] == type_task.task_id
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"name": "email"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data["count"] == 1
|
||||
assert response.data["results"][0]["task_id"] == source_task.task_id
|
||||
|
||||
def test_filter_by_task_result(self, admin_client: APIClient) -> None:
|
||||
"""?result= searches common structured task result messages."""
|
||||
reason_task = PaperlessTaskFactory(result_data={"reason": "Manual review"})
|
||||
error_task = PaperlessTaskFactory(
|
||||
result_data={"error_message": "Duplicate detected"},
|
||||
)
|
||||
document_task = PaperlessTaskFactory(result_data={"document_id": 321})
|
||||
duplicate_task = PaperlessTaskFactory(result_data={"duplicate_of": 123})
|
||||
PaperlessTaskFactory(result_data={"reason": "unrelated"})
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"result": "manual"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data["count"] == 1
|
||||
assert response.data["results"][0]["task_id"] == reason_task.task_id
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"result": "duplicate"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
returned_ids = {task["task_id"] for task in response.data["results"]}
|
||||
assert returned_ids == {error_task.task_id, duplicate_task.task_id}
|
||||
|
||||
response = admin_client.get(ENDPOINT, {"result": "321"})
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data["count"] == 1
|
||||
assert response.data["results"][0]["task_id"] == document_task.task_id
|
||||
|
||||
def test_empty_task_name_and_result_filters(self) -> None:
|
||||
"""Empty name/result values leave the queryset unchanged."""
|
||||
PaperlessTaskFactory.create_batch(2)
|
||||
queryset = PaperlessTask.objects.all()
|
||||
filterset = PaperlessTaskFilterSet()
|
||||
|
||||
assert filterset.filter_name(queryset, "name", "").count() == 2
|
||||
assert filterset.filter_result(queryset, "result", "").count() == 2
|
||||
|
||||
def test_status_counts_respects_filters(self, admin_client: APIClient) -> None:
|
||||
"""status_counts/ returns section counts for the filtered task queryset."""
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.FAILURE,
|
||||
input_data={"filename": "invoice-a.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.REVOKED,
|
||||
input_data={"filename": "invoice-b.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.PENDING,
|
||||
input_data={"filename": "invoice-c.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.STARTED,
|
||||
input_data={"filename": "invoice-d.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.SUCCESS,
|
||||
input_data={"filename": "invoice-e.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=True,
|
||||
status=PaperlessTask.Status.SUCCESS,
|
||||
input_data={"filename": "invoice-acknowledged.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.SUCCESS,
|
||||
input_data={"filename": "unrelated.pdf"},
|
||||
)
|
||||
|
||||
response = admin_client.get(
|
||||
f"{ENDPOINT}status_counts/",
|
||||
{"acknowledged": "false", "name": "invoice"},
|
||||
)
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data == {
|
||||
"all": 5,
|
||||
"needs_attention": 2,
|
||||
"in_progress": 2,
|
||||
"completed": 1,
|
||||
}
|
||||
|
||||
def test_status_counts_ignores_section_filters(
|
||||
self,
|
||||
admin_client: APIClient,
|
||||
) -> None:
|
||||
"""status_counts/ ignores status-like filters for the sections it counts."""
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.FAILURE,
|
||||
input_data={"filename": "invoice-a.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.PENDING,
|
||||
input_data={"filename": "invoice-b.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.SUCCESS,
|
||||
input_data={"filename": "invoice-c.pdf"},
|
||||
)
|
||||
PaperlessTaskFactory(
|
||||
acknowledged=False,
|
||||
status=PaperlessTask.Status.FAILURE,
|
||||
input_data={"filename": "unrelated.pdf"},
|
||||
)
|
||||
|
||||
response = admin_client.get(
|
||||
f"{ENDPOINT}status_counts/",
|
||||
{
|
||||
"acknowledged": "false",
|
||||
"name": "invoice",
|
||||
"status": PaperlessTask.Status.FAILURE,
|
||||
"is_complete": "false",
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data == {
|
||||
"all": 3,
|
||||
"needs_attention": 1,
|
||||
"in_progress": 1,
|
||||
"completed": 1,
|
||||
}
|
||||
|
||||
def test_default_ordering_is_newest_first(self, admin_client: APIClient) -> None:
|
||||
"""Tasks are returned in descending date_created order (newest first)."""
|
||||
base = timezone.now()
|
||||
@@ -522,6 +682,27 @@ class TestAcknowledge:
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data == {"result": 2}
|
||||
|
||||
def test_acknowledge_all_returns_count(self, admin_client: APIClient) -> None:
|
||||
"""POST acknowledge/ with all=true acknowledges all unacknowledged tasks."""
|
||||
unacknowledged_task1 = PaperlessTaskFactory(acknowledged=False)
|
||||
unacknowledged_task2 = PaperlessTaskFactory(acknowledged=False)
|
||||
acknowledged_task = PaperlessTaskFactory(acknowledged=True)
|
||||
|
||||
response = admin_client.post(
|
||||
ENDPOINT + "acknowledge/",
|
||||
{"all": True},
|
||||
format="json",
|
||||
)
|
||||
|
||||
assert response.status_code == status.HTTP_200_OK
|
||||
assert response.data == {"result": 2}
|
||||
unacknowledged_task1.refresh_from_db()
|
||||
unacknowledged_task2.refresh_from_db()
|
||||
acknowledged_task.refresh_from_db()
|
||||
assert unacknowledged_task1.acknowledged
|
||||
assert unacknowledged_task2.acknowledged
|
||||
assert acknowledged_task.acknowledged
|
||||
|
||||
def test_acknowledged_tasks_excluded_from_unacked_filter(
|
||||
self,
|
||||
admin_client: APIClient,
|
||||
|
||||
@@ -3,6 +3,7 @@ from datetime import date
|
||||
from pathlib import Path
|
||||
from unittest import mock
|
||||
|
||||
import pikepdf
|
||||
from django.contrib.auth.models import Group
|
||||
from django.contrib.auth.models import User
|
||||
from django.test import TestCase
|
||||
@@ -615,6 +616,18 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
self.img_doc.archive_filename = img_doc_archive
|
||||
self.img_doc.save()
|
||||
|
||||
@staticmethod
|
||||
def mock_password_required_pdf(
|
||||
mock_open: mock.Mock,
|
||||
fake_pdf: mock.Mock,
|
||||
) -> None:
|
||||
password_context = mock.MagicMock()
|
||||
password_context.__enter__.return_value = fake_pdf
|
||||
mock_open.side_effect = [
|
||||
pikepdf.PasswordError("password required"),
|
||||
password_context,
|
||||
]
|
||||
|
||||
@mock.patch("documents.tasks.consume_file.s")
|
||||
def test_merge(self, mock_consume_file) -> None:
|
||||
"""
|
||||
@@ -764,7 +777,7 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
sig.set.return_value.apply_async.side_effect = Exception("boom")
|
||||
mock_consume_file.return_value = sig
|
||||
|
||||
with self.assertRaisesRegex(Exception, "boom"):
|
||||
with self.assertRaises(Exception):
|
||||
bulk_edit.merge(doc_ids, delete_originals=True)
|
||||
|
||||
self.doc1.refresh_from_db()
|
||||
@@ -1047,7 +1060,6 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
for call, expected_id in zip(
|
||||
mock_consume_delay.call_args_list,
|
||||
doc_ids,
|
||||
strict=False,
|
||||
):
|
||||
task_kwargs = call.kwargs["kwargs"]
|
||||
self.assertEqual(task_kwargs["input_doc"].root_document_id, expected_id)
|
||||
@@ -1306,7 +1318,7 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
sig.apply_async.side_effect = Exception("boom")
|
||||
mock_chord.return_value = sig
|
||||
|
||||
with self.assertRaisesRegex(Exception, "boom"):
|
||||
with self.assertRaises(Exception):
|
||||
bulk_edit.edit_pdf(doc_ids, operations, delete_original=True)
|
||||
|
||||
self.doc2.refresh_from_db()
|
||||
@@ -1418,7 +1430,7 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
{"page": 9999}, # invalid page, forces error during PDF load
|
||||
]
|
||||
with self.assertLogs("paperless.bulk_edit", level="ERROR"):
|
||||
with self.assertRaises(ValueError):
|
||||
with self.assertRaises(Exception):
|
||||
bulk_edit.edit_pdf(doc_ids, operations)
|
||||
mock_group.assert_not_called()
|
||||
mock_consume_file.assert_not_called()
|
||||
@@ -1467,6 +1479,7 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
|
||||
fake_pdf = mock.MagicMock()
|
||||
fake_pdf.pages = [mock.Mock(), mock.Mock(), mock.Mock()]
|
||||
fake_pdf.is_encrypted = True
|
||||
|
||||
def save_side_effect(target_path):
|
||||
Path(target_path).write_bytes(b"new pdf content")
|
||||
@@ -1481,7 +1494,13 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(doc.source_path, password="secret")
|
||||
self.assertEqual(
|
||||
mock_open.call_args_list,
|
||||
[
|
||||
mock.call(doc.source_path),
|
||||
mock.call(doc.source_path, password="secret"),
|
||||
],
|
||||
)
|
||||
fake_pdf.remove_unreferenced_resources.assert_called_once()
|
||||
mock_update_document.assert_not_called()
|
||||
mock_consume_delay.assert_called_once()
|
||||
@@ -1495,6 +1514,33 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
self.assertEqual(task_kwargs["input_doc"].root_document_id, doc.id)
|
||||
self.assertIsNotNone(task_kwargs["overrides"])
|
||||
|
||||
@mock.patch("documents.tasks.consume_file.apply_async")
|
||||
@mock.patch("documents.bulk_edit.tempfile.mkdtemp")
|
||||
@mock.patch("pikepdf.open")
|
||||
def test_remove_password_update_document_skips_unencrypted_pdf(
|
||||
self,
|
||||
mock_open,
|
||||
mock_mkdtemp,
|
||||
mock_consume_delay,
|
||||
) -> None:
|
||||
doc = self.doc1
|
||||
fake_pdf = mock.MagicMock()
|
||||
fake_pdf.is_encrypted = False
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
|
||||
result = bulk_edit.remove_password(
|
||||
[doc.id],
|
||||
password="secret",
|
||||
update_document=True,
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(doc.source_path)
|
||||
fake_pdf.remove_unreferenced_resources.assert_not_called()
|
||||
fake_pdf.save.assert_not_called()
|
||||
mock_mkdtemp.assert_not_called()
|
||||
mock_consume_delay.assert_not_called()
|
||||
|
||||
@mock.patch("documents.bulk_edit.update_document_content_maybe_archive_file.delay")
|
||||
@mock.patch("documents.tasks.consume_file.apply_async")
|
||||
@mock.patch("documents.bulk_edit.tempfile.mkdtemp")
|
||||
@@ -1514,12 +1560,12 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
mock_mkdtemp.return_value = str(temp_dir)
|
||||
|
||||
fake_pdf = mock.MagicMock()
|
||||
self.mock_password_required_pdf(mock_open, fake_pdf)
|
||||
|
||||
def save_side_effect(target_path):
|
||||
Path(target_path).write_bytes(b"new pdf content")
|
||||
|
||||
fake_pdf.save.side_effect = save_side_effect
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
|
||||
result = bulk_edit.remove_password(
|
||||
[doc.id],
|
||||
@@ -1529,7 +1575,13 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(source_file, password="secret")
|
||||
self.assertEqual(
|
||||
mock_open.call_args_list,
|
||||
[
|
||||
mock.call(source_file),
|
||||
mock.call(source_file, password="secret"),
|
||||
],
|
||||
)
|
||||
mock_update_document.assert_not_called()
|
||||
mock_consume_delay.assert_called_once()
|
||||
|
||||
@@ -1548,7 +1600,7 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
root_document=self.doc1,
|
||||
)
|
||||
fake_pdf = mock.MagicMock()
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
self.mock_password_required_pdf(mock_open, fake_pdf)
|
||||
|
||||
result = bulk_edit.remove_password(
|
||||
[self.doc1.id],
|
||||
@@ -1558,7 +1610,13 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(self.doc1.source_path, password="secret")
|
||||
self.assertEqual(
|
||||
mock_open.call_args_list,
|
||||
[
|
||||
mock.call(self.doc1.source_path),
|
||||
mock.call(self.doc1.source_path, password="secret"),
|
||||
],
|
||||
)
|
||||
mock_consume_delay.assert_called_once()
|
||||
|
||||
@mock.patch("documents.bulk_edit.chord")
|
||||
@@ -1581,12 +1639,12 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
|
||||
fake_pdf = mock.MagicMock()
|
||||
fake_pdf.pages = [mock.Mock(), mock.Mock()]
|
||||
self.mock_password_required_pdf(mock_open, fake_pdf)
|
||||
|
||||
def save_side_effect(target_path: Path) -> None:
|
||||
target_path.write_bytes(b"password removed")
|
||||
|
||||
fake_pdf.save.side_effect = save_side_effect
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
mock_group.return_value.delay.return_value = None
|
||||
|
||||
user = User.objects.create(username="owner")
|
||||
@@ -1601,7 +1659,13 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(doc.source_path, password="secret")
|
||||
self.assertEqual(
|
||||
mock_open.call_args_list,
|
||||
[
|
||||
mock.call(doc.source_path),
|
||||
mock.call(doc.source_path, password="secret"),
|
||||
],
|
||||
)
|
||||
mock_consume_file.assert_called_once()
|
||||
call_kwargs = mock_consume_file.call_args.kwargs
|
||||
consumable_document = call_kwargs["input_doc"]
|
||||
@@ -1619,6 +1683,43 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
mock_group.return_value.delay.assert_called_once()
|
||||
mock_chord.assert_not_called()
|
||||
|
||||
@mock.patch("documents.bulk_edit.delete")
|
||||
@mock.patch("documents.bulk_edit.chord")
|
||||
@mock.patch("documents.bulk_edit.group")
|
||||
@mock.patch("documents.tasks.consume_file.s")
|
||||
@mock.patch("documents.bulk_edit.tempfile.mkdtemp")
|
||||
@mock.patch("pikepdf.open")
|
||||
def test_remove_password_skips_unencrypted_pdf_without_queueing(
|
||||
self,
|
||||
mock_open: mock.Mock,
|
||||
mock_mkdtemp: mock.Mock,
|
||||
mock_consume_file: mock.Mock,
|
||||
mock_group: mock.Mock,
|
||||
mock_chord: mock.Mock,
|
||||
mock_delete: mock.Mock,
|
||||
) -> None:
|
||||
doc = self.doc2
|
||||
fake_pdf = mock.MagicMock()
|
||||
fake_pdf.is_encrypted = False
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
|
||||
result = bulk_edit.remove_password(
|
||||
[doc.id],
|
||||
password="secret",
|
||||
update_document=False,
|
||||
delete_original=True,
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(doc.source_path)
|
||||
fake_pdf.remove_unreferenced_resources.assert_not_called()
|
||||
fake_pdf.save.assert_not_called()
|
||||
mock_mkdtemp.assert_not_called()
|
||||
mock_consume_file.assert_not_called()
|
||||
mock_group.assert_not_called()
|
||||
mock_chord.assert_not_called()
|
||||
mock_delete.si.assert_not_called()
|
||||
|
||||
@mock.patch("documents.bulk_edit.delete")
|
||||
@mock.patch("documents.bulk_edit.chord")
|
||||
@mock.patch("documents.bulk_edit.group")
|
||||
@@ -1641,12 +1742,12 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
|
||||
fake_pdf = mock.MagicMock()
|
||||
fake_pdf.pages = [mock.Mock(), mock.Mock()]
|
||||
self.mock_password_required_pdf(mock_open, fake_pdf)
|
||||
|
||||
def save_side_effect(target_path: Path) -> None:
|
||||
target_path.write_bytes(b"password removed")
|
||||
|
||||
fake_pdf.save.side_effect = save_side_effect
|
||||
mock_open.return_value.__enter__.return_value = fake_pdf
|
||||
mock_chord.return_value.delay.return_value = None
|
||||
|
||||
result = bulk_edit.remove_password(
|
||||
@@ -1658,7 +1759,13 @@ class TestPDFActions(DirectoriesMixin, TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(result, "OK")
|
||||
mock_open.assert_called_once_with(doc.source_path, password="secret")
|
||||
self.assertEqual(
|
||||
mock_open.call_args_list,
|
||||
[
|
||||
mock.call(doc.source_path),
|
||||
mock.call(doc.source_path, password="secret"),
|
||||
],
|
||||
)
|
||||
mock_consume_file.assert_called_once()
|
||||
mock_group.assert_not_called()
|
||||
mock_chord.assert_called_once()
|
||||
|
||||
@@ -782,8 +782,8 @@ class TestClassifier(DirectoriesMixin, TestCase):
|
||||
load_classifier(raise_exception=True)
|
||||
|
||||
Path(settings.MODEL_FILE).touch()
|
||||
mock_load.side_effect = RuntimeError()
|
||||
with self.assertRaises(RuntimeError):
|
||||
mock_load.side_effect = Exception()
|
||||
with self.assertRaises(Exception):
|
||||
load_classifier(raise_exception=True)
|
||||
|
||||
|
||||
|
||||
@@ -59,7 +59,7 @@ class TestDoubleSided(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
def create_staging_file(self, src="double-sided-odd.pdf", datetime=None) -> None:
|
||||
shutil.copy(self.SAMPLE_DIR / src, self.staging_file)
|
||||
if datetime is None:
|
||||
datetime = dt.datetime.now(tz=dt.UTC)
|
||||
datetime = dt.datetime.now()
|
||||
os.utime(str(self.staging_file), (datetime.timestamp(),) * 2)
|
||||
|
||||
def test_odd_numbered_moved_to_staging(self) -> None:
|
||||
@@ -79,8 +79,8 @@ class TestDoubleSided(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
|
||||
self.assertIsFile(self.staging_file)
|
||||
self.assertAlmostEqual(
|
||||
dt.datetime.fromtimestamp(self.staging_file.stat().st_mtime, tz=dt.UTC),
|
||||
dt.datetime.now(tz=dt.UTC),
|
||||
dt.datetime.fromtimestamp(self.staging_file.stat().st_mtime),
|
||||
dt.datetime.now(),
|
||||
delta=dt.timedelta(seconds=5),
|
||||
)
|
||||
self.assertIn("Received odd numbered pages", msg["reason"])
|
||||
@@ -124,7 +124,7 @@ class TestDoubleSided(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
"""
|
||||
|
||||
self.create_staging_file(
|
||||
datetime=dt.datetime.now(tz=dt.UTC)
|
||||
datetime=dt.datetime.now()
|
||||
- dt.timedelta(minutes=TIMEOUT_MINUTES, seconds=1),
|
||||
)
|
||||
msg = self.consume_file("double-sided-odd.pdf")
|
||||
|
||||
@@ -12,6 +12,7 @@ from django.contrib.auth.models import User
|
||||
from django.db import DatabaseError
|
||||
from django.test import TestCase
|
||||
from django.test import override_settings
|
||||
from django.utils import timezone
|
||||
|
||||
from documents.file_handling import create_source_path_directory
|
||||
from documents.file_handling import delete_empty_directories
|
||||
@@ -23,6 +24,7 @@ from documents.models import CustomFieldInstance
|
||||
from documents.models import Document
|
||||
from documents.models import DocumentType
|
||||
from documents.models import StoragePath
|
||||
from documents.serialisers import DocumentSerializer
|
||||
from documents.tasks import empty_trash
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.utils import DirectoriesMixin
|
||||
@@ -220,11 +222,8 @@ class TestFileHandling(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
doc = Document.objects.create(
|
||||
title="document",
|
||||
mime_type="application/pdf",
|
||||
checksum=hashlib.md5(original_bytes, usedforsecurity=False).hexdigest(),
|
||||
archive_checksum=hashlib.md5(
|
||||
archive_bytes,
|
||||
usedforsecurity=False,
|
||||
).hexdigest(),
|
||||
checksum=hashlib.sha256(original_bytes).hexdigest(),
|
||||
archive_checksum=hashlib.sha256(archive_bytes).hexdigest(),
|
||||
filename="old/document.pdf",
|
||||
archive_filename="old/document.pdf",
|
||||
storage_path=old_storage_path,
|
||||
@@ -253,6 +252,46 @@ class TestFileHandling(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
self.assertIsNotFile(settings.ORIGINALS_DIR / "old" / "document.pdf")
|
||||
self.assertIsNotFile(settings.ARCHIVE_DIR / "old" / "document.pdf")
|
||||
|
||||
@override_settings(FILENAME_FORMAT="{title}")
|
||||
def test_serializer_stale_update_does_not_clobber_filename(self) -> None:
|
||||
old_path = settings.ORIGINALS_DIR / "original.pdf"
|
||||
old_path.touch()
|
||||
doc = Document.objects.create(
|
||||
title="original",
|
||||
mime_type="application/pdf",
|
||||
checksum=hashlib.sha256(b"").hexdigest(),
|
||||
filename="original.pdf",
|
||||
)
|
||||
|
||||
first_instance = Document.objects.get(pk=doc.pk)
|
||||
stale_instance = Document.objects.get(pk=doc.pk)
|
||||
|
||||
serializer = DocumentSerializer(
|
||||
first_instance,
|
||||
data={"title": "first"},
|
||||
partial=True,
|
||||
)
|
||||
self.assertTrue(serializer.is_valid(), serializer.errors)
|
||||
serializer.save()
|
||||
|
||||
doc.refresh_from_db()
|
||||
self.assertEqual(doc.filename, "first.pdf")
|
||||
self.assertIsFile(settings.ORIGINALS_DIR / "first.pdf")
|
||||
|
||||
serializer = DocumentSerializer(
|
||||
stale_instance,
|
||||
data={"title": "second"},
|
||||
partial=True,
|
||||
)
|
||||
self.assertTrue(serializer.is_valid(), serializer.errors)
|
||||
serializer.save()
|
||||
|
||||
doc.refresh_from_db()
|
||||
self.assertEqual(doc.filename, "second.pdf")
|
||||
self.assertIsFile(settings.ORIGINALS_DIR / "second.pdf")
|
||||
self.assertIsNotFile(settings.ORIGINALS_DIR / "first.pdf")
|
||||
self.assertIsNotFile(old_path)
|
||||
|
||||
@override_settings(FILENAME_FORMAT="{correspondent}/{correspondent}")
|
||||
def test_document_delete(self) -> None:
|
||||
document = Document()
|
||||
@@ -413,7 +452,7 @@ class TestFileHandling(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
FILENAME_FORMAT="{created_year}-{created_month}-{created_day}",
|
||||
)
|
||||
def test_created_year_month_day(self) -> None:
|
||||
d1 = datetime.datetime(2020, 3, 6, 1, 1, 1, tzinfo=datetime.UTC)
|
||||
d1 = timezone.make_aware(datetime.datetime(2020, 3, 6, 1, 1, 1))
|
||||
doc1 = Document.objects.create(
|
||||
title="doc1",
|
||||
mime_type="application/pdf",
|
||||
@@ -430,7 +469,7 @@ class TestFileHandling(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
FILENAME_FORMAT="{added_year}-{added_month}-{added_day}",
|
||||
)
|
||||
def test_added_year_month_day(self) -> None:
|
||||
d1 = datetime.datetime(1232, 1, 9, 1, 1, 1, tzinfo=datetime.UTC)
|
||||
d1 = timezone.make_aware(datetime.datetime(1232, 1, 9, 1, 1, 1))
|
||||
doc1 = Document.objects.create(
|
||||
title="doc1",
|
||||
mime_type="application/pdf",
|
||||
@@ -443,7 +482,7 @@ class TestFileHandling(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
|
||||
self.assertEqual(generate_filename(doc1), expected_filename)
|
||||
|
||||
doc1.added = datetime.datetime(2020, 11, 16, 1, 1, 1, tzinfo=datetime.UTC)
|
||||
doc1.added = timezone.make_aware(datetime.datetime(2020, 11, 16, 1, 1, 1))
|
||||
|
||||
self.assertEqual(generate_filename(doc1), Path("2020-11-16.pdf"))
|
||||
|
||||
@@ -1227,7 +1266,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
def test_short_names_added(self) -> None:
|
||||
doc = Document.objects.create(
|
||||
title="The Title",
|
||||
added=datetime.datetime(1984, 8, 21, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(1984, 8, 21, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1466,7 +1505,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc_a = Document.objects.create(
|
||||
title="Does Matter",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1538,7 +1577,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc = Document.objects.create(
|
||||
title="scan_017562",
|
||||
created=datetime.date(2025, 7, 2),
|
||||
added=datetime.datetime(2026, 3, 3, 11, 53, 16, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2026, 3, 3, 11, 53, 16)),
|
||||
mime_type="application/pdf",
|
||||
checksum="test-checksum",
|
||||
storage_path=sp,
|
||||
@@ -1567,7 +1606,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc_a = Document.objects.create(
|
||||
title="Does Matter",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1602,7 +1641,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc_a = Document.objects.create(
|
||||
title="Does Matter",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1634,7 +1673,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc_a = Document.objects.create(
|
||||
title="Some Title",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1739,7 +1778,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc_a = Document.objects.create(
|
||||
title="Some Title",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
@@ -1753,15 +1792,8 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
CustomFieldInstance.objects.create(
|
||||
document=doc_a,
|
||||
field=CustomField.objects.get(name="Invoice Date"),
|
||||
value_date=datetime.datetime(
|
||||
2024,
|
||||
10,
|
||||
1,
|
||||
7,
|
||||
36,
|
||||
51,
|
||||
153,
|
||||
tzinfo=datetime.UTC,
|
||||
value_date=timezone.make_aware(
|
||||
datetime.datetime(2024, 10, 1, 7, 36, 51, 153),
|
||||
),
|
||||
)
|
||||
|
||||
@@ -1801,7 +1833,7 @@ class TestFilenameGeneration(DirectoriesMixin, TestCase):
|
||||
doc = Document.objects.create(
|
||||
title="Some Title! With @ Special # Characters",
|
||||
created=datetime.date(2020, 6, 25),
|
||||
added=datetime.datetime(2024, 10, 1, 7, 36, 51, 153, tzinfo=datetime.UTC),
|
||||
added=timezone.make_aware(datetime.datetime(2024, 10, 1, 7, 36, 51, 153)),
|
||||
mime_type="application/pdf",
|
||||
pk=2,
|
||||
checksum="2",
|
||||
|
||||
@@ -0,0 +1,187 @@
|
||||
"""
|
||||
Tests for NFC Unicode normalization in generate_filename / FilePathTemplate.render().
|
||||
|
||||
NFC `ü` (UTF-8: c3 bc) and NFD `ü` (UTF-8: 75 cc 88) are visually identical but
|
||||
produce different byte sequences. On Linux (ext4, ZFS) these are distinct filenames.
|
||||
All paths produced by the templating system must be NFC-normalized.
|
||||
"""
|
||||
|
||||
import unicodedata
|
||||
|
||||
import pytest
|
||||
|
||||
from documents.file_handling import generate_filename
|
||||
from documents.models import CustomField
|
||||
from documents.models import CustomFieldInstance
|
||||
from documents.tests.factories import CorrespondentFactory
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.factories import StoragePathFactory
|
||||
from documents.tests.factories import TagFactory
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestGenerateFilenameNFCNormalization:
|
||||
@pytest.mark.parametrize(
|
||||
"raw,display",
|
||||
[
|
||||
(unicodedata.normalize("NFD", "Gemüse"), "Gemüse"),
|
||||
(unicodedata.normalize("NFD", "Café"), "Café"),
|
||||
(unicodedata.normalize("NFD", "naïve"), "naïve"),
|
||||
],
|
||||
)
|
||||
def test_nfd_title_normalized_to_nfc(self, settings, raw, display):
|
||||
"""NFD title must produce NFC path bytes."""
|
||||
settings.FILENAME_FORMAT = "{{ title }}"
|
||||
nfc = unicodedata.normalize("NFC", display)
|
||||
assert raw != nfc # confirm byte-level difference
|
||||
|
||||
doc = DocumentFactory(title=raw, mime_type="application/pdf")
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result) == f"{nfc}.pdf"
|
||||
assert str(result).encode() == f"{nfc}.pdf".encode()
|
||||
|
||||
def test_nfd_correspondent_normalized_to_nfc(self, settings):
|
||||
"""NFD correspondent name must produce NFC path component."""
|
||||
settings.FILENAME_FORMAT = "{{ correspondent }}/{{ title }}"
|
||||
nfd = unicodedata.normalize("NFD", "Müller")
|
||||
nfc = unicodedata.normalize("NFC", "Müller")
|
||||
|
||||
correspondent = CorrespondentFactory(name=nfd)
|
||||
doc = DocumentFactory(
|
||||
title="invoice",
|
||||
correspondent=correspondent,
|
||||
mime_type="application/pdf",
|
||||
)
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result) == f"{nfc}/invoice.pdf"
|
||||
assert str(result).encode() == f"{nfc}/invoice.pdf".encode()
|
||||
|
||||
def test_nfd_storage_path_normalized_to_nfc(self, settings):
|
||||
"""NFD literal in StoragePath.path template must produce NFC path bytes."""
|
||||
settings.FILENAME_FORMAT = None
|
||||
nfd = unicodedata.normalize("NFD", "Büro")
|
||||
nfc = unicodedata.normalize("NFC", "Büro")
|
||||
|
||||
# StoragePath.path is used directly as the format/template string.
|
||||
# Literal NFD characters in the template must survive rendering as NFC.
|
||||
sp = StoragePathFactory(path=f"{nfd}/{{{{ title }}}}")
|
||||
doc = DocumentFactory(title="doc", storage_path=sp, mime_type="application/pdf")
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result).encode() == f"{nfc}/doc.pdf".encode()
|
||||
|
||||
def test_nfd_raw_document_title_normalized_to_nfc(self, settings):
|
||||
"""NFD title accessed via document.title (unsanitized context) must also be NFC."""
|
||||
settings.FILENAME_FORMAT = "{{ document.title }}"
|
||||
nfd = unicodedata.normalize("NFD", "Café")
|
||||
nfc = unicodedata.normalize("NFC", "Café")
|
||||
|
||||
doc = DocumentFactory(title=nfd, mime_type="application/pdf")
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result) == f"{nfc}.pdf"
|
||||
assert str(result).encode() == f"{nfc}.pdf".encode()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestContextBuilderNFCNormalization:
|
||||
"""
|
||||
Defense-in-depth: context builder functions must NFC-normalize string inputs
|
||||
before passing them to sanitize_filename(). Task 1 already normalizes the
|
||||
final rendered path via clean_filepath(), so these tests may already pass;
|
||||
they exist as regression guards for the context-builder layer.
|
||||
"""
|
||||
|
||||
def test_nfd_tag_name_normalized_in_tag_list(self, settings):
|
||||
"""NFD tag name must appear as NFC bytes in the {{ tag_list }} shorthand."""
|
||||
settings.FILENAME_FORMAT = "{{ tag_list }}/{{ title }}"
|
||||
nfd = unicodedata.normalize("NFD", "Büro")
|
||||
nfc = unicodedata.normalize("NFC", "Büro")
|
||||
assert nfd != nfc # confirm they differ at byte level
|
||||
|
||||
tag = TagFactory(name=nfd)
|
||||
doc = DocumentFactory(title="doc", mime_type="application/pdf")
|
||||
doc.tags.set([tag])
|
||||
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result).encode() == f"{nfc}/doc.pdf".encode()
|
||||
|
||||
def test_nfd_original_name_normalized_to_nfc(self, settings):
|
||||
settings.FILENAME_FORMAT = "{{ original_name }}"
|
||||
nfd = unicodedata.normalize("NFD", "Rechnung März")
|
||||
nfc = unicodedata.normalize("NFC", "Rechnung März")
|
||||
|
||||
doc = DocumentFactory(
|
||||
original_filename=f"{nfd}.pdf",
|
||||
mime_type="application/pdf",
|
||||
)
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result).encode() == f"{nfc}.pdf".encode()
|
||||
|
||||
def test_nfd_custom_field_string_value_normalized(self, settings):
|
||||
"""NFD value in a STRING-type custom field must appear as NFC in the context."""
|
||||
settings.FILENAME_FORMAT = (
|
||||
"{{ custom_fields['Location']['value'] }}/{{ title }}"
|
||||
)
|
||||
nfd_value = unicodedata.normalize("NFD", "Düsseldorf")
|
||||
nfc_value = unicodedata.normalize("NFC", "Düsseldorf")
|
||||
assert nfd_value != nfc_value
|
||||
|
||||
doc = DocumentFactory(title="report", mime_type="application/pdf")
|
||||
cf = CustomField.objects.create(
|
||||
name="Location",
|
||||
data_type=CustomField.FieldDataType.STRING,
|
||||
)
|
||||
CustomFieldInstance.objects.create(
|
||||
document=doc,
|
||||
field=cf,
|
||||
value_text=nfd_value,
|
||||
)
|
||||
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result).encode() == f"{nfc_value}/report.pdf".encode()
|
||||
|
||||
def test_nfd_custom_field_name_normalized_as_key(self, settings):
|
||||
"""NFD characters in a custom field name must appear as NFC in the context dict key."""
|
||||
nfd_name = unicodedata.normalize("NFD", "Größe")
|
||||
nfc_name = unicodedata.normalize("NFC", "Größe")
|
||||
assert nfd_name != nfc_name
|
||||
|
||||
settings.FILENAME_FORMAT = f"{{% if custom_fields['{nfc_name}'] %}}{{{{ custom_fields['{nfc_name}']['value'] }}}}/{{{{ title }}}}{{% else %}}{{{{ title }}}}{{% endif %}}"
|
||||
|
||||
doc = DocumentFactory(title="letter", mime_type="application/pdf")
|
||||
cf = CustomField.objects.create(
|
||||
name=nfd_name,
|
||||
data_type=CustomField.FieldDataType.STRING,
|
||||
)
|
||||
CustomFieldInstance.objects.create(
|
||||
document=doc,
|
||||
field=cf,
|
||||
value_text="Berlin",
|
||||
)
|
||||
|
||||
result = generate_filename(doc)
|
||||
|
||||
# If field name key is NFC-normalized, the template condition succeeds
|
||||
# and result is "Berlin/letter.pdf"; otherwise it falls back to "letter.pdf"
|
||||
assert str(result) == "Berlin/letter.pdf"
|
||||
|
||||
def test_nfd_tag_name_list_normalized_to_nfc(self, settings):
|
||||
"""NFD tag names in tag_name_list must appear as NFC bytes when iterated."""
|
||||
settings.FILENAME_FORMAT = (
|
||||
"{% for t in tag_name_list %}{{ t }}{% endfor %}/{{ title }}"
|
||||
)
|
||||
nfd = unicodedata.normalize("NFD", "Büro")
|
||||
nfc = unicodedata.normalize("NFC", "Büro")
|
||||
assert nfd != nfc # confirm byte-level difference
|
||||
|
||||
doc = DocumentFactory(title="doc", mime_type="application/pdf")
|
||||
doc.tags.add(TagFactory(name=nfd))
|
||||
result = generate_filename(doc)
|
||||
|
||||
assert str(result).encode() == f"{nfc}/doc.pdf".encode()
|
||||
@@ -243,7 +243,7 @@ class TestViews(DirectoriesMixin, TestCase):
|
||||
"change": {"users": [], "groups": []},
|
||||
}
|
||||
else:
|
||||
raise AssertionError(f"Unexpected tag found: {tag['name']}")
|
||||
assert False, f"Unexpected tag found: {tag['name']}"
|
||||
|
||||
def test_list_no_n_plus_1_queries(self) -> None:
|
||||
"""
|
||||
|
||||
@@ -2760,14 +2760,7 @@ class TestWorkflows(
|
||||
doc = Document.objects.create(
|
||||
title="test",
|
||||
)
|
||||
self.assertRaisesRegex(
|
||||
Exception,
|
||||
"not yet supported",
|
||||
document_matches_workflow,
|
||||
doc,
|
||||
w,
|
||||
99,
|
||||
)
|
||||
self.assertRaises(Exception, document_matches_workflow, doc, w, 99)
|
||||
|
||||
def test_removal_action_document_updated_workflow(self) -> None:
|
||||
"""
|
||||
|
||||
@@ -129,12 +129,11 @@ def util_call_with_backoff(
|
||||
status_codes.append(cause_exec.response.status_code)
|
||||
warnings.warn(
|
||||
f"HTTP Exception for {cause_exec.request.url} - {cause_exec}",
|
||||
stacklevel=2,
|
||||
)
|
||||
else:
|
||||
warnings.warn(f"Unexpected error: {e}", stacklevel=2)
|
||||
warnings.warn(f"Unexpected error: {e}")
|
||||
except Exception as e: # pragma: no cover
|
||||
warnings.warn(f"Unexpected error: {e}", stacklevel=2)
|
||||
warnings.warn(f"Unexpected error: {e}")
|
||||
|
||||
retry_count = retry_count + 1
|
||||
|
||||
|
||||
+142
-50
@@ -7,11 +7,12 @@ import tempfile
|
||||
import zipfile
|
||||
from collections import defaultdict
|
||||
from collections import deque
|
||||
from datetime import UTC
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
from http import HTTPStatus
|
||||
from pathlib import Path
|
||||
from time import mktime
|
||||
from time import sleep
|
||||
from typing import TYPE_CHECKING
|
||||
from typing import Any
|
||||
from typing import Literal
|
||||
@@ -60,6 +61,7 @@ from django.http import StreamingHttpResponse
|
||||
from django.shortcuts import get_object_or_404
|
||||
from django.utils import timezone
|
||||
from django.utils.decorators import method_decorator
|
||||
from django.utils.timezone import make_aware
|
||||
from django.utils.translation import get_language
|
||||
from django.utils.translation import gettext_lazy as _
|
||||
from django.views import View
|
||||
@@ -284,7 +286,7 @@ def _get_more_like_id(query_params: dict[str, Any], user: User | None) -> int:
|
||||
pk=more_like_doc_id,
|
||||
)
|
||||
except (TypeError, ValueError, Document.DoesNotExist):
|
||||
raise PermissionDenied(_("Invalid more_like_id")) from None
|
||||
raise PermissionDenied(_("Invalid more_like_id"))
|
||||
|
||||
if user and not has_perms_owner_aware(
|
||||
user,
|
||||
@@ -1100,7 +1102,7 @@ class DocumentViewSet(
|
||||
"root_document",
|
||||
).get(pk=pk)
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
root_doc = get_root_document(doc)
|
||||
if request.user is not None and not has_perms_owner_aware(
|
||||
@@ -1263,7 +1265,7 @@ class DocumentViewSet(
|
||||
"root_document",
|
||||
).get(id=pk)
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
root_doc = get_root_document(
|
||||
request_doc,
|
||||
@@ -1399,7 +1401,7 @@ class DocumentViewSet(
|
||||
)
|
||||
if request.user is not None and not has_perms_owner_aware(
|
||||
request.user,
|
||||
"view_document",
|
||||
"change_document",
|
||||
doc,
|
||||
):
|
||||
return HttpResponseForbidden("Insufficient permissions")
|
||||
@@ -1459,7 +1461,7 @@ class DocumentViewSet(
|
||||
)
|
||||
if request.user is not None and not has_perms_owner_aware(
|
||||
request.user,
|
||||
"view_document",
|
||||
"change_document",
|
||||
doc,
|
||||
):
|
||||
return HttpResponseForbidden("Insufficient permissions")
|
||||
@@ -1505,6 +1507,7 @@ class DocumentViewSet(
|
||||
"document %s: %s",
|
||||
doc.pk,
|
||||
exc,
|
||||
exc_info=True,
|
||||
)
|
||||
raise ValidationError({"ai": [_("Invalid AI configuration.")]}) from exc
|
||||
|
||||
@@ -1578,7 +1581,7 @@ class DocumentViewSet(
|
||||
disposition="inline",
|
||||
)
|
||||
except FileNotFoundError:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
@action(methods=["get"], detail=True, filter_backends=[])
|
||||
@method_decorator(cache_control(no_cache=True))
|
||||
@@ -1603,14 +1606,14 @@ class DocumentViewSet(
|
||||
|
||||
return FileResponse(handle, content_type="image/webp")
|
||||
except FileNotFoundError:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
@action(methods=["get"], detail=True)
|
||||
def download(self, request, pk=None):
|
||||
try:
|
||||
return self.file_response(pk, request, "attachment")
|
||||
except (FileNotFoundError, Document.DoesNotExist):
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
@action(
|
||||
methods=["get", "post", "delete"],
|
||||
@@ -1635,7 +1638,7 @@ class DocumentViewSet(
|
||||
):
|
||||
return HttpResponseForbidden("Insufficient permissions to view notes")
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
serializer = self.get_serializer(doc)
|
||||
|
||||
@@ -1706,7 +1709,7 @@ class DocumentViewSet(
|
||||
try:
|
||||
note_id_int = int(note_id)
|
||||
except ValueError:
|
||||
raise ValidationError({"id": "A valid integer is required."}) from None
|
||||
raise ValidationError({"id": "A valid integer is required."})
|
||||
note = get_object_or_404(Note, id=note_id_int, document=doc)
|
||||
if settings.AUDIT_LOG_ENABLED:
|
||||
LogEntry.objects.log_create(
|
||||
@@ -1750,7 +1753,7 @@ class DocumentViewSet(
|
||||
"Insufficient permissions to add share link",
|
||||
)
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
if request.method == "GET":
|
||||
now = timezone.now()
|
||||
@@ -1778,7 +1781,7 @@ class DocumentViewSet(
|
||||
"Insufficient permissions",
|
||||
)
|
||||
except Document.DoesNotExist: # pragma: no cover
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
# documents
|
||||
entries = [
|
||||
@@ -1799,28 +1802,28 @@ class DocumentViewSet(
|
||||
]
|
||||
|
||||
# custom fields
|
||||
entries.extend(
|
||||
{
|
||||
"id": entry.id,
|
||||
"timestamp": entry.timestamp,
|
||||
"action": entry.get_action_display(),
|
||||
"changes": {
|
||||
"custom_fields": {
|
||||
"type": "custom_field",
|
||||
"field": str(entry.object_repr).split(":")[0].strip(),
|
||||
"value": str(entry.object_repr).split(":")[1].strip(),
|
||||
for entry in LogEntry.objects.get_for_objects(
|
||||
doc.custom_fields.all(),
|
||||
).select_related("actor"):
|
||||
entries.append(
|
||||
{
|
||||
"id": entry.id,
|
||||
"timestamp": entry.timestamp,
|
||||
"action": entry.get_action_display(),
|
||||
"changes": {
|
||||
"custom_fields": {
|
||||
"type": "custom_field",
|
||||
"field": str(entry.object_repr).split(":")[0].strip(),
|
||||
"value": str(entry.object_repr).split(":")[1].strip(),
|
||||
},
|
||||
},
|
||||
"actor": (
|
||||
{"id": entry.actor.id, "username": entry.actor.username}
|
||||
if entry.actor
|
||||
else None
|
||||
),
|
||||
},
|
||||
"actor": (
|
||||
{"id": entry.actor.id, "username": entry.actor.username}
|
||||
if entry.actor
|
||||
else None
|
||||
),
|
||||
}
|
||||
for entry in LogEntry.objects.get_for_objects(
|
||||
doc.custom_fields.all(),
|
||||
).select_related("actor")
|
||||
)
|
||||
)
|
||||
|
||||
return Response(sorted(entries, key=lambda x: x["timestamp"], reverse=True))
|
||||
|
||||
@@ -1928,13 +1931,13 @@ class DocumentViewSet(
|
||||
):
|
||||
return HttpResponseForbidden("Insufficient permissions")
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
try:
|
||||
doc_name, doc_data = serializer.validated_data.get("document")
|
||||
version_label = serializer.validated_data.get("version_label")
|
||||
|
||||
t = int(timezone.now().timestamp())
|
||||
t = int(mktime(datetime.now().timetuple()))
|
||||
|
||||
settings.SCRATCH_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
@@ -1979,7 +1982,7 @@ class DocumentViewSet(
|
||||
"root_document",
|
||||
).get(pk=pk)
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
return get_root_document(root_doc)
|
||||
|
||||
def _get_version_doc_for_root(self, root_doc: Document, version_id) -> Document:
|
||||
@@ -1988,7 +1991,7 @@ class DocumentViewSet(
|
||||
pk=version_id,
|
||||
)
|
||||
except Document.DoesNotExist:
|
||||
raise Http404 from None
|
||||
raise Http404
|
||||
|
||||
if (
|
||||
version_doc.id != root_doc.id
|
||||
@@ -2274,6 +2277,7 @@ class UnifiedSearchViewSet(DocumentViewSet):
|
||||
return super().list(request)
|
||||
|
||||
from documents.search import SearchHit
|
||||
from documents.search import SearchQueryError
|
||||
from documents.search import TantivyBackend
|
||||
from documents.search import TantivyRelevanceList
|
||||
from documents.search import get_backend
|
||||
@@ -2466,6 +2470,11 @@ class UnifiedSearchViewSet(DocumentViewSet):
|
||||
return HttpResponseForbidden(_("Insufficient permissions."))
|
||||
except ValidationError:
|
||||
raise
|
||||
except SearchQueryError as e:
|
||||
# User-fixable query error (e.g. an unparsable date): surface the
|
||||
# specific message so the user can correct it, rather than a generic
|
||||
# 400 or silently empty results.
|
||||
raise ValidationError({"query": [str(e)]}) from e
|
||||
except Exception as e:
|
||||
logger.warning(f"An error occurred listing search results: {e!s}")
|
||||
return HttpResponseBadRequest(
|
||||
@@ -2543,7 +2552,7 @@ class LogViewSet(ViewSet):
|
||||
try:
|
||||
limit = int(limit_param)
|
||||
except (TypeError, ValueError):
|
||||
raise ValidationError({"limit": "Must be a positive integer"}) from None
|
||||
raise ValidationError({"limit": "Must be a positive integer"})
|
||||
if limit < 1:
|
||||
raise ValidationError({"limit": "Must be a positive integer"})
|
||||
else:
|
||||
@@ -3124,6 +3133,7 @@ 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)
|
||||
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")
|
||||
@@ -3134,7 +3144,7 @@ class PostDocumentView(GenericAPIView[Any]):
|
||||
cf = serializer.validated_data.get("custom_fields")
|
||||
from_webui = serializer.validated_data.get("from_webui")
|
||||
|
||||
t = int(timezone.now().timestamp())
|
||||
t = int(mktime(datetime.now().timetuple()))
|
||||
|
||||
settings.SCRATCH_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
@@ -4009,7 +4019,7 @@ class RemoteVersionView(GenericAPIView[Any]):
|
||||
|
||||
|
||||
class _TasksViewSetSchema(AutoSchema):
|
||||
_UNPAGINATED_ACTIONS = frozenset({"summary", "active"})
|
||||
_UNPAGINATED_ACTIONS = frozenset({"summary", "active", "status_counts"})
|
||||
|
||||
def _get_paginator(self):
|
||||
if getattr(self.view, "action", None) in self._UNPAGINATED_ACTIONS:
|
||||
@@ -4031,7 +4041,7 @@ class _TasksViewSetSchema(AutoSchema):
|
||||
),
|
||||
acknowledge=extend_schema(
|
||||
operation_id="acknowledge_tasks",
|
||||
description="Acknowledge a list of tasks",
|
||||
description="Acknowledge a list of tasks, or all visible unacknowledged tasks",
|
||||
request=AcknowledgeTasksViewSerializer,
|
||||
responses={
|
||||
(200, "application/json"): inline_serializer(
|
||||
@@ -4069,6 +4079,19 @@ class _TasksViewSetSchema(AutoSchema):
|
||||
),
|
||||
],
|
||||
),
|
||||
status_counts=extend_schema(
|
||||
responses={
|
||||
200: inline_serializer(
|
||||
name="TaskStatusCounts",
|
||||
fields={
|
||||
"all": serializers.IntegerField(),
|
||||
"needs_attention": serializers.IntegerField(),
|
||||
"in_progress": serializers.IntegerField(),
|
||||
"completed": serializers.IntegerField(),
|
||||
},
|
||||
),
|
||||
},
|
||||
),
|
||||
active=extend_schema(
|
||||
description="Currently pending and running tasks (capped at 50).",
|
||||
responses={200: TaskSerializerV10(many=True)},
|
||||
@@ -4122,6 +4145,7 @@ class TasksViewSet(ReadOnlyModelViewSet[PaperlessTask]):
|
||||
PaperlessTask.TaskType.SANITY_CHECK: (sanity_check, {"raise_on_error": False}),
|
||||
PaperlessTask.TaskType.LLM_INDEX: (llmindex_index, {"rebuild": False}),
|
||||
}
|
||||
_STATUS_COUNT_EXCLUDED_FILTERS = frozenset({"status", "is_complete"})
|
||||
|
||||
def get_serializer_class(self):
|
||||
# v9: use backwards-compatible serializer with old field names
|
||||
@@ -4162,16 +4186,38 @@ class TasksViewSet(ReadOnlyModelViewSet[PaperlessTask]):
|
||||
queryset = queryset.filter(task_id=task_id)
|
||||
return queryset
|
||||
|
||||
def get_status_count_queryset(self):
|
||||
"""Apply task filters except the status dimensions represented by the counts."""
|
||||
query_params = self.request.query_params.copy()
|
||||
for param in self._STATUS_COUNT_EXCLUDED_FILTERS:
|
||||
query_params.pop(param, None)
|
||||
|
||||
filterset = self.filterset_class(
|
||||
data=query_params,
|
||||
queryset=self.get_queryset(),
|
||||
request=self.request,
|
||||
)
|
||||
if not filterset.is_valid():
|
||||
raise ValidationError(filterset.errors)
|
||||
return filterset.qs
|
||||
|
||||
@action(
|
||||
methods=["post"],
|
||||
detail=False,
|
||||
permission_classes=[IsAuthenticated, AcknowledgeTasksPermissions],
|
||||
)
|
||||
def acknowledge(self, request):
|
||||
serializer = AcknowledgeTasksViewSerializer(data=request.data)
|
||||
queryset = self.get_queryset()
|
||||
serializer = AcknowledgeTasksViewSerializer(
|
||||
data=request.data,
|
||||
context={"queryset": queryset},
|
||||
)
|
||||
serializer.is_valid(raise_exception=True)
|
||||
task_ids = serializer.validated_data.get("tasks")
|
||||
tasks = self.get_queryset().filter(id__in=task_ids)
|
||||
if serializer.validated_data.get("all", False):
|
||||
tasks = queryset.filter(acknowledged=False)
|
||||
else:
|
||||
task_ids = serializer.validated_data.get("tasks")
|
||||
tasks = queryset.filter(id__in=task_ids)
|
||||
count = tasks.update(acknowledged=True)
|
||||
return Response({"result": count})
|
||||
|
||||
@@ -4224,6 +4270,34 @@ class TasksViewSet(ReadOnlyModelViewSet[PaperlessTask]):
|
||||
serializer = TaskSummarySerializer(data, many=True)
|
||||
return Response(serializer.data)
|
||||
|
||||
@action(methods=["get"], detail=False)
|
||||
def status_counts(self, request):
|
||||
"""Aggregated task counts for task UI sections."""
|
||||
queryset = self.get_status_count_queryset()
|
||||
counts = queryset.aggregate(
|
||||
all=Count("id"),
|
||||
needs_attention=Count(
|
||||
"id",
|
||||
filter=Q(
|
||||
status__in=[
|
||||
PaperlessTask.Status.FAILURE,
|
||||
PaperlessTask.Status.REVOKED,
|
||||
],
|
||||
),
|
||||
),
|
||||
in_progress=Count(
|
||||
"id",
|
||||
filter=Q(
|
||||
status__in=[
|
||||
PaperlessTask.Status.PENDING,
|
||||
PaperlessTask.Status.STARTED,
|
||||
],
|
||||
),
|
||||
),
|
||||
completed=Count("id", filter=Q(status=PaperlessTask.Status.SUCCESS)),
|
||||
)
|
||||
return Response(counts)
|
||||
|
||||
@action(methods=["get"], detail=False)
|
||||
def active(self, request):
|
||||
"""Currently pending and running tasks (capped at 50)."""
|
||||
@@ -4923,11 +4997,29 @@ class SystemStatusView(PassUserMixin):
|
||||
celery_error = None
|
||||
celery_url = None
|
||||
try:
|
||||
celery_ping = celery_app.control.inspect().ping()
|
||||
celery_url = next(iter(celery_ping.keys()))
|
||||
first_worker_ping = celery_ping[celery_url]
|
||||
if first_worker_ping["ok"] == "pong":
|
||||
celery_active = "OK"
|
||||
celery_ping = None
|
||||
for ping_attempt in range(3):
|
||||
celery_ping = celery_app.control.inspect().ping()
|
||||
if celery_ping:
|
||||
break
|
||||
if ping_attempt < 2:
|
||||
sleep(0.25)
|
||||
|
||||
if not celery_ping:
|
||||
celery_active = "WARNING"
|
||||
celery_error = (
|
||||
"No celery workers responded to ping. This may be temporary."
|
||||
)
|
||||
else:
|
||||
celery_url, first_worker_ping = next(iter(celery_ping.items()))
|
||||
if (
|
||||
isinstance(first_worker_ping, dict)
|
||||
and first_worker_ping.get("ok") == "pong"
|
||||
):
|
||||
celery_active = "OK"
|
||||
else:
|
||||
celery_active = "WARNING"
|
||||
celery_error = "Celery worker responded unexpectedly."
|
||||
except Exception as e:
|
||||
celery_active = "ERROR"
|
||||
logger.exception(
|
||||
@@ -4946,7 +5038,7 @@ class SystemStatusView(PassUserMixin):
|
||||
index_dir = settings.INDEX_DIR
|
||||
mtimes = [p.stat().st_mtime for p in index_dir.iterdir() if p.is_file()]
|
||||
index_last_modified = (
|
||||
datetime.fromtimestamp(max(mtimes), tz=UTC) if mtimes else None
|
||||
make_aware(datetime.fromtimestamp(max(mtimes))) if mtimes else None
|
||||
)
|
||||
except Exception as e:
|
||||
index_status = "ERROR"
|
||||
|
||||
+13
-14
@@ -84,11 +84,10 @@ def binaries_check(app_configs: Any, **kwargs: Any) -> list[Error]:
|
||||
|
||||
binaries = (settings.CONVERT_BINARY, "tesseract", "gs")
|
||||
|
||||
check_messages = [
|
||||
Warning(error.format(binary), hint)
|
||||
for binary in binaries
|
||||
if shutil.which(binary) is None
|
||||
]
|
||||
check_messages = []
|
||||
for binary in binaries:
|
||||
if shutil.which(binary) is None:
|
||||
check_messages.append(Warning(error.format(binary), hint))
|
||||
|
||||
return check_messages
|
||||
|
||||
@@ -384,14 +383,14 @@ def check_default_language_available(app_configs: Any, **kwargs: Any) -> list[Er
|
||||
|
||||
specified_langs = [x.strip() for x in settings.OCR_LANGUAGE.split("+")]
|
||||
|
||||
errs.extend(
|
||||
Error(
|
||||
f"The selected ocr language {lang} is "
|
||||
f"not installed. Paperless cannot OCR your documents "
|
||||
f"without it. Please fix PAPERLESS_OCR_LANGUAGE.",
|
||||
)
|
||||
for lang in specified_langs
|
||||
if lang not in installed_langs
|
||||
)
|
||||
for lang in specified_langs:
|
||||
if lang not in installed_langs:
|
||||
errs.append(
|
||||
Error(
|
||||
f"The selected ocr language {lang} is "
|
||||
f"not installed. Paperless cannot OCR your documents "
|
||||
f"without it. Please fix PAPERLESS_OCR_LANGUAGE.",
|
||||
),
|
||||
)
|
||||
|
||||
return errs
|
||||
|
||||
@@ -649,10 +649,11 @@ class MailDocumentParser:
|
||||
if data["bcc"]:
|
||||
data["bcc_label"] = "BCC"
|
||||
|
||||
att = [
|
||||
f"{a.filename} ({naturalsize(a.size, binary=True, format='%.2f')})"
|
||||
for a in mail.attachments
|
||||
]
|
||||
att = []
|
||||
for a in mail.attachments:
|
||||
att.append(
|
||||
f"{a.filename} ({naturalsize(a.size, binary=True, format='%.2f')})",
|
||||
)
|
||||
data["attachments"] = clean_html(", ".join(att))
|
||||
if data["attachments"]:
|
||||
data["attachments_label"] = "Attachments"
|
||||
|
||||
@@ -20,6 +20,7 @@ from PIL import Image
|
||||
from PIL import ImageDraw
|
||||
from PIL import ImageFont
|
||||
|
||||
from paperless.parsers.utils import read_file_handle_unicode_errors
|
||||
from paperless.version import __full_version_str__
|
||||
|
||||
if TYPE_CHECKING:
|
||||
@@ -183,7 +184,7 @@ class TextDocumentParser:
|
||||
documents.parsers.ParseError
|
||||
If the file cannot be read.
|
||||
"""
|
||||
self._text = self._read_text(document_path)
|
||||
self._text = read_file_handle_unicode_errors(document_path, log=logger)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Result accessors
|
||||
@@ -295,30 +296,3 @@ class TextDocumentParser:
|
||||
Always ``[]`` — plain text files carry no structured metadata.
|
||||
"""
|
||||
return []
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Private helpers
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def _read_text(self, filepath: Path) -> str:
|
||||
"""Read file content, replacing invalid UTF-8 bytes rather than failing.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
filepath:
|
||||
Path to the file to read.
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
File content as a string.
|
||||
"""
|
||||
try:
|
||||
return filepath.read_text(encoding="utf-8")
|
||||
except UnicodeDecodeError as exc:
|
||||
logger.warning(
|
||||
"Unicode error reading %s, replacing bad bytes: %s",
|
||||
filepath,
|
||||
exc,
|
||||
)
|
||||
return filepath.read_bytes().decode("utf-8", errors="replace")
|
||||
|
||||
@@ -8,6 +8,7 @@ share implementation.
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import codecs
|
||||
import logging
|
||||
import re
|
||||
import tempfile
|
||||
@@ -114,7 +115,7 @@ def read_file_handle_unicode_errors(
|
||||
filepath: Path,
|
||||
log: logging.Logger | None = None,
|
||||
) -> str:
|
||||
"""Read a file as UTF-8 text, replacing invalid bytes rather than raising.
|
||||
"""Read a file as text, detecting encoding via BOM and stripping NUL bytes.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -127,15 +128,27 @@ def read_file_handle_unicode_errors(
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
File content as a string, with any invalid UTF-8 sequences replaced
|
||||
by the Unicode replacement character.
|
||||
File content as a string, with NUL bytes removed so the result is
|
||||
safe to store in PostgreSQL text fields.
|
||||
"""
|
||||
_log = log or logger
|
||||
raw = filepath.read_bytes()
|
||||
|
||||
if raw.startswith((codecs.BOM_UTF16_LE, codecs.BOM_UTF16_BE)):
|
||||
encoding = "utf-16"
|
||||
elif raw.startswith(codecs.BOM_UTF8):
|
||||
encoding = "utf-8-sig"
|
||||
else:
|
||||
encoding = "utf-8"
|
||||
|
||||
try:
|
||||
return filepath.read_text(encoding="utf-8")
|
||||
text = raw.decode(encoding)
|
||||
except UnicodeDecodeError as e:
|
||||
_log.warning("Unicode error during text reading, continuing: %s", e)
|
||||
return filepath.read_bytes().decode("utf-8", errors="replace")
|
||||
text = raw.decode("utf-8", errors="replace")
|
||||
|
||||
# PostgreSQL rejects NUL (0x00) bytes in text fields
|
||||
return text.replace("\x00", "")
|
||||
|
||||
|
||||
def get_page_count_for_pdf(
|
||||
|
||||
@@ -97,8 +97,14 @@ MODEL_FILE = get_path_from_env(
|
||||
DATA_DIR / "classification_model.pickle",
|
||||
)
|
||||
LLM_INDEX_DIR = DATA_DIR / "llm_index"
|
||||
LLM_INDEX_LOCK = DATA_DIR / "locks" / "llm_index.lock"
|
||||
(DATA_DIR / "locks").mkdir(parents=True, exist_ok=True)
|
||||
LLM_INDEX_LOCK = LLM_INDEX_DIR / "index.lock"
|
||||
# Cross-process read/write lock guarding the LLM index compaction/migration
|
||||
# file swap. Readers hold it shared; the swap takes it exclusively so it never
|
||||
# runs while a reader connection is open. Must be a SQLite (.db) file.
|
||||
LLM_INDEX_RWLOCK = LLM_INDEX_DIR / "llmindex.rwlock.db"
|
||||
# Seconds the compaction swap waits for active readers to drain before skipping
|
||||
# this cycle (it is a maintenance operation; the next run retries).
|
||||
LLM_INDEX_COMPACTION_LOCK_TIMEOUT = 30
|
||||
|
||||
LOGGING_DIR = get_path_from_env("PAPERLESS_LOGGING_DIR", DATA_DIR / "log")
|
||||
|
||||
@@ -644,6 +650,7 @@ LOGGING = {
|
||||
"kombu": {"handlers": ["file_celery"], "level": "DEBUG"},
|
||||
"_granian": {"handlers": ["file_paperless"], "level": "DEBUG"},
|
||||
"granian.access": {"handlers": ["file_paperless"], "level": "DEBUG"},
|
||||
"httpx": {"level": "WARNING"},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
@@ -252,6 +252,9 @@ def parse_db_settings(data_dir: Path) -> dict[str, dict[str, Any]]:
|
||||
"NAME": os.getenv("PAPERLESS_DBNAME", "paperless"),
|
||||
"USER": os.getenv("PAPERLESS_DBUSER", "paperless"),
|
||||
"PASSWORD": os.getenv("PAPERLESS_DBPASS", "paperless"),
|
||||
# Validate pooled connections so a connection closed server-side
|
||||
# is replaced rather than handed out as "the connection is closed".
|
||||
"CONN_HEALTH_CHECKS": True,
|
||||
}
|
||||
|
||||
base_options = {
|
||||
@@ -331,7 +334,7 @@ def parse_dateparser_languages(languages: str | None) -> list[str]:
|
||||
language_list = languages.split("+") if languages else []
|
||||
# There is an unfixed issue in zh-Hant and zh-Hans locales in the dateparser lib.
|
||||
# See: https://github.com/scrapinghub/dateparser/issues/875
|
||||
for _, language in enumerate(language_list):
|
||||
for index, language in enumerate(language_list):
|
||||
if language.startswith("zh-") and "zh" not in language_list:
|
||||
logger.warning(
|
||||
f"Chinese locale detected: {language}. dateparser might fail to parse"
|
||||
|
||||
@@ -398,6 +398,7 @@ class TestParseDbSettings:
|
||||
{
|
||||
"default": {
|
||||
"ENGINE": "django.db.backends.postgresql",
|
||||
"CONN_HEALTH_CHECKS": True,
|
||||
"HOST": "localhost",
|
||||
"NAME": "paperless",
|
||||
"USER": "paperless",
|
||||
@@ -426,6 +427,7 @@ class TestParseDbSettings:
|
||||
{
|
||||
"default": {
|
||||
"ENGINE": "django.db.backends.postgresql",
|
||||
"CONN_HEALTH_CHECKS": True,
|
||||
"HOST": "paperless-db-host",
|
||||
"PORT": 1111,
|
||||
"NAME": "customdb",
|
||||
@@ -455,6 +457,7 @@ class TestParseDbSettings:
|
||||
{
|
||||
"default": {
|
||||
"ENGINE": "django.db.backends.postgresql",
|
||||
"CONN_HEALTH_CHECKS": True,
|
||||
"HOST": "pghost",
|
||||
"NAME": "paperless",
|
||||
"USER": "paperless",
|
||||
@@ -485,6 +488,7 @@ class TestParseDbSettings:
|
||||
{
|
||||
"default": {
|
||||
"ENGINE": "django.db.backends.postgresql",
|
||||
"CONN_HEALTH_CHECKS": True,
|
||||
"HOST": "pghost",
|
||||
"NAME": "paperless",
|
||||
"USER": "paperless",
|
||||
|
||||
@@ -2,13 +2,50 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import codecs
|
||||
from pathlib import Path
|
||||
|
||||
from paperless.parsers.utils import is_tagged_pdf
|
||||
from paperless.parsers.utils import read_file_handle_unicode_errors
|
||||
|
||||
SAMPLES = Path(__file__).parent / "samples" / "tesseract"
|
||||
|
||||
|
||||
class TestReadFileHandleUnicodeErrors:
|
||||
def test_plain_utf8(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "plain.txt"
|
||||
f.write_bytes(b"hello world")
|
||||
assert read_file_handle_unicode_errors(f) == "hello world"
|
||||
|
||||
def test_utf8_bom(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "bom.txt"
|
||||
f.write_bytes(codecs.BOM_UTF8 + b"hello")
|
||||
assert read_file_handle_unicode_errors(f) == "hello"
|
||||
|
||||
def test_utf16_le(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "utf16le.txt"
|
||||
f.write_bytes(codecs.BOM_UTF16_LE + "hello".encode("utf-16-le"))
|
||||
assert read_file_handle_unicode_errors(f) == "hello"
|
||||
|
||||
def test_utf16_be(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "utf16be.txt"
|
||||
f.write_bytes(codecs.BOM_UTF16_BE + "hello".encode("utf-16-be"))
|
||||
assert read_file_handle_unicode_errors(f) == "hello"
|
||||
|
||||
def test_nul_bytes_stripped(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "null-bytes.txt"
|
||||
f.write_bytes(b"foo\x00bar")
|
||||
assert read_file_handle_unicode_errors(f) == "foobar"
|
||||
|
||||
def test_invalid_utf8_replaced(self, tmp_path: Path) -> None:
|
||||
f = tmp_path / "bad.txt"
|
||||
f.write_bytes(b"ok\x80\x81bad")
|
||||
result = read_file_handle_unicode_errors(f)
|
||||
assert "ok" in result
|
||||
assert "bad" in result
|
||||
assert "\x00" not in result
|
||||
|
||||
|
||||
class TestIsTaggedPdf:
|
||||
def test_tagged_pdf_returns_true(self) -> None:
|
||||
assert is_tagged_pdf(SAMPLES / "simple-digital.pdf") is True
|
||||
|
||||
@@ -193,7 +193,7 @@ def reject_dangerous_svg(file: UploadedFile) -> None:
|
||||
tree = etree.parse(file, parser)
|
||||
root = tree.getroot()
|
||||
except etree.XMLSyntaxError:
|
||||
raise ValidationError("Invalid SVG file.") from None
|
||||
raise ValidationError("Invalid SVG file.")
|
||||
|
||||
for element in root.iter():
|
||||
tag: str = etree.QName(element.tag).localname.lower()
|
||||
|
||||
@@ -49,7 +49,7 @@ from paperless.serialisers import GroupSerializer
|
||||
from paperless.serialisers import PaperlessAuthTokenSerializer
|
||||
from paperless.serialisers import ProfileSerializer
|
||||
from paperless.serialisers import UserSerializer
|
||||
from paperless_ai.indexing import vector_store_file_exists
|
||||
from paperless_ai.indexing import llm_index_exists
|
||||
|
||||
|
||||
class PaperlessObtainAuthTokenView(ObtainAuthToken):
|
||||
@@ -467,7 +467,7 @@ class ApplicationConfigurationViewSet(ModelViewSet[ApplicationConfiguration]):
|
||||
or old_llm_context_size != new_llm_context_size
|
||||
)
|
||||
rebuild_needed = new_ai_index_enabled and (
|
||||
not vector_store_file_exists() or embedding_config_changed
|
||||
not llm_index_exists() or embedding_config_changed
|
||||
)
|
||||
|
||||
if rebuild_needed:
|
||||
|
||||
@@ -8,6 +8,7 @@ from documents.models import Document
|
||||
from documents.permissions import get_objects_for_user_owner_aware
|
||||
from paperless.config import AIConfig
|
||||
from paperless_ai.client import AIClient
|
||||
from paperless_ai.db import db_connection_released
|
||||
from paperless_ai.indexing import query_similar_documents
|
||||
from paperless_ai.indexing import truncate_content
|
||||
|
||||
@@ -24,9 +25,14 @@ def get_language_name(language_code: str) -> str:
|
||||
|
||||
def build_prompt_without_rag(
|
||||
document: Document,
|
||||
config: AIConfig,
|
||||
) -> str:
|
||||
filename = document.filename or ""
|
||||
content = truncate_content(document.content[:4000] or "")
|
||||
content = truncate_content(
|
||||
document.content[:4000] or "",
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
context_size=config.llm_context_size,
|
||||
)
|
||||
|
||||
return f"""
|
||||
You are a document classification assistant.
|
||||
@@ -49,10 +55,15 @@ def build_prompt_without_rag(
|
||||
|
||||
def build_prompt_with_rag(
|
||||
document: Document,
|
||||
config: AIConfig,
|
||||
user: User | None = None,
|
||||
) -> str:
|
||||
base_prompt = build_prompt_without_rag(document)
|
||||
context = truncate_content(get_context_for_document(document, user))
|
||||
base_prompt = build_prompt_without_rag(document, config)
|
||||
context = truncate_content(
|
||||
get_context_for_document(document, user),
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
context_size=config.llm_context_size,
|
||||
)
|
||||
|
||||
return f"""{base_prompt}
|
||||
|
||||
@@ -130,26 +141,29 @@ def get_ai_document_classification(
|
||||
ai_config = AIConfig()
|
||||
|
||||
prompt = (
|
||||
build_prompt_with_rag(document, user)
|
||||
build_prompt_with_rag(document, ai_config, user)
|
||||
if ai_config.llm_embedding_backend
|
||||
else build_prompt_without_rag(document)
|
||||
else build_prompt_without_rag(document, ai_config)
|
||||
)
|
||||
|
||||
client = AIClient()
|
||||
result = client.run_llm_query(prompt)
|
||||
suggestions = parse_ai_response(result)
|
||||
if output_language:
|
||||
localized = client.run_llm_query(
|
||||
build_localization_prompt(suggestions, output_language),
|
||||
)
|
||||
localized_suggestions = parse_ai_response(localized)
|
||||
suggestions = {
|
||||
**suggestions,
|
||||
"title": localized_suggestions["title"] or suggestions["title"],
|
||||
"tags": localized_suggestions["tags"] or suggestions["tags"],
|
||||
"document_types": localized_suggestions["document_types"]
|
||||
or suggestions["document_types"],
|
||||
"storage_paths": localized_suggestions["storage_paths"]
|
||||
or suggestions["storage_paths"],
|
||||
}
|
||||
# Hand the pooled DB connection back while the (slow) LLM query runs so it
|
||||
# is not pinned for the call's duration; see paperless_ai.db and #12976.
|
||||
with db_connection_released():
|
||||
result = client.run_llm_query(prompt)
|
||||
suggestions = parse_ai_response(result)
|
||||
if output_language:
|
||||
localized = client.run_llm_query(
|
||||
build_localization_prompt(suggestions, output_language),
|
||||
)
|
||||
localized_suggestions = parse_ai_response(localized)
|
||||
suggestions = {
|
||||
**suggestions,
|
||||
"title": localized_suggestions["title"] or suggestions["title"],
|
||||
"tags": localized_suggestions["tags"] or suggestions["tags"],
|
||||
"document_types": localized_suggestions["document_types"]
|
||||
or suggestions["document_types"],
|
||||
"storage_paths": localized_suggestions["storage_paths"]
|
||||
or suggestions["storage_paths"],
|
||||
}
|
||||
return suggestions
|
||||
|
||||
+56
-122
@@ -3,9 +3,13 @@ import logging
|
||||
import sys
|
||||
|
||||
from documents.models import Document
|
||||
from paperless.config import AIConfig
|
||||
from paperless_ai.client import AIClient
|
||||
from paperless_ai.db import db_connection_released
|
||||
from paperless_ai.indexing import _document_id_filters
|
||||
from paperless_ai.indexing import get_rag_prompt_helper
|
||||
from paperless_ai.indexing import load_or_build_index
|
||||
from paperless_ai.indexing import read_store
|
||||
|
||||
logger = logging.getLogger("paperless_ai.chat")
|
||||
|
||||
@@ -75,82 +79,6 @@ def _format_chat_metadata_trailer(references: list[dict[str, int | str]]) -> str
|
||||
)
|
||||
|
||||
|
||||
def _get_document_filtered_retriever(index, doc_ids: set[str], similarity_top_k: int):
|
||||
from llama_index.core.base.base_retriever import BaseRetriever
|
||||
from llama_index.core.schema import NodeWithScore
|
||||
from llama_index.core.vector_stores import VectorStoreQuery
|
||||
|
||||
class DocumentFilteredFaissRetriever(BaseRetriever):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._cached_query_str = None
|
||||
self._cached_nodes = []
|
||||
|
||||
def _retrieve(self, query_bundle):
|
||||
if query_bundle.query_str == self._cached_query_str:
|
||||
return self._cached_nodes
|
||||
|
||||
if query_bundle.embedding is None:
|
||||
query_bundle.embedding = (
|
||||
index._embed_model.get_agg_embedding_from_queries(
|
||||
query_bundle.embedding_strs,
|
||||
)
|
||||
)
|
||||
|
||||
faiss_index = index.vector_store._faiss_index
|
||||
max_top_k = faiss_index.ntotal
|
||||
if max_top_k == 0:
|
||||
self._cached_query_str = query_bundle.query_str
|
||||
self._cached_nodes = []
|
||||
return []
|
||||
|
||||
query_top_k = min(max(similarity_top_k, 1), max_top_k)
|
||||
allowed_nodes: list[NodeWithScore] = []
|
||||
seen_node_ids: set[str] = set()
|
||||
|
||||
while query_top_k <= max_top_k:
|
||||
query_result = index.vector_store.query(
|
||||
VectorStoreQuery(
|
||||
query_embedding=query_bundle.embedding,
|
||||
similarity_top_k=query_top_k,
|
||||
),
|
||||
)
|
||||
|
||||
for vector_id, score in zip(
|
||||
query_result.ids or [],
|
||||
query_result.similarities or [],
|
||||
strict=False,
|
||||
):
|
||||
node_id = index.index_struct.nodes_dict.get(vector_id)
|
||||
if node_id is None or node_id in seen_node_ids:
|
||||
continue
|
||||
|
||||
node = index.docstore.docs.get(node_id)
|
||||
if node is None or node.metadata.get("document_id") not in doc_ids:
|
||||
continue
|
||||
|
||||
seen_node_ids.add(node_id)
|
||||
allowed_nodes.append(NodeWithScore(node=node, score=score))
|
||||
|
||||
if len(allowed_nodes) >= similarity_top_k:
|
||||
self._cached_query_str = query_bundle.query_str
|
||||
self._cached_nodes = allowed_nodes
|
||||
return allowed_nodes
|
||||
|
||||
if query_top_k == max_top_k:
|
||||
self._cached_query_str = query_bundle.query_str
|
||||
self._cached_nodes = allowed_nodes
|
||||
return allowed_nodes
|
||||
|
||||
query_top_k = min(query_top_k * 2, max_top_k)
|
||||
|
||||
self._cached_query_str = query_bundle.query_str
|
||||
self._cached_nodes = allowed_nodes
|
||||
return allowed_nodes
|
||||
|
||||
return DocumentFilteredFaissRetriever()
|
||||
|
||||
|
||||
def stream_chat_with_documents(query_str: str, documents: list[Document]):
|
||||
try:
|
||||
yield from _stream_chat_with_documents(query_str, documents)
|
||||
@@ -160,63 +88,69 @@ def stream_chat_with_documents(query_str: str, documents: list[Document]):
|
||||
|
||||
|
||||
def _stream_chat_with_documents(query_str: str, documents: list[Document]):
|
||||
client = AIClient()
|
||||
index = load_or_build_index()
|
||||
|
||||
doc_ids = [str(doc.pk) for doc in documents]
|
||||
|
||||
# Filter only the node(s) that match the document IDs
|
||||
nodes = [
|
||||
node
|
||||
for node in index.docstore.docs.values()
|
||||
if node.metadata.get("document_id") in doc_ids
|
||||
]
|
||||
|
||||
if len(nodes) == 0:
|
||||
logger.warning("No nodes found for the given documents.")
|
||||
if not documents:
|
||||
yield CHAT_NO_CONTENT_MESSAGE
|
||||
return
|
||||
|
||||
from llama_index.core.prompts import PromptTemplate
|
||||
from llama_index.core.query_engine import RetrieverQueryEngine
|
||||
from llama_index.core.response_synthesizers import get_response_synthesizer
|
||||
from llama_index.core.retrievers import VectorIndexRetriever
|
||||
|
||||
retriever = _get_document_filtered_retriever(
|
||||
index,
|
||||
set(doc_ids),
|
||||
CHAT_RETRIEVER_TOP_K,
|
||||
)
|
||||
config = AIConfig()
|
||||
filters = _document_id_filters(str(doc.pk) for doc in documents)
|
||||
|
||||
top_nodes = retriever.retrieve(query_str)
|
||||
if len(top_nodes) == 0:
|
||||
logger.warning("Retriever returned no nodes for the given documents.")
|
||||
yield CHAT_NO_CONTENT_MESSAGE
|
||||
return
|
||||
# Hold the shared read lock for the whole operation: the query engine
|
||||
# retrieves from the vector store again during synthesis, so the connection
|
||||
# must stay open (and the swap must not run) until the stream finishes.
|
||||
with read_store() as store:
|
||||
index = load_or_build_index(config, store)
|
||||
retriever = VectorIndexRetriever(
|
||||
index=index,
|
||||
similarity_top_k=CHAT_RETRIEVER_TOP_K,
|
||||
filters=filters,
|
||||
)
|
||||
|
||||
references = _get_document_references(documents, top_nodes)
|
||||
# Slow query-embedding + vector search; no Django ORM access happens
|
||||
# during it, so release the pooled DB connection for its duration. See
|
||||
# #12976.
|
||||
with db_connection_released():
|
||||
top_nodes = retriever.retrieve(query_str)
|
||||
if not top_nodes:
|
||||
logger.warning("No nodes found for the given documents.")
|
||||
yield CHAT_NO_CONTENT_MESSAGE
|
||||
return
|
||||
|
||||
prompt_template = PromptTemplate(template=CHAT_PROMPT_TMPL)
|
||||
response_synthesizer = get_response_synthesizer(
|
||||
llm=client.llm,
|
||||
prompt_helper=get_rag_prompt_helper(),
|
||||
text_qa_template=prompt_template,
|
||||
streaming=True,
|
||||
)
|
||||
client = AIClient()
|
||||
|
||||
query_engine = RetrieverQueryEngine.from_args(
|
||||
retriever=retriever,
|
||||
llm=client.llm,
|
||||
response_synthesizer=response_synthesizer,
|
||||
streaming=True,
|
||||
)
|
||||
references = _get_document_references(documents, top_nodes)
|
||||
|
||||
logger.debug("Document chat query: %s", query_str)
|
||||
prompt_template = PromptTemplate(template=CHAT_PROMPT_TMPL)
|
||||
response_synthesizer = get_response_synthesizer(
|
||||
llm=client.llm,
|
||||
prompt_helper=get_rag_prompt_helper(
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
context_size=config.llm_context_size,
|
||||
),
|
||||
text_qa_template=prompt_template,
|
||||
streaming=True,
|
||||
)
|
||||
query_engine = RetrieverQueryEngine.from_args(
|
||||
retriever=retriever,
|
||||
llm=client.llm,
|
||||
response_synthesizer=response_synthesizer,
|
||||
streaming=True,
|
||||
)
|
||||
|
||||
response_stream = query_engine.query(query_str)
|
||||
logger.debug("Document chat query: %s", query_str)
|
||||
# Release the pooled DB connection for the slow streaming LLM response
|
||||
# so it is not pinned for the whole stream; see paperless_ai.db and
|
||||
# #12976.
|
||||
with db_connection_released():
|
||||
response_stream = query_engine.query(query_str)
|
||||
for chunk in response_stream.response_gen:
|
||||
yield chunk
|
||||
sys.stdout.flush()
|
||||
|
||||
for chunk in response_stream.response_gen:
|
||||
yield chunk
|
||||
sys.stdout.flush()
|
||||
|
||||
if references:
|
||||
yield _format_chat_metadata_trailer(references)
|
||||
if references:
|
||||
yield _format_chat_metadata_trailer(references)
|
||||
|
||||
@@ -0,0 +1,30 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from contextlib import contextmanager
|
||||
|
||||
from django.db import connections
|
||||
|
||||
|
||||
@contextmanager
|
||||
def db_connection_released():
|
||||
"""
|
||||
Return any checked-out DB connections to the pool for the duration of the
|
||||
wrapped block.
|
||||
|
||||
The AI endpoints run inside a synchronous web request (``ai_suggestions``)
|
||||
or a streaming response (``chat``). Django keeps the request's database
|
||||
connection checked out for the entire request/response, so a blocking LLM
|
||||
call - which can take many seconds - pins a pooled connection the whole
|
||||
time. With connection pooling enabled, enough concurrent AI requests check
|
||||
out every slot and all other requests then fail with
|
||||
``psycopg_pool.PoolTimeout`` (see issue #12976).
|
||||
|
||||
No Django ORM access happens during the LLM call, so we hand the connection
|
||||
back to the pool first; Django transparently re-checks-out a connection on
|
||||
the next ORM use after the block.
|
||||
"""
|
||||
connections.close_all()
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
connections.close_all()
|
||||
@@ -1,12 +1,9 @@
|
||||
import json
|
||||
import re
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from django.conf import settings
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from pathlib import Path
|
||||
|
||||
from llama_index.core.base.embeddings.base import BaseEmbedding
|
||||
|
||||
from documents.models import Document
|
||||
@@ -23,9 +20,7 @@ OCR_LEADER_REGEX = re.compile(r"[._\-\u00b7]{4,}")
|
||||
HORIZONTAL_WHITESPACE_REGEX = re.compile(r"[ \t\u00a0]+")
|
||||
|
||||
|
||||
def get_embedding_model() -> "BaseEmbedding":
|
||||
config = AIConfig()
|
||||
|
||||
def get_embedding_model(config: AIConfig) -> "BaseEmbedding":
|
||||
match config.llm_embedding_backend:
|
||||
case LLMEmbeddingBackend.OPENAI_LIKE:
|
||||
from llama_index.embeddings.openai_like import OpenAILikeEmbedding
|
||||
@@ -95,41 +90,24 @@ def get_embedding_model() -> "BaseEmbedding":
|
||||
)
|
||||
|
||||
|
||||
def get_embedding_dim() -> int:
|
||||
"""
|
||||
Loads embedding dimension from meta.json if available, otherwise infers it
|
||||
from a dummy embedding and stores it for future use.
|
||||
"""
|
||||
config = AIConfig()
|
||||
default_model = {
|
||||
LLMEmbeddingBackend.OPENAI_LIKE: "text-embedding-3-small",
|
||||
LLMEmbeddingBackend.HUGGINGFACE: "sentence-transformers/all-MiniLM-L6-v2",
|
||||
LLMEmbeddingBackend.OLLAMA: "embeddinggemma",
|
||||
}.get(
|
||||
config.llm_embedding_backend,
|
||||
"sentence-transformers/all-MiniLM-L6-v2",
|
||||
_DEFAULT_MODEL_NAMES = {
|
||||
LLMEmbeddingBackend.OPENAI_LIKE: "text-embedding-3-small",
|
||||
LLMEmbeddingBackend.HUGGINGFACE: "sentence-transformers/all-MiniLM-L6-v2",
|
||||
LLMEmbeddingBackend.OLLAMA: "embeddinggemma",
|
||||
}
|
||||
|
||||
|
||||
def get_configured_model_name(config: AIConfig) -> str:
|
||||
"""Return the canonical name of the currently configured embedding model."""
|
||||
# dict.get(key, default) overload resolution fails for TextChoices keys in some
|
||||
# type checkers; use `or` fallback to avoid the ambiguity.
|
||||
default = (
|
||||
_DEFAULT_MODEL_NAMES.get(
|
||||
config.llm_embedding_backend,
|
||||
)
|
||||
or "sentence-transformers/all-MiniLM-L6-v2"
|
||||
)
|
||||
model = config.llm_embedding_model or default_model
|
||||
|
||||
meta_path: Path = settings.LLM_INDEX_DIR / "meta.json"
|
||||
if meta_path.exists():
|
||||
with meta_path.open() as f:
|
||||
meta = json.load(f)
|
||||
if meta.get("embedding_model") != model:
|
||||
raise RuntimeError(
|
||||
f"Embedding model changed from {meta.get('embedding_model')} to {model}. "
|
||||
"You must rebuild the index.",
|
||||
)
|
||||
return meta["dim"]
|
||||
|
||||
embedding_model = get_embedding_model()
|
||||
test_embed = embedding_model.get_text_embedding("test")
|
||||
dim = len(test_embed)
|
||||
|
||||
with meta_path.open("w") as f:
|
||||
json.dump({"embedding_model": model, "dim": dim}, f)
|
||||
|
||||
return dim
|
||||
return config.llm_embedding_model or default
|
||||
|
||||
|
||||
def _normalize_llm_index_text(text: str) -> str:
|
||||
@@ -138,24 +116,16 @@ def _normalize_llm_index_text(text: str) -> str:
|
||||
|
||||
|
||||
def build_llm_index_text(doc: Document) -> str:
|
||||
# Short structured fields (filename, storage path, ASN, title, tags, ...) live
|
||||
# in node.metadata: excluded from embeddings, shown to the LLM via metadata
|
||||
# prepend. Notes and Custom Fields stay in the body: Notes can be long free
|
||||
# text, Custom Fields are dynamic in count and best kept in the embedding.
|
||||
lines = [
|
||||
f"Title: {doc.title}",
|
||||
f"Filename: {doc.filename}",
|
||||
f"Created: {doc.created}",
|
||||
f"Added: {doc.added}",
|
||||
f"Modified: {doc.modified}",
|
||||
f"Tags: {', '.join(tag.name for tag in doc.tags.all())}",
|
||||
f"Document Type: {doc.document_type.name if doc.document_type else ''}",
|
||||
f"Correspondent: {doc.correspondent.name if doc.correspondent else ''}",
|
||||
f"Storage Path: {doc.storage_path.name if doc.storage_path else ''}",
|
||||
f"Archive Serial Number: {doc.archive_serial_number or ''}",
|
||||
f"Notes: {','.join([str(c.note) for c in Note.objects.filter(document=doc)])}",
|
||||
]
|
||||
|
||||
lines.extend(
|
||||
f"Custom Field - {instance.field.name}: {instance}"
|
||||
for instance in doc.custom_fields.all()
|
||||
)
|
||||
for instance in doc.custom_fields.all():
|
||||
lines.append(f"Custom Field - {instance.field.name}: {instance}")
|
||||
|
||||
lines.append("\nContent:\n")
|
||||
lines.append(doc.content or "")
|
||||
|
||||
+269
-243
@@ -1,28 +1,30 @@
|
||||
import logging
|
||||
import shutil
|
||||
from collections import defaultdict
|
||||
from collections.abc import Iterable
|
||||
from contextlib import contextmanager
|
||||
from datetime import timedelta
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from django.conf import settings
|
||||
from django.utils import timezone
|
||||
from filelock import FileLock
|
||||
from filelock import ReadWriteLock
|
||||
from filelock import Timeout
|
||||
|
||||
from documents.models import Document
|
||||
from documents.models import PaperlessTask
|
||||
from documents.utils import IterWrapper
|
||||
from documents.utils import identity
|
||||
from paperless.config import AIConfig
|
||||
from paperless_ai.db import db_connection_released
|
||||
from paperless_ai.embedding import build_llm_index_text
|
||||
from paperless_ai.embedding import get_embedding_dim
|
||||
from paperless_ai.embedding import get_configured_model_name
|
||||
from paperless_ai.embedding import get_embedding_model
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from llama_index.core import VectorStoreIndex
|
||||
from llama_index.core.schema import BaseNode
|
||||
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
|
||||
logger = logging.getLogger("paperless_ai.indexing")
|
||||
|
||||
@@ -30,21 +32,11 @@ RAG_NUM_OUTPUT = 512
|
||||
RAG_CHUNK_OVERLAP = 200
|
||||
|
||||
|
||||
def _index_lock_path() -> Path:
|
||||
"""Return the path used as the file lock for FAISS index mutations.
|
||||
|
||||
The lock file lives in DATA_DIR/locks/ (not inside LLM_INDEX_DIR) so that a
|
||||
rebuild — which calls shutil.rmtree(LLM_INDEX_DIR) — cannot delete the lock
|
||||
while another worker still holds it.
|
||||
"""
|
||||
return settings.LLM_INDEX_LOCK
|
||||
|
||||
|
||||
def queue_llm_index_update_if_needed(*, rebuild: bool, reason: str) -> bool:
|
||||
# NOTE: The check-then-enqueue sequence below is non-atomic (TOCTOU): two
|
||||
# concurrent workers can both observe no running task and both enqueue a
|
||||
# full rebuild. This is wasteful but not data-corrupting — update_llm_index
|
||||
# is itself protected by _index_lock_path(), so only one rebuild runs at a
|
||||
# is itself protected by settings.LLM_INDEX_LOCK, so only one rebuild runs at a
|
||||
# time and the second one is serialised after the first completes.
|
||||
from documents.tasks import llmindex_index
|
||||
|
||||
@@ -71,46 +63,110 @@ def queue_llm_index_update_if_needed(*, rebuild: bool, reason: str) -> bool:
|
||||
return True
|
||||
|
||||
|
||||
def get_or_create_storage_context(*, rebuild=False):
|
||||
"""
|
||||
Loads or creates the StorageContext (vector store, docstore, index store).
|
||||
If rebuild=True, deletes and recreates everything.
|
||||
"""
|
||||
if rebuild:
|
||||
shutil.rmtree(settings.LLM_INDEX_DIR, ignore_errors=True)
|
||||
settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
def get_vector_store() -> "PaperlessSqliteVecVectorStore":
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
if rebuild or not settings.LLM_INDEX_DIR.exists():
|
||||
import faiss
|
||||
from llama_index.core import StorageContext
|
||||
from llama_index.core.storage.docstore import SimpleDocumentStore
|
||||
from llama_index.core.storage.index_store import SimpleIndexStore
|
||||
from llama_index.vector_stores.faiss import FaissVectorStore
|
||||
|
||||
settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
embedding_dim = get_embedding_dim()
|
||||
faiss_index = faiss.IndexFlatL2(embedding_dim)
|
||||
vector_store = FaissVectorStore(faiss_index=faiss_index)
|
||||
docstore = SimpleDocumentStore()
|
||||
index_store = SimpleIndexStore()
|
||||
else:
|
||||
from llama_index.core import StorageContext
|
||||
from llama_index.core.storage.docstore import SimpleDocumentStore
|
||||
from llama_index.core.storage.index_store import SimpleIndexStore
|
||||
from llama_index.vector_stores.faiss import FaissVectorStore
|
||||
|
||||
vector_store = FaissVectorStore.from_persist_dir(settings.LLM_INDEX_DIR)
|
||||
docstore = SimpleDocumentStore.from_persist_dir(settings.LLM_INDEX_DIR)
|
||||
index_store = SimpleIndexStore.from_persist_dir(settings.LLM_INDEX_DIR)
|
||||
|
||||
return StorageContext.from_defaults(
|
||||
docstore=docstore,
|
||||
index_store=index_store,
|
||||
vector_store=vector_store,
|
||||
persist_dir=settings.LLM_INDEX_DIR,
|
||||
settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
return PaperlessSqliteVecVectorStore(
|
||||
uri=str(settings.LLM_INDEX_DIR),
|
||||
)
|
||||
|
||||
|
||||
# --- LLM index locking ---------------------------------------------------
|
||||
#
|
||||
# Two locks guard the index; they answer different questions and are NOT
|
||||
# interchangeable:
|
||||
#
|
||||
# * settings.LLM_INDEX_LOCK (FileLock, exclusive) -- serializes WRITERS against
|
||||
# each other, so only one rebuild/upsert/delete/compaction runs at a time.
|
||||
# Taken by write_store(). Readers never take it, so it never blocks reads.
|
||||
#
|
||||
# * settings.LLM_INDEX_RWLOCK (ReadWriteLock) -- coordinates readers against the
|
||||
# compaction/migration file swap. read_store() takes it SHARED (readers run
|
||||
# concurrently); _exclude_readers() takes it EXCLUSIVE, only for the swap, so
|
||||
# the database file is never replaced while a reader connection is open (that
|
||||
# would alias the old WAL onto the new file and corrupt it).
|
||||
#
|
||||
# | vs another writer | vs a reader
|
||||
# -----------------+-------------------+----------------------------
|
||||
# normal write | LLM_INDEX_LOCK | nothing (WAL gives MVCC)
|
||||
# compaction/swap | LLM_INDEX_LOCK | LLM_INDEX_RWLOCK (exclusive)
|
||||
# reader | nothing (WAL) | LLM_INDEX_RWLOCK (shared)
|
||||
#
|
||||
# They can't be merged into one ReadWriteLock: a normal write must exclude other
|
||||
# writers WITHOUT blocking readers (WAL already gives reader/writer concurrency),
|
||||
# and ReadWriteLock has no "exclusive vs writers, shared vs readers" mode. Only
|
||||
# the swap needs to exclude readers.
|
||||
def _index_rwlock() -> ReadWriteLock:
|
||||
"""Return a fresh read/write lock instance for the index swap.
|
||||
|
||||
``is_singleton=False`` so reads and the swap always coordinate through
|
||||
SQLite (the actual cross-process case) rather than hitting the in-process
|
||||
reentrant-upgrade guard; callers must ``close()`` it (the context managers
|
||||
below do).
|
||||
"""
|
||||
settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
return ReadWriteLock(str(settings.LLM_INDEX_RWLOCK), is_singleton=False)
|
||||
|
||||
|
||||
@contextmanager
|
||||
def read_store():
|
||||
"""Acquire the shared read lock and yield the vector store for a read.
|
||||
|
||||
The shared lock is held for the whole lifetime of the connection (and
|
||||
closed on exit) so the compaction/migration swap, which takes the exclusive
|
||||
lock, never runs while this connection is open. Concurrent readers do not
|
||||
block each other; only the swap does.
|
||||
"""
|
||||
lock = _index_rwlock()
|
||||
try:
|
||||
with lock.read_lock(), get_vector_store() as store:
|
||||
yield store
|
||||
finally:
|
||||
lock.close()
|
||||
|
||||
|
||||
@contextmanager
|
||||
def _exclude_readers():
|
||||
"""Acquire exclusive index access, blocking until readers have drained.
|
||||
|
||||
The exclusive counterpart to ``read_store()``: a compaction or migration
|
||||
must not run while any reader connection is open. Raises
|
||||
:class:`filelock.Timeout` if active readers do not drain within
|
||||
``LLM_INDEX_COMPACTION_LOCK_TIMEOUT``; callers skip the operation on timeout.
|
||||
"""
|
||||
lock = _index_rwlock()
|
||||
try:
|
||||
with lock.write_lock(timeout=settings.LLM_INDEX_COMPACTION_LOCK_TIMEOUT):
|
||||
yield
|
||||
finally:
|
||||
lock.close()
|
||||
|
||||
|
||||
@contextmanager
|
||||
def write_store(embed_model_name: str | None = None):
|
||||
"""Acquire the write lock and yield the vector store.
|
||||
|
||||
All mutating operations (upsert, delete, rebuild, compact) must go through
|
||||
this context manager to serialise concurrent Celery writers.
|
||||
Read paths use ``read_store()`` so they hold the shared read lock.
|
||||
|
||||
Pass ``embed_model_name`` whenever the operation may create the table so
|
||||
the model name is recorded in the schema metadata for future mismatch checks.
|
||||
"""
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
|
||||
with (
|
||||
FileLock(settings.LLM_INDEX_LOCK),
|
||||
PaperlessSqliteVecVectorStore(
|
||||
uri=str(settings.LLM_INDEX_DIR),
|
||||
embed_model_name=embed_model_name,
|
||||
) as store,
|
||||
):
|
||||
yield store
|
||||
|
||||
|
||||
def build_document_node(
|
||||
document: Document,
|
||||
*,
|
||||
@@ -130,6 +186,9 @@ def build_document_node(
|
||||
"document_type": document.document_type.name
|
||||
if document.document_type
|
||||
else None,
|
||||
"filename": document.filename,
|
||||
"storage_path": document.storage_path.name if document.storage_path else None,
|
||||
"archive_serial_number": document.archive_serial_number,
|
||||
"created": document.created.isoformat() if document.created else None,
|
||||
"added": document.added.isoformat() if document.added else None,
|
||||
"modified": document.modified.isoformat(),
|
||||
@@ -142,9 +201,11 @@ def build_document_node(
|
||||
# the token count and exceed embedding models with small context windows
|
||||
# (e.g. nomic-embed-text via Ollama defaults to num_ctx=2048).
|
||||
doc = LlamaDocument(
|
||||
id_=str(document.id),
|
||||
text=text,
|
||||
metadata=metadata,
|
||||
excluded_embed_metadata_keys=list(metadata.keys()),
|
||||
excluded_llm_metadata_keys=["document_id"],
|
||||
)
|
||||
chunk_size = chunk_size or get_rag_chunk_size()
|
||||
parser = SimpleNodeParser(
|
||||
@@ -154,76 +215,33 @@ def build_document_node(
|
||||
return parser.get_nodes_from_documents([doc])
|
||||
|
||||
|
||||
def load_or_build_index(nodes=None):
|
||||
"""
|
||||
Load an existing VectorStoreIndex if present,
|
||||
or build a new one using provided nodes if storage is empty.
|
||||
def load_or_build_index(config: AIConfig, store: "PaperlessSqliteVecVectorStore"):
|
||||
"""Return a VectorStoreIndex backed by ``store``.
|
||||
|
||||
``store`` is supplied by the caller's ``read_store()`` context so the shared
|
||||
read lock and the connection stay alive for the whole retrieval.
|
||||
"""
|
||||
import llama_index.core.settings as llama_settings
|
||||
from llama_index.core import VectorStoreIndex
|
||||
from llama_index.core import load_index_from_storage
|
||||
|
||||
embed_model = get_embedding_model()
|
||||
embed_model = get_embedding_model(config)
|
||||
llama_settings.Settings.embed_model = embed_model
|
||||
storage_context = get_or_create_storage_context()
|
||||
try:
|
||||
return load_index_from_storage(storage_context=storage_context)
|
||||
except ValueError as e:
|
||||
logger.warning("Failed to load index from storage: %s", e)
|
||||
if not nodes:
|
||||
queue_llm_index_update_if_needed(
|
||||
rebuild=vector_store_file_exists(),
|
||||
reason="LLM index missing or invalid while loading.",
|
||||
)
|
||||
logger.info("No nodes provided for index creation.")
|
||||
raise
|
||||
return VectorStoreIndex(
|
||||
nodes=nodes,
|
||||
storage_context=storage_context,
|
||||
embed_model=embed_model,
|
||||
)
|
||||
return VectorStoreIndex.from_vector_store(
|
||||
vector_store=store,
|
||||
embed_model=embed_model,
|
||||
)
|
||||
|
||||
|
||||
def remove_document_docstore_nodes(document: Document, index: "VectorStoreIndex"):
|
||||
"""
|
||||
Removes existing documents from docstore for a given document from the index.
|
||||
This is necessary because FAISS IndexFlatL2 is append-only.
|
||||
"""
|
||||
all_node_ids = list(index.docstore.docs.keys())
|
||||
existing_nodes = [
|
||||
node.node_id
|
||||
for node in index.docstore.get_nodes(all_node_ids)
|
||||
if node.metadata.get("document_id") == str(document.id)
|
||||
]
|
||||
for node_id in existing_nodes:
|
||||
# Delete from docstore, FAISS IndexFlatL2 are append-only
|
||||
index.docstore.delete_document(node_id)
|
||||
# Also purge the FAISS position -> UUID mapping so subsequent similarity
|
||||
# queries don't raise KeyError on ghost vector positions.
|
||||
stale_keys = [
|
||||
k for k, v in index.index_struct.nodes_dict.items() if v == node_id
|
||||
]
|
||||
for key in stale_keys:
|
||||
del index.index_struct.nodes_dict[key]
|
||||
# Re-sync the mutated index_struct so persist() writes the updated nodes_dict.
|
||||
index.storage_context.index_store.add_index_struct(index.index_struct)
|
||||
|
||||
|
||||
def vector_store_file_exists():
|
||||
"""
|
||||
Check if the vector store file exists in the LLM index directory.
|
||||
"""
|
||||
return Path(settings.LLM_INDEX_DIR / "default__vector_store.json").exists()
|
||||
def llm_index_exists() -> bool:
|
||||
"""True when the index table exists on disk."""
|
||||
with read_store() as store:
|
||||
return store.table_exists()
|
||||
|
||||
|
||||
def get_rag_chunk_size() -> int:
|
||||
return AIConfig().llm_embedding_chunk_size
|
||||
|
||||
|
||||
def get_rag_context_size() -> int:
|
||||
return AIConfig().llm_context_size
|
||||
|
||||
|
||||
def get_rag_chunk_overlap(chunk_size: int | None = None) -> int:
|
||||
chunk_size = chunk_size or get_rag_chunk_size()
|
||||
return min(RAG_CHUNK_OVERLAP, chunk_size - 1)
|
||||
@@ -249,123 +267,149 @@ def get_rag_prompt_helper(
|
||||
)
|
||||
|
||||
|
||||
def _embed_nodes(nodes: list["BaseNode"], embed_model) -> None:
|
||||
"""Embed ``nodes`` in place using ``embed_model``."""
|
||||
from llama_index.core.schema import MetadataMode
|
||||
|
||||
texts = [n.get_content(metadata_mode=MetadataMode.EMBED) for n in nodes]
|
||||
for node, emb in zip(
|
||||
nodes,
|
||||
embed_model.get_text_embedding_batch(texts),
|
||||
strict=True,
|
||||
):
|
||||
node.embedding = emb
|
||||
|
||||
|
||||
def _document_id_filters(doc_ids):
|
||||
"""Return a MetadataFilters IN filter scoped to ``doc_ids``."""
|
||||
from llama_index.core.vector_stores.types import FilterOperator
|
||||
from llama_index.core.vector_stores.types import MetadataFilter
|
||||
from llama_index.core.vector_stores.types import MetadataFilters
|
||||
|
||||
return MetadataFilters(
|
||||
filters=[
|
||||
MetadataFilter(
|
||||
key="document_id",
|
||||
operator=FilterOperator.IN,
|
||||
value=sorted(doc_ids),
|
||||
),
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
def update_llm_index(
|
||||
*,
|
||||
iter_wrapper: IterWrapper[Document] = identity,
|
||||
rebuild=False,
|
||||
) -> str:
|
||||
"""
|
||||
Rebuild or update the LLM index.
|
||||
"""
|
||||
from llama_index.core import VectorStoreIndex
|
||||
|
||||
nodes = []
|
||||
|
||||
"""Rebuild or incrementally update the LLM index."""
|
||||
with write_store() as store:
|
||||
try:
|
||||
with _exclude_readers():
|
||||
needs_reembed = store.check_and_run_migrations()
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index migration check: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
needs_reembed = False
|
||||
if needs_reembed:
|
||||
logger.warning(
|
||||
"LLM index migration requires re-embedding; forcing rebuild.",
|
||||
)
|
||||
rebuild = True
|
||||
documents = Document.objects.all()
|
||||
if not documents.exists():
|
||||
no_documents = not documents.exists()
|
||||
|
||||
# Fast exit before touching config: nothing to index and no existing index.
|
||||
if no_documents and not rebuild and not llm_index_exists():
|
||||
logger.warning("No documents found to index.")
|
||||
if not rebuild and not vector_store_file_exists():
|
||||
return "No documents found to index."
|
||||
return "No documents found to index."
|
||||
|
||||
config = AIConfig()
|
||||
model_name = get_configured_model_name(config)
|
||||
|
||||
if not rebuild and llm_index_exists():
|
||||
with read_store() as store:
|
||||
config_mismatch = store.config_mismatch(model_name)
|
||||
if config_mismatch:
|
||||
logger.warning("Embedding model changed; forcing LLM index rebuild.")
|
||||
rebuild = True
|
||||
|
||||
if no_documents:
|
||||
logger.warning("No documents found to index.")
|
||||
|
||||
chunk_size = config.llm_embedding_chunk_size
|
||||
embed_model = get_embedding_model(config)
|
||||
|
||||
with FileLock(_index_lock_path()):
|
||||
if rebuild or not vector_store_file_exists():
|
||||
# remove meta.json to force re-detection of embedding dim
|
||||
(settings.LLM_INDEX_DIR / "meta.json").unlink(missing_ok=True)
|
||||
# Rebuild index from scratch
|
||||
with write_store(embed_model_name=model_name) as store:
|
||||
if rebuild or not store.table_exists():
|
||||
logger.info("Rebuilding LLM index.")
|
||||
import llama_index.core.settings as llama_settings
|
||||
|
||||
embed_model = get_embedding_model()
|
||||
llama_settings.Settings.embed_model = embed_model
|
||||
storage_context = get_or_create_storage_context(rebuild=True)
|
||||
store.drop_table()
|
||||
for document in iter_wrapper(documents):
|
||||
document_nodes = build_document_node(document, chunk_size=chunk_size)
|
||||
nodes.extend(document_nodes)
|
||||
|
||||
index = VectorStoreIndex(
|
||||
nodes=nodes,
|
||||
storage_context=storage_context,
|
||||
embed_model=embed_model,
|
||||
show_progress=False,
|
||||
)
|
||||
nodes = build_document_node(document, chunk_size=chunk_size)
|
||||
_embed_nodes(nodes, embed_model)
|
||||
store.add(nodes)
|
||||
msg = "LLM index rebuilt successfully."
|
||||
else:
|
||||
# Update existing index
|
||||
index = load_or_build_index()
|
||||
existing_nodes: defaultdict[str, list] = defaultdict(list)
|
||||
for node in index.docstore.docs.values():
|
||||
doc_id = node.metadata.get("document_id")
|
||||
if doc_id is not None:
|
||||
existing_nodes[doc_id].append(node)
|
||||
|
||||
existing = store.get_modified_times()
|
||||
changed = 0
|
||||
for document in iter_wrapper(documents):
|
||||
doc_id = str(document.id)
|
||||
document_modified = document.modified.isoformat()
|
||||
if existing.get(doc_id) == document.modified.isoformat():
|
||||
continue
|
||||
nodes = build_document_node(document, chunk_size=chunk_size)
|
||||
_embed_nodes(nodes, embed_model)
|
||||
store.upsert_document(doc_id, nodes)
|
||||
changed += 1
|
||||
msg = (
|
||||
"LLM index updated successfully."
|
||||
if changed
|
||||
else "No changes detected in LLM index."
|
||||
)
|
||||
|
||||
if doc_id in existing_nodes:
|
||||
doc_nodes = existing_nodes[doc_id]
|
||||
node_modified = doc_nodes[0].metadata.get("modified")
|
||||
|
||||
if node_modified == document_modified:
|
||||
continue
|
||||
|
||||
# Delete from docstore, FAISS IndexFlatL2 are append-only
|
||||
for _ in doc_nodes:
|
||||
remove_document_docstore_nodes(document, index)
|
||||
|
||||
nodes.extend(build_document_node(document, chunk_size=chunk_size))
|
||||
|
||||
if nodes:
|
||||
msg = "LLM index updated successfully."
|
||||
logger.info(
|
||||
"Updating %d nodes in LLM index.",
|
||||
len(nodes),
|
||||
)
|
||||
index.insert_nodes(nodes)
|
||||
else:
|
||||
msg = "No changes detected in LLM index."
|
||||
logger.info(msg)
|
||||
|
||||
index.storage_context.persist(persist_dir=settings.LLM_INDEX_DIR)
|
||||
try:
|
||||
with _exclude_readers():
|
||||
store.compact()
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index compaction: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
return msg
|
||||
|
||||
|
||||
def llm_index_add_or_update_document(document: Document):
|
||||
"""
|
||||
Adds or updates a document in the LLM index.
|
||||
If the document already exists, it will be replaced.
|
||||
"""
|
||||
new_nodes = build_document_node(document, chunk_size=get_rag_chunk_size())
|
||||
if not new_nodes:
|
||||
logger.warning(
|
||||
"No indexable content for document %s; skipping LLM index update.",
|
||||
document.pk,
|
||||
)
|
||||
return
|
||||
"""Add or atomically replace a document's chunks in the index."""
|
||||
config = AIConfig()
|
||||
new_nodes = build_document_node(
|
||||
document,
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
)
|
||||
if new_nodes:
|
||||
_embed_nodes(new_nodes, get_embedding_model(config))
|
||||
|
||||
with FileLock(_index_lock_path()):
|
||||
index = load_or_build_index(nodes=new_nodes)
|
||||
with write_store(embed_model_name=get_configured_model_name(config)) as store:
|
||||
store.upsert_document(str(document.id), new_nodes)
|
||||
|
||||
remove_document_docstore_nodes(document, index)
|
||||
|
||||
index.insert_nodes(new_nodes)
|
||||
|
||||
index.storage_context.persist(persist_dir=settings.LLM_INDEX_DIR)
|
||||
def llm_index_compact() -> None:
|
||||
"""Compact the index immediately, rebuilding the table to reclaim space."""
|
||||
with write_store() as store:
|
||||
try:
|
||||
with _exclude_readers():
|
||||
store.compact(force=True)
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index compaction: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
|
||||
|
||||
def llm_index_remove_document(document: Document):
|
||||
"""
|
||||
Removes a document from the LLM index.
|
||||
"""
|
||||
with FileLock(_index_lock_path()):
|
||||
index = load_or_build_index()
|
||||
|
||||
remove_document_docstore_nodes(document, index)
|
||||
|
||||
index.storage_context.persist(persist_dir=settings.LLM_INDEX_DIR)
|
||||
"""Remove a document's chunks from the LLM index."""
|
||||
with write_store() as store:
|
||||
store.delete(str(document.id))
|
||||
|
||||
|
||||
def truncate_content(
|
||||
@@ -410,77 +454,59 @@ def query_similar_documents(
|
||||
top_k: int = 5,
|
||||
document_ids: Iterable[int | str] | None = None,
|
||||
) -> list[Document]:
|
||||
"""
|
||||
Runs a similarity query and returns top-k similar Document objects.
|
||||
"""
|
||||
"""Return up to ``top_k`` Documents most similar to ``document``."""
|
||||
allowed_document_ids = normalize_document_ids(document_ids)
|
||||
if allowed_document_ids is not None and not allowed_document_ids:
|
||||
return []
|
||||
|
||||
if not vector_store_file_exists():
|
||||
if not llm_index_exists():
|
||||
queue_llm_index_update_if_needed(
|
||||
rebuild=False,
|
||||
reason="LLM index not found for similarity query.",
|
||||
)
|
||||
return []
|
||||
|
||||
with FileLock(_index_lock_path()):
|
||||
index = load_or_build_index()
|
||||
config = AIConfig()
|
||||
|
||||
# constrain only the node(s) that match the document IDs, if given
|
||||
doc_node_ids = (
|
||||
[
|
||||
node.node_id
|
||||
for node in index.docstore.docs.values()
|
||||
if node.metadata.get("document_id") in allowed_document_ids
|
||||
]
|
||||
if allowed_document_ids is not None
|
||||
else None
|
||||
)
|
||||
if doc_node_ids is not None and not doc_node_ids:
|
||||
return []
|
||||
from llama_index.core.retrievers import VectorIndexRetriever
|
||||
|
||||
from llama_index.core.retrievers import VectorIndexRetriever
|
||||
filters = (
|
||||
_document_id_filters(allowed_document_ids)
|
||||
if allowed_document_ids is not None
|
||||
else None
|
||||
)
|
||||
|
||||
query_text = truncate_content(
|
||||
(document.title or "") + "\n" + (document.content or ""),
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
context_size=config.llm_context_size,
|
||||
)
|
||||
# Hold the shared read lock for the whole retrieval so the connection is
|
||||
# never open across a compaction swap. The retrieve() call generates a
|
||||
# query embedding (a slow external request) and searches the vector store;
|
||||
# no Django ORM access happens during it, so release the pooled DB
|
||||
# connection for its duration. See #12976.
|
||||
with read_store() as store:
|
||||
index = load_or_build_index(config, store)
|
||||
retriever = VectorIndexRetriever(
|
||||
index=index,
|
||||
similarity_top_k=top_k,
|
||||
doc_ids=doc_node_ids,
|
||||
filters=filters,
|
||||
)
|
||||
|
||||
config = AIConfig()
|
||||
query_text = truncate_content(
|
||||
(document.title or "") + "\n" + (document.content or ""),
|
||||
chunk_size=config.llm_embedding_chunk_size,
|
||||
context_size=config.llm_context_size,
|
||||
)
|
||||
try:
|
||||
with db_connection_released():
|
||||
results = retriever.retrieve(query_text)
|
||||
except KeyError as e:
|
||||
# Ghost FAISS positions remain after deletion because IndexFlatL2 is
|
||||
# append-only. Treat them as absent and return no results.
|
||||
logger.debug(
|
||||
"Skipping LLM similarity query for document %s due to a stale "
|
||||
"FAISS position with no docstore node: %s",
|
||||
document.pk,
|
||||
e,
|
||||
)
|
||||
return []
|
||||
|
||||
retrieved_document_ids: list[int] = []
|
||||
for node in results:
|
||||
document_id = node.metadata.get("document_id")
|
||||
if document_id is None:
|
||||
continue
|
||||
normalized_document_id = str(document_id)
|
||||
if (
|
||||
allowed_document_ids is not None
|
||||
and normalized_document_id not in allowed_document_ids
|
||||
):
|
||||
normalized = str(document_id)
|
||||
if allowed_document_ids is not None and normalized not in allowed_document_ids:
|
||||
continue
|
||||
try:
|
||||
retrieved_document_ids.append(int(normalized_document_id))
|
||||
except ValueError:
|
||||
retrieved_document_ids.append(int(normalized))
|
||||
except ValueError: # pragma: no cover
|
||||
logger.warning(
|
||||
"Skipping LLM index result with invalid document_id %r.",
|
||||
document_id,
|
||||
|
||||
@@ -1,10 +1,36 @@
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
import pytest_mock
|
||||
from llama_index.core.base.embeddings.base import BaseEmbedding
|
||||
from pytest_django.fixtures import SettingsWrapper
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def temp_llm_index_dir(tmp_path: Path, settings: SettingsWrapper):
|
||||
def temp_llm_index_dir(tmp_path: Path, settings: SettingsWrapper) -> Path:
|
||||
settings.LLM_INDEX_DIR = tmp_path
|
||||
settings.LLM_INDEX_LOCK = tmp_path / "index.lock"
|
||||
settings.LLM_INDEX_RWLOCK = tmp_path / "llmindex.rwlock.db"
|
||||
return tmp_path
|
||||
|
||||
|
||||
class FakeEmbedding(BaseEmbedding):
|
||||
async def _aget_query_embedding(self, query: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def _get_query_embedding(self, query: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def _get_text_embedding(self, text: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def get_query_embedding_dim(self) -> int:
|
||||
return 384
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_embed_model(mocker: pytest_mock.MockerFixture) -> pytest_mock.MockType:
|
||||
fake = FakeEmbedding()
|
||||
mocker.patch("paperless_ai.indexing.get_embedding_model", return_value=fake)
|
||||
mocker.patch("paperless_ai.embedding.get_embedding_model", return_value=fake)
|
||||
return fake
|
||||
|
||||
@@ -6,6 +6,7 @@ import pytest
|
||||
from django.test import override_settings
|
||||
|
||||
from documents.models import Document
|
||||
from paperless.config import AIConfig
|
||||
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
|
||||
@@ -155,7 +156,7 @@ def test_get_ai_document_classification_failure(mock_run_llm_query, mock_documen
|
||||
mock_run_llm_query.side_effect = Exception("LLM query failed")
|
||||
|
||||
# assert raises an exception
|
||||
with pytest.raises(ValueError, match="Unsupported LLM backend"):
|
||||
with pytest.raises(Exception):
|
||||
get_ai_document_classification(mock_document)
|
||||
|
||||
|
||||
@@ -211,11 +212,12 @@ def test_prompt_with_without_rag(mock_document):
|
||||
"paperless_ai.ai_classifier.get_context_for_document",
|
||||
return_value="Context from similar documents",
|
||||
):
|
||||
prompt = build_prompt_without_rag(mock_document)
|
||||
config = AIConfig()
|
||||
prompt = build_prompt_without_rag(mock_document, config)
|
||||
assert "Additional context from similar documents" not in prompt
|
||||
assert "for generated" not in prompt
|
||||
|
||||
prompt = build_prompt_with_rag(mock_document)
|
||||
prompt = build_prompt_with_rag(mock_document, config)
|
||||
assert "Additional context from similar documents" in prompt
|
||||
|
||||
prompt = build_localization_prompt(
|
||||
|
||||
@@ -1,15 +1,12 @@
|
||||
import json
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
import pytest_mock
|
||||
from django.contrib.auth.models import User
|
||||
from django.test import override_settings
|
||||
from django.utils import timezone
|
||||
from faker import Faker
|
||||
from llama_index.core.base.embeddings.base import BaseEmbedding
|
||||
from llama_index.core.schema import MetadataMode
|
||||
|
||||
from documents.models import Document
|
||||
from documents.models import PaperlessTask
|
||||
@@ -19,10 +16,12 @@ from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.factories import PaperlessTaskFactory
|
||||
from paperless.models import ApplicationConfiguration
|
||||
from paperless_ai import indexing
|
||||
from paperless_ai.tests.conftest import FakeEmbedding
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def real_document(db):
|
||||
def real_document(db: None) -> Document:
|
||||
return Document.objects.create(
|
||||
title="Test Document",
|
||||
content="This is some test content.",
|
||||
@@ -30,44 +29,39 @@ def real_document(db):
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_embed_model():
|
||||
fake = FakeEmbedding()
|
||||
with (
|
||||
patch("paperless_ai.indexing.get_embedding_model") as mock_index,
|
||||
patch(
|
||||
"paperless_ai.embedding.get_embedding_model",
|
||||
) as mock_embedding,
|
||||
):
|
||||
mock_index.return_value = fake
|
||||
mock_embedding.return_value = fake
|
||||
yield mock_index
|
||||
|
||||
|
||||
class FakeEmbedding(BaseEmbedding):
|
||||
# TODO: maybe a better way to do this?
|
||||
def _aget_query_embedding(self, query: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def _get_query_embedding(self, query: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def _get_text_embedding(self, text: str) -> list[float]:
|
||||
return [0.1] * self.get_query_embedding_dim()
|
||||
|
||||
def get_query_embedding_dim(self) -> int:
|
||||
return 384 # Match your real FAISS config
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node(real_document) -> None:
|
||||
def test_build_document_node(real_document: Document) -> None:
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
assert len(nodes) > 0
|
||||
assert nodes[0].metadata["document_id"] == str(real_document.id)
|
||||
assert nodes[0].metadata["filename"] == real_document.filename
|
||||
assert nodes[0].metadata["storage_path"] == (
|
||||
real_document.storage_path.name if real_document.storage_path else None
|
||||
)
|
||||
assert (
|
||||
nodes[0].metadata["archive_serial_number"]
|
||||
== real_document.archive_serial_number
|
||||
)
|
||||
assert "filename" in nodes[0].excluded_embed_metadata_keys
|
||||
assert "filename" not in nodes[0].excluded_llm_metadata_keys
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node_excludes_metadata_from_embedding(real_document) -> None:
|
||||
def test_build_document_node_sets_ref_doc_id(real_document: Document) -> None:
|
||||
"""Every node produced by build_document_node must carry the paperless document id
|
||||
as its ref_doc_id so that the vector store's delete(str(doc.id)) works correctly."""
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
assert len(nodes) > 0, "Expected at least one node"
|
||||
for node in nodes:
|
||||
assert node.ref_doc_id == str(real_document.id), (
|
||||
f"Expected ref_doc_id={real_document.id!r}, got {node.ref_doc_id!r}"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node_excludes_metadata_from_embedding(
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
"""Metadata keys must not be prepended to the embedding text.
|
||||
|
||||
build_llm_index_text already encodes all metadata in the body text, so
|
||||
@@ -75,8 +69,6 @@ def test_build_document_node_excludes_metadata_from_embedding(real_document) ->
|
||||
double the token count and exceed embedding models with small context
|
||||
windows (e.g. nomic-embed-text via Ollama defaults to num_ctx=2048).
|
||||
"""
|
||||
from llama_index.core.schema import MetadataMode
|
||||
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
for node in nodes:
|
||||
embed_text = node.get_content(metadata_mode=MetadataMode.EMBED)
|
||||
@@ -87,7 +79,36 @@ def test_build_document_node_excludes_metadata_from_embedding(real_document) ->
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node_uses_rag_chunk_settings(real_document) -> None:
|
||||
def test_build_document_node_structured_fields_in_metadata(
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
"""Structured fields must be in node.metadata so the LLM receives them via metadata prepend."""
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
assert len(nodes) > 0
|
||||
for node in nodes:
|
||||
assert "title" in node.metadata
|
||||
assert "tags" in node.metadata
|
||||
assert "correspondent" in node.metadata
|
||||
assert "document_type" in node.metadata
|
||||
assert "created" in node.metadata
|
||||
assert "added" in node.metadata
|
||||
assert "modified" in node.metadata
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node_excludes_document_id_from_llm_context(
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
"""document_id is an internal key and must not appear in LLM context text."""
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
assert len(nodes) > 0
|
||||
for node in nodes:
|
||||
assert "document_id" in node.excluded_llm_metadata_keys
|
||||
assert "document_id" not in node.get_content(metadata_mode=MetadataMode.LLM)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node_uses_rag_chunk_settings(real_document: Document) -> None:
|
||||
app_config, _ = ApplicationConfiguration.objects.get_or_create()
|
||||
app_config.llm_embedding_chunk_size = 512
|
||||
app_config.save()
|
||||
@@ -118,9 +139,9 @@ def test_get_rag_prompt_helper_uses_context_setting() -> None:
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_update_llm_index(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
mock_config = MagicMock()
|
||||
mock_config.llm_embedding_chunk_size = 512
|
||||
@@ -138,44 +159,49 @@ def test_update_llm_index(
|
||||
|
||||
ai_config.assert_called_once()
|
||||
build_document_node.assert_called_once_with(real_document, chunk_size=512)
|
||||
assert any(temp_llm_index_dir.glob("*.json"))
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_update_llm_index_removes_meta(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
def test_update_llm_index_rebuilds_on_model_name_change(
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
# Pre-create a meta.json with incorrect data
|
||||
(temp_llm_index_dir / "meta.json").write_text(
|
||||
json.dumps({"embedding_model": "old", "dim": 1}),
|
||||
)
|
||||
|
||||
# Build initial index with model "model-a".
|
||||
with patch("documents.models.Document.objects.all") as mock_all:
|
||||
mock_queryset = MagicMock()
|
||||
mock_queryset.exists.return_value = True
|
||||
mock_queryset.__iter__.return_value = iter([real_document])
|
||||
mock_all.return_value = mock_queryset
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
with patch(
|
||||
"paperless_ai.indexing.get_configured_model_name",
|
||||
return_value="model-a",
|
||||
):
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
meta = json.loads((temp_llm_index_dir / "meta.json").read_text())
|
||||
from paperless.config import AIConfig
|
||||
# Simulate config change to "model-b"; the incremental run must force a rebuild.
|
||||
with patch("documents.models.Document.objects.all") as mock_all:
|
||||
mock_queryset = MagicMock()
|
||||
mock_queryset.exists.return_value = True
|
||||
mock_queryset.__iter__.return_value = iter([real_document])
|
||||
mock_all.return_value = mock_queryset
|
||||
with patch(
|
||||
"paperless_ai.indexing.get_configured_model_name",
|
||||
return_value="model-b",
|
||||
):
|
||||
indexing.update_llm_index(rebuild=False)
|
||||
|
||||
config = AIConfig()
|
||||
expected_model = config.llm_embedding_model or (
|
||||
"text-embedding-3-small"
|
||||
if config.llm_embedding_backend == "openai-like"
|
||||
else "sentence-transformers/all-MiniLM-L6-v2"
|
||||
)
|
||||
assert meta == {"embedding_model": expected_model, "dim": 384}
|
||||
with indexing.get_vector_store() as store:
|
||||
# Schema metadata only updates when the table is dropped and recreated, never
|
||||
# on incremental writes -- so "model-b" here proves a full rebuild happened.
|
||||
assert store.stored_model_name() == "model-b"
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_update_llm_index_partial_update(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
doc2 = Document.objects.create(
|
||||
title="Test Document 2",
|
||||
@@ -210,131 +236,34 @@ def test_update_llm_index_partial_update(
|
||||
mock_queryset.__iter__.return_value = iter([updated_document, doc2, doc3])
|
||||
mock_all.return_value = mock_queryset
|
||||
|
||||
# assert logs "Updating LLM index with %d new nodes and removing %d old nodes."
|
||||
with patch("paperless_ai.indexing.logger") as mock_logger:
|
||||
indexing.update_llm_index(rebuild=False)
|
||||
mock_logger.info.assert_called_once_with(
|
||||
"Updating %d nodes in LLM index.",
|
||||
2,
|
||||
)
|
||||
indexing.update_llm_index(rebuild=False)
|
||||
|
||||
assert any(temp_llm_index_dir.glob("*.json"))
|
||||
|
||||
|
||||
def test_get_or_create_storage_context_raises_exception(
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
with pytest.raises(ValueError):
|
||||
indexing.get_or_create_storage_context(rebuild=False)
|
||||
|
||||
|
||||
@override_settings(
|
||||
LLM_EMBEDDING_BACKEND="huggingface",
|
||||
)
|
||||
def test_load_or_build_index_builds_when_nodes_given(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
with (
|
||||
patch(
|
||||
"llama_index.core.load_index_from_storage",
|
||||
side_effect=ValueError("Index not found"),
|
||||
),
|
||||
patch(
|
||||
"llama_index.core.VectorStoreIndex",
|
||||
return_value=MagicMock(),
|
||||
) as mock_index_cls,
|
||||
patch(
|
||||
"paperless_ai.indexing.get_or_create_storage_context",
|
||||
return_value=MagicMock(),
|
||||
) as mock_storage,
|
||||
):
|
||||
mock_storage.return_value.persist_dir = temp_llm_index_dir
|
||||
indexing.load_or_build_index(
|
||||
nodes=[indexing.build_document_node(real_document)],
|
||||
with indexing.get_vector_store() as store:
|
||||
assert store.table_exists(), (
|
||||
"Expected the vector store table to exist after incremental update"
|
||||
)
|
||||
mock_index_cls.assert_called_once()
|
||||
|
||||
|
||||
def test_load_or_build_index_raises_exception_when_no_nodes(
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
with (
|
||||
patch(
|
||||
"llama_index.core.load_index_from_storage",
|
||||
side_effect=ValueError("Index not found"),
|
||||
),
|
||||
patch(
|
||||
"paperless_ai.indexing.get_or_create_storage_context",
|
||||
return_value=MagicMock(),
|
||||
),
|
||||
):
|
||||
with pytest.raises(Exception): # noqa: B017
|
||||
indexing.load_or_build_index()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_load_or_build_index_succeeds_when_nodes_given(
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
with (
|
||||
patch(
|
||||
"llama_index.core.load_index_from_storage",
|
||||
side_effect=ValueError("Index not found"),
|
||||
),
|
||||
patch(
|
||||
"llama_index.core.VectorStoreIndex",
|
||||
return_value=MagicMock(),
|
||||
) as mock_index_cls,
|
||||
patch(
|
||||
"paperless_ai.indexing.get_or_create_storage_context",
|
||||
return_value=MagicMock(),
|
||||
) as mock_storage,
|
||||
):
|
||||
mock_storage.return_value.persist_dir = temp_llm_index_dir
|
||||
indexing.load_or_build_index(
|
||||
nodes=[MagicMock()],
|
||||
)
|
||||
mock_index_cls.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_add_or_update_document_updates_existing_entry(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
indexing.llm_index_add_or_update_document(real_document)
|
||||
|
||||
assert any(temp_llm_index_dir.glob("*.json"))
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_remove_document_deletes_node_from_docstore(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
index = indexing.load_or_build_index()
|
||||
assert len(index.docstore.docs) == 1
|
||||
|
||||
indexing.llm_index_remove_document(real_document)
|
||||
index = indexing.load_or_build_index()
|
||||
assert len(index.docstore.docs) == 0
|
||||
with indexing.get_vector_store() as store:
|
||||
assert store.table_exists(), (
|
||||
"Expected the vector store table to exist after add-or-update"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_query_after_remove_does_not_raise_key_error(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
mock_embed_model,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
@@ -352,8 +281,8 @@ def test_query_after_remove_does_not_raise_key_error(
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_update_llm_index_no_documents(
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
with patch("documents.models.Document.objects.all") as mock_all:
|
||||
mock_queryset = MagicMock()
|
||||
@@ -369,6 +298,22 @@ def test_update_llm_index_no_documents(
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_update_no_documents_no_index_returns_early(
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""update with no documents and no existing index must return early."""
|
||||
mock_qs = MagicMock()
|
||||
mock_qs.exists.return_value = False
|
||||
mock_qs.__iter__ = MagicMock(return_value=iter([]))
|
||||
mocker.patch("paperless_ai.indexing.Document.objects.all", return_value=mock_qs)
|
||||
|
||||
result = indexing.update_llm_index(rebuild=False)
|
||||
|
||||
assert result == "No documents found to index."
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_queue_llm_index_update_if_needed_enqueues_when_idle_or_skips_recent() -> None:
|
||||
# No existing tasks
|
||||
@@ -406,20 +351,17 @@ def test_queue_llm_index_update_if_needed_enqueues_when_idle_or_skips_recent() -
|
||||
LLM_BACKEND="ollama",
|
||||
)
|
||||
def test_query_similar_documents(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
with (
|
||||
patch("paperless_ai.indexing.get_or_create_storage_context") as mock_storage,
|
||||
patch("paperless_ai.indexing.load_or_build_index") as mock_load_or_build_index,
|
||||
patch(
|
||||
"paperless_ai.indexing.vector_store_file_exists",
|
||||
"paperless_ai.indexing.llm_index_exists",
|
||||
) as mock_vector_store_exists,
|
||||
patch("llama_index.core.retrievers.VectorIndexRetriever") as mock_retriever_cls,
|
||||
patch("paperless_ai.indexing.Document.objects.filter") as mock_filter,
|
||||
):
|
||||
mock_storage.return_value = MagicMock()
|
||||
mock_storage.return_value.persist_dir = temp_llm_index_dir
|
||||
mock_vector_store_exists.return_value = True
|
||||
|
||||
mock_index = MagicMock()
|
||||
@@ -453,12 +395,12 @@ def test_query_similar_documents(
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_query_similar_documents_triggers_update_when_index_missing(
|
||||
temp_llm_index_dir,
|
||||
real_document,
|
||||
temp_llm_index_dir: Path,
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
with (
|
||||
patch(
|
||||
"paperless_ai.indexing.vector_store_file_exists",
|
||||
"paperless_ai.indexing.llm_index_exists",
|
||||
return_value=False,
|
||||
),
|
||||
patch(
|
||||
@@ -479,120 +421,13 @@ def test_query_similar_documents_triggers_update_when_index_missing(
|
||||
assert result == []
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_query_similar_documents_normalizes_and_post_filters_allowed_ids(
|
||||
real_document,
|
||||
) -> None:
|
||||
real_document.owner = User.objects.create_user(username="rag-owner")
|
||||
real_document.save()
|
||||
private_owner = User.objects.create_user(username="rag-private-owner")
|
||||
private_document = Document.objects.create(
|
||||
title="Private similar document",
|
||||
content="Similar private content that must not reach RAG.",
|
||||
owner=private_owner,
|
||||
added=timezone.now(),
|
||||
)
|
||||
|
||||
with (
|
||||
patch(
|
||||
"paperless_ai.indexing.vector_store_file_exists",
|
||||
return_value=True,
|
||||
),
|
||||
patch("paperless_ai.indexing.load_or_build_index") as mock_load_or_build_index,
|
||||
patch("llama_index.core.retrievers.VectorIndexRetriever") as mock_retriever_cls,
|
||||
):
|
||||
allowed_node = MagicMock()
|
||||
allowed_node.node_id = "allowed-node"
|
||||
allowed_node.metadata = {"document_id": str(real_document.pk)}
|
||||
private_node = MagicMock()
|
||||
private_node.node_id = "private-node"
|
||||
private_node.metadata = {"document_id": str(private_document.pk)}
|
||||
|
||||
mock_index = MagicMock()
|
||||
mock_index.docstore.docs.values.return_value = [allowed_node, private_node]
|
||||
mock_load_or_build_index.return_value = mock_index
|
||||
|
||||
mock_retriever = MagicMock()
|
||||
mock_retriever.retrieve.return_value = [private_node, allowed_node]
|
||||
mock_retriever_cls.return_value = mock_retriever
|
||||
|
||||
result = indexing.query_similar_documents(
|
||||
real_document,
|
||||
top_k=2,
|
||||
document_ids=[real_document.pk],
|
||||
)
|
||||
|
||||
mock_retriever_cls.assert_called_once_with(
|
||||
index=mock_index,
|
||||
similarity_top_k=2,
|
||||
doc_ids=["allowed-node"],
|
||||
)
|
||||
assert result == [real_document]
|
||||
assert private_document not in result
|
||||
|
||||
|
||||
class TestUpdateLlmIndexStaleNodes:
|
||||
"""Tests that update_llm_index removes ALL nodes for a multi-chunk document."""
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_incremental_update_removes_all_old_nodes_for_multi_chunk_document(
|
||||
self,
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model: MagicMock,
|
||||
) -> None:
|
||||
"""Ghost nodes from all chunks of a modified document must be removed.
|
||||
|
||||
When a document is split into multiple chunks (chunk_size=1024), the
|
||||
incremental update path must delete every old node, not just the last
|
||||
one captured by a dict comprehension keyed on document_id.
|
||||
"""
|
||||
# Content long enough to produce at least two chunks at chunk_size=1024.
|
||||
# Generate many paragraphs so the token count comfortably exceeds 1024.
|
||||
fake = Faker()
|
||||
long_content = "\n\n".join(fake.paragraph(nb_sentences=20) for _ in range(20))
|
||||
doc = DocumentFactory(content=long_content)
|
||||
|
||||
# Build the initial index (rebuild=True) so it has multiple nodes
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
# Verify the initial index has more than one node for this document
|
||||
initial_index = indexing.load_or_build_index()
|
||||
initial_node_ids = [
|
||||
nid
|
||||
for nid, node in initial_index.docstore.docs.items()
|
||||
if node.metadata.get("document_id") == str(doc.id)
|
||||
]
|
||||
assert len(initial_node_ids) > 1, (
|
||||
f"Expected multiple chunks but got {len(initial_node_ids)}; "
|
||||
"increase long_content length"
|
||||
)
|
||||
|
||||
# Simulate a modification so the incremental path treats it as changed.
|
||||
# Use queryset.update() to bypass auto_now and actually change the DB value.
|
||||
new_modified = timezone.now()
|
||||
Document.objects.filter(pk=doc.pk).update(modified=new_modified)
|
||||
|
||||
# Run incremental update (rebuild=False) with the modified document
|
||||
indexing.update_llm_index(rebuild=False)
|
||||
|
||||
# Reload the persisted index and check that no OLD node ids remain
|
||||
updated_index = indexing.load_or_build_index()
|
||||
remaining_old_node_ids = [
|
||||
nid for nid in initial_node_ids if nid in updated_index.docstore.docs
|
||||
]
|
||||
assert remaining_old_node_ids == [], (
|
||||
f"Ghost nodes still present after incremental update: "
|
||||
f"{remaining_old_node_ids}"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_query_similar_documents_empty_allow_list_fails_closed(
|
||||
real_document,
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
with (
|
||||
patch(
|
||||
"paperless_ai.indexing.vector_store_file_exists",
|
||||
"paperless_ai.indexing.llm_index_exists",
|
||||
return_value=True,
|
||||
) as mock_vector_store_exists,
|
||||
patch("paperless_ai.indexing.load_or_build_index") as mock_load_or_build_index,
|
||||
@@ -610,27 +445,25 @@ def test_query_similar_documents_empty_allow_list_fails_closed(
|
||||
|
||||
|
||||
class TestUpdateLlmIndexEmptyDocumentSet:
|
||||
"""update_llm_index must persist an empty index when all documents are deleted.
|
||||
"""update_llm_index must clear the vector store table when all documents are deleted.
|
||||
|
||||
Without this, the stale on-disk FAISS vectors are never cleared and
|
||||
subsequent similarity searches return phantom hits for document IDs that
|
||||
no longer exist in the DB.
|
||||
Without this, the stale vectors are never cleared and subsequent similarity
|
||||
searches return phantom hits for document IDs that no longer exist in the DB.
|
||||
"""
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_rebuild_clears_stale_index_when_no_documents_exist(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: MagicMock,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
"""After deleting all documents, rebuild=True must persist an empty index.
|
||||
"""After deleting all documents, rebuild=True must produce a table with zero rows.
|
||||
|
||||
Steps:
|
||||
1. Build an index with one document so the on-disk state is non-empty.
|
||||
2. Delete all documents from the DB.
|
||||
3. Call update_llm_index(rebuild=True).
|
||||
4. Reload the index from disk.
|
||||
5. Assert the reloaded index has zero nodes (no phantom vectors).
|
||||
4. Open the LanceDB table directly and assert zero rows.
|
||||
"""
|
||||
# Step 1: create a document and build a non-empty index
|
||||
Document.objects.create(
|
||||
@@ -640,27 +473,26 @@ class TestUpdateLlmIndexEmptyDocumentSet:
|
||||
)
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
initial_index = indexing.load_or_build_index()
|
||||
assert len(initial_index.docstore.docs) > 0, (
|
||||
"Precondition failed: expected at least one node before deletion"
|
||||
)
|
||||
with indexing.get_vector_store() as store:
|
||||
assert store.table_exists(), (
|
||||
"Precondition failed: expected the vector store table to exist "
|
||||
"before deletion"
|
||||
)
|
||||
|
||||
# Step 2: delete all documents
|
||||
Document.objects.all().delete()
|
||||
assert not Document.objects.exists()
|
||||
|
||||
# Step 3: rebuild with no documents
|
||||
# Step 3: rebuild with no documents — drop_table is called so the table
|
||||
# is removed (no rows to re-insert, so it stays absent).
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
# Step 4: reload the persisted index from disk
|
||||
reloaded_index = indexing.load_or_build_index()
|
||||
|
||||
# Step 5: phantom vectors must be gone
|
||||
assert len(reloaded_index.docstore.docs) == 0, (
|
||||
f"Expected 0 nodes after clearing all documents, "
|
||||
f"but found {len(reloaded_index.docstore.docs)}: "
|
||||
f"{list(reloaded_index.docstore.docs.keys())}"
|
||||
)
|
||||
# Step 4: the table must be absent (no rows) — phantom vectors gone
|
||||
with indexing.get_vector_store() as store2:
|
||||
assert not store2.table_exists(), (
|
||||
"Expected the vector store table to be absent after rebuilding "
|
||||
"with no documents"
|
||||
)
|
||||
|
||||
|
||||
class TestDocumentUpdatedSignalTriggersLlmReindex:
|
||||
@@ -709,10 +541,14 @@ class TestLlmIndexAddOrUpdateDocumentEmptyContent:
|
||||
def test_returns_without_error_when_build_document_node_returns_empty(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""When build_document_node returns [], the function must return without error
|
||||
and must not call load_or_build_index at all."""
|
||||
"""When build_document_node returns [], the function must return without error.
|
||||
|
||||
The store's upsert_document treats an empty node list as a removal (no-op
|
||||
delete), so load_or_build_index must not be called.
|
||||
"""
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.build_document_node",
|
||||
return_value=[],
|
||||
@@ -720,6 +556,7 @@ class TestLlmIndexAddOrUpdateDocumentEmptyContent:
|
||||
mock_load = mocker.patch("paperless_ai.indexing.load_or_build_index")
|
||||
|
||||
doc = MagicMock(spec=Document)
|
||||
doc.id = 42
|
||||
# Must not raise
|
||||
indexing.llm_index_add_or_update_document(doc)
|
||||
|
||||
@@ -727,172 +564,165 @@ class TestLlmIndexAddOrUpdateDocumentEmptyContent:
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestLlmIndexLocking:
|
||||
"""The FAISS index mutation functions must acquire the index lock before touching the index.
|
||||
def test_llm_index_compact_uses_force(
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""compact must use force=True to rebuild the table and reclaim space immediately."""
|
||||
mock_store = mocker.MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
|
||||
Without locking, two concurrent Celery workers can each load the same
|
||||
on-disk index, make independent modifications, and the last writer silently
|
||||
overwrites the first's changes.
|
||||
indexing.llm_index_compact()
|
||||
|
||||
mock_store.compact.assert_called_once_with(force=True)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestLlmIndexLocking:
|
||||
"""Index mutation functions must go through write_store(), which holds the lock.
|
||||
|
||||
Without locking, two concurrent Celery workers can open the same store,
|
||||
make independent modifications, and trigger CommitConflictError.
|
||||
"""
|
||||
|
||||
def test_add_or_update_document_acquires_lock(
|
||||
def test_add_or_update_document_uses_write_store(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""llm_index_add_or_update_document must enter the file lock before touching the index."""
|
||||
call_order: list[str] = []
|
||||
|
||||
mock_lock_instance = MagicMock()
|
||||
mock_lock_instance.__enter__ = MagicMock(
|
||||
side_effect=lambda *_: call_order.append("lock_acquired"),
|
||||
)
|
||||
mock_lock_instance.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
mock_file_lock_cls = mocker.patch(
|
||||
"paperless_ai.indexing.FileLock",
|
||||
return_value=mock_lock_instance,
|
||||
)
|
||||
|
||||
mock_load = mocker.patch(
|
||||
"paperless_ai.indexing.load_or_build_index",
|
||||
side_effect=lambda *_a, **_kw: (
|
||||
call_order.append("index_loaded") or MagicMock()
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
mock_node = MagicMock()
|
||||
mock_node.get_content.return_value = "fake node text"
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.build_document_node",
|
||||
return_value=[MagicMock()],
|
||||
return_value=[mock_node],
|
||||
)
|
||||
mocker.patch("paperless_ai.indexing.remove_document_docstore_nodes")
|
||||
|
||||
doc = MagicMock(spec=Document)
|
||||
doc.id = 1
|
||||
indexing.llm_index_add_or_update_document(doc)
|
||||
|
||||
mock_file_lock_cls.assert_called_once()
|
||||
mock_lock_instance.__enter__.assert_called_once()
|
||||
mock_load.assert_called_once()
|
||||
assert call_order.index("lock_acquired") < call_order.index("index_loaded"), (
|
||||
"Lock must be acquired before the index is loaded"
|
||||
)
|
||||
mock_store.upsert_document.assert_called_once()
|
||||
|
||||
def test_remove_document_acquires_lock(
|
||||
def test_remove_document_uses_write_store(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""llm_index_remove_document must enter the file lock before loading the index."""
|
||||
call_order: list[str] = []
|
||||
|
||||
mock_lock_instance = MagicMock()
|
||||
mock_lock_instance.__enter__ = MagicMock(
|
||||
side_effect=lambda *_: call_order.append("lock_acquired"),
|
||||
)
|
||||
mock_lock_instance.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
mock_file_lock_cls = mocker.patch(
|
||||
"paperless_ai.indexing.FileLock",
|
||||
return_value=mock_lock_instance,
|
||||
)
|
||||
|
||||
mock_load = mocker.patch(
|
||||
"paperless_ai.indexing.load_or_build_index",
|
||||
side_effect=lambda *_a, **_kw: (
|
||||
call_order.append("index_loaded") or MagicMock()
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
mocker.patch("paperless_ai.indexing.remove_document_docstore_nodes")
|
||||
|
||||
doc = MagicMock(spec=Document)
|
||||
doc.id = 1
|
||||
indexing.llm_index_remove_document(doc)
|
||||
|
||||
mock_file_lock_cls.assert_called_once()
|
||||
mock_lock_instance.__enter__.assert_called_once()
|
||||
mock_load.assert_called_once()
|
||||
assert call_order.index("lock_acquired") < call_order.index("index_loaded"), (
|
||||
"Lock must be acquired before the index is loaded"
|
||||
)
|
||||
mock_store.delete.assert_called_once_with("1")
|
||||
|
||||
def test_update_llm_index_rebuild_acquires_lock(
|
||||
def test_update_llm_index_rebuild_uses_write_store(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: MagicMock,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""update_llm_index must enter the file lock during the rebuild/persist cycle."""
|
||||
mock_lock_instance = MagicMock()
|
||||
mock_lock_instance.__enter__ = MagicMock(return_value=None)
|
||||
mock_lock_instance.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
mock_file_lock_cls = mocker.patch(
|
||||
"paperless_ai.indexing.FileLock",
|
||||
return_value=mock_lock_instance,
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
|
||||
# exists=True so the code reaches the lock; iterate over an empty
|
||||
# queryset so VectorStoreIndex is called with no nodes (still exercises
|
||||
# the lock path without needing heavy FAISS fixture data)
|
||||
mock_qs = MagicMock()
|
||||
mock_qs.exists.return_value = True
|
||||
mock_qs.__iter__ = MagicMock(return_value=iter([]))
|
||||
mocker.patch("paperless_ai.indexing.Document.objects.all", return_value=mock_qs)
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.get_or_create_storage_context",
|
||||
return_value=MagicMock(),
|
||||
)
|
||||
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
|
||||
mock_file_lock_cls.assert_called_once()
|
||||
mock_lock_instance.__enter__.assert_called_once()
|
||||
mock_store.drop_table.assert_called_once()
|
||||
|
||||
def test_query_similar_documents_acquires_lock(
|
||||
|
||||
@pytest.mark.django_db
|
||||
@pytest.mark.django_db
|
||||
class TestVectorStoreIndexing:
|
||||
def test_get_vector_store_roundtrip(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
"""query_similar_documents must enter the file lock before loading the index."""
|
||||
call_order: list[str] = []
|
||||
with indexing.get_vector_store() as store:
|
||||
assert isinstance(store, PaperlessSqliteVecVectorStore)
|
||||
|
||||
mock_lock_instance = MagicMock()
|
||||
mock_lock_instance.__enter__ = MagicMock(
|
||||
side_effect=lambda *_: call_order.append("lock_acquired"),
|
||||
)
|
||||
mock_lock_instance.__exit__ = MagicMock(return_value=False)
|
||||
def test_add_then_remove_document(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
indexing.llm_index_add_or_update_document(real_document)
|
||||
with indexing.get_vector_store() as store:
|
||||
assert store.table_exists()
|
||||
count_sql = "SELECT count(*) FROM documents"
|
||||
assert store.client.execute(count_sql).fetchone()[0] >= 1
|
||||
|
||||
mock_file_lock_cls = mocker.patch(
|
||||
"paperless_ai.indexing.FileLock",
|
||||
return_value=mock_lock_instance,
|
||||
)
|
||||
indexing.llm_index_remove_document(real_document)
|
||||
assert store.client.execute(count_sql).fetchone()[0] == 0
|
||||
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.vector_store_file_exists",
|
||||
return_value=True,
|
||||
)
|
||||
def test_update_shrinks_chunks_without_orphans(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
real_document: Document,
|
||||
) -> None:
|
||||
real_document.content = "word " * 4000 # many chunks
|
||||
real_document.save()
|
||||
indexing.llm_index_add_or_update_document(real_document)
|
||||
count_sql = "SELECT count(*) FROM documents"
|
||||
with indexing.get_vector_store() as store:
|
||||
big = store.client.execute(count_sql).fetchone()[0]
|
||||
|
||||
mock_index = MagicMock()
|
||||
mock_index.docstore.docs = {}
|
||||
real_document.content = "short" # one chunk
|
||||
real_document.save()
|
||||
indexing.llm_index_add_or_update_document(real_document)
|
||||
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.load_or_build_index",
|
||||
side_effect=lambda *_a, **_kw: (
|
||||
call_order.append("index_loaded") or mock_index
|
||||
),
|
||||
)
|
||||
rows = store.client.execute(count_sql).fetchone()[0]
|
||||
assert rows < big
|
||||
assert rows >= 1
|
||||
|
||||
mock_retriever = MagicMock()
|
||||
mock_retriever.retrieve.return_value = []
|
||||
mocker.patch(
|
||||
"llama_index.core.retrievers.VectorIndexRetriever",
|
||||
return_value=mock_retriever,
|
||||
)
|
||||
|
||||
mocker.patch("paperless_ai.indexing.truncate_content", return_value="")
|
||||
@pytest.mark.django_db
|
||||
class TestQuerySimilarDocuments:
|
||||
def test_query_similar_documents_respects_allowed_ids(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
a = DocumentFactory.create(content="alpha shared content here")
|
||||
b = DocumentFactory.create(content="beta shared content here")
|
||||
c = DocumentFactory.create(content="gamma shared content here")
|
||||
for doc in (a, b, c):
|
||||
indexing.llm_index_add_or_update_document(doc)
|
||||
|
||||
indexing.query_similar_documents(MagicMock(spec=Document))
|
||||
results = indexing.query_similar_documents(a, document_ids=[b.id])
|
||||
|
||||
mock_file_lock_cls.assert_called()
|
||||
mock_lock_instance.__enter__.assert_called()
|
||||
assert call_order.index("lock_acquired") < call_order.index("index_loaded"), (
|
||||
"Lock must be acquired before the index is loaded"
|
||||
)
|
||||
assert all(doc.id == b.id for doc in results)
|
||||
|
||||
+110
-130
@@ -3,19 +3,20 @@ from unittest.mock import MagicMock
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
from llama_index.core import settings as llama_settings
|
||||
from llama_index.core.embeddings.mock_embed_model import MockEmbedding
|
||||
from llama_index.core.schema import TextNode
|
||||
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from paperless_ai import chat
|
||||
from paperless_ai import indexing
|
||||
from paperless_ai.chat import CHAT_ERROR_MESSAGE
|
||||
from paperless_ai.chat import CHAT_METADATA_DELIMITER
|
||||
from paperless_ai.chat import _get_document_filtered_retriever
|
||||
from paperless_ai.chat import stream_chat_with_documents
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def patch_embed_model():
|
||||
from llama_index.core import settings as llama_settings
|
||||
from llama_index.core.embeddings.mock_embed_model import MockEmbedding
|
||||
|
||||
# Use a real BaseEmbedding subclass to satisfy llama-index 0.14 validation
|
||||
llama_settings.Settings.embed_model = MockEmbedding(embed_dim=1536)
|
||||
yield
|
||||
@@ -58,91 +59,6 @@ def assert_chat_output(
|
||||
}
|
||||
|
||||
|
||||
def add_vector_query_results(mock_index, nodes: list[TextNode]) -> None:
|
||||
mock_index.index_struct.nodes_dict = {
|
||||
str(vector_id): node.node_id for vector_id, node in enumerate(nodes)
|
||||
}
|
||||
mock_index.docstore.docs.get.side_effect = {
|
||||
node.node_id: node for node in nodes
|
||||
}.get
|
||||
mock_index.vector_store._faiss_index.ntotal = len(nodes)
|
||||
mock_index.vector_store.query.return_value = MagicMock(
|
||||
ids=list(mock_index.index_struct.nodes_dict),
|
||||
similarities=[0.1] * len(nodes),
|
||||
)
|
||||
mock_index._embed_model.get_agg_embedding_from_queries.return_value = [0.1] * 1536
|
||||
|
||||
|
||||
def test_document_filtered_retriever_expands_filters_and_caches() -> None:
|
||||
allowed_node1 = TextNode(
|
||||
text="Allowed content 1.",
|
||||
metadata={"document_id": "1", "title": "Allowed 1"},
|
||||
)
|
||||
allowed_node2 = TextNode(
|
||||
text="Allowed content 2.",
|
||||
metadata={"document_id": "2", "title": "Allowed 2"},
|
||||
)
|
||||
foreign_node = TextNode(
|
||||
text="Foreign content.",
|
||||
metadata={"document_id": "3", "title": "Foreign"},
|
||||
)
|
||||
missing_node = TextNode(
|
||||
text="Missing content.",
|
||||
metadata={"document_id": "1", "title": "Missing"},
|
||||
)
|
||||
|
||||
mock_index = MagicMock()
|
||||
mock_index.index_struct.nodes_dict = {
|
||||
"0": foreign_node.node_id,
|
||||
"1": missing_node.node_id,
|
||||
"2": allowed_node1.node_id,
|
||||
"3": allowed_node2.node_id,
|
||||
}
|
||||
mock_index.docstore.docs.get.side_effect = {
|
||||
allowed_node1.node_id: allowed_node1,
|
||||
allowed_node2.node_id: allowed_node2,
|
||||
foreign_node.node_id: foreign_node,
|
||||
}.get
|
||||
mock_index.vector_store._faiss_index.ntotal = 4
|
||||
mock_index.vector_store.query.side_effect = [
|
||||
MagicMock(ids=["0", "2"], similarities=[0.9, 0.8]),
|
||||
MagicMock(ids=["0", "1", "3"], similarities=[0.9, 0.7, 0.6]),
|
||||
]
|
||||
mock_index._embed_model.get_agg_embedding_from_queries.return_value = [0.1] * 1536
|
||||
|
||||
retriever = _get_document_filtered_retriever(
|
||||
mock_index,
|
||||
{"1", "2"},
|
||||
similarity_top_k=2,
|
||||
)
|
||||
|
||||
nodes = retriever.retrieve("question")
|
||||
cached_nodes = retriever.retrieve("question")
|
||||
|
||||
assert [node.node.node_id for node in nodes] == [
|
||||
allowed_node1.node_id,
|
||||
allowed_node2.node_id,
|
||||
]
|
||||
assert cached_nodes == nodes
|
||||
assert mock_index.vector_store.query.call_count == 2
|
||||
assert mock_index._embed_model.get_agg_embedding_from_queries.call_count == 1
|
||||
|
||||
|
||||
def test_document_filtered_retriever_handles_empty_faiss_index() -> None:
|
||||
mock_index = MagicMock()
|
||||
mock_index.vector_store._faiss_index.ntotal = 0
|
||||
mock_index._embed_model.get_agg_embedding_from_queries.return_value = [0.1] * 1536
|
||||
|
||||
retriever = _get_document_filtered_retriever(
|
||||
mock_index,
|
||||
{"1"},
|
||||
similarity_top_k=2,
|
||||
)
|
||||
|
||||
assert retriever.retrieve("question") == []
|
||||
mock_index.vector_store.query.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_stream_chat_with_one_document_retrieval(
|
||||
mock_document,
|
||||
@@ -164,17 +80,31 @@ def test_stream_chat_with_one_document_retrieval(
|
||||
metadata={"document_id": str(mock_document.pk), "title": "Test Document"},
|
||||
)
|
||||
mock_index = MagicMock()
|
||||
mock_index.docstore.docs.values.return_value = [mock_node]
|
||||
add_vector_query_results(mock_index, [mock_node])
|
||||
# Simulate get_nodes returning nodes (content exists)
|
||||
mock_index.vector_store.get_nodes.return_value = [mock_node]
|
||||
mock_load_index.return_value = mock_index
|
||||
|
||||
mock_retriever_instance = MagicMock()
|
||||
mock_retriever_instance.retrieve.return_value = [
|
||||
MagicMock(
|
||||
metadata={
|
||||
"document_id": str(mock_document.pk),
|
||||
"title": "Test Document",
|
||||
},
|
||||
),
|
||||
]
|
||||
|
||||
mock_response_stream = MagicMock()
|
||||
mock_response_stream.response_gen = iter(["chunk1", "chunk2"])
|
||||
mock_query_engine = MagicMock()
|
||||
mock_query_engine_cls.return_value = mock_query_engine
|
||||
mock_query_engine.query.return_value = mock_response_stream
|
||||
|
||||
output = list(stream_chat_with_documents("What is this?", [mock_document]))
|
||||
with patch(
|
||||
"llama_index.core.retrievers.VectorIndexRetriever",
|
||||
return_value=mock_retriever_instance,
|
||||
):
|
||||
output = list(stream_chat_with_documents("What is this?", [mock_document]))
|
||||
|
||||
mock_query_engine.query.assert_called_once_with("What is this?")
|
||||
patch_embed_nodes.assert_not_called()
|
||||
@@ -196,12 +126,10 @@ def test_stream_chat_with_multiple_documents_retrieval(patch_embed_nodes) -> Non
|
||||
"llama_index.core.query_engine.RetrieverQueryEngine.from_args",
|
||||
) as mock_query_engine_cls,
|
||||
):
|
||||
# Mock AIClient and LLM
|
||||
mock_client = MagicMock()
|
||||
mock_client_cls.return_value = mock_client
|
||||
mock_client.llm = MagicMock()
|
||||
|
||||
# Create two real TextNodes
|
||||
mock_node1 = TextNode(
|
||||
text="Content for doc 1.",
|
||||
metadata={"document_id": "1", "title": "Document 1"},
|
||||
@@ -210,41 +138,32 @@ def test_stream_chat_with_multiple_documents_retrieval(patch_embed_nodes) -> Non
|
||||
text="Content for doc 2.",
|
||||
metadata={"document_id": "2", "title": "Document 2"},
|
||||
)
|
||||
mock_duplicate_node = TextNode(
|
||||
text="More content for doc 1.",
|
||||
metadata={"document_id": "1", "title": "Document 1 Duplicate"},
|
||||
)
|
||||
mock_foreign_node = TextNode(
|
||||
text="Content for doc 3.",
|
||||
metadata={"document_id": "3", "title": "Document 3"},
|
||||
)
|
||||
mock_index = MagicMock()
|
||||
mock_index.docstore.docs.values.return_value = [
|
||||
mock_node1,
|
||||
mock_node2,
|
||||
mock_duplicate_node,
|
||||
mock_foreign_node,
|
||||
]
|
||||
add_vector_query_results(
|
||||
mock_index,
|
||||
[mock_node1, mock_duplicate_node, mock_node2, mock_foreign_node],
|
||||
)
|
||||
# Simulate get_nodes returning nodes (content exists)
|
||||
mock_index.vector_store.get_nodes.return_value = [mock_node1, mock_node2]
|
||||
mock_load_index.return_value = mock_index
|
||||
|
||||
# Mock response stream
|
||||
mock_retriever_instance = MagicMock()
|
||||
mock_retriever_instance.retrieve.return_value = [
|
||||
MagicMock(metadata={"document_id": "1", "title": "Document 1"}),
|
||||
MagicMock(metadata={"document_id": "2", "title": "Document 2"}),
|
||||
]
|
||||
|
||||
mock_response_stream = MagicMock()
|
||||
mock_response_stream.response_gen = iter(["chunk1", "chunk2"])
|
||||
|
||||
# Mock RetrieverQueryEngine
|
||||
mock_query_engine = MagicMock()
|
||||
mock_query_engine_cls.return_value = mock_query_engine
|
||||
mock_query_engine.query.return_value = mock_response_stream
|
||||
|
||||
# Fake documents
|
||||
doc1 = MagicMock(pk=1, title="Document 1", filename="doc1.pdf")
|
||||
doc2 = MagicMock(pk=2, title="Document 2", filename="doc2.pdf")
|
||||
|
||||
output = list(stream_chat_with_documents("What's up?", [doc1, doc2]))
|
||||
with patch(
|
||||
"llama_index.core.retrievers.VectorIndexRetriever",
|
||||
return_value=mock_retriever_instance,
|
||||
):
|
||||
output = list(stream_chat_with_documents("What's up?", [doc1, doc2]))
|
||||
|
||||
mock_query_engine.query.assert_called_once_with("What's up?")
|
||||
patch_embed_nodes.assert_not_called()
|
||||
@@ -258,8 +177,16 @@ def test_stream_chat_with_multiple_documents_retrieval(patch_embed_nodes) -> Non
|
||||
)
|
||||
|
||||
|
||||
def test_stream_chat_empty_document_list() -> None:
|
||||
with patch("paperless_ai.chat.load_or_build_index") as mock_load_index:
|
||||
output = list(stream_chat_with_documents("Any info?", []))
|
||||
mock_load_index.assert_not_called()
|
||||
assert output == ["Sorry, I couldn't find any content to answer your question."]
|
||||
|
||||
|
||||
def test_stream_chat_no_matching_nodes() -> None:
|
||||
with (
|
||||
patch("paperless_ai.chat.AIConfig"),
|
||||
patch("paperless_ai.chat.AIClient") as mock_client_cls,
|
||||
patch("paperless_ai.chat.load_or_build_index") as mock_load_index,
|
||||
):
|
||||
@@ -268,8 +195,8 @@ def test_stream_chat_no_matching_nodes() -> None:
|
||||
mock_client.llm = MagicMock()
|
||||
|
||||
mock_index = MagicMock()
|
||||
# No matching nodes
|
||||
mock_index.docstore.docs.values.return_value = []
|
||||
# No matching nodes in the store
|
||||
mock_index.vector_store.get_nodes.return_value = []
|
||||
mock_load_index.return_value = mock_index
|
||||
|
||||
output = list(stream_chat_with_documents("Any info?", [MagicMock(pk=1)]))
|
||||
@@ -279,30 +206,83 @@ def test_stream_chat_no_matching_nodes() -> None:
|
||||
|
||||
def test_stream_chat_unexpected_failure_returns_generic_error(caplog) -> None:
|
||||
with (
|
||||
patch("paperless_ai.chat.AIConfig"),
|
||||
patch("paperless_ai.chat.AIClient") as mock_client_cls,
|
||||
patch("paperless_ai.chat.load_or_build_index") as mock_load_index,
|
||||
patch(
|
||||
"paperless_ai.chat._get_document_filtered_retriever",
|
||||
) as mock_get_retriever,
|
||||
):
|
||||
mock_client = MagicMock()
|
||||
mock_client_cls.return_value = mock_client
|
||||
mock_client.llm = MagicMock()
|
||||
|
||||
mock_node = TextNode(
|
||||
text="This is node content.",
|
||||
metadata={"document_id": "1", "title": "Test Document"},
|
||||
)
|
||||
mock_index = MagicMock()
|
||||
mock_index.docstore.docs.values.return_value = [mock_node]
|
||||
# Nodes found so we get past the pre-check
|
||||
mock_index.vector_store.get_nodes.return_value = [MagicMock()]
|
||||
mock_load_index.return_value = mock_index
|
||||
|
||||
mock_retriever = MagicMock()
|
||||
mock_retriever.retrieve.side_effect = RuntimeError("private provider detail")
|
||||
mock_get_retriever.return_value = mock_retriever
|
||||
with patch(
|
||||
"llama_index.core.retrievers.VectorIndexRetriever",
|
||||
) as mock_retriever_cls:
|
||||
mock_retriever = MagicMock()
|
||||
mock_retriever.retrieve.side_effect = RuntimeError(
|
||||
"private provider detail",
|
||||
)
|
||||
mock_retriever_cls.return_value = mock_retriever
|
||||
|
||||
output = list(stream_chat_with_documents("Any info?", [MagicMock(pk=1)]))
|
||||
output = list(stream_chat_with_documents("Any info?", [MagicMock(pk=1)]))
|
||||
|
||||
assert output == [CHAT_ERROR_MESSAGE]
|
||||
assert "Failed to stream document chat response" in caplog.text
|
||||
assert "private provider detail" in caplog.text
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestStreamChatRetrieval:
|
||||
def test_no_nodes_yields_no_content_message(
|
||||
self,
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
) -> None:
|
||||
doc = DocumentFactory.create(content="hello world")
|
||||
# Nothing indexed for this document yet.
|
||||
out = list(chat.stream_chat_with_documents("question?", [doc]))
|
||||
assert chat.CHAT_NO_CONTENT_MESSAGE in out
|
||||
|
||||
def test_chat_filter_contains_only_requested_document_ids(
|
||||
self,
|
||||
temp_llm_index_dir,
|
||||
mock_embed_model,
|
||||
mocker,
|
||||
) -> None:
|
||||
"""The MetadataFilter passed to the retriever must be scoped to the
|
||||
requested documents only — content from other indexed documents must
|
||||
not be surfaced.
|
||||
"""
|
||||
included = DocumentFactory.create(content="included document content")
|
||||
excluded = DocumentFactory.create(content="excluded document content")
|
||||
indexing.llm_index_add_or_update_document(included)
|
||||
indexing.llm_index_add_or_update_document(excluded)
|
||||
|
||||
# VectorIndexRetriever is imported inside _stream_chat_with_documents;
|
||||
# patch it at the llama_index source so the lazy import picks it up.
|
||||
captured_filters = []
|
||||
mock_retriever = mocker.MagicMock()
|
||||
mock_retriever.retrieve.return_value = []
|
||||
|
||||
def capture_retriever(*args, **kwargs):
|
||||
captured_filters.append(kwargs.get("filters"))
|
||||
return mock_retriever
|
||||
|
||||
mocker.patch("paperless_ai.chat.AIClient")
|
||||
mocker.patch(
|
||||
"llama_index.core.retrievers.VectorIndexRetriever",
|
||||
side_effect=capture_retriever,
|
||||
)
|
||||
|
||||
list(chat.stream_chat_with_documents("question?", [included]))
|
||||
|
||||
assert captured_filters, "VectorIndexRetriever was never constructed"
|
||||
filt = captured_filters[0]
|
||||
assert filt is not None, "Retriever must receive a MetadataFilters"
|
||||
filter_values = filt.filters[0].value
|
||||
assert str(included.pk) in filter_values
|
||||
assert str(excluded.pk) not in filter_values
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
import json
|
||||
from unittest.mock import ANY
|
||||
from unittest.mock import MagicMock
|
||||
from unittest.mock import patch
|
||||
@@ -10,7 +9,7 @@ from documents.models import Document
|
||||
from paperless.models import LLMEmbeddingBackend
|
||||
from paperless_ai.embedding import _normalize_llm_index_text
|
||||
from paperless_ai.embedding import build_llm_index_text
|
||||
from paperless_ai.embedding import get_embedding_dim
|
||||
from paperless_ai.embedding import get_configured_model_name
|
||||
from paperless_ai.embedding import get_embedding_model
|
||||
|
||||
|
||||
@@ -67,7 +66,7 @@ def test_get_embedding_model_openai(mock_ai_config):
|
||||
with patch(
|
||||
"llama_index.embeddings.openai_like.OpenAILikeEmbedding",
|
||||
) as MockOpenAIEmbedding:
|
||||
model = get_embedding_model()
|
||||
model = get_embedding_model(mock_ai_config.return_value)
|
||||
MockOpenAIEmbedding.assert_called_once_with(
|
||||
model_name="text-embedding-3-small",
|
||||
api_key="test_api_key",
|
||||
@@ -88,7 +87,7 @@ def test_get_embedding_model_openai_prefers_embedding_endpoint(mock_ai_config):
|
||||
with patch(
|
||||
"llama_index.embeddings.openai_like.OpenAILikeEmbedding",
|
||||
) as MockOpenAIEmbedding:
|
||||
model = get_embedding_model()
|
||||
model = get_embedding_model(mock_ai_config.return_value)
|
||||
MockOpenAIEmbedding.assert_called_once_with(
|
||||
model_name="text-embedding-3-small",
|
||||
api_key="test_api_key",
|
||||
@@ -109,7 +108,7 @@ def test_get_embedding_model_openai_blocks_internal_endpoint_when_disallowed(
|
||||
mock_ai_config.return_value.llm_allow_internal_endpoints = False
|
||||
|
||||
with pytest.raises(ValueError, match="non-public address"):
|
||||
get_embedding_model()
|
||||
get_embedding_model(mock_ai_config.return_value)
|
||||
|
||||
|
||||
def test_get_embedding_model_huggingface(mock_ai_config):
|
||||
@@ -121,7 +120,7 @@ def test_get_embedding_model_huggingface(mock_ai_config):
|
||||
with patch(
|
||||
"llama_index.embeddings.huggingface.HuggingFaceEmbedding",
|
||||
) as MockHuggingFaceEmbedding:
|
||||
model = get_embedding_model()
|
||||
model = get_embedding_model(mock_ai_config.return_value)
|
||||
MockHuggingFaceEmbedding.assert_called_once_with(
|
||||
model_name="sentence-transformers/all-MiniLM-L6-v2",
|
||||
cache_folder=str(settings.DATA_DIR / "hf_cache"),
|
||||
@@ -137,7 +136,7 @@ def test_get_embedding_model_ollama(mock_ai_config):
|
||||
with patch(
|
||||
"llama_index.embeddings.ollama.OllamaEmbedding",
|
||||
) as MockOllamaEmbedding:
|
||||
model = get_embedding_model()
|
||||
model = get_embedding_model(mock_ai_config.return_value)
|
||||
MockOllamaEmbedding.assert_called_once_with(
|
||||
model_name="embeddinggemma",
|
||||
base_url="http://test-url",
|
||||
@@ -155,7 +154,7 @@ def test_get_embedding_model_ollama_prefers_embedding_endpoint(mock_ai_config):
|
||||
with patch(
|
||||
"llama_index.embeddings.ollama.OllamaEmbedding",
|
||||
) as MockOllamaEmbedding:
|
||||
model = get_embedding_model()
|
||||
model = get_embedding_model(mock_ai_config.return_value)
|
||||
MockOllamaEmbedding.assert_called_once_with(
|
||||
model_name="embeddinggemma",
|
||||
base_url="http://embedding-url",
|
||||
@@ -173,7 +172,7 @@ def test_get_embedding_model_ollama_blocks_internal_endpoint_when_disallowed(
|
||||
mock_ai_config.return_value.llm_allow_internal_endpoints = False
|
||||
|
||||
with pytest.raises(ValueError, match="non-public address"):
|
||||
get_embedding_model()
|
||||
get_embedding_model(mock_ai_config.return_value)
|
||||
|
||||
|
||||
def test_get_embedding_model_invalid_backend(mock_ai_config):
|
||||
@@ -183,55 +182,37 @@ def test_get_embedding_model_invalid_backend(mock_ai_config):
|
||||
ValueError,
|
||||
match="Unsupported embedding backend: INVALID_BACKEND",
|
||||
):
|
||||
get_embedding_model()
|
||||
get_embedding_model(mock_ai_config.return_value)
|
||||
|
||||
|
||||
def test_get_embedding_dim_infers_and_saves(temp_llm_index_dir, mock_ai_config):
|
||||
mock_ai_config.return_value.llm_embedding_backend = "openai-like"
|
||||
mock_ai_config.return_value.llm_embedding_model = None
|
||||
|
||||
class DummyEmbedding:
|
||||
def get_text_embedding(self, text):
|
||||
return [0.0] * 7
|
||||
|
||||
with patch(
|
||||
"paperless_ai.embedding.get_embedding_model",
|
||||
return_value=DummyEmbedding(),
|
||||
) as mock_get:
|
||||
dim = get_embedding_dim()
|
||||
mock_get.assert_called_once()
|
||||
|
||||
assert dim == 7
|
||||
meta = json.loads((temp_llm_index_dir / "meta.json").read_text())
|
||||
assert meta == {"embedding_model": "text-embedding-3-small", "dim": 7}
|
||||
@pytest.mark.parametrize(
|
||||
("backend", "expected_default"),
|
||||
[
|
||||
(LLMEmbeddingBackend.OPENAI_LIKE, "text-embedding-3-small"),
|
||||
(LLMEmbeddingBackend.HUGGINGFACE, "sentence-transformers/all-MiniLM-L6-v2"),
|
||||
(LLMEmbeddingBackend.OLLAMA, "embeddinggemma"),
|
||||
],
|
||||
)
|
||||
def test_get_configured_model_name_falls_back_to_backend_default(
|
||||
mock_ai_config,
|
||||
backend,
|
||||
expected_default,
|
||||
):
|
||||
"""When no model is explicitly configured, each backend has a distinct default."""
|
||||
config = mock_ai_config.return_value
|
||||
config.llm_embedding_backend = backend
|
||||
config.llm_embedding_model = None
|
||||
assert get_configured_model_name(config) == expected_default
|
||||
|
||||
|
||||
def test_get_embedding_dim_reads_existing_meta(temp_llm_index_dir, mock_ai_config):
|
||||
mock_ai_config.return_value.llm_embedding_backend = "openai-like"
|
||||
mock_ai_config.return_value.llm_embedding_model = None
|
||||
|
||||
(temp_llm_index_dir / "meta.json").write_text(
|
||||
json.dumps({"embedding_model": "text-embedding-3-small", "dim": 11}),
|
||||
)
|
||||
|
||||
with patch("paperless_ai.embedding.get_embedding_model") as mock_get:
|
||||
assert get_embedding_dim() == 11
|
||||
mock_get.assert_not_called()
|
||||
|
||||
|
||||
def test_get_embedding_dim_raises_on_model_change(temp_llm_index_dir, mock_ai_config):
|
||||
mock_ai_config.return_value.llm_embedding_backend = "openai-like"
|
||||
mock_ai_config.return_value.llm_embedding_model = None
|
||||
|
||||
(temp_llm_index_dir / "meta.json").write_text(
|
||||
json.dumps({"embedding_model": "old", "dim": 11}),
|
||||
)
|
||||
|
||||
with pytest.raises(
|
||||
RuntimeError,
|
||||
match="Embedding model changed from old to text-embedding-3-small",
|
||||
):
|
||||
get_embedding_dim()
|
||||
def test_get_configured_model_name_explicit_overrides_default(mock_ai_config):
|
||||
"""An explicit model name overrides the backend default for all backends."""
|
||||
config = mock_ai_config.return_value
|
||||
config.llm_embedding_backend = LLMEmbeddingBackend.OPENAI_LIKE
|
||||
config.llm_embedding_model = "my-custom-model"
|
||||
# The backend default for OPENAI_LIKE is "text-embedding-3-small", so if
|
||||
# the explicit name was ignored we'd get the wrong result.
|
||||
assert get_configured_model_name(config) == "my-custom-model"
|
||||
|
||||
|
||||
def test_build_llm_index_text(mock_document):
|
||||
@@ -243,12 +224,17 @@ def test_build_llm_index_text(mock_document):
|
||||
|
||||
result = build_llm_index_text(mock_document)
|
||||
|
||||
assert "Title: Test Title" in result
|
||||
assert "Filename: test_file.pdf" in result
|
||||
assert "Created: 2023-01-01" in result
|
||||
assert "Tags: Tag1, Tag2" in result
|
||||
assert "Document Type: Invoice" in result
|
||||
assert "Correspondent: Test Correspondent" in result
|
||||
# Structured fields live in node.metadata for LLM context -- not body text
|
||||
assert "Title: Test Title" not in result
|
||||
assert "Created: 2023-01-01" not in result
|
||||
assert "Tags: Tag1, Tag2" not in result
|
||||
assert "Document Type: Invoice" not in result
|
||||
assert "Correspondent: Test Correspondent" not in result
|
||||
assert "Filename:" not in result
|
||||
assert "Storage Path:" not in result
|
||||
assert "Archive Serial Number:" not in result
|
||||
|
||||
# Fields without a metadata equivalent stay in body text
|
||||
assert "Notes: Note1,Note2" in result
|
||||
assert "Content:\n\nThis is the document content." in result
|
||||
assert "Custom Field - Field1: Value1\nCustom Field - Field2: Value2" in result
|
||||
|
||||
@@ -0,0 +1,134 @@
|
||||
import logging
|
||||
import sqlite3
|
||||
import threading
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
from django.conf import settings
|
||||
from filelock import ReadWriteLock
|
||||
from llama_index.core.schema import TextNode
|
||||
from pytest_django.fixtures import SettingsWrapper
|
||||
|
||||
from paperless_ai import indexing
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
DIM = 8
|
||||
|
||||
|
||||
def _node(node_id: str, document_id: str, *, seed: float = 0.0) -> TextNode:
|
||||
node = TextNode(
|
||||
id_=node_id,
|
||||
text="chunk",
|
||||
metadata={"document_id": document_id, "modified": "2026-06-01T00:00:00"},
|
||||
)
|
||||
node.relationships = {}
|
||||
node.embedding = [seed + i / 100 for i in range(DIM)]
|
||||
return node
|
||||
|
||||
|
||||
def _seed_bloated_index(index_dir: Path) -> None:
|
||||
"""Create an index whose cumulative inserts far exceed live rows."""
|
||||
store = PaperlessSqliteVecVectorStore(uri=str(index_dir))
|
||||
store.add([_node(f"d{j}", str(j), seed=float(j)) for j in range(20)])
|
||||
for cycle in range(6):
|
||||
for j in range(20):
|
||||
store.upsert_document(
|
||||
str(j),
|
||||
[_node(f"d{j}-c{cycle}", str(j), seed=float(j))],
|
||||
)
|
||||
store.client.close()
|
||||
|
||||
|
||||
def _bloat_ratio(index_dir: Path) -> float:
|
||||
store = PaperlessSqliteVecVectorStore(uri=str(index_dir))
|
||||
live = store.client.execute("SELECT count(*) FROM documents").fetchone()[0]
|
||||
row = store.client.execute(
|
||||
"SELECT value FROM index_meta WHERE key = 'total_inserts'",
|
||||
).fetchone()
|
||||
total = int(row["value"]) if row else live
|
||||
store.client.close()
|
||||
return total / max(live, 1)
|
||||
|
||||
|
||||
def _integrity_ok(index_dir: Path) -> bool:
|
||||
store = PaperlessSqliteVecVectorStore(uri=str(index_dir))
|
||||
result = store.client.execute("PRAGMA integrity_check").fetchone()[0]
|
||||
rows = store.client.execute("SELECT count(*) FROM documents").fetchone()[0]
|
||||
store.client.close()
|
||||
return result == "ok" and rows == 20
|
||||
|
||||
|
||||
def _reader_lock() -> ReadWriteLock:
|
||||
# A distinct instance simulates a reader in another process: it coordinates
|
||||
# with the production lock purely through SQLite, never reentrant upgrade.
|
||||
return ReadWriteLock(str(settings.LLM_INDEX_RWLOCK), is_singleton=False)
|
||||
|
||||
|
||||
class TestCompactionLock:
|
||||
def test_compaction_skips_when_a_reader_holds_the_lock(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
settings: SettingsWrapper,
|
||||
caplog: pytest.LogCaptureFixture,
|
||||
) -> None:
|
||||
_seed_bloated_index(temp_llm_index_dir)
|
||||
settings.LLM_INDEX_COMPACTION_LOCK_TIMEOUT = 0.3
|
||||
|
||||
lock = _reader_lock()
|
||||
with lock.read_lock(), caplog.at_level(logging.INFO):
|
||||
indexing.llm_index_compact() # must not raise
|
||||
lock.close()
|
||||
|
||||
# Swap was skipped: bloat remains, nothing corrupted, data intact.
|
||||
assert _integrity_ok(temp_llm_index_dir)
|
||||
assert _bloat_ratio(temp_llm_index_dir) > 2
|
||||
assert "Skipping LLM index compaction" in caplog.text
|
||||
|
||||
def test_compaction_runs_when_no_reader_holds_the_lock(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
) -> None:
|
||||
_seed_bloated_index(temp_llm_index_dir)
|
||||
assert _bloat_ratio(temp_llm_index_dir) > 2
|
||||
|
||||
indexing.llm_index_compact()
|
||||
|
||||
assert _bloat_ratio(temp_llm_index_dir) == pytest.approx(1.0)
|
||||
assert _integrity_ok(temp_llm_index_dir)
|
||||
|
||||
def test_normal_write_is_not_gated_by_the_compaction_lock(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
) -> None:
|
||||
"""A held exclusive lock must not block ordinary writes (WAL handles them)."""
|
||||
_seed_bloated_index(temp_llm_index_dir)
|
||||
done = threading.Event()
|
||||
|
||||
def remove() -> None:
|
||||
indexing.llm_index_remove_document(MagicMock(id=999))
|
||||
done.set()
|
||||
|
||||
holder = _reader_lock()
|
||||
with holder.write_lock():
|
||||
t = threading.Thread(target=remove)
|
||||
t.start()
|
||||
finished = done.wait(timeout=5)
|
||||
t.join(timeout=2)
|
||||
holder.close()
|
||||
assert finished, "a normal write blocked on the compaction lock"
|
||||
|
||||
|
||||
class TestReadStore:
|
||||
def test_closes_connection_on_exit(self, temp_llm_index_dir: Path) -> None:
|
||||
with indexing.read_store() as store:
|
||||
conn = store.client
|
||||
assert conn.execute("SELECT 1").fetchone()[0] == 1
|
||||
with pytest.raises(sqlite3.ProgrammingError):
|
||||
conn.execute("SELECT 1")
|
||||
|
||||
def test_concurrent_readers_do_not_block(self, temp_llm_index_dir: Path) -> None:
|
||||
_seed_bloated_index(temp_llm_index_dir)
|
||||
with indexing.read_store() as a, indexing.read_store() as b:
|
||||
assert a.table_exists()
|
||||
assert b.table_exists()
|
||||
@@ -0,0 +1,25 @@
|
||||
import subprocess
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
_SRC_DIR = Path(__file__).parent.parent.parent
|
||||
|
||||
|
||||
class TestLazyAiImports:
|
||||
def test_importing_tasks_does_not_load_ai_libraries(self) -> None:
|
||||
code = (
|
||||
"import os, django, sys\n"
|
||||
"os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'paperless.settings')\n"
|
||||
"django.setup()\n"
|
||||
"import documents.tasks # noqa: F401\n"
|
||||
"leaked = [m for m in ('lancedb', 'pyarrow', 'llama_index', 'sqlite_vec') "
|
||||
"if m in sys.modules]\n"
|
||||
"assert not leaked, f'AI libraries leaked into the light path: {leaked}'\n"
|
||||
)
|
||||
result = subprocess.run(
|
||||
[sys.executable, "-c", code],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
cwd=_SRC_DIR,
|
||||
)
|
||||
assert result.returncode == 0, result.stdout + result.stderr
|
||||
@@ -0,0 +1,606 @@
|
||||
import sqlite3
|
||||
from collections.abc import Generator
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
from llama_index.core.schema import TextNode
|
||||
from llama_index.core.vector_stores.types import FilterOperator
|
||||
from llama_index.core.vector_stores.types import MetadataFilter
|
||||
from llama_index.core.vector_stores.types import MetadataFilters
|
||||
from llama_index.core.vector_stores.types import VectorStoreQuery
|
||||
|
||||
from paperless_ai.vector_store import DB_FILENAME
|
||||
from paperless_ai.vector_store import DEFAULT_TABLE_NAME
|
||||
from paperless_ai.vector_store import MIGRATIONS
|
||||
from paperless_ai.vector_store import SCHEMA_VERSION
|
||||
from paperless_ai.vector_store import Migration
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
from paperless_ai.vector_store import _build_where
|
||||
|
||||
DIM = 16
|
||||
|
||||
|
||||
def make_node(
|
||||
node_id: str,
|
||||
document_id: str,
|
||||
*,
|
||||
modified: str = "2026-06-10T00:00:00",
|
||||
seed: float = 0.0,
|
||||
text: str = "some text",
|
||||
) -> TextNode:
|
||||
node = TextNode(
|
||||
id_=node_id,
|
||||
text=text,
|
||||
metadata={"document_id": document_id, "modified": modified},
|
||||
)
|
||||
node.relationships = {}
|
||||
node.embedding = [seed + i / 100 for i in range(DIM)]
|
||||
return node
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def store(tmp_path: Path) -> Generator[PaperlessSqliteVecVectorStore, None, None]:
|
||||
with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as store:
|
||||
yield store
|
||||
|
||||
|
||||
def _query(
|
||||
store: PaperlessSqliteVecVectorStore,
|
||||
embedding: list[float],
|
||||
top_k: int = 5,
|
||||
filters=None,
|
||||
):
|
||||
return store.query(
|
||||
VectorStoreQuery(
|
||||
query_embedding=embedding,
|
||||
similarity_top_k=top_k,
|
||||
filters=filters,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def _eq_filter(key: str, value: str):
|
||||
return MetadataFilters(
|
||||
filters=[MetadataFilter(key=key, operator=FilterOperator.EQ, value=value)],
|
||||
)
|
||||
|
||||
|
||||
def _in_filter(document_ids: list[str]):
|
||||
return MetadataFilters(
|
||||
filters=[
|
||||
MetadataFilter(
|
||||
key="document_id",
|
||||
operator=FilterOperator.IN,
|
||||
value=document_ids,
|
||||
),
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class TestCrud:
|
||||
def test_add_then_query_returns_node(self, store) -> None:
|
||||
node = make_node("n1", "1")
|
||||
assert store.add([node]) == ["n1"]
|
||||
result = _query(store, node.embedding, top_k=1)
|
||||
assert result.ids == ["n1"]
|
||||
assert result.nodes[0].metadata["document_id"] == "1"
|
||||
# cosine distance of the identical vector is 0 -> similarity 1
|
||||
assert result.similarities[0] == pytest.approx(1.0)
|
||||
|
||||
def test_query_empty_store_returns_empty_no_raise(self, store) -> None:
|
||||
result = _query(store, [0.0] * DIM)
|
||||
assert result.ids == [] and result.nodes == [] and result.similarities == []
|
||||
|
||||
def test_add_empty_list_is_noop(self, store) -> None:
|
||||
assert store.add([]) == []
|
||||
assert not store.table_exists()
|
||||
|
||||
def test_delete_removes_all_chunks_of_document(self, store) -> None:
|
||||
store.add([make_node("a1", "1"), make_node("a2", "1"), make_node("b1", "2")])
|
||||
store.delete("1")
|
||||
result = _query(store, [0.0] * DIM, top_k=10)
|
||||
assert result.ids == ["b1"]
|
||||
|
||||
def test_query_with_in_filter_scopes_results(self, store) -> None:
|
||||
store.add(
|
||||
[
|
||||
make_node("a1", "1", seed=0.0),
|
||||
make_node("b1", "2", seed=1.0),
|
||||
make_node("c1", "3", seed=2.0),
|
||||
],
|
||||
)
|
||||
result = _query(store, [0.0] * DIM, top_k=10, filters=_in_filter(["2", "3"]))
|
||||
assert sorted(result.ids) == ["b1", "c1"]
|
||||
|
||||
def test_query_respects_top_k_with_filter(self, store) -> None:
|
||||
# k semantics: global top-k even with IN filters (document_id is a
|
||||
# metadata column, not a partition key -- see design doc).
|
||||
store.add(
|
||||
[make_node(f"n{i}", str(i % 4), seed=float(i)) for i in range(12)],
|
||||
)
|
||||
result = _query(
|
||||
store,
|
||||
[0.0] * DIM,
|
||||
top_k=3,
|
||||
filters=_in_filter(["0", "1", "2", "3"]),
|
||||
)
|
||||
assert len(result.ids) == 3
|
||||
assert result.similarities == sorted(result.similarities, reverse=True)
|
||||
|
||||
def test_get_nodes_filter_and_empty_paths(self, store) -> None:
|
||||
assert store.get_nodes(filters=_in_filter(["1"])) == [] # no table yet
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2")])
|
||||
nodes = store.get_nodes(filters=_in_filter(["1"]))
|
||||
assert [n.node_id for n in nodes] == ["a1"]
|
||||
assert nodes[0].embedding is not None
|
||||
assert store.get_nodes(filters=_in_filter(["999"])) == []
|
||||
|
||||
def test_query_with_eq_filter_scopes_results(self, store) -> None:
|
||||
store.add(
|
||||
[
|
||||
make_node("a1", "1", seed=0.0),
|
||||
make_node("b1", "2", seed=1.0),
|
||||
make_node("c1", "3", seed=2.0),
|
||||
],
|
||||
)
|
||||
result = _query(
|
||||
store,
|
||||
[0.0] * DIM,
|
||||
top_k=10,
|
||||
filters=_eq_filter("document_id", "2"),
|
||||
)
|
||||
assert result.ids == ["b1"]
|
||||
|
||||
def test_get_nodes_node_ids_not_implemented(self, store) -> None:
|
||||
with pytest.raises(NotImplementedError):
|
||||
store.get_nodes(node_ids=["x"])
|
||||
|
||||
def test_fresh_instance_sees_existing_table(self, store, tmp_path: Path) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reopened:
|
||||
assert reopened.table_exists()
|
||||
assert reopened.vector_dim() == DIM
|
||||
assert _query(reopened, [0.0] * DIM, top_k=1).ids == ["a1"]
|
||||
|
||||
def test_table_exists_and_drop(self, store) -> None:
|
||||
assert not store.table_exists()
|
||||
store.add([make_node("a1", "1")])
|
||||
assert store.table_exists()
|
||||
store.drop_table()
|
||||
assert not store.table_exists()
|
||||
assert store.vector_dim() is None
|
||||
|
||||
|
||||
class TestBuildWhere:
|
||||
def test_fails_closed_when_no_filter_is_translatable(self) -> None:
|
||||
# A nested MetadataFilters is not a MetadataFilter, so it is skipped.
|
||||
# With no translatable clauses, the function must fail closed rather
|
||||
# than emit "()" (invalid SQL) and never widen document access.
|
||||
nested = MetadataFilters(
|
||||
filters=[
|
||||
MetadataFilter(
|
||||
key="document_id",
|
||||
operator=FilterOperator.EQ,
|
||||
value="1",
|
||||
),
|
||||
],
|
||||
)
|
||||
where, params = _build_where(MetadataFilters(filters=[nested]))
|
||||
assert where == "1 = 0"
|
||||
assert params == []
|
||||
|
||||
def test_query_with_untranslatable_filter_returns_no_rows(self, store) -> None:
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2")])
|
||||
nested = MetadataFilters(
|
||||
filters=[
|
||||
MetadataFilter(
|
||||
key="document_id",
|
||||
operator=FilterOperator.EQ,
|
||||
value="1",
|
||||
),
|
||||
],
|
||||
)
|
||||
filters = MetadataFilters(filters=[nested])
|
||||
# Must not raise (no "WHERE ()") and must return nothing (fail closed).
|
||||
assert _query(store, [0.0] * DIM, top_k=5, filters=filters).ids == []
|
||||
assert store.get_nodes(filters=filters) == []
|
||||
|
||||
|
||||
class TestUpsert:
|
||||
def test_upsert_replaces_and_prunes_stale_chunks(self, store) -> None:
|
||||
store.add(
|
||||
[make_node("d1c1", "1"), make_node("d1c2", "1"), make_node("d2c1", "2")],
|
||||
)
|
||||
store.upsert_document("1", [make_node("d1new", "1")])
|
||||
result = _query(store, [0.0] * DIM, top_k=10)
|
||||
assert sorted(result.ids) == ["d1new", "d2c1"]
|
||||
|
||||
def test_upsert_creates_table_when_missing(self, store) -> None:
|
||||
store.upsert_document("1", [make_node("a1", "1")])
|
||||
assert _query(store, [0.0] * DIM, top_k=1).ids == ["a1"]
|
||||
|
||||
def test_upsert_empty_nodes_removes_document(self, store) -> None:
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2")])
|
||||
store.upsert_document("1", [])
|
||||
assert _query(store, [0.0] * DIM, top_k=10).ids == ["b1"]
|
||||
|
||||
def test_upsert_is_atomic_for_concurrent_readers(
|
||||
self,
|
||||
store,
|
||||
tmp_path: Path,
|
||||
) -> None:
|
||||
"""A second connection must never observe document 1 half-replaced."""
|
||||
store.add([make_node("a1", "1"), make_node("a2", "1")])
|
||||
with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reader:
|
||||
store.upsert_document("1", [make_node("a3", "1")])
|
||||
ids = [n.node_id for n in reader.get_nodes(filters=_in_filter(["1"]))]
|
||||
assert ids == ["a3"]
|
||||
|
||||
|
||||
class TestMetadataCoercion:
|
||||
def test_none_metadata_values_become_empty_strings(self, store) -> None:
|
||||
node = make_node("a1", "1")
|
||||
node.metadata["modified"] = None
|
||||
store.add([node]) # must not raise (vec0 rejects NULL metadata)
|
||||
assert store.get_modified_times() == {"1": ""}
|
||||
|
||||
|
||||
class TestModelNameTracking:
|
||||
def test_stored_model_name_none_without_table(self, tmp_path: Path) -> None:
|
||||
with PaperlessSqliteVecVectorStore(
|
||||
uri=str(tmp_path),
|
||||
embed_model_name="model-a",
|
||||
) as store:
|
||||
assert store.stored_model_name() is None
|
||||
|
||||
def test_model_name_stored_after_add_and_persists(self, tmp_path: Path) -> None:
|
||||
with PaperlessSqliteVecVectorStore(
|
||||
uri=str(tmp_path),
|
||||
embed_model_name="model-a",
|
||||
) as store:
|
||||
store.add([make_node("a1", "1")])
|
||||
assert store.stored_model_name() == "model-a"
|
||||
with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reopened:
|
||||
assert reopened.stored_model_name() == "model-a"
|
||||
|
||||
def test_config_mismatch_semantics(self, tmp_path: Path) -> None:
|
||||
with PaperlessSqliteVecVectorStore(
|
||||
uri=str(tmp_path),
|
||||
embed_model_name="model-a",
|
||||
) as store:
|
||||
assert not store.config_mismatch("anything") # no table yet
|
||||
store.add([make_node("a1", "1")])
|
||||
assert not store.config_mismatch("model-a")
|
||||
assert store.config_mismatch("model-b")
|
||||
|
||||
def test_config_mismatch_false_when_table_predates_tracking(
|
||||
self,
|
||||
tmp_path: Path,
|
||||
) -> None:
|
||||
with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as store: # no model name
|
||||
store.add([make_node("a1", "1")])
|
||||
assert not store.config_mismatch("model-a")
|
||||
|
||||
|
||||
class TestGetModifiedTimes:
|
||||
def test_empty_store_returns_empty_dict(self, store) -> None:
|
||||
assert store.get_modified_times() == {}
|
||||
|
||||
def test_returns_one_entry_per_document(self, store) -> None:
|
||||
store.add(
|
||||
[
|
||||
make_node("a1", "1", modified="2026-01-01T00:00:00"),
|
||||
make_node("a2", "1", modified="2026-01-01T00:00:00"),
|
||||
make_node("b1", "2", modified="2026-02-02T00:00:00"),
|
||||
],
|
||||
)
|
||||
assert store.get_modified_times() == {
|
||||
"1": "2026-01-01T00:00:00",
|
||||
"2": "2026-02-02T00:00:00",
|
||||
}
|
||||
|
||||
|
||||
class TestCompact:
|
||||
def _bloat_ratio(self, store) -> float:
|
||||
live = store.client.execute(
|
||||
"SELECT count(*) FROM documents",
|
||||
).fetchone()[0]
|
||||
# vec0 0.1.9 does not accumulate deleted rows in the _rowids shadow
|
||||
# table, so we track cumulative inserts in index_meta instead.
|
||||
row = store.client.execute(
|
||||
"SELECT value FROM index_meta WHERE key = 'total_inserts'",
|
||||
).fetchone()
|
||||
total = int(row["value"]) if row else live
|
||||
return total / max(live, 1)
|
||||
|
||||
def _churn(self, store, cycles: int) -> None:
|
||||
for i in range(cycles):
|
||||
store.upsert_document(
|
||||
"1",
|
||||
[make_node(f"gen{i}-{j}", "1", seed=float(j)) for j in range(20)],
|
||||
)
|
||||
|
||||
def test_compact_noop_below_threshold(self, store) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
store.compact()
|
||||
assert _query(store, [0.0] * DIM, top_k=1).ids == ["a1"]
|
||||
|
||||
def test_force_compact_preserves_rows_and_metadata(self, store) -> None:
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2", seed=3.0)])
|
||||
self._churn(store, 5)
|
||||
before = {
|
||||
n.node_id: n.metadata
|
||||
for n in store.get_nodes(filters=_in_filter(["1", "2"]))
|
||||
}
|
||||
store.compact(force=True)
|
||||
after = {
|
||||
n.node_id: n.metadata
|
||||
for n in store.get_nodes(filters=_in_filter(["1", "2"]))
|
||||
}
|
||||
assert after == before
|
||||
assert self._bloat_ratio(store) == pytest.approx(1.0)
|
||||
# store remains fully usable after the rebuild; use a seed far from all
|
||||
# existing nodes (gen4-0..gen4-19 have seeds 0..19) so cosine KNN is
|
||||
# unambiguous at top_k=1.
|
||||
store.upsert_document("3", [make_node("c1", "3", seed=100.0)])
|
||||
assert "c1" in _query(store, [100.0] * DIM, top_k=1).ids
|
||||
|
||||
def test_auto_compact_triggers_on_churn(self, store) -> None:
|
||||
store.add([make_node(f"s{j}", "1", seed=float(j)) for j in range(20)])
|
||||
self._churn(store, 5)
|
||||
assert self._bloat_ratio(store) > 2
|
||||
store.compact()
|
||||
assert self._bloat_ratio(store) == pytest.approx(1.0)
|
||||
|
||||
def test_compact_on_missing_table_is_noop(self, store) -> None:
|
||||
store.compact()
|
||||
store.compact(force=True)
|
||||
|
||||
def test_failed_compact_removes_temp_wal_and_shm(
|
||||
self,
|
||||
store,
|
||||
tmp_path: Path,
|
||||
monkeypatch,
|
||||
) -> None:
|
||||
"""A compact() that raises mid-rebuild must leave no .compact* files.
|
||||
|
||||
Normally the sole connection's close() checkpoints the temp WAL away,
|
||||
but a concurrent reader keeps -wal/-shm alive, so the cleanup must
|
||||
unlink them explicitly (as the structural-migration path does).
|
||||
"""
|
||||
store.add([make_node("a1", "1")])
|
||||
compact_path = str(tmp_path / DB_FILENAME) + ".compact"
|
||||
held: list[sqlite3.Connection] = []
|
||||
|
||||
def boom(conn: sqlite3.Connection, dim: int) -> None:
|
||||
# Hold an extra connection so close() of the rebuild connection is
|
||||
# not the last one -> the temp -wal/-shm survive the checkpoint.
|
||||
extra = sqlite3.connect(compact_path)
|
||||
extra.execute("SELECT 1").fetchall()
|
||||
held.append(extra)
|
||||
raise RuntimeError("boom")
|
||||
|
||||
monkeypatch.setattr(
|
||||
PaperlessSqliteVecVectorStore,
|
||||
"_create_vec_table",
|
||||
staticmethod(boom),
|
||||
)
|
||||
try:
|
||||
with pytest.raises(RuntimeError):
|
||||
store.compact(force=True)
|
||||
assert sorted(p.name for p in tmp_path.glob("*.compact*")) == []
|
||||
finally:
|
||||
for c in held:
|
||||
c.close()
|
||||
|
||||
|
||||
class TestDbFile:
|
||||
def test_single_db_file_in_index_dir(self, store, tmp_path: Path) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
assert (tmp_path / DB_FILENAME).exists()
|
||||
|
||||
def test_wal_mode_enabled(self, store) -> None:
|
||||
assert (
|
||||
store.client.execute("PRAGMA journal_mode").fetchone()[0].lower() == "wal"
|
||||
)
|
||||
|
||||
|
||||
class TestMigrations:
|
||||
"""Tests for the schema migration machinery."""
|
||||
|
||||
def _schema_version(self, store: PaperlessSqliteVecVectorStore) -> int | None:
|
||||
row = store.client.execute(
|
||||
"SELECT value FROM index_meta WHERE key = 'schema_version'",
|
||||
).fetchone()
|
||||
return int(row[0]) if row else None
|
||||
|
||||
def test_new_table_records_schema_version(self, store) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
assert self._schema_version(store) == SCHEMA_VERSION
|
||||
|
||||
def test_check_migrations_no_table_returns_false(self, store) -> None:
|
||||
assert store.check_and_run_migrations() is False
|
||||
|
||||
def test_check_migrations_current_version_returns_false(self, store) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
assert store.check_and_run_migrations() is False
|
||||
|
||||
def test_reembed_migration_returns_true(self, store, tmp_path: Path) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
migration = Migration(
|
||||
from_version=1,
|
||||
to_version=2,
|
||||
kind="re-embed",
|
||||
description="test re-embed",
|
||||
)
|
||||
MIGRATIONS.append(migration)
|
||||
try:
|
||||
from paperless_ai import vector_store as vs_mod
|
||||
|
||||
original = vs_mod.SCHEMA_VERSION
|
||||
vs_mod.SCHEMA_VERSION = 2
|
||||
result = store.check_and_run_migrations()
|
||||
finally:
|
||||
MIGRATIONS.remove(migration)
|
||||
vs_mod.SCHEMA_VERSION = original
|
||||
assert result is True
|
||||
|
||||
def test_structural_migration_copies_rows_and_updates_version(
|
||||
self,
|
||||
store,
|
||||
tmp_path: Path,
|
||||
) -> None:
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2")])
|
||||
|
||||
def apply(
|
||||
src: sqlite3.Connection,
|
||||
dst: sqlite3.Connection,
|
||||
dim: int,
|
||||
) -> None:
|
||||
dst.execute( # nosemgrep
|
||||
f"CREATE VIRTUAL TABLE {DEFAULT_TABLE_NAME} USING vec0("
|
||||
"id TEXT PRIMARY KEY, document_id TEXT, modified TEXT,"
|
||||
f" +node_content TEXT, embedding float[{dim}] distance_metric=cosine"
|
||||
")",
|
||||
)
|
||||
dst.execute(
|
||||
"INSERT INTO index_meta (key, value) VALUES ('dim', ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value",
|
||||
(str(dim),),
|
||||
)
|
||||
rows = src.execute(
|
||||
"SELECT id, document_id, modified, node_content, embedding "
|
||||
f"FROM {DEFAULT_TABLE_NAME}",
|
||||
).fetchall()
|
||||
dst.execute("BEGIN IMMEDIATE")
|
||||
dst.executemany(
|
||||
f"INSERT INTO {DEFAULT_TABLE_NAME} "
|
||||
"(id, document_id, modified, node_content, embedding) "
|
||||
"VALUES (?, ?, ?, ?, ?)",
|
||||
[
|
||||
(
|
||||
r["id"],
|
||||
r["document_id"],
|
||||
r["modified"],
|
||||
r["node_content"],
|
||||
bytes(r["embedding"]),
|
||||
)
|
||||
for r in rows
|
||||
],
|
||||
)
|
||||
dst.execute(
|
||||
"INSERT INTO index_meta (key, value) VALUES ('total_inserts', ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value",
|
||||
(str(len(rows)),),
|
||||
)
|
||||
dst.execute("COMMIT")
|
||||
|
||||
migration = Migration(
|
||||
from_version=1,
|
||||
to_version=2,
|
||||
kind="structural",
|
||||
description="test structural",
|
||||
apply=apply,
|
||||
)
|
||||
MIGRATIONS.append(migration)
|
||||
try:
|
||||
from paperless_ai import vector_store as vs_mod
|
||||
|
||||
original = vs_mod.SCHEMA_VERSION
|
||||
vs_mod.SCHEMA_VERSION = 2
|
||||
result = store.check_and_run_migrations()
|
||||
finally:
|
||||
MIGRATIONS.remove(migration)
|
||||
vs_mod.SCHEMA_VERSION = original
|
||||
|
||||
assert result is False
|
||||
assert self._schema_version(store) == 2
|
||||
ids = {n.node_id for n in store.get_nodes()}
|
||||
assert ids == {"a1", "b1"}
|
||||
|
||||
def test_compact_preserves_schema_version(self, store) -> None:
|
||||
store.add([make_node("a1", "1")])
|
||||
assert self._schema_version(store) == SCHEMA_VERSION
|
||||
store.compact(force=True)
|
||||
assert self._schema_version(store) == SCHEMA_VERSION
|
||||
|
||||
def test_stop_at_reembed_boundary(self, store) -> None:
|
||||
# Registry: structural v2, re-embed v3, structural v4.
|
||||
# Only v2 should apply; the re-embed boundary must stop execution
|
||||
# before v4 runs, and the stored version must stay at 2.
|
||||
store.add([make_node("a1", "1"), make_node("b1", "2")])
|
||||
|
||||
def copy_apply(
|
||||
src: sqlite3.Connection,
|
||||
dst: sqlite3.Connection,
|
||||
dim: int,
|
||||
) -> None:
|
||||
dst.execute( # nosemgrep
|
||||
f"CREATE VIRTUAL TABLE {DEFAULT_TABLE_NAME} USING vec0("
|
||||
"id TEXT PRIMARY KEY, document_id TEXT, modified TEXT,"
|
||||
f" +node_content TEXT, embedding float[{dim}] distance_metric=cosine"
|
||||
")",
|
||||
)
|
||||
dst.execute(
|
||||
"INSERT INTO index_meta (key, value) VALUES ('dim', ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value",
|
||||
(str(dim),),
|
||||
)
|
||||
rows = src.execute(
|
||||
"SELECT id, document_id, modified, node_content, embedding "
|
||||
f"FROM {DEFAULT_TABLE_NAME}",
|
||||
).fetchall()
|
||||
dst.execute("BEGIN IMMEDIATE")
|
||||
dst.executemany(
|
||||
f"INSERT INTO {DEFAULT_TABLE_NAME} "
|
||||
"(id, document_id, modified, node_content, embedding) "
|
||||
"VALUES (?, ?, ?, ?, ?)",
|
||||
[
|
||||
(
|
||||
r["id"],
|
||||
r["document_id"],
|
||||
r["modified"],
|
||||
r["node_content"],
|
||||
bytes(r["embedding"]),
|
||||
)
|
||||
for r in rows
|
||||
],
|
||||
)
|
||||
dst.execute("COMMIT")
|
||||
|
||||
migrations = [
|
||||
Migration(
|
||||
from_version=1,
|
||||
to_version=2,
|
||||
kind="structural",
|
||||
description="v2 structural",
|
||||
apply=copy_apply,
|
||||
),
|
||||
Migration(
|
||||
from_version=2,
|
||||
to_version=3,
|
||||
kind="re-embed",
|
||||
description="v3 re-embed boundary",
|
||||
),
|
||||
Migration(
|
||||
from_version=3,
|
||||
to_version=4,
|
||||
kind="structural",
|
||||
description="v4 structural - must not run",
|
||||
apply=copy_apply,
|
||||
),
|
||||
]
|
||||
MIGRATIONS.extend(migrations)
|
||||
try:
|
||||
from paperless_ai import vector_store as vs_mod
|
||||
|
||||
original = vs_mod.SCHEMA_VERSION
|
||||
vs_mod.SCHEMA_VERSION = 4
|
||||
result = store.check_and_run_migrations()
|
||||
finally:
|
||||
for m in migrations:
|
||||
MIGRATIONS.remove(m)
|
||||
vs_mod.SCHEMA_VERSION = original
|
||||
|
||||
assert result is True
|
||||
assert self._schema_version(store) == 2
|
||||
@@ -0,0 +1,604 @@
|
||||
import json
|
||||
import logging
|
||||
import sqlite3
|
||||
import struct
|
||||
from collections.abc import Callable
|
||||
from collections.abc import Iterator
|
||||
from collections.abc import Sequence
|
||||
from contextlib import contextmanager
|
||||
from dataclasses import dataclass
|
||||
from dataclasses import field
|
||||
from pathlib import Path
|
||||
from types import TracebackType
|
||||
from typing import Any
|
||||
from typing import Literal
|
||||
|
||||
import sqlite_vec
|
||||
from llama_index.core.bridge.pydantic import PrivateAttr
|
||||
from llama_index.core.schema import BaseNode
|
||||
from llama_index.core.vector_stores.types import BasePydanticVectorStore
|
||||
from llama_index.core.vector_stores.types import FilterCondition
|
||||
from llama_index.core.vector_stores.types import FilterOperator
|
||||
from llama_index.core.vector_stores.types import MetadataFilter
|
||||
from llama_index.core.vector_stores.types import MetadataFilters
|
||||
from llama_index.core.vector_stores.types import VectorStoreQuery
|
||||
from llama_index.core.vector_stores.types import VectorStoreQueryResult
|
||||
from llama_index.core.vector_stores.utils import metadata_dict_to_node
|
||||
from llama_index.core.vector_stores.utils import node_to_metadata_dict
|
||||
|
||||
logger = logging.getLogger("paperless_ai.vector_store")
|
||||
|
||||
DB_FILENAME = "llmindex.db"
|
||||
DEFAULT_TABLE_NAME = "documents"
|
||||
|
||||
# Current schema version. Written to index_meta at table creation and bumped
|
||||
# whenever a Migration is added to MIGRATIONS. check_and_run_migrations() uses
|
||||
# this to decide which migrations to run on an existing store.
|
||||
SCHEMA_VERSION = 1
|
||||
|
||||
# compact(): rebuild when the cumulative rowid count exceeds this multiple of
|
||||
# the live row count. DELETEs on vec0 tables never reclaim space (upstream
|
||||
# asg017/sqlite-vec#54), so per-document re-index churn grows the file until
|
||||
# a rebuild copies the live rows into a fresh table.
|
||||
COMPACT_BLOAT_RATIO = 2.0
|
||||
|
||||
# Filterable vec0 metadata columns. _build_where() only ever receives filter
|
||||
# keys we construct ourselves, but allowlisting keeps SQL identifiers safe by
|
||||
# construction.
|
||||
_FILTER_COLUMNS = frozenset({"document_id", "modified"})
|
||||
|
||||
|
||||
@dataclass
|
||||
class Migration:
|
||||
"""A schema migration for the sqlite-vec vector store.
|
||||
|
||||
kind="structural": rows are copied into a new-schema file with no
|
||||
re-embedding needed. Supply ``apply(src_conn, dst_conn, dim)`` which
|
||||
must create the vec0 table in ``dst_conn``, copy all rows from
|
||||
``src_conn``, and write ``dim`` / ``embed_model`` / ``total_inserts`` to
|
||||
``dst_conn``'s ``index_meta``. ``schema_version`` is written by the
|
||||
migration runner after ``apply`` returns.
|
||||
|
||||
kind="re-embed": the new schema requires fresh embeddings.
|
||||
``check_and_run_migrations()`` returns True when it encounters one of
|
||||
these so the caller can force a full rebuild (which recreates the table
|
||||
at the current SCHEMA_VERSION).
|
||||
"""
|
||||
|
||||
from_version: int
|
||||
to_version: int
|
||||
kind: Literal["structural", "re-embed"]
|
||||
description: str
|
||||
apply: Callable[[sqlite3.Connection, sqlite3.Connection, int], None] | None = field(
|
||||
default=None,
|
||||
repr=False,
|
||||
)
|
||||
|
||||
|
||||
# Registry of all schema migrations in order. Empty at v1 -- this is the
|
||||
# baseline. Add entries here (and bump SCHEMA_VERSION) when the schema changes.
|
||||
MIGRATIONS: list[Migration] = []
|
||||
|
||||
|
||||
def _pack(embedding: Sequence[float]) -> bytes:
|
||||
return struct.pack(f"{len(embedding)}f", *embedding)
|
||||
|
||||
|
||||
def _unpack(blob: bytes) -> list[float]:
|
||||
return list(struct.unpack(f"{len(blob) // 4}f", blob))
|
||||
|
||||
|
||||
def _build_where(filters: MetadataFilters | None) -> tuple[str, list[str]]:
|
||||
"""Translate the EQ / IN filters we use into a parameterized SQL clause
|
||||
on vec0 metadata columns. Returns ("", []) when there is nothing to filter.
|
||||
"""
|
||||
if filters is None or not filters.filters:
|
||||
return "", []
|
||||
clauses: list[str] = []
|
||||
params: list[str] = []
|
||||
for f in filters.filters:
|
||||
# filters.filters is Union[MetadataFilter, ExactMatchFilter, MetadataFilters];
|
||||
# we only build MetadataFilter entries, so skip anything else at runtime.
|
||||
if not isinstance(f, MetadataFilter):
|
||||
continue
|
||||
if f.key not in _FILTER_COLUMNS: # pragma: no cover - we build the keys
|
||||
raise NotImplementedError(f"Unsupported filter column: {f.key}")
|
||||
if f.operator == FilterOperator.IN:
|
||||
values = [str(v) for v in f.value] # type: ignore[union-attr] # value is list when operator is IN
|
||||
if not values: # pragma: no cover
|
||||
clauses.append("1 = 0")
|
||||
continue
|
||||
placeholders = ",".join("?" for _ in values)
|
||||
clauses.append(f"{f.key} IN ({placeholders})")
|
||||
params.extend(values)
|
||||
elif f.operator == FilterOperator.EQ:
|
||||
clauses.append(f"{f.key} = ?")
|
||||
params.append(str(f.value))
|
||||
else: # pragma: no cover - we only ever build EQ/IN filters
|
||||
raise NotImplementedError(f"Unsupported filter operator: {f.operator}")
|
||||
if not clauses:
|
||||
# Filters were requested but none could be translated. Fail closed
|
||||
# rather than emit "()" (invalid SQL): filters scope document access,
|
||||
# so an empty translation must match no rows, never widen the scope.
|
||||
return "1 = 0", []
|
||||
joiner = " OR " if filters.condition == FilterCondition.OR else " AND "
|
||||
return "(" + joiner.join(clauses) + ")", params
|
||||
|
||||
|
||||
class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
"""A llama-index vector store backed by a sqlite-vec vec0 table.
|
||||
|
||||
Stores one row per node: the node id (TEXT primary key), its document id
|
||||
(metadata column, used for EQ/IN filtering and per-document delete), the
|
||||
document's modified timestamp, the embedding (float32, cosine metric), and
|
||||
the serialized node (text + metadata) as JSON in an auxiliary column.
|
||||
``stores_text`` lets llama-index run off this store alone, with no
|
||||
separate docstore or index store.
|
||||
|
||||
Everything lives in one SQLite database file (``DB_FILENAME``) inside the
|
||||
directory given as ``uri`` (kept as a directory for compatibility with the
|
||||
previous LanceDB layout). WAL mode allows readers in other processes to
|
||||
proceed while the (FileLock-serialized) writer holds a transaction.
|
||||
|
||||
Implemented surface of ``BasePydanticVectorStore``
|
||||
---------------------------------------------------
|
||||
Only the methods actively used by this codebase are implemented.
|
||||
``delete_nodes`` and the ``node_ids`` lookup path of ``get_nodes`` are
|
||||
part of the llama-index interface contract and may be needed if a future
|
||||
retriever or extension invokes them — add them then, with tests.
|
||||
"""
|
||||
|
||||
stores_text: bool = True
|
||||
flat_metadata: bool = False
|
||||
|
||||
_uri: str = PrivateAttr()
|
||||
_embed_model_name: str | None = PrivateAttr()
|
||||
_conn: Any = PrivateAttr()
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
uri: str,
|
||||
embed_model_name: str | None = None,
|
||||
) -> None:
|
||||
super().__init__(stores_text=True, flat_metadata=False)
|
||||
self._uri = uri
|
||||
self._embed_model_name = embed_model_name
|
||||
self._conn = self._open_connection(str(Path(uri) / DB_FILENAME))
|
||||
|
||||
@staticmethod
|
||||
def _open_connection(db_path: str) -> sqlite3.Connection:
|
||||
conn = sqlite3.connect(
|
||||
db_path,
|
||||
timeout=30,
|
||||
isolation_level=None, # autocommit; explicit transactions below
|
||||
)
|
||||
conn.row_factory = sqlite3.Row
|
||||
conn.enable_load_extension(True) # noqa: FBT003
|
||||
sqlite_vec.load(conn)
|
||||
conn.enable_load_extension(False) # noqa: FBT003
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute("PRAGMA synchronous=NORMAL")
|
||||
conn.execute(
|
||||
"CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
|
||||
)
|
||||
return conn
|
||||
|
||||
@property
|
||||
def client(self) -> Any:
|
||||
return self._conn
|
||||
|
||||
def close(self) -> None:
|
||||
"""Close the underlying SQLite connection (idempotent)."""
|
||||
self._conn.close()
|
||||
|
||||
def __enter__(self) -> "PaperlessSqliteVecVectorStore":
|
||||
return self
|
||||
|
||||
def __exit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: TracebackType | None,
|
||||
) -> None:
|
||||
# Deterministically release the connection (and its WAL/SHM handles) so
|
||||
# it is never left open across a compaction/migration file swap.
|
||||
self.close()
|
||||
|
||||
@contextmanager
|
||||
def _transaction(self) -> Iterator[None]:
|
||||
self._conn.execute("BEGIN IMMEDIATE")
|
||||
try:
|
||||
yield
|
||||
except BaseException: # pragma: no cover
|
||||
self._conn.execute("ROLLBACK")
|
||||
raise
|
||||
else:
|
||||
self._conn.execute("COMMIT")
|
||||
|
||||
def _meta_get(self, key: str) -> str | None:
|
||||
row = self._conn.execute(
|
||||
"SELECT value FROM index_meta WHERE key = ?",
|
||||
(key,),
|
||||
).fetchone()
|
||||
return row["value"] if row else None
|
||||
|
||||
@staticmethod
|
||||
def _meta_set_on(conn: sqlite3.Connection, key: str, value: str) -> None:
|
||||
conn.execute(
|
||||
"INSERT INTO index_meta (key, value) VALUES (?, ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value",
|
||||
(key, value),
|
||||
)
|
||||
|
||||
def _meta_set(self, key: str, value: str) -> None:
|
||||
self._meta_set_on(self._conn, key, value)
|
||||
|
||||
def table_exists(self) -> bool:
|
||||
return (
|
||||
self._conn.execute(
|
||||
"SELECT 1 FROM sqlite_master WHERE type = 'table' AND name = ?",
|
||||
(DEFAULT_TABLE_NAME,),
|
||||
).fetchone()
|
||||
is not None
|
||||
)
|
||||
|
||||
def vector_dim(self) -> int | None:
|
||||
if not self.table_exists():
|
||||
return None
|
||||
value = self._meta_get("dim")
|
||||
return int(value) if value else None
|
||||
|
||||
def drop_table(self) -> None:
|
||||
self._conn.execute("DROP TABLE IF EXISTS " + DEFAULT_TABLE_NAME)
|
||||
self._conn.execute("DELETE FROM index_meta")
|
||||
|
||||
def stored_model_name(self) -> str | None:
|
||||
"""Return the embedding model name recorded at table creation, or None."""
|
||||
if not self.table_exists():
|
||||
return None
|
||||
return self._meta_get("embed_model")
|
||||
|
||||
def config_mismatch(self, model_name: str) -> bool:
|
||||
"""True when the stored model name differs from ``model_name``.
|
||||
|
||||
Returns False when no table exists or when the table predates
|
||||
model-name tracking — conservative default avoids spurious rebuilds.
|
||||
"""
|
||||
stored = self.stored_model_name()
|
||||
if stored is None:
|
||||
return False
|
||||
return stored != model_name
|
||||
|
||||
@staticmethod
|
||||
def _create_vec_table(conn: sqlite3.Connection, dim: int) -> None:
|
||||
# document_id is deliberately a metadata column, NOT a partition key:
|
||||
# partition keys change KNN `k` to per-partition semantics under IN
|
||||
# filters (asg017/sqlite-vec#142); metadata columns give a correct
|
||||
# global top-k.
|
||||
conn.execute( # nosemgrep: python.sqlalchemy.security.sqlalchemy-execute-raw-query.sqlalchemy-execute-raw-query
|
||||
"CREATE VIRTUAL TABLE "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " USING vec0("
|
||||
+ "id TEXT PRIMARY KEY,"
|
||||
+ " document_id TEXT,"
|
||||
+ " modified TEXT,"
|
||||
+ " +node_content TEXT,"
|
||||
+ " embedding float["
|
||||
+ str(int(dim))
|
||||
+ "] distance_metric=cosine"
|
||||
+ ")",
|
||||
)
|
||||
|
||||
def _create_table(self, dim: int) -> None:
|
||||
self._create_vec_table(self._conn, dim)
|
||||
self._meta_set("dim", str(dim))
|
||||
self._meta_set("schema_version", str(SCHEMA_VERSION))
|
||||
if self._embed_model_name:
|
||||
self._meta_set("embed_model", self._embed_model_name)
|
||||
|
||||
def _ensure_table(self, dim: int) -> None:
|
||||
if not self.table_exists():
|
||||
self._create_table(dim)
|
||||
|
||||
def _row(self, node: BaseNode) -> tuple[str, str, str, str, bytes]:
|
||||
meta = node_to_metadata_dict(
|
||||
node,
|
||||
remove_text=False,
|
||||
flat_metadata=self.flat_metadata,
|
||||
)
|
||||
# vec0 metadata columns reject NULL (asg017/sqlite-vec#141): coerce
|
||||
# every value to a string, with "" as the absent sentinel.
|
||||
document_id = node.ref_doc_id or node.metadata.get("document_id")
|
||||
return (
|
||||
node.node_id,
|
||||
str(document_id or ""),
|
||||
str(node.metadata.get("modified") or ""),
|
||||
json.dumps(meta),
|
||||
_pack(node.get_embedding()),
|
||||
)
|
||||
|
||||
_INSERT = (
|
||||
"INSERT INTO "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " (id, document_id, modified, node_content, embedding) VALUES (?, ?, ?, ?, ?)"
|
||||
)
|
||||
|
||||
def _increment_total_inserts(self, count: int) -> None:
|
||||
"""Increment the cumulative insert counter stored in index_meta.
|
||||
|
||||
This counter never decreases (DELETEs do not decrement it) and is
|
||||
used by compact() to estimate the bloat ratio: when total_inserts /
|
||||
live_rows exceeds COMPACT_BLOAT_RATIO the table has accumulated
|
||||
enough deleted-but-not-freed rows to warrant a rebuild.
|
||||
"""
|
||||
current = int(self._meta_get("total_inserts") or "0")
|
||||
self._meta_set("total_inserts", str(current + count))
|
||||
|
||||
def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:
|
||||
if not nodes:
|
||||
return []
|
||||
rows = [self._row(node) for node in nodes]
|
||||
with self._transaction():
|
||||
self._ensure_table(len(nodes[0].get_embedding()))
|
||||
self._conn.executemany(self._INSERT, rows)
|
||||
self._increment_total_inserts(len(rows))
|
||||
return [node.node_id for node in nodes]
|
||||
|
||||
def upsert_document(self, document_id: str, nodes: list[BaseNode]) -> list[str]:
|
||||
"""Atomically replace all stored chunks of ``document_id`` with ``nodes``.
|
||||
|
||||
One transaction deletes the document's existing rows and inserts the
|
||||
new set (vec0's INSERT OR REPLACE is broken upstream, #259, so
|
||||
delete+insert it is). WAL readers in other processes see either the
|
||||
old or the new chunk set, never a partial state.
|
||||
"""
|
||||
rows = [self._row(node) for node in nodes]
|
||||
with self._transaction():
|
||||
if nodes:
|
||||
self._ensure_table(len(nodes[0].get_embedding()))
|
||||
if self.table_exists():
|
||||
self._conn.execute(
|
||||
"DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
|
||||
(str(document_id),),
|
||||
)
|
||||
if rows:
|
||||
self._conn.executemany(self._INSERT, rows)
|
||||
self._increment_total_inserts(len(rows))
|
||||
return [node.node_id for node in nodes]
|
||||
|
||||
def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
|
||||
if self.table_exists():
|
||||
with self._transaction():
|
||||
self._conn.execute(
|
||||
"DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
|
||||
(str(ref_doc_id),),
|
||||
)
|
||||
|
||||
def _rows_to_nodes(self, rows: list[sqlite3.Row]) -> list[BaseNode]:
|
||||
nodes: list[BaseNode] = []
|
||||
for row in rows:
|
||||
node = metadata_dict_to_node(json.loads(row["node_content"]))
|
||||
node.embedding = _unpack(row["embedding"])
|
||||
nodes.append(node)
|
||||
return nodes
|
||||
|
||||
def get_nodes(
|
||||
self,
|
||||
node_ids: list[str] | None = None,
|
||||
filters: MetadataFilters | None = None,
|
||||
**kwargs: Any,
|
||||
) -> list[BaseNode]:
|
||||
if node_ids is not None: # pragma: no cover
|
||||
# node_ids lookup is not implemented; see class docstring.
|
||||
raise NotImplementedError(
|
||||
"PaperlessSqliteVecVectorStore does not support node_ids lookup",
|
||||
)
|
||||
if not self.table_exists():
|
||||
return []
|
||||
where, params = _build_where(filters)
|
||||
sql = "SELECT node_content, embedding FROM " + DEFAULT_TABLE_NAME
|
||||
if where:
|
||||
sql += " WHERE " + where
|
||||
return self._rows_to_nodes(self._conn.execute(sql, params).fetchall())
|
||||
|
||||
def query(
|
||||
self,
|
||||
query: VectorStoreQuery,
|
||||
**kwargs: Any,
|
||||
) -> VectorStoreQueryResult:
|
||||
if not self.table_exists():
|
||||
return VectorStoreQueryResult(nodes=[], similarities=[], ids=[])
|
||||
if query.query_embedding is None: # pragma: no cover
|
||||
return VectorStoreQueryResult(nodes=[], similarities=[], ids=[])
|
||||
top_k = query.similarity_top_k if query.similarity_top_k is not None else 10
|
||||
where, params = _build_where(query.filters)
|
||||
sql = (
|
||||
"SELECT id, node_content, embedding, distance FROM "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " WHERE embedding MATCH ? AND k = ?"
|
||||
)
|
||||
if where:
|
||||
sql += " AND " + where
|
||||
rows = self._conn.execute(
|
||||
sql,
|
||||
[_pack(query.query_embedding), top_k, *params],
|
||||
).fetchall()
|
||||
# vec0 returns rows distance-sorted ascending; slice defensively in
|
||||
# case future schema changes alter k semantics (e.g. partition keys
|
||||
# return k rows per partition).
|
||||
rows = rows[:top_k]
|
||||
nodes = self._rows_to_nodes(rows)
|
||||
# Cosine distance in [0, 2]; map to a descending similarity.
|
||||
# vec0 returns None distance when the query embedding is the zero vector
|
||||
# (no meaningful cosine angle); treat that as maximum distance (1.0) so
|
||||
# the row is included but ranked last.
|
||||
sims = [
|
||||
1.0 - float(row["distance"] if row["distance"] is not None else 1.0)
|
||||
for row in rows
|
||||
]
|
||||
ids = [row["id"] for row in rows]
|
||||
return VectorStoreQueryResult(nodes=nodes, similarities=sims, ids=ids)
|
||||
|
||||
def get_modified_times(self) -> dict[str, str]:
|
||||
"""Return {document_id: stored_modified_isoformat} for all indexed documents.
|
||||
|
||||
All chunks of a document share the same ``modified`` value, so the
|
||||
first row seen per document is sufficient.
|
||||
"""
|
||||
if not self.table_exists():
|
||||
return {}
|
||||
result: dict[str, str] = {}
|
||||
for row in self._conn.execute(
|
||||
"SELECT document_id, modified FROM " + DEFAULT_TABLE_NAME,
|
||||
):
|
||||
doc_id = str(row["document_id"])
|
||||
if doc_id not in result:
|
||||
result[doc_id] = str(row["modified"] or "")
|
||||
return result
|
||||
|
||||
def compact(self, *, force: bool = False) -> None:
|
||||
"""Rebuild the database file to reclaim space left behind by DELETEs.
|
||||
|
||||
vec0 DELETE only invalidates rows; the vector data stays in the file
|
||||
forever (asg017/sqlite-vec#54), and per-document re-indexing is a
|
||||
delete+insert. The cumulative insert counter in ``index_meta`` tracks
|
||||
total rows ever written; when that exceeds ``COMPACT_BLOAT_RATIO`` x
|
||||
the live row count (or when forced), live rows are copied into a fresh
|
||||
database file and swapped in via ``os.replace``.
|
||||
|
||||
Note: ``ALTER TABLE ... RENAME TO`` on vec0 virtual tables does NOT
|
||||
rename the shadow tables (sqlite-vec upstream limitation), so
|
||||
an in-place rename-based rebuild is not safe. The file-swap approach
|
||||
is the maintainer-endorsed workaround (asg017/sqlite-vec#205).
|
||||
"""
|
||||
if not self.table_exists():
|
||||
return
|
||||
live = self._conn.execute(
|
||||
"SELECT count(*) FROM " + DEFAULT_TABLE_NAME,
|
||||
).fetchone()[0]
|
||||
total = int(self._meta_get("total_inserts") or str(live))
|
||||
if not force and total <= max(live, 1) * COMPACT_BLOAT_RATIO:
|
||||
return
|
||||
dim = self.vector_dim()
|
||||
if dim is None: # pragma: no cover - dim is written at creation
|
||||
logger.warning("Skipping compact: no stored vector dimension")
|
||||
return
|
||||
logger.info(
|
||||
"Compacting LLM index (%d live rows, %d cumulative inserts)",
|
||||
live,
|
||||
total,
|
||||
)
|
||||
db_path = str(Path(self._uri) / DB_FILENAME)
|
||||
compact_path = db_path + ".compact"
|
||||
|
||||
# Copy all live rows into a fresh database file.
|
||||
new_conn = self._open_connection(compact_path)
|
||||
try:
|
||||
self._create_vec_table(new_conn, dim)
|
||||
self._meta_set_on(new_conn, "dim", str(dim))
|
||||
for key in ("embed_model", "schema_version"):
|
||||
value = self._meta_get(key)
|
||||
if value is not None:
|
||||
self._meta_set_on(new_conn, key, value)
|
||||
rows = self._conn.execute(
|
||||
"SELECT id, document_id, modified, node_content, embedding "
|
||||
"FROM " + DEFAULT_TABLE_NAME,
|
||||
).fetchall()
|
||||
new_conn.execute("BEGIN IMMEDIATE")
|
||||
new_conn.executemany(
|
||||
self._INSERT,
|
||||
[
|
||||
(
|
||||
r["id"],
|
||||
r["document_id"],
|
||||
r["modified"],
|
||||
r["node_content"],
|
||||
bytes(r["embedding"]),
|
||||
)
|
||||
for r in rows
|
||||
],
|
||||
)
|
||||
# Reset the cumulative counter: after compact, total_inserts == live.
|
||||
self._meta_set_on(new_conn, "total_inserts", str(live))
|
||||
new_conn.execute("COMMIT")
|
||||
except BaseException:
|
||||
new_conn.close()
|
||||
for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
|
||||
Path(p).unlink(missing_ok=True)
|
||||
raise
|
||||
new_conn.close()
|
||||
self._swap_in_compact(compact_path, db_path)
|
||||
|
||||
def _swap_in_compact(self, compact_path: str, db_path: str) -> None:
|
||||
"""Atomically replace the live database with the compacted copy."""
|
||||
self._conn.close()
|
||||
for suffix in ["-wal", "-shm"]:
|
||||
stale = Path(compact_path + suffix)
|
||||
if stale.exists(): # pragma: no cover
|
||||
stale.unlink()
|
||||
Path(compact_path).replace(db_path)
|
||||
self._conn = self._open_connection(db_path)
|
||||
|
||||
def check_and_run_migrations(self) -> bool:
|
||||
"""Apply any pending schema migrations to the store.
|
||||
|
||||
Structural migrations copy live rows into a new-schema file with no
|
||||
re-embedding. Re-embed migrations cannot be applied automatically;
|
||||
this method returns True when one is encountered so the caller can
|
||||
force a full rebuild (which recreates the table at SCHEMA_VERSION).
|
||||
|
||||
Must be called under the write FileLock. No-op when the table does
|
||||
not exist or is already at SCHEMA_VERSION.
|
||||
"""
|
||||
if not self.table_exists():
|
||||
return False
|
||||
|
||||
raw = self._meta_get("schema_version")
|
||||
current = int(raw) if raw is not None else SCHEMA_VERSION
|
||||
if current >= SCHEMA_VERSION:
|
||||
return False
|
||||
|
||||
pending = sorted(
|
||||
[m for m in MIGRATIONS if current <= m.from_version < SCHEMA_VERSION],
|
||||
key=lambda m: m.from_version,
|
||||
)
|
||||
|
||||
for migration in pending:
|
||||
if migration.kind == "re-embed":
|
||||
logger.warning(
|
||||
"LLM index schema v%d -> v%d requires re-embedding (%s); "
|
||||
"forcing full rebuild.",
|
||||
migration.from_version,
|
||||
migration.to_version,
|
||||
migration.description,
|
||||
)
|
||||
return True
|
||||
logger.info(
|
||||
"Running structural LLM index migration v%d -> v%d: %s",
|
||||
migration.from_version,
|
||||
migration.to_version,
|
||||
migration.description,
|
||||
)
|
||||
self._run_structural_migration(migration)
|
||||
|
||||
return False
|
||||
|
||||
def _run_structural_migration(self, migration: Migration) -> None:
|
||||
"""Execute a structural migration using the same file-swap as compact()."""
|
||||
assert migration.apply is not None, "structural migration must have apply()"
|
||||
dim = self.vector_dim()
|
||||
if dim is None: # pragma: no cover
|
||||
raise RuntimeError("Cannot migrate: no stored vector dimension")
|
||||
db_path = str(Path(self._uri) / DB_FILENAME)
|
||||
compact_path = db_path + ".compact"
|
||||
new_conn = self._open_connection(compact_path)
|
||||
try:
|
||||
migration.apply(self._conn, new_conn, dim)
|
||||
self._meta_set_on(new_conn, "schema_version", str(migration.to_version))
|
||||
except BaseException: # pragma: no cover
|
||||
new_conn.close()
|
||||
for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
|
||||
Path(p).unlink(missing_ok=True)
|
||||
raise
|
||||
new_conn.close()
|
||||
self._swap_in_compact(compact_path, db_path)
|
||||
@@ -4,6 +4,8 @@ import logging
|
||||
import ssl
|
||||
import tempfile
|
||||
import traceback
|
||||
import unicodedata
|
||||
from datetime import date
|
||||
from datetime import timedelta
|
||||
from fnmatch import fnmatch
|
||||
from pathlib import Path
|
||||
@@ -384,7 +386,7 @@ def make_criterias(rule: MailRule, *, supports_gmail_labels: bool):
|
||||
Returns criteria to be applied to MailBox.fetch for the given rule.
|
||||
"""
|
||||
|
||||
maximum_age = timezone.now().date() - timedelta(days=rule.maximum_age)
|
||||
maximum_age = date.today() - timedelta(days=rule.maximum_age)
|
||||
criterias = {}
|
||||
if rule.maximum_age > 0:
|
||||
criterias["date_gte"] = maximum_age
|
||||
@@ -495,10 +497,10 @@ class MailAccountHandler(LoggingMixin):
|
||||
rule: MailRule,
|
||||
) -> str | None:
|
||||
if rule.assign_title_from == MailRule.TitleSource.FROM_SUBJECT:
|
||||
return message.subject
|
||||
return unicodedata.normalize("NFC", message.subject)
|
||||
|
||||
elif rule.assign_title_from == MailRule.TitleSource.FROM_FILENAME:
|
||||
return Path(att.filename).stem
|
||||
return unicodedata.normalize("NFC", Path(att.filename).stem)
|
||||
|
||||
elif rule.assign_title_from == MailRule.TitleSource.NONE:
|
||||
return None
|
||||
@@ -636,8 +638,8 @@ class MailAccountHandler(LoggingMixin):
|
||||
self.log.info(f"Located folder: {folder_info.name}")
|
||||
except Exception as e:
|
||||
self.log.error(
|
||||
"Exception during folder listing, unable to provide list folders: %s",
|
||||
e,
|
||||
"Exception during folder listing, unable to provide list folders: "
|
||||
+ str(e),
|
||||
)
|
||||
|
||||
raise MailError(
|
||||
@@ -865,7 +867,9 @@ class MailAccountHandler(LoggingMixin):
|
||||
),
|
||||
)
|
||||
|
||||
attachment_name = pathvalidate.sanitize_filename(att.filename)
|
||||
attachment_name = pathvalidate.sanitize_filename(
|
||||
unicodedata.normalize("NFC", att.filename),
|
||||
)
|
||||
if attachment_name:
|
||||
temp_filename = temp_dir / attachment_name
|
||||
else: # pragma: no cover
|
||||
@@ -881,7 +885,7 @@ class MailAccountHandler(LoggingMixin):
|
||||
)
|
||||
doc_overrides = DocumentMetadataOverrides(
|
||||
title=title,
|
||||
filename=pathvalidate.sanitize_filename(att.filename),
|
||||
filename=attachment_name,
|
||||
correspondent_id=correspondent.id if correspondent else None,
|
||||
document_type_id=doc_type.id if doc_type else None,
|
||||
tag_ids=tag_ids,
|
||||
@@ -987,7 +991,9 @@ class MailAccountHandler(LoggingMixin):
|
||||
)
|
||||
doc_overrides = DocumentMetadataOverrides(
|
||||
title=message.subject,
|
||||
filename=pathvalidate.sanitize_filename(f"{message.subject}.eml"),
|
||||
filename=pathvalidate.sanitize_filename(
|
||||
unicodedata.normalize("NFC", f"{message.subject}.eml"),
|
||||
),
|
||||
correspondent_id=correspondent.id if correspondent else None,
|
||||
document_type_id=doc_type.id if doc_type else None,
|
||||
tag_ids=tag_ids,
|
||||
|
||||
@@ -349,10 +349,9 @@ class MailMocker(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
len(expected_call_args),
|
||||
)
|
||||
|
||||
for (_, mock_kwargs), expected_signatures in zip(
|
||||
for (mock_args, mock_kwargs), expected_signatures in zip(
|
||||
self._queue_consumption_tasks_mock.call_args_list,
|
||||
expected_call_args,
|
||||
strict=False,
|
||||
):
|
||||
consume_tasks = mock_kwargs["consume_tasks"]
|
||||
|
||||
@@ -362,7 +361,6 @@ class MailMocker(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
for consume_task, expected_signature in zip(
|
||||
consume_tasks,
|
||||
expected_signatures,
|
||||
strict=False,
|
||||
):
|
||||
input_doc = consume_task.kwargs["input_doc"]
|
||||
overrides = consume_task.kwargs["overrides"]
|
||||
@@ -385,7 +383,7 @@ class MailMocker(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
|
||||
"""
|
||||
Applies pending actions to mails by inspecting calls to the queue_consumption_tasks method.
|
||||
"""
|
||||
for _, kwargs in self._queue_consumption_tasks_mock.call_args_list:
|
||||
for args, kwargs in self._queue_consumption_tasks_mock.call_args_list:
|
||||
message = kwargs["message"]
|
||||
rule = kwargs["rule"]
|
||||
apply_mail_action([], rule.pk, message.uid, message.subject, message.date)
|
||||
|
||||
@@ -0,0 +1,182 @@
|
||||
"""
|
||||
Tests that mail attachment filenames and EML subject filenames are
|
||||
normalized to NFC Unicode before being stored as document overrides.
|
||||
|
||||
Filenames from MIME headers can arrive in NFD form (e.g. from macOS Mail),
|
||||
and must be normalized to NFC so filenames are consistent regardless of the
|
||||
sending client.
|
||||
"""
|
||||
|
||||
import unicodedata
|
||||
from pathlib import Path
|
||||
from unittest import mock
|
||||
|
||||
import pytest
|
||||
|
||||
from documents.tests.utils import remove_dirs
|
||||
from documents.tests.utils import setup_directories
|
||||
from paperless_mail.models import MailRule
|
||||
from paperless_mail.tests.factories import MailAccountFactory
|
||||
from paperless_mail.tests.test_mail import MessageBuilder
|
||||
from paperless_mail.tests.test_mail import _AttachmentDef
|
||||
from paperless_mail.tests.test_mail import fake_magic_from_buffer
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def directories(settings):
|
||||
dirs = setup_directories()
|
||||
yield dirs
|
||||
remove_dirs(dirs)
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def queue_consumption_tasks_mock():
|
||||
with mock.patch("paperless_mail.mail.queue_consumption_tasks") as m:
|
||||
yield m
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def mail_account(db):
|
||||
return MailAccountFactory()
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def attachment_rule(mail_account):
|
||||
rule = MailRule(
|
||||
name="attachment rule",
|
||||
account=mail_account,
|
||||
assign_title_from=MailRule.TitleSource.FROM_FILENAME,
|
||||
consumption_scope=MailRule.ConsumptionScope.ATTACHMENTS_ONLY,
|
||||
attachment_type=MailRule.AttachmentProcessing.ATTACHMENTS_ONLY,
|
||||
)
|
||||
rule.save()
|
||||
return rule
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def eml_rule(mail_account):
|
||||
rule = MailRule(
|
||||
name="eml rule",
|
||||
account=mail_account,
|
||||
assign_title_from=MailRule.TitleSource.FROM_SUBJECT,
|
||||
consumption_scope=MailRule.ConsumptionScope.EML_ONLY,
|
||||
attachment_type=MailRule.AttachmentProcessing.ATTACHMENTS_ONLY,
|
||||
)
|
||||
rule.save()
|
||||
return rule
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def message_builder():
|
||||
return MessageBuilder()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@mock.patch("paperless_mail.mail.magic.from_buffer", fake_magic_from_buffer)
|
||||
class TestMailNFCNormalization:
|
||||
"""Attachment filenames and EML subject filenames must be NFC-normalized."""
|
||||
|
||||
def test_attachment_nfd_filename_normalized_to_nfc(
|
||||
self,
|
||||
directories,
|
||||
queue_consumption_tasks_mock,
|
||||
attachment_rule,
|
||||
mail_account_handler,
|
||||
message_builder,
|
||||
):
|
||||
"""Attachment filename arriving as NFD must be stored as NFC in both
|
||||
the overrides and the temp file written to disk.
|
||||
"""
|
||||
nfd_filename = unicodedata.normalize("NFD", "Rechnung März.pdf")
|
||||
nfc_filename = unicodedata.normalize("NFC", "Rechnung März.pdf")
|
||||
|
||||
# Confirm the fixture is actually NFD (not already NFC)
|
||||
assert unicodedata.is_normalized("NFD", nfd_filename)
|
||||
assert not unicodedata.is_normalized("NFC", nfd_filename)
|
||||
|
||||
message = message_builder.create_message(
|
||||
subject="Test invoice",
|
||||
from_="sender@example.com",
|
||||
attachments=[
|
||||
_AttachmentDef(filename=nfd_filename, content=b"%PDF-1.4 test"),
|
||||
],
|
||||
)
|
||||
|
||||
result = mail_account_handler._handle_message(message, attachment_rule)
|
||||
|
||||
assert result == 1
|
||||
queue_consumption_tasks_mock.assert_called_once()
|
||||
|
||||
call_kwargs = queue_consumption_tasks_mock.call_args.kwargs
|
||||
consume_tasks = call_kwargs["consume_tasks"]
|
||||
assert len(consume_tasks) == 1
|
||||
|
||||
overrides = consume_tasks[0].kwargs["overrides"]
|
||||
assert overrides.filename == nfc_filename
|
||||
assert unicodedata.is_normalized("NFC", overrides.filename)
|
||||
assert unicodedata.is_normalized("NFC", overrides.title)
|
||||
|
||||
input_doc = consume_tasks[0].kwargs["input_doc"]
|
||||
original_file = Path(input_doc.original_file)
|
||||
assert original_file.exists()
|
||||
assert original_file.name == nfc_filename
|
||||
|
||||
def test_eml_subject_filename_nfc(
|
||||
self,
|
||||
directories,
|
||||
queue_consumption_tasks_mock,
|
||||
eml_rule,
|
||||
mail_account_handler,
|
||||
message_builder,
|
||||
):
|
||||
"""EML filename derived from subject arriving as NFD must be stored as NFC."""
|
||||
nfd_subject = unicodedata.normalize("NFD", "Rechnung März 2024")
|
||||
nfc_expected_filename = unicodedata.normalize("NFC", "Rechnung März 2024.eml")
|
||||
|
||||
# Confirm the fixture is actually NFD
|
||||
assert unicodedata.is_normalized("NFD", nfd_subject)
|
||||
|
||||
message = message_builder.create_message(
|
||||
subject=nfd_subject,
|
||||
from_="sender@example.com",
|
||||
attachments=0,
|
||||
)
|
||||
|
||||
mail_account_handler._handle_message(message, eml_rule)
|
||||
|
||||
queue_consumption_tasks_mock.assert_called_once()
|
||||
|
||||
call_kwargs = queue_consumption_tasks_mock.call_args.kwargs
|
||||
consume_tasks = call_kwargs["consume_tasks"]
|
||||
assert len(consume_tasks) == 1
|
||||
|
||||
overrides = consume_tasks[0].kwargs["overrides"]
|
||||
assert overrides.filename == nfc_expected_filename
|
||||
assert unicodedata.is_normalized("NFC", overrides.filename)
|
||||
|
||||
def test_already_nfc_attachment_filename_unchanged(
|
||||
self,
|
||||
directories,
|
||||
queue_consumption_tasks_mock,
|
||||
attachment_rule,
|
||||
mail_account_handler,
|
||||
message_builder,
|
||||
):
|
||||
"""An attachment filename already in NFC must pass through unchanged."""
|
||||
nfc_filename = "Invoice_2024.pdf"
|
||||
assert unicodedata.is_normalized("NFC", nfc_filename)
|
||||
|
||||
message = message_builder.create_message(
|
||||
subject="Invoice",
|
||||
from_="sender@example.com",
|
||||
attachments=[
|
||||
_AttachmentDef(filename=nfc_filename, content=b"%PDF-1.4 test"),
|
||||
],
|
||||
)
|
||||
|
||||
mail_account_handler._handle_message(message, attachment_rule)
|
||||
|
||||
call_kwargs = queue_consumption_tasks_mock.call_args.kwargs
|
||||
consume_tasks = call_kwargs["consume_tasks"]
|
||||
overrides = consume_tasks[0].kwargs["overrides"]
|
||||
assert overrides.filename == nfc_filename
|
||||
@@ -184,12 +184,7 @@ class TestMailMessageGpgDecryptor(TestMail):
|
||||
EMAIL_GNUPG_HOME=empty_gpg_home,
|
||||
):
|
||||
message_decryptor = MailMessageDecryptor()
|
||||
self.assertRaisesRegex(
|
||||
Exception,
|
||||
"Decryption failed",
|
||||
message_decryptor.run,
|
||||
encrypted_message,
|
||||
)
|
||||
self.assertRaises(Exception, message_decryptor.run, encrypted_message)
|
||||
finally:
|
||||
# Clean up the temporary GPG home used only by this test
|
||||
try:
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import datetime
|
||||
import logging
|
||||
from datetime import timedelta
|
||||
from http import HTTPStatus
|
||||
@@ -85,7 +86,7 @@ class MailAccountViewSet(PassUserMixin, ModelViewSet[MailAccount]):
|
||||
@action(methods=["post"], detail=False)
|
||||
def test(self, request):
|
||||
logger = logging.getLogger("paperless_mail")
|
||||
request.data["name"] = timezone.now().isoformat()
|
||||
request.data["name"] = datetime.datetime.now().isoformat()
|
||||
serializer = self.get_serializer(data=request.data)
|
||||
serializer.is_valid(raise_exception=True)
|
||||
existing_account = None
|
||||
|
||||
@@ -1200,23 +1200,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/27/8d/2bc5f5546ff2ccb3f7de06742853483ab75bf74f36a92254702f8baecc79/factory_boy-3.3.3-py2.py3-none-any.whl", hash = "sha256:1c39e3289f7e667c4285433f305f8d506efc2fe9c73aaea4151ebd5cdea394fc", size = 37036, upload-time = "2025-02-03T09:49:01.659Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "faiss-cpu"
|
||||
version = "1.13.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "numpy", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "packaging", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
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]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/07/c9/671f66f6b31ec48e5825d36435f0cb91189fa8bb6b50724029dbff4ca83c/faiss_cpu-1.13.2-cp310-abi3-macosx_14_0_arm64.whl", hash = "sha256:a9064eb34f8f64438dd5b95c8f03a780b1a3f0b99c46eeacb1f0b5d15fc02dc1", size = 3452776, upload-time = "2025-12-24T10:27:01.419Z" },
|
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{ url = "https://files.pythonhosted.org/packages/5a/4a/97150aa1582fb9c2bca95bd8fc37f27d3b470acec6f0a6833844b21e4b40/faiss_cpu-1.13.2-cp310-abi3-macosx_14_0_x86_64.whl", hash = "sha256:c8d097884521e1ecaea6467aeebbf1aa56ee4a36350b48b2ca6b39366565c317", size = 7896434, upload-time = "2025-12-24T10:27:03.592Z" },
|
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{ url = "https://files.pythonhosted.org/packages/0b/d0/0940575f059591ca31b63a881058adb16a387020af1709dcb7669460115c/faiss_cpu-1.13.2-cp310-abi3-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0ee330a284042c2480f2e90450a10378fd95655d62220159b1408f59ee83ebf1", size = 11485825, upload-time = "2025-12-24T10:27:05.681Z" },
|
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{ url = "https://files.pythonhosted.org/packages/e7/e1/a5acac02aa593809f0123539afe7b4aff61d1db149e7093239888c9053e1/faiss_cpu-1.13.2-cp310-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ab88ee287c25a119213153d033f7dd64c3ccec466ace267395872f554b648cd7", size = 23845772, upload-time = "2025-12-24T10:27:08.194Z" },
|
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{ url = "https://files.pythonhosted.org/packages/9c/7b/49dcaf354834ec457e85ca769d50bc9b5f3003fab7c94a9dcf08cf742793/faiss_cpu-1.13.2-cp310-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:85511129b34f890d19c98b82a0cd5ffb27d89d1cec2ee41d2621ee9f9ef8cf3f", size = 13477567, upload-time = "2025-12-24T10:27:10.822Z" },
|
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{ url = "https://files.pythonhosted.org/packages/f7/6b/12bb4037921c38bb2c0b4cfc213ca7e04bbbebbfea89b0b5746248ce446e/faiss_cpu-1.13.2-cp310-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:8b32eb4065bac352b52a9f5ae07223567fab0a976c7d05017c01c45a1c24264f", size = 25102239, upload-time = "2025-12-24T10:27:13.476Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "faker"
|
||||
version = "40.15.0"
|
||||
@@ -2280,18 +2263,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f4/0c/fdddaee5391d915d3d568d2d8dbdb7c95647e65bb94d4ddb31d47cef5daf/llama_index_llms_openai_like-0.7.2-py3-none-any.whl", hash = "sha256:1f45a7b1cec8fb3f5997684327ffe6c19f93e789c2fff35dc5522465850faf0b", size = 6602, upload-time = "2026-04-23T23:05:31.708Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "llama-index-vector-stores-faiss"
|
||||
version = "0.6.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "llama-index-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/7c/32/89a04e38fa9595b7116c61955d9a67085f0a5480738e9c14063e374724c2/llama_index_vector_stores_faiss-0.6.0.tar.gz", hash = "sha256:00bfeb6cb7571e0e856566cb4f10c89b415b6108f151d9ad48ee9c31da563f5e", size = 6045, upload-time = "2026-03-12T20:46:31.454Z" }
|
||||
wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/5b/85/465b4f199075ae7773c181b2f98cf689f3107a8de031e7a9d4cd5e906446/llama_index_vector_stores_faiss-0.6.0-py3-none-any.whl", hash = "sha256:d4600c60ef5411d9e35ba573b4f416a5e13ea04c6f942c8e6f49f03f2feb4f3b", size = 7739, upload-time = "2026-03-12T20:46:30.736Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "llama-index-workflows"
|
||||
version = "2.20.0"
|
||||
@@ -2912,7 +2883,6 @@ dependencies = [
|
||||
{ name = "drf-spectacular", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "drf-spectacular-sidecar", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "drf-writable-nested", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "faiss-cpu", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "filelock", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "flower", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "gotenberg-client", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
@@ -2927,7 +2897,6 @@ dependencies = [
|
||||
{ name = "llama-index-embeddings-openai-like", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "llama-index-llms-ollama", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "llama-index-llms-openai-like", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "llama-index-vector-stores-faiss", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "nltk", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "ocrmypdf", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "openai", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
@@ -2944,6 +2913,7 @@ dependencies = [
|
||||
{ name = "scikit-learn", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "sentence-transformers", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "setproctitle", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "sqlite-vec", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "tantivy", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "tika-client", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "torch", version = "2.11.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" },
|
||||
@@ -3062,7 +3032,6 @@ requires-dist = [
|
||||
{ name = "drf-spectacular", specifier = "~=0.28" },
|
||||
{ name = "drf-spectacular-sidecar", specifier = "~=2026.5.1" },
|
||||
{ name = "drf-writable-nested", specifier = "~=0.7.1" },
|
||||
{ name = "faiss-cpu", specifier = ">=1.10" },
|
||||
{ name = "filelock", specifier = "~=3.29.0" },
|
||||
{ name = "flower", specifier = "~=2.0.1" },
|
||||
{ name = "gotenberg-client", specifier = "~=0.14.0" },
|
||||
@@ -3078,7 +3047,6 @@ requires-dist = [
|
||||
{ name = "llama-index-embeddings-openai-like", specifier = ">=0.2.2" },
|
||||
{ name = "llama-index-llms-ollama", specifier = ">=0.9.1" },
|
||||
{ name = "llama-index-llms-openai-like", specifier = ">=0.7.1" },
|
||||
{ name = "llama-index-vector-stores-faiss", specifier = ">=0.5.2" },
|
||||
{ name = "mysqlclient", marker = "extra == 'mariadb'", specifier = "~=2.2.7" },
|
||||
{ name = "nltk", specifier = "~=3.9.1" },
|
||||
{ name = "ocrmypdf", specifier = "~=17.4.2" },
|
||||
@@ -3101,6 +3069,7 @@ requires-dist = [
|
||||
{ name = "scikit-learn", specifier = "~=1.8.0" },
|
||||
{ name = "sentence-transformers", specifier = ">=5.4.1" },
|
||||
{ name = "setproctitle", specifier = "~=1.3.4" },
|
||||
{ name = "sqlite-vec", specifier = "==0.1.9" },
|
||||
{ name = "tantivy", specifier = "~=0.26.0" },
|
||||
{ name = "tika-client", specifier = "~=0.11.0" },
|
||||
{ name = "torch", specifier = "~=2.11.0", index = "https://download.pytorch.org/whl/cpu" },
|
||||
@@ -4699,6 +4668,17 @@ asyncio = [
|
||||
{ name = "greenlet", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "sqlite-vec"
|
||||
version = "0.1.9"
|
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source = { registry = "https://pypi.org/simple" }
|
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wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/68/85/9fad0045d8e7c8df3e0fa5a56c630e8e15ad6e5ca2e6106fceb666aa6638/sqlite_vec-0.1.9-py3-none-macosx_10_6_x86_64.whl", hash = "sha256:1b62a7f0a060d9475575d4e599bbf94a13d85af896bc1ce86ee80d1b5b48e5fb", size = 131171, upload-time = "2026-03-31T08:02:31.717Z" },
|
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{ url = "https://files.pythonhosted.org/packages/a4/3d/3677e0cd2f92e5ebc43cd29fbf565b75582bff1ccfa0b8327c7508e1084f/sqlite_vec-0.1.9-py3-none-macosx_11_0_arm64.whl", hash = "sha256:1d52e30513bae4cc9778ddbf6145610434081be4c3afe57cd877893bad9f6b6c", size = 165434, upload-time = "2026-03-31T08:02:32.712Z" },
|
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{ url = "https://files.pythonhosted.org/packages/00/d4/f2b936d3bdc38eadcbd2a87875815db36430fab0363182ba5d12cd8e0b51/sqlite_vec-0.1.9-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e921e592f24a5f9a18f590b6ddd530eb637e2d474e3b1972f9bbeb773aa3cb9", size = 160076, upload-time = "2026-03-31T08:02:33.796Z" },
|
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{ url = "https://files.pythonhosted.org/packages/6f/ad/6afd073b0f817b3e03f9e37ad626ae341805891f23c74b5292818f49ac63/sqlite_vec-0.1.9-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux1_x86_64.whl", hash = "sha256:1515727990b49e79bcaf75fdee2ffc7d461f8b66905013231251f1c8938e7786", size = 163388, upload-time = "2026-03-31T08:02:34.888Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "sqlparse"
|
||||
version = "0.5.5"
|
||||
|
||||
Reference in New Issue
Block a user