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| Author | SHA1 | Date | |
|---|---|---|---|
 stumpylog
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5865e96a06 | ||
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Trenton Holmes
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172af8362d | ||
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Trenton Holmes
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e46163bfdf | ||
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Trenton Holmes
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f8e5aea8dd |
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<source>by Paperless-ngx</source>
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<source>User menu</source>
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<source>Logged in as <x id="INTERPOLATION" equiv-text="{{this.settingsService.displayName}}"/></source>
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<source>My Profile</source>
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<source>Documentation</source>
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<source>Saved views</source>
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<source>Open documents</source>
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<context context-type="linenumber">151,152</context>
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<source>Close all</source>
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<source>Manage</source>
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<source>Correspondents</source>
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<source>Document types</source>
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<context context-type="sourcefile">src/app/components/manage/document-attributes/document-attributes.component.ts</context>
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<source>Storage paths</source>
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<source>Custom fields</source>
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<context context-type="sourcefile">src/app/components/document-list/bulk-editor/bulk-editor.component.html</context>
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<source>Workflows</source>
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<context context-type="sourcefile">src/app/components/manage/workflows/workflows.component.html</context>
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<source>Mail</source>
|
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<context context-type="linenumber">263</context>
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<trans-unit id="7844706011418789951" datatype="html">
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<source>Administration</source>
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<source>Configuration</source>
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<context context-type="linenumber">289</context>
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<context context-type="linenumber">293</context>
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<source>GitHub</source>
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<context context-type="linenumber">338</context>
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<trans-unit id="4112664765954374539" datatype="html">
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<source>is available.</source>
|
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<context context-type="linenumber">344</context>
|
||||
<context context-type="linenumber">348</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="1175891574282637937" datatype="html">
|
||||
<source>Click to view.</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.html</context>
|
||||
<context context-type="linenumber">344</context>
|
||||
<context context-type="linenumber">348</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="9811291095862612" datatype="html">
|
||||
<source>Paperless-ngx can automatically check for updates</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.html</context>
|
||||
<context context-type="linenumber">348</context>
|
||||
<context context-type="linenumber">352</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="894819944961861800" datatype="html">
|
||||
<source> How does this work? </source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.html</context>
|
||||
<context context-type="linenumber">356</context>
|
||||
<context context-type="linenumber">360</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="509090351011426949" datatype="html">
|
||||
<source>Update available</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.html</context>
|
||||
<context context-type="linenumber">368</context>
|
||||
<context context-type="linenumber">372</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="1329827712962827905" datatype="html">
|
||||
<source>Configure update checking</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.html</context>
|
||||
<context context-type="linenumber">373</context>
|
||||
<context context-type="linenumber">377</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="1542489069631984294" datatype="html">
|
||||
<source>Sidebar views updated</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.ts</context>
|
||||
<context context-type="linenumber">427</context>
|
||||
<context context-type="linenumber">425</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="3547923076537026828" datatype="html">
|
||||
<source>Error updating sidebar views</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.ts</context>
|
||||
<context context-type="linenumber">430</context>
|
||||
<context context-type="linenumber">428</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="2526035785704676448" datatype="html">
|
||||
<source>An error occurred while saving update checking settings.</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/app-frame/app-frame.component.ts</context>
|
||||
<context context-type="linenumber">451</context>
|
||||
<context context-type="linenumber">449</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="4580988005648117665" datatype="html">
|
||||
@@ -8021,35 +8021,35 @@
|
||||
<source>Paperless-ngx is running!</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/dashboard/widgets/welcome-widget/welcome-widget.component.html</context>
|
||||
<context context-type="linenumber">6</context>
|
||||
<context context-type="linenumber">2</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="3326049540711826572" datatype="html">
|
||||
<source>You're ready to start uploading documents! Explore the various features of this web app on your own, or start a quick tour using the button below.</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/dashboard/widgets/welcome-widget/welcome-widget.component.html</context>
|
||||
<context context-type="linenumber">8,9</context>
|
||||
<context context-type="linenumber">3,4</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="4474647174688421179" datatype="html">
|
||||
<source>More detail on how to use and configure Paperless-ngx is always available in the <x id="START_LINK" ctype="x-a" equiv-text="<a href="https://docs.paperless-ngx.com" target="_blank">"/>documentation<x id="CLOSE_LINK" ctype="x-a" equiv-text="</a>"/>.</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/dashboard/widgets/welcome-widget/welcome-widget.component.html</context>
|
||||
<context context-type="linenumber">9,10</context>
|
||||
<context context-type="linenumber">4,6</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="4294899532887357745" datatype="html">
|
||||
<source>Thanks for being a part of the Paperless-ngx community!</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/dashboard/widgets/welcome-widget/welcome-widget.component.html</context>
|
||||
<context context-type="linenumber">13,14</context>
|
||||
<context context-type="linenumber">7,8</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="1415832194529539652" datatype="html">
|
||||
<source>Start the tour</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/dashboard/widgets/welcome-widget/welcome-widget.component.html</context>
|
||||
<context context-type="linenumber">14</context>
|
||||
<context context-type="linenumber">8</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="7822640317427130239" datatype="html">
|
||||
|
||||
@@ -10,12 +10,16 @@
|
||||
tourAnchor="tour.intro">
|
||||
@if (!hasCustomBranding) {
|
||||
<pngx-logo extra_classes="navbar-official-logo px-1" height="2.4rem"></pngx-logo>
|
||||
<pngx-brand-mark class="brand-mark brand-mark-slim d-none"></pngx-brand-mark>
|
||||
<svg class="brand-mark brand-mark-slim d-none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1000 1000" width="1.5em" height="1.5em" fill="currentColor">
|
||||
<path d="M341,949.1c-6.9-20.3-20.7-61.2-21.9-61-199.6-88.9-182.5-229.8-134.3-347.5,30,137.2,268.8,148.9,146.2,336-.9,2.2,10,27.8,19.5,51.3,22.7-51.9,58.6-115.5,55.8-120.8C178,398.7,724.9,299,807.1,18.5c83,251.5,53.1,659.8-377.4,814.9-2,1.4-63.5,148.6-66.9,150.2-.2-2.1-33.2,2.9-30.1-8.7,1.6-7,4.8-16.2,8.2-25.6h0v-.2h.1ZM323.1,846.2c48.3-71.9-12.7-120.8-56.9-152.2,81.2,107.4,66.4,120.8,56.9,152.2h0Z"/>
|
||||
</svg>
|
||||
} @else {
|
||||
@if (customAppLogo) {
|
||||
<img class="brand-logo" [src]="customAppLogo" alt="" />
|
||||
} @else {
|
||||
<pngx-brand-mark class="brand-mark"></pngx-brand-mark>
|
||||
<svg class="brand-mark" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1000 1000" width="1.5em" height="1.5em" fill="currentColor">
|
||||
<path d="M341,949.1c-6.9-20.3-20.7-61.2-21.9-61-199.6-88.9-182.5-229.8-134.3-347.5,30,137.2,268.8,148.9,146.2,336-.9,2.2,10,27.8,19.5,51.3,22.7-51.9,58.6-115.5,55.8-120.8C178,398.7,724.9,299,807.1,18.5c83,251.5,53.1,659.8-377.4,814.9-2,1.4-63.5,148.6-66.9,150.2-.2-2.1-33.2,2.9-30.1-8.7,1.6-7,4.8-16.2,8.2-25.6h0v-.2h.1ZM323.1,846.2c48.3-71.9-12.7-120.8-56.9-152.2,81.2,107.4,66.4,120.8,56.9,152.2h0Z"/>
|
||||
</svg>
|
||||
}
|
||||
<div class="brand-copy ms-2 text-truncate" [class.d-md-none]="slimSidebarEnabled">
|
||||
<span class="brand-title text-truncate">{{ appTitle }}</span>
|
||||
|
||||
@@ -45,7 +45,6 @@ import { TasksService } from 'src/app/services/tasks.service'
|
||||
import { ToastService } from 'src/app/services/toast.service'
|
||||
import { environment } from 'src/environments/environment'
|
||||
import { ChatComponent } from '../chat/chat/chat.component'
|
||||
import { BrandMarkComponent } from '../common/logo/brand-mark/brand-mark.component'
|
||||
import { LogoComponent } from '../common/logo/logo.component'
|
||||
import { ProfileEditDialogComponent } from '../common/profile-edit-dialog/profile-edit-dialog.component'
|
||||
import { DocumentDetailComponent } from '../document-detail/document-detail.component'
|
||||
@@ -62,7 +61,6 @@ const SCROLL_THRESHOLD = 16
|
||||
imports: [
|
||||
GlobalSearchComponent,
|
||||
LogoComponent,
|
||||
BrandMarkComponent,
|
||||
DocumentTitlePipe,
|
||||
IfPermissionsDirective,
|
||||
ToastsDropdownComponent,
|
||||
|
||||
@@ -1,3 +0,0 @@
|
||||
<svg class="w-100 h-100 d-block" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1000 1000" fill="currentColor" aria-hidden="true">
|
||||
<path d="M341,949.1c-6.9-20.3-20.7-61.2-21.9-61-199.6-88.9-182.5-229.8-134.3-347.5,30,137.2,268.8,148.9,146.2,336-.9,2.2,10,27.8,19.5,51.3,22.7-51.9,58.6-115.5,55.8-120.8C178,398.7,724.9,299,807.1,18.5c83,251.5,53.1,659.8-377.4,814.9-2,1.4-63.5,148.6-66.9,150.2-.2-2.1-33.2,2.9-30.1-8.7,1.6-7,4.8-16.2,8.2-25.6h0v-.2h.1ZM323.1,846.2c48.3-71.9-12.7-120.8-56.9-152.2,81.2,107.4,66.4,120.8,56.9,152.2h0Z"/>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 545 B |
@@ -1,14 +0,0 @@
|
||||
import { Component, input } from '@angular/core'
|
||||
|
||||
@Component({
|
||||
selector: 'pngx-brand-mark',
|
||||
templateUrl: './brand-mark.component.html',
|
||||
host: {
|
||||
'[style.width]': 'width()',
|
||||
'[style.height]': 'height()',
|
||||
},
|
||||
})
|
||||
export class BrandMarkComponent {
|
||||
readonly width = input<string>(null)
|
||||
readonly height = input<string>(null)
|
||||
}
|
||||
+8
-16
@@ -1,18 +1,10 @@
|
||||
<ngb-alert class="welcome-widget bg-light shadow-sm pe-3 position-relative overflow-hidden" type="primary" [dismissible]="true" (closed)="dismiss.emit(true)">
|
||||
<pngx-brand-mark class="welcome-watermark d-none d-md-block position-absolute top-50 translate-middle-y text-primary pe-none" width="26rem" height="26rem"></pngx-brand-mark>
|
||||
<div class="d-flex align-items-start gap-3 gap-md-4 position-relative">
|
||||
<pngx-brand-mark class="d-none d-sm-block flex-shrink-0 text-primary" width="3rem" height="3rem"></pngx-brand-mark>
|
||||
<div class="flex-grow-1">
|
||||
<h4 class="alert-heading text-primary fw-semibold"><ng-container i18n>Paperless-ngx is running!</ng-container> 🎉</h4>
|
||||
<div class="welcome-copy text-dark">
|
||||
<p i18n>You're ready to start uploading documents! Explore the various features of this web app on your own, or start a quick tour using the button below.</p>
|
||||
<p class="mb-0" i18n>More detail on how to use and configure Paperless-ngx is always available in the <a href="https://docs.paperless-ngx.com" target="_blank">documentation</a>.</p>
|
||||
</div>
|
||||
<hr class="opacity-100">
|
||||
<div class="d-flex flex-column flex-sm-row align-items-sm-center gap-3">
|
||||
<p class="m-0 text-secondary"><em i18n>Thanks for being a part of the Paperless-ngx community!</em></p>
|
||||
<button class="btn btn-primary ms-sm-auto flex-shrink-0 align-self-start align-self-sm-auto" (click)="tourService.start()"><ng-container i18n>Start the tour</ng-container> →</button>
|
||||
</div>
|
||||
</div>
|
||||
<ngb-alert class="pe-3" type="primary" [dismissible]="true" (closed)="dismiss.emit(true)">
|
||||
<h4 class="alert-heading"><ng-container i18n>Paperless-ngx is running!</ng-container> 🎉</h4>
|
||||
<p i18n>You're ready to start uploading documents! Explore the various features of this web app on your own, or start a quick tour using the button below.</p>
|
||||
<p i18n>More detail on how to use and configure Paperless-ngx is always available in the <a href="https://docs.paperless-ngx.com" target="_blank">documentation</a>.</p>
|
||||
<hr>
|
||||
<div class="d-flex align-items-end">
|
||||
<p class="lead fs-6 m-0"><em i18n>Thanks for being a part of the Paperless-ngx community!</em></p>
|
||||
<button class="btn btn-primary ms-auto flex-shrink-0" (click)="tourService.start()"><ng-container i18n>Start the tour</ng-container> →</button>
|
||||
</div>
|
||||
</ngb-alert>
|
||||
|
||||
-16
@@ -1,16 +0,0 @@
|
||||
.welcome-widget {
|
||||
border-color: color-mix(in srgb, var(--bs-primary) 50%, transparent);
|
||||
|
||||
hr {
|
||||
border-top-color: color-mix(in srgb, var(--bs-primary) 25%, transparent);
|
||||
}
|
||||
}
|
||||
|
||||
.welcome-copy {
|
||||
max-width: 68ch;
|
||||
}
|
||||
|
||||
.welcome-watermark {
|
||||
right: -6rem;
|
||||
opacity: .07;
|
||||
}
|
||||
|
||||
+1
-2
@@ -1,13 +1,12 @@
|
||||
import { Component, EventEmitter, Output, inject } from '@angular/core'
|
||||
import { NgbAlertModule } from '@ng-bootstrap/ng-bootstrap'
|
||||
import { TourService } from 'ngx-ui-tour-ng-bootstrap'
|
||||
import { BrandMarkComponent } from '../../../common/logo/brand-mark/brand-mark.component'
|
||||
|
||||
@Component({
|
||||
selector: 'pngx-welcome-widget',
|
||||
templateUrl: './welcome-widget.component.html',
|
||||
styleUrls: ['./welcome-widget.component.scss'],
|
||||
imports: [NgbAlertModule, BrandMarkComponent],
|
||||
imports: [NgbAlertModule],
|
||||
})
|
||||
export class WelcomeWidgetComponent {
|
||||
readonly tourService = inject(TourService)
|
||||
|
||||
@@ -129,7 +129,7 @@ class DocumentMetadataOverrides:
|
||||
)
|
||||
overrides.custom_fields = {
|
||||
custom_field.field.id: custom_field.value
|
||||
for custom_field in doc.custom_fields.all()
|
||||
for custom_field in doc.custom_fields.select_related("field").all()
|
||||
}
|
||||
|
||||
groups_with_perms = get_groups_with_perms(
|
||||
|
||||
@@ -3,6 +3,7 @@ from __future__ import annotations
|
||||
import logging
|
||||
import math
|
||||
import re
|
||||
from collections.abc import Iterable
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
from decimal import Decimal
|
||||
@@ -876,8 +877,106 @@ def validate_documentlink_targets(user, doc_ids):
|
||||
)
|
||||
|
||||
|
||||
# drf-writable-nested revalidates a document's custom_fields more than once
|
||||
# per request: once as the ordinary nested list, then again per-item while
|
||||
# matching existing vs. new CustomFieldInstance rows during save() -- and
|
||||
# that second pass builds a brand new serializer (and field) instance per
|
||||
# item (see its update_or_create_reverse_relations / _get_serializer_for_field),
|
||||
# so a cache on the field instance alone only helps the first pass. It does,
|
||||
# however, explicitly pass `context=self.context` to every one of those
|
||||
# fresh serializers -- the *same* dict object the outer DocumentSerializer
|
||||
# is using, not a copy. That context dict is already request-scoped (DRF
|
||||
# builds it fresh per request via get_serializer_context()), so stashing the
|
||||
# resolved CustomField objects there -- rather than in some new global/
|
||||
# thread-local cache -- lets every later pass reuse them for free while
|
||||
# staying entirely within DRF's existing, already-request-scoped machinery.
|
||||
_CUSTOM_FIELD_CONTEXT_CACHE_KEY = "_custom_field_lookup_cache"
|
||||
|
||||
|
||||
class _CachingCustomFieldPrimaryKeyField(serializers.PrimaryKeyRelatedField):
|
||||
"""
|
||||
Resolves CustomField ids with as few queries as possible: a per-instance
|
||||
cache for repeat lookups on this exact field instance, backed by a
|
||||
shared cache on the serializer context (see _CUSTOM_FIELD_CONTEXT_CACHE_KEY
|
||||
above) so later, separately-instantiated fields for the same request
|
||||
reuse what was already resolved instead of re-querying.
|
||||
"""
|
||||
|
||||
def __init__(self, **kwargs: Any) -> None:
|
||||
super().__init__(**kwargs)
|
||||
self._cache: dict[int, CustomField] = {}
|
||||
|
||||
def _shared_cache(self) -> dict[int, CustomField]:
|
||||
return self.context.setdefault(_CUSTOM_FIELD_CONTEXT_CACHE_KEY, {})
|
||||
|
||||
@staticmethod
|
||||
def _normalize_pk(data: Any) -> int | None:
|
||||
"""
|
||||
Returns `data` coerced to the int a valid CustomField pk would be,
|
||||
or None if `data` isn't a plausible pk (wrong type, unhashable,
|
||||
non-numeric, or a bool -- DRF itself rejects bools as pks since
|
||||
`True == 1` would otherwise silently match). None tells callers to
|
||||
leave `data` alone and let `super().to_internal_value()` report the
|
||||
normal validation error instead of touching the cache/queryset with
|
||||
it directly.
|
||||
"""
|
||||
if isinstance(data, bool):
|
||||
return None
|
||||
try:
|
||||
return int(data)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
|
||||
def prefetch(self, ids: Iterable[Any]) -> None:
|
||||
shared_cache = self._shared_cache()
|
||||
candidates = {pk for i in ids if (pk := self._normalize_pk(i)) is not None}
|
||||
missing = {
|
||||
i for i in candidates if i not in self._cache and i not in shared_cache
|
||||
}
|
||||
if missing:
|
||||
for obj in self.get_queryset().filter(pk__in=missing):
|
||||
shared_cache[obj.pk] = obj
|
||||
for i in candidates:
|
||||
obj = shared_cache.get(i)
|
||||
if obj is not None:
|
||||
self._cache[i] = obj
|
||||
|
||||
def to_internal_value(self, data: Any) -> CustomField:
|
||||
pk = self._normalize_pk(data)
|
||||
if pk is None:
|
||||
return super().to_internal_value(data)
|
||||
if pk in self._cache:
|
||||
return self._cache[pk]
|
||||
shared_cache = self._shared_cache()
|
||||
if pk in shared_cache:
|
||||
obj = shared_cache[pk]
|
||||
self._cache[pk] = obj
|
||||
return obj
|
||||
obj: CustomField = super().to_internal_value(data)
|
||||
self._cache[obj.pk] = obj
|
||||
shared_cache[obj.pk] = obj
|
||||
return obj
|
||||
|
||||
|
||||
class CustomFieldInstanceListSerializer(serializers.ListSerializer):
|
||||
def to_internal_value(self, data: Any) -> list[Any]:
|
||||
if isinstance(data, list):
|
||||
field_ids = []
|
||||
for item in data:
|
||||
if not isinstance(item, dict) or "field" not in item:
|
||||
continue
|
||||
try:
|
||||
hash(item["field"])
|
||||
except TypeError:
|
||||
continue
|
||||
field_ids.append(item["field"])
|
||||
if field_ids:
|
||||
self.child.fields["field"].prefetch(field_ids)
|
||||
return super().to_internal_value(data)
|
||||
|
||||
|
||||
class CustomFieldInstanceSerializer(serializers.ModelSerializer[CustomFieldInstance]):
|
||||
field = serializers.PrimaryKeyRelatedField(queryset=CustomField.objects.all())
|
||||
field = _CachingCustomFieldPrimaryKeyField(queryset=CustomField.objects.all())
|
||||
value = ReadWriteSerializerMethodField(allow_null=True)
|
||||
|
||||
def create(self, validated_data):
|
||||
@@ -978,6 +1077,7 @@ class CustomFieldInstanceSerializer(serializers.ModelSerializer[CustomFieldInsta
|
||||
|
||||
class Meta:
|
||||
model = CustomFieldInstance
|
||||
list_serializer_class = CustomFieldInstanceListSerializer
|
||||
fields = [
|
||||
"value",
|
||||
"field",
|
||||
|
||||
@@ -5,7 +5,9 @@ from unittest.mock import ANY
|
||||
|
||||
from django.contrib.auth.models import Permission
|
||||
from django.contrib.auth.models import User
|
||||
from django.db import connection
|
||||
from django.test import override_settings
|
||||
from django.test.utils import CaptureQueriesContext
|
||||
from guardian.shortcuts import assign_perm
|
||||
from rest_framework import status
|
||||
from rest_framework.test import APITestCase
|
||||
@@ -13,6 +15,9 @@ from rest_framework.test import APITestCase
|
||||
from documents.models import CustomField
|
||||
from documents.models import CustomFieldInstance
|
||||
from documents.models import Document
|
||||
from documents.serialisers import CustomFieldInstanceSerializer
|
||||
from documents.serialisers import DocumentSerializer
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.utils import DirectoriesMixin
|
||||
|
||||
|
||||
@@ -530,6 +535,136 @@ class TestCustomFieldsAPI(DirectoriesMixin, APITestCase):
|
||||
doc.refresh_from_db()
|
||||
self.assertEqual(len(doc.custom_fields.all()), 10)
|
||||
|
||||
def test_document_serializer_custom_fields_validation_batches_field_lookup(
|
||||
self,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document is being validated with several custom field values
|
||||
at once (as happens on every PATCH/PUT/POST)
|
||||
WHEN:
|
||||
- The serializer is validated
|
||||
THEN:
|
||||
- The referenced CustomField objects are resolved with a single
|
||||
query, not one query per custom field
|
||||
"""
|
||||
doc = DocumentFactory(mime_type="application/pdf")
|
||||
custom_fields = [
|
||||
CustomField.objects.create(
|
||||
name=f"Test Custom Field {i}",
|
||||
data_type=CustomField.FieldDataType.STRING,
|
||||
)
|
||||
for i in range(5)
|
||||
]
|
||||
|
||||
serializer = DocumentSerializer(
|
||||
doc,
|
||||
data={
|
||||
"custom_fields": [
|
||||
{"field": custom_field.id, "value": "test value"}
|
||||
for custom_field in custom_fields
|
||||
],
|
||||
},
|
||||
partial=True,
|
||||
)
|
||||
|
||||
with CaptureQueriesContext(connection) as ctx:
|
||||
self.assertTrue(serializer.is_valid(), serializer.errors)
|
||||
|
||||
custom_field_lookups = [
|
||||
query
|
||||
for query in ctx.captured_queries
|
||||
if 'FROM "documents_customfield" WHERE "documents_customfield"."id"'
|
||||
in query["sql"]
|
||||
]
|
||||
self.assertEqual(
|
||||
len(custom_field_lookups),
|
||||
1,
|
||||
"Expected a single batched query to resolve the custom fields, "
|
||||
f"got {len(custom_field_lookups)}: {custom_field_lookups}",
|
||||
)
|
||||
|
||||
def test_custom_field_lookup_reuses_shared_context_cache(self) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A CustomField has already been resolved once, by a serializer
|
||||
sharing a given `context` dict
|
||||
WHEN:
|
||||
- A second, separately-instantiated CustomFieldInstanceSerializer
|
||||
validates the same field id, sharing that same context
|
||||
(this is what drf-writable-nested does: it rebuilds a fresh
|
||||
serializer -- and fresh field instances -- per item while
|
||||
matching existing vs. new instances during save())
|
||||
THEN:
|
||||
- No additional query is issued to resolve the CustomField
|
||||
"""
|
||||
custom_field = CustomField.objects.create(
|
||||
name="Test Custom Field",
|
||||
data_type=CustomField.FieldDataType.STRING,
|
||||
)
|
||||
|
||||
context: dict = {}
|
||||
first_pass = CustomFieldInstanceSerializer(
|
||||
data={"field": custom_field.id, "value": "a"},
|
||||
context=context,
|
||||
)
|
||||
self.assertTrue(first_pass.is_valid(), first_pass.errors)
|
||||
|
||||
second_pass = CustomFieldInstanceSerializer(
|
||||
data={"field": custom_field.id, "value": "b"},
|
||||
context=context,
|
||||
)
|
||||
with CaptureQueriesContext(connection) as ctx:
|
||||
self.assertTrue(second_pass.is_valid(), second_pass.errors)
|
||||
|
||||
custom_field_lookups = [
|
||||
query
|
||||
for query in ctx.captured_queries
|
||||
if 'FROM "documents_customfield" WHERE "documents_customfield"."id"'
|
||||
in query["sql"]
|
||||
]
|
||||
self.assertEqual(
|
||||
len(custom_field_lookups),
|
||||
0,
|
||||
"Expected the second, separately-instantiated serializer to reuse "
|
||||
f"the already-resolved CustomField, got: {custom_field_lookups}",
|
||||
)
|
||||
|
||||
def test_custom_field_validation_rejects_malformed_field_value(self) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document is being validated with a malformed custom_fields
|
||||
entry whose "field" value is neither a valid CustomField id
|
||||
nor a type DRF's own PrimaryKeyRelatedField can safely reject
|
||||
on its own (unhashable, or a non-numeric scalar)
|
||||
WHEN:
|
||||
- The serializer is validated
|
||||
THEN:
|
||||
- A normal validation error is raised, not an unhandled
|
||||
TypeError/ValueError escaping past DRF's validation layer
|
||||
"""
|
||||
doc = DocumentFactory(mime_type="application/pdf")
|
||||
|
||||
bad_field_values = {
|
||||
"unhashable-list": [],
|
||||
"unhashable-dict": {},
|
||||
"non-numeric-scalar": "abc",
|
||||
}
|
||||
for case_id, bad_field_value in bad_field_values.items():
|
||||
with self.subTest(case_id):
|
||||
serializer = DocumentSerializer(
|
||||
doc,
|
||||
data={
|
||||
"custom_fields": [
|
||||
{"field": bad_field_value, "value": "test value"},
|
||||
],
|
||||
},
|
||||
partial=True,
|
||||
)
|
||||
|
||||
self.assertFalse(serializer.is_valid())
|
||||
self.assertIn("custom_fields", serializer.errors)
|
||||
|
||||
def test_change_custom_field_instance_value(self) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
|
||||
@@ -0,0 +1,58 @@
|
||||
from django.db import connection
|
||||
from django.test import TestCase
|
||||
from django.test.utils import CaptureQueriesContext
|
||||
|
||||
from documents.data_models import DocumentMetadataOverrides
|
||||
from documents.models import CustomField
|
||||
from documents.models import CustomFieldInstance
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.utils import DirectoriesMixin
|
||||
|
||||
|
||||
class TestDocumentMetadataOverridesFromDocument(DirectoriesMixin, TestCase):
|
||||
def test_from_document_batches_custom_field_lookup_after_refresh_from_db(
|
||||
self,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document has several custom field values
|
||||
- The document instance has just been refreshed from the database,
|
||||
which drops any prefetched related objects (as
|
||||
send_websocket_document_updated does before building overrides)
|
||||
WHEN:
|
||||
- DocumentMetadataOverrides.from_document() reads the document's
|
||||
custom field values
|
||||
THEN:
|
||||
- The referenced CustomField objects are resolved with a single
|
||||
query, not one query per custom field
|
||||
"""
|
||||
doc = DocumentFactory(mime_type="application/pdf")
|
||||
for i in range(5):
|
||||
CustomFieldInstance.objects.create(
|
||||
document=doc,
|
||||
field=CustomField.objects.create(
|
||||
name=f"Test Custom Field {i}",
|
||||
data_type=CustomField.FieldDataType.STRING,
|
||||
),
|
||||
value_text="value",
|
||||
)
|
||||
|
||||
doc.refresh_from_db()
|
||||
|
||||
with CaptureQueriesContext(connection) as ctx:
|
||||
overrides = DocumentMetadataOverrides.from_document(doc)
|
||||
|
||||
self.assertEqual(len(overrides.custom_fields), 5)
|
||||
unbatched_field_lookups = [
|
||||
query
|
||||
for query in ctx.captured_queries
|
||||
if 'FROM "documents_customfield" WHERE "documents_customfield"."id"'
|
||||
in query["sql"]
|
||||
]
|
||||
self.assertEqual(
|
||||
unbatched_field_lookups,
|
||||
[],
|
||||
"Expected CustomField data to come from the CustomFieldInstance "
|
||||
"join, not a separate per-instance lookup, "
|
||||
f"got: {unbatched_field_lookups}",
|
||||
)
|
||||
@@ -1133,8 +1133,7 @@ class DocumentViewSet(
|
||||
"custom_fields",
|
||||
queryset=CustomFieldInstance.objects.select_related("field"),
|
||||
),
|
||||
# NotesSerializer nests the author, this avoids query per note
|
||||
Prefetch("notes", queryset=Note.objects.select_related("user")),
|
||||
"notes",
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
@@ -2,7 +2,7 @@ msgid ""
|
||||
msgstr ""
|
||||
"Project-Id-Version: paperless-ngx\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2026-08-25 21:36+0000\n"
|
||||
"POT-Creation-Date: 2026-08-24 21:43+0000\n"
|
||||
"PO-Revision-Date: 2022-02-17 04:17\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: English\n"
|
||||
@@ -1580,7 +1580,7 @@ msgid "workflow runs"
|
||||
msgstr ""
|
||||
|
||||
#: documents/serialisers.py:523 documents/serialisers.py:875
|
||||
#: documents/serialisers.py:2827 documents/views.py:311 documents/views.py:2613
|
||||
#: documents/serialisers.py:2827 documents/views.py:311 documents/views.py:2612
|
||||
#: paperless_mail/serialisers.py:155
|
||||
msgid "Insufficient permissions."
|
||||
msgstr ""
|
||||
@@ -1621,7 +1621,7 @@ msgstr ""
|
||||
msgid "Duplicate document identifiers are not allowed."
|
||||
msgstr ""
|
||||
|
||||
#: documents/serialisers.py:2913 documents/views.py:4607
|
||||
#: documents/serialisers.py:2913 documents/views.py:4606
|
||||
#, python-format
|
||||
msgid "Documents not found: %(ids)s"
|
||||
msgstr ""
|
||||
@@ -1889,36 +1889,36 @@ msgstr ""
|
||||
msgid "Unable to parse URI {value}"
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:304 documents/views.py:2610
|
||||
#: documents/views.py:304 documents/views.py:2609
|
||||
msgid "Invalid more_like_id"
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:1587
|
||||
#: documents/views.py:1586
|
||||
msgid "Invalid AI configuration."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:1598
|
||||
#: documents/views.py:1597
|
||||
msgid "AI backend request timed out."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:2435 documents/views.py:2756
|
||||
#: documents/views.py:2434 documents/views.py:2755
|
||||
msgid "Specify only one of text, title_search, query, or more_like_id."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:4620
|
||||
#: documents/views.py:4619
|
||||
#, python-format
|
||||
msgid "Insufficient permissions to share document %(id)s."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:4666
|
||||
#: documents/views.py:4665
|
||||
msgid "Bundle is already being processed."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:4727
|
||||
#: documents/views.py:4726
|
||||
msgid "The share link bundle is still being prepared. Please try again later."
|
||||
msgstr ""
|
||||
|
||||
#: documents/views.py:4737
|
||||
#: documents/views.py:4736
|
||||
msgid "The share link bundle is unavailable."
|
||||
msgstr ""
|
||||
|
||||
|
||||
@@ -5,12 +5,13 @@ from django.conf import settings
|
||||
from django.contrib.auth.models import User
|
||||
|
||||
from documents.models import Document
|
||||
from documents.permissions import permitted_object_ids
|
||||
from documents.permissions import get_objects_for_user_owner_aware
|
||||
from paperless.config import AIConfig
|
||||
from paperless_ai.base_model import ClassificationSuggestions
|
||||
from paperless_ai.base_model import TaxonomyChoiceDict
|
||||
from paperless_ai.client import AIClient
|
||||
from paperless_ai.db import db_connection_released
|
||||
from paperless_ai.indexing import _node_document_ids
|
||||
from paperless_ai.indexing import retrieve_similar_nodes
|
||||
from paperless_ai.indexing import truncate_content
|
||||
from paperless_ai.prompts.context import ClassificationPromptContext
|
||||
@@ -18,9 +19,7 @@ from paperless_ai.prompts.context import LocalizationPromptContext
|
||||
from paperless_ai.prompts.context import RagContextPromptContext
|
||||
from paperless_ai.prompts.render import render_prompt
|
||||
from paperless_ai.taxonomy import AssignedMetadata
|
||||
from paperless_ai.taxonomy import SimilarDocument
|
||||
from paperless_ai.taxonomy import TaxonomyCandidates
|
||||
from paperless_ai.taxonomy import _node_document_weights
|
||||
from paperless_ai.taxonomy import build_taxonomy_candidates
|
||||
from paperless_ai.taxonomy import empty_taxonomy_candidates
|
||||
from paperless_ai.taxonomy import format_taxonomy_for_prompt
|
||||
@@ -40,35 +39,6 @@ logger = logging.getLogger("paperless_ai.rag_classifier")
|
||||
TAXONOMY_CANDIDATE_TOP_K = 15
|
||||
|
||||
|
||||
def _fulltext_similar_documents(
|
||||
document: Document,
|
||||
user: User | None,
|
||||
top_k: int,
|
||||
) -> list[SimilarDocument]:
|
||||
"""Rank-based fallback when no embedding backend is configured. Uses
|
||||
Tantivy's "More Like This" (term-overlap similarity) instead of vector
|
||||
similarity - cruder, but far better than no candidates at all.
|
||||
more_like_this_ids returns only a ranked ID list, no scores, so weight is
|
||||
synthesized from rank (descending from top_k) rather than claiming a
|
||||
similarity magnitude that doesn't exist. A superuser is normalized to
|
||||
``None`` before calling, since the backend's permission filter has no
|
||||
superuser short-circuit of its own.
|
||||
"""
|
||||
from documents.search import get_backend
|
||||
|
||||
search_user = None if user is not None and user.is_superuser else user
|
||||
backend = get_backend()
|
||||
similar_ids = backend.more_like_this_ids(
|
||||
document.pk,
|
||||
user=search_user,
|
||||
limit=top_k,
|
||||
)
|
||||
return [
|
||||
SimilarDocument(document_id=doc_id, weight=float(top_k - rank))
|
||||
for rank, doc_id in enumerate(similar_ids)
|
||||
]
|
||||
|
||||
|
||||
def get_language_name(language_code: str) -> str:
|
||||
normalized_language_code = language_code.lower()
|
||||
for code, name in settings.LANGUAGES:
|
||||
@@ -161,52 +131,44 @@ def get_taxonomy_context(
|
||||
user: User | None = None,
|
||||
max_docs: int = 5,
|
||||
) -> tuple[TaxonomyCandidates, AssignedMetadata, str]:
|
||||
"""One retrieval feeds both taxonomy candidates and RAG text context. Uses
|
||||
vector similarity when an embedding backend is configured, otherwise
|
||||
falls back to Tantivy full-text "More Like This" similarity - see
|
||||
_fulltext_similar_documents. On any retrieval failure, degrades to empty
|
||||
candidates/context rather than propagating the exception - neither a
|
||||
vector-store outage nor a search-index issue should block classification,
|
||||
only its context-assisted enrichment.
|
||||
"""One retrieval feeds both taxonomy candidates and RAG text context.
|
||||
On any retrieval failure, degrades to empty candidates/context rather than
|
||||
propagating the exception - a vector-store outage should not block
|
||||
classification, only its RAG-assisted enrichment.
|
||||
"""
|
||||
assigned = get_assigned_metadata(document, user)
|
||||
ai_config = AIConfig()
|
||||
try:
|
||||
if ai_config.llm_embedding_backend:
|
||||
# None means "no restriction" to retrieve_similar_nodes. A superuser
|
||||
# (like no user at all) can see every document, so skip materializing
|
||||
# every visible pk into a Python list and passing it through as an IN
|
||||
# filter: for a large library that is a wasted quadratic scan in the
|
||||
# vector store at best, and past ~32,763 documents a hard
|
||||
# sqlite3.OperationalError (SQLite's bound-parameter limit) at worst.
|
||||
# permitted_object_ids() has its own superuser shortcut that would
|
||||
# return every Document's id anyway, so this changes nothing about
|
||||
# which documents are considered -- only how we get there.
|
||||
visible_document_ids = (
|
||||
None
|
||||
if user is None or user.is_superuser
|
||||
else list(permitted_object_ids(user, Document, "view_document"))
|
||||
)
|
||||
nodes = retrieve_similar_nodes(
|
||||
document,
|
||||
top_k=TAXONOMY_CANDIDATE_TOP_K,
|
||||
document_ids=visible_document_ids,
|
||||
)
|
||||
similar_documents = _node_document_weights(nodes)
|
||||
else:
|
||||
# See _fulltext_similar_documents: it applies its own permission
|
||||
# filter via `user`, so no visible-document-id list is needed here.
|
||||
similar_documents = _fulltext_similar_documents(
|
||||
document,
|
||||
user,
|
||||
top_k=TAXONOMY_CANDIDATE_TOP_K,
|
||||
# None means "no restriction" to retrieve_similar_nodes. A superuser
|
||||
# (like no user at all) can see every document, so skip materializing
|
||||
# every visible pk into a Python list and passing it through as an IN
|
||||
# filter: for a large library that is a wasted quadratic scan in the
|
||||
# vector store at best, and past ~32,763 documents a hard
|
||||
# sqlite3.OperationalError (SQLite's bound-parameter limit) at worst.
|
||||
# get_objects_for_user_owner_aware() would return every Document for a
|
||||
# superuser anyway (guardian's own with_superuser shortcut), so this
|
||||
# changes nothing about which documents are considered -- only how we
|
||||
# get there.
|
||||
visible_document_ids = (
|
||||
None
|
||||
if user is None or user.is_superuser
|
||||
else list(
|
||||
get_objects_for_user_owner_aware(
|
||||
user,
|
||||
"view_document",
|
||||
Document,
|
||||
).values_list("pk", flat=True),
|
||||
)
|
||||
)
|
||||
nodes = retrieve_similar_nodes(
|
||||
document,
|
||||
top_k=TAXONOMY_CANDIDATE_TOP_K,
|
||||
document_ids=visible_document_ids,
|
||||
)
|
||||
|
||||
candidates = build_taxonomy_candidates(similar_documents, user)
|
||||
candidates = build_taxonomy_candidates(nodes, user)
|
||||
|
||||
similar_doc_ids = [s["document_id"] for s in similar_documents]
|
||||
similar_docs = list(
|
||||
Document.objects.filter(pk__in=similar_doc_ids)[:max_docs],
|
||||
Document.objects.filter(pk__in=_node_document_ids(nodes))[:max_docs],
|
||||
)
|
||||
context_blocks = []
|
||||
for similar in similar_docs:
|
||||
@@ -215,8 +177,8 @@ def get_taxonomy_context(
|
||||
context_blocks.append(f"TITLE: {title}\n{text}")
|
||||
except Exception:
|
||||
logger.exception(
|
||||
"Failed to retrieve similar-document context for document %s; "
|
||||
"continuing without taxonomy candidates or similar-document context.",
|
||||
"Failed to retrieve RAG neighbours for document %s; continuing "
|
||||
"without taxonomy candidates or similar-document context.",
|
||||
document.pk,
|
||||
)
|
||||
return empty_taxonomy_candidates(), assigned, ""
|
||||
@@ -299,14 +261,23 @@ def get_ai_document_classification(
|
||||
) -> ClassificationSuggestions:
|
||||
ai_config = AIConfig()
|
||||
|
||||
candidates, assigned, context = get_taxonomy_context(document, user)
|
||||
prompt = build_prompt_with_rag(
|
||||
document,
|
||||
ai_config,
|
||||
candidates=candidates,
|
||||
assigned=assigned,
|
||||
context=context,
|
||||
)
|
||||
if ai_config.llm_embedding_backend:
|
||||
candidates, assigned, context = get_taxonomy_context(document, user)
|
||||
prompt = build_prompt_with_rag(
|
||||
document,
|
||||
ai_config,
|
||||
candidates=candidates,
|
||||
assigned=assigned,
|
||||
context=context,
|
||||
)
|
||||
else:
|
||||
candidates = empty_taxonomy_candidates()
|
||||
prompt = build_prompt_without_rag(
|
||||
document,
|
||||
ai_config,
|
||||
candidates=candidates,
|
||||
assigned=get_assigned_metadata(document, user),
|
||||
)
|
||||
|
||||
client = AIClient()
|
||||
# Hand the pooled DB connection back while the (slow) LLM query runs so it
|
||||
|
||||
@@ -33,11 +33,6 @@ class TaxonomyCandidate(TypedDict):
|
||||
weight: float
|
||||
|
||||
|
||||
class SimilarDocument(TypedDict):
|
||||
document_id: int
|
||||
weight: float
|
||||
|
||||
|
||||
class TaxonomyCandidates(TypedDict):
|
||||
tags: list[TaxonomyCandidate]
|
||||
document_types: list[TaxonomyCandidate]
|
||||
@@ -110,10 +105,10 @@ def get_assigned_metadata(document: Document, user: User | None) -> AssignedMeta
|
||||
)
|
||||
|
||||
|
||||
def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument]:
|
||||
"""Sum each node's similarity score into its document_id (a document can
|
||||
appear via multiple chunks/nodes) and return one SimilarDocument per
|
||||
distinct document_id."""
|
||||
def _node_document_weights(nodes: list["NodeWithScore"]) -> dict[int, float]:
|
||||
"""document_id -> that node's similarity score, summed if a document_id
|
||||
appears more than once across the retrieved nodes (e.g. multiple chunks
|
||||
of the same source document)."""
|
||||
weights: dict[int, float] = defaultdict(float)
|
||||
for node in nodes:
|
||||
document_id = node.metadata.get("document_id")
|
||||
@@ -126,10 +121,7 @@ def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument
|
||||
weights[int(document_id)] += float(node.score or 0.0)
|
||||
except (TypeError, ValueError): # pragma: no cover
|
||||
continue
|
||||
return [
|
||||
SimilarDocument(document_id=document_id, weight=weight)
|
||||
for document_id, weight in weights.items()
|
||||
]
|
||||
return weights
|
||||
|
||||
|
||||
def _visible_ranked_candidates(
|
||||
@@ -165,25 +157,20 @@ def _visible_ranked_candidates(
|
||||
|
||||
|
||||
def build_taxonomy_candidates(
|
||||
similar_documents: list[SimilarDocument],
|
||||
nodes: list["NodeWithScore"],
|
||||
user: User | None,
|
||||
) -> TaxonomyCandidates:
|
||||
"""Resolve each similar document's id to a live Document, read its
|
||||
*current* tags/type/correspondent/storage_path via the ORM (never any
|
||||
possibly-stale names an adapter's source might have cached), weight each
|
||||
distinct taxonomy object by aggregate similarity weight, permission-filter
|
||||
"""Resolve each neighbour node's document_id to a live Document, read its
|
||||
*current* tags/type/correspondent/storage_path via the ORM (never the
|
||||
possibly-stale names cached in vector-index node metadata), weight each
|
||||
distinct taxonomy object by aggregate neighbour similarity, permission-filter
|
||||
against what ``user`` can see, and return each category ranked by weight
|
||||
and capped. ``similar_documents`` may come from either the vector-RAG
|
||||
adapter or the full-text fallback adapter - both produce this same shape.
|
||||
and capped.
|
||||
"""
|
||||
if not similar_documents:
|
||||
return empty_taxonomy_candidates()
|
||||
|
||||
# Both adapters guarantee at most one SimilarDocument per document_id, so
|
||||
# this never silently drops a duplicate's weight.
|
||||
document_weights: dict[int, float] = {
|
||||
s["document_id"]: s["weight"] for s in similar_documents
|
||||
}
|
||||
document_weights = _node_document_weights(nodes)
|
||||
if not document_weights:
|
||||
return empty_taxonomy_candidates()
|
||||
|
||||
# Only .tags.all() needs prefetching (a reverse M2M, one extra query for
|
||||
# the whole batch). document_type/correspondent/storage_path are read
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
from collections.abc import Generator
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import MagicMock
|
||||
from unittest.mock import patch
|
||||
@@ -8,13 +7,10 @@ import pytest_mock
|
||||
from django.test import override_settings
|
||||
|
||||
from documents.models import Document
|
||||
from documents.search import TantivyBackend
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.factories import TagFactory
|
||||
from documents.tests.factories import UserFactory
|
||||
from paperless.config import AIConfig
|
||||
from paperless_ai.ai_classifier import TAXONOMY_CANDIDATE_TOP_K
|
||||
from paperless_ai.ai_classifier import _fulltext_similar_documents
|
||||
from paperless_ai.ai_classifier import _restrict_to_shown_candidates
|
||||
from paperless_ai.ai_classifier import build_localization_prompt
|
||||
from paperless_ai.ai_classifier import build_prompt_with_rag
|
||||
@@ -24,7 +20,6 @@ from paperless_ai.ai_classifier import get_language_name
|
||||
from paperless_ai.ai_classifier import get_taxonomy_context
|
||||
from paperless_ai.base_model import ClassificationSuggestions
|
||||
from paperless_ai.base_model import TaxonomyChoiceDict
|
||||
from paperless_ai.taxonomy import SimilarDocument
|
||||
from paperless_ai.taxonomy import TaxonomyCandidate
|
||||
from paperless_ai.taxonomy import TaxonomyCandidates
|
||||
from paperless_ai.taxonomy import empty_taxonomy_candidates
|
||||
@@ -209,10 +204,12 @@ def test_use_rag_if_configured(
|
||||
|
||||
@pytest.mark.django_db
|
||||
@patch("paperless_ai.client.AIClient.run_llm_query")
|
||||
@patch("paperless_ai.ai_classifier.build_prompt_with_rag")
|
||||
@patch("paperless_ai.ai_classifier.build_prompt_without_rag")
|
||||
@patch("paperless_ai.ai_classifier.AIConfig")
|
||||
@override_settings(LLM_BACKEND="ollama", LLM_MODEL="some_model")
|
||||
def test_use_rag_prompt_even_without_embedding_backend(
|
||||
mock_build_prompt_with_rag,
|
||||
def test_use_without_rag_if_not_configured(
|
||||
mock_ai_config,
|
||||
mock_build_prompt_without_rag,
|
||||
mock_run_llm_query,
|
||||
mock_document,
|
||||
):
|
||||
@@ -222,13 +219,13 @@ def test_use_rag_prompt_even_without_embedding_backend(
|
||||
WHEN:
|
||||
- get_ai_document_classification() is called
|
||||
THEN:
|
||||
- The RAG-context prompt builder is still used (fed by the full-text
|
||||
fallback's context/candidates instead of the vector store's)
|
||||
- The non-RAG prompt builder is used
|
||||
"""
|
||||
mock_build_prompt_with_rag.return_value = "Prompt with RAG"
|
||||
mock_ai_config.return_value.llm_embedding_backend = None
|
||||
mock_build_prompt_without_rag.return_value = "Prompt without RAG"
|
||||
mock_run_llm_query.return_value = NESTED_SUGGESTIONS
|
||||
get_ai_document_classification(mock_document)
|
||||
mock_build_prompt_with_rag.assert_called_once()
|
||||
mock_build_prompt_without_rag.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@@ -306,7 +303,6 @@ def test_build_localization_prompt_preserves_unicode_characters():
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_get_taxonomy_context_assembles_rag_text_and_candidates():
|
||||
"""
|
||||
GIVEN:
|
||||
@@ -348,7 +344,6 @@ def test_get_taxonomy_context_assembles_rag_text_and_candidates():
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_get_taxonomy_context_no_similar_docs():
|
||||
"""
|
||||
GIVEN:
|
||||
@@ -372,67 +367,6 @@ def test_get_taxonomy_context_no_similar_docs():
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_get_taxonomy_context_uses_fulltext_fallback_when_no_embedding_backend(
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- No LLM embedding backend is configured (the default test settings)
|
||||
WHEN:
|
||||
- get_taxonomy_context() is called
|
||||
THEN:
|
||||
- _fulltext_similar_documents() is called with the document, the user
|
||||
and TAXONOMY_CANDIDATE_TOP_K
|
||||
- retrieve_similar_nodes() (the vector path) is never called
|
||||
"""
|
||||
document = DocumentFactory.create(content="Some content")
|
||||
mock_fulltext = mocker.patch(
|
||||
"paperless_ai.ai_classifier._fulltext_similar_documents",
|
||||
return_value=[],
|
||||
)
|
||||
mock_retrieve = mocker.patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
|
||||
|
||||
get_taxonomy_context(document, user=None)
|
||||
|
||||
mock_fulltext.assert_called_once_with(
|
||||
document,
|
||||
None,
|
||||
top_k=TAXONOMY_CANDIDATE_TOP_K,
|
||||
)
|
||||
mock_retrieve.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_get_taxonomy_context_uses_vector_path_when_embedding_backend_configured(
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- An LLM embedding backend is configured
|
||||
WHEN:
|
||||
- get_taxonomy_context() is called
|
||||
THEN:
|
||||
- retrieve_similar_nodes() (the vector path) is called
|
||||
- _fulltext_similar_documents() (the no-embedding-backend fallback)
|
||||
is never called
|
||||
"""
|
||||
document = DocumentFactory.create(content="Some content")
|
||||
mock_retrieve = mocker.patch(
|
||||
"paperless_ai.ai_classifier.retrieve_similar_nodes",
|
||||
return_value=[],
|
||||
)
|
||||
mock_fulltext = mocker.patch(
|
||||
"paperless_ai.ai_classifier._fulltext_similar_documents",
|
||||
)
|
||||
|
||||
get_taxonomy_context(document, user=None)
|
||||
|
||||
mock_retrieve.assert_called_once()
|
||||
mock_fulltext.assert_not_called()
|
||||
|
||||
|
||||
class TestGetTaxonomyContextVisibility:
|
||||
"""get_taxonomy_context must not materialize every visible document id
|
||||
for a user who can already see the whole library: a superuser (like no
|
||||
@@ -445,7 +379,6 @@ class TestGetTaxonomyContextVisibility:
|
||||
"""
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_skips_permission_lookup_for_superuser(
|
||||
self,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
@@ -464,18 +397,17 @@ class TestGetTaxonomyContextVisibility:
|
||||
"paperless_ai.ai_classifier.retrieve_similar_nodes",
|
||||
return_value=[],
|
||||
)
|
||||
mock_permitted = mocker.patch(
|
||||
"paperless_ai.ai_classifier.permitted_object_ids",
|
||||
mock_get_objects = mocker.patch(
|
||||
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
|
||||
)
|
||||
user = UserFactory.create(is_superuser=True)
|
||||
|
||||
get_taxonomy_context(document, user)
|
||||
|
||||
mock_permitted.assert_not_called()
|
||||
mock_get_objects.assert_not_called()
|
||||
assert mock_retrieve.call_args.kwargs["document_ids"] is None
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_skips_permission_lookup_when_no_user(
|
||||
self,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
@@ -494,17 +426,16 @@ class TestGetTaxonomyContextVisibility:
|
||||
"paperless_ai.ai_classifier.retrieve_similar_nodes",
|
||||
return_value=[],
|
||||
)
|
||||
mock_permitted = mocker.patch(
|
||||
"paperless_ai.ai_classifier.permitted_object_ids",
|
||||
mock_get_objects = mocker.patch(
|
||||
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
|
||||
)
|
||||
|
||||
get_taxonomy_context(document, None)
|
||||
|
||||
mock_permitted.assert_not_called()
|
||||
mock_get_objects.assert_not_called()
|
||||
assert mock_retrieve.call_args.kwargs["document_ids"] is None
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
def test_restricts_to_visible_documents_for_non_superuser(
|
||||
self,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
@@ -515,7 +446,7 @@ class TestGetTaxonomyContextVisibility:
|
||||
WHEN:
|
||||
- get_taxonomy_context() is called
|
||||
THEN:
|
||||
- The user's permitted document ids are looked up and passed to
|
||||
- The user's visible document ids are looked up and passed to
|
||||
retrieve_similar_nodes() as a restriction
|
||||
"""
|
||||
document = DocumentFactory.create(content="Some content")
|
||||
@@ -523,185 +454,21 @@ class TestGetTaxonomyContextVisibility:
|
||||
"paperless_ai.ai_classifier.retrieve_similar_nodes",
|
||||
return_value=[],
|
||||
)
|
||||
mock_permitted = mocker.patch(
|
||||
"paperless_ai.ai_classifier.permitted_object_ids",
|
||||
return_value=[1, 2, 3],
|
||||
mock_queryset = mocker.MagicMock()
|
||||
mock_queryset.values_list.return_value = [1, 2, 3]
|
||||
mock_get_objects = mocker.patch(
|
||||
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
|
||||
return_value=mock_queryset,
|
||||
)
|
||||
user = UserFactory.create(is_superuser=False)
|
||||
|
||||
get_taxonomy_context(document, user)
|
||||
|
||||
mock_permitted.assert_called_once_with(user, Document, "view_document")
|
||||
mock_get_objects.assert_called_once_with(user, "view_document", Document)
|
||||
assert mock_retrieve.call_args.kwargs["document_ids"] == [1, 2, 3]
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestFulltextSimilarDocuments:
|
||||
"""_fulltext_similar_documents is the no-embedding-backend fallback: it
|
||||
asks the Tantivy full-text index for "More Like This" neighbours instead
|
||||
of the vector store, and synthesizes a rank-based weight since Tantivy's
|
||||
more_like_this_ids returns only an ordered id list, no scores.
|
||||
"""
|
||||
|
||||
@pytest.fixture
|
||||
def fulltext_backend(
|
||||
self,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> Generator[TantivyBackend, None, None]:
|
||||
"""An in-memory Tantivy backend, wired up as the module-level
|
||||
singleton _fulltext_similar_documents resolves via get_backend()."""
|
||||
backend = TantivyBackend(path=None)
|
||||
backend.open()
|
||||
mocker.patch("documents.search.get_backend", return_value=backend)
|
||||
try:
|
||||
yield backend
|
||||
finally:
|
||||
backend.close()
|
||||
|
||||
def test_ranks_by_rank_based_weight_descending(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A source document and two similar documents indexed in Tantivy
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called
|
||||
THEN:
|
||||
- Each result's weight reflects its rank (first result weighted
|
||||
higher than the second), not a raw similarity score
|
||||
"""
|
||||
source = DocumentFactory.create(content="quarterly financial report details")
|
||||
first = DocumentFactory.create(content="quarterly financial report details")
|
||||
second = DocumentFactory.create(content="financial report")
|
||||
for doc in (source, first, second):
|
||||
fulltext_backend.add_or_update(doc)
|
||||
|
||||
result = _fulltext_similar_documents(source, user=None, top_k=5)
|
||||
|
||||
assert len(result) == 2
|
||||
weight_by_id = {s["document_id"]: s["weight"] for s in result}
|
||||
assert weight_by_id[first.pk] > weight_by_id[second.pk]
|
||||
|
||||
def test_excludes_source_document(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A source document indexed in Tantivy with no other documents
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called
|
||||
THEN:
|
||||
- An empty list is returned - the source document is never its
|
||||
own similar document
|
||||
"""
|
||||
source = DocumentFactory.create(content="unique unrelated content")
|
||||
fulltext_backend.add_or_update(source)
|
||||
|
||||
result = _fulltext_similar_documents(source, user=None, top_k=5)
|
||||
|
||||
assert result == []
|
||||
|
||||
def test_empty_index_returns_empty_list(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document that has never been indexed (fresh/empty Tantivy index)
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called
|
||||
THEN:
|
||||
- An empty list is returned rather than raising
|
||||
"""
|
||||
source = DocumentFactory.create(content="never indexed")
|
||||
|
||||
result = _fulltext_similar_documents(source, user=None, top_k=5)
|
||||
|
||||
assert result == []
|
||||
|
||||
def test_respects_top_k_limit(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A source document and four similar documents indexed
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called with top_k=2
|
||||
THEN:
|
||||
- At most 2 results are returned
|
||||
"""
|
||||
source = DocumentFactory.create(content="shared overlapping keyword text")
|
||||
for _ in range(4):
|
||||
fulltext_backend.add_or_update(
|
||||
DocumentFactory.create(content="shared overlapping keyword text"),
|
||||
)
|
||||
|
||||
result = _fulltext_similar_documents(source, user=None, top_k=2)
|
||||
|
||||
assert len(result) <= 2
|
||||
|
||||
def test_result_shape_is_similar_document(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A source document and one similar document indexed
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called
|
||||
THEN:
|
||||
- Each result is a SimilarDocument (document_id + weight only)
|
||||
"""
|
||||
source = DocumentFactory.create(content="shared content phrase")
|
||||
other = DocumentFactory.create(content="shared content phrase")
|
||||
fulltext_backend.add_or_update(source)
|
||||
fulltext_backend.add_or_update(other)
|
||||
|
||||
result = _fulltext_similar_documents(source, user=None, top_k=5)
|
||||
|
||||
# rank 0 (the only/best result) with top_k=5 -> weight = top_k - rank = 5.0,
|
||||
# per the "first result gets top_k, the last gets 1" formula.
|
||||
assert result == [SimilarDocument(document_id=other.pk, weight=5.0)]
|
||||
|
||||
def test_superuser_sees_other_users_documents(
|
||||
self,
|
||||
fulltext_backend: TantivyBackend,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A source document owned by one user and a similar document
|
||||
owned by a different user, with no sharing between them
|
||||
WHEN:
|
||||
- _fulltext_similar_documents() is called with a superuser
|
||||
THEN:
|
||||
- The other user's document is still returned as a similar
|
||||
document - a superuser must not be narrowed by the backend's
|
||||
owner-based permission filter
|
||||
"""
|
||||
owner = UserFactory.create()
|
||||
other_owner = UserFactory.create()
|
||||
superuser = UserFactory.create(is_superuser=True)
|
||||
source = DocumentFactory.create(
|
||||
content="shared content phrase",
|
||||
owner=owner,
|
||||
)
|
||||
other = DocumentFactory.create(
|
||||
content="shared content phrase",
|
||||
owner=other_owner,
|
||||
)
|
||||
fulltext_backend.add_or_update(source)
|
||||
fulltext_backend.add_or_update(other)
|
||||
|
||||
result = _fulltext_similar_documents(source, user=superuser, top_k=5)
|
||||
|
||||
assert [s["document_id"] for s in result] == [other.pk]
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
|
||||
def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrieve):
|
||||
"""
|
||||
@@ -728,7 +495,6 @@ def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrie
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
|
||||
@patch("paperless_ai.ai_classifier.build_taxonomy_candidates")
|
||||
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
|
||||
def test_get_taxonomy_context_candidate_building_failure_degrades_to_no_hints(
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import json
|
||||
from types import SimpleNamespace
|
||||
|
||||
import pytest
|
||||
import pytest_mock
|
||||
@@ -10,7 +11,6 @@ from documents.tests.factories import StoragePathFactory
|
||||
from documents.tests.factories import TagFactory
|
||||
from documents.tests.factories import UserFactory
|
||||
from paperless_ai.taxonomy import AssignedMetadata
|
||||
from paperless_ai.taxonomy import SimilarDocument
|
||||
from paperless_ai.taxonomy import TaxonomyCandidates
|
||||
from paperless_ai.taxonomy import build_taxonomy_candidates
|
||||
from paperless_ai.taxonomy import format_taxonomy_for_prompt
|
||||
@@ -132,8 +132,9 @@ class TestGetAssignedMetadata:
|
||||
assert result["tags"] == ["Owned By Someone Else"]
|
||||
|
||||
|
||||
def make_similar(document_id: int, weight: float) -> SimilarDocument:
|
||||
return SimilarDocument(document_id=document_id, weight=weight)
|
||||
def make_node(document_id: int, score: float) -> SimpleNamespace:
|
||||
"""A stand-in for NodeWithScore: only ``.metadata``/``.score`` are read."""
|
||||
return SimpleNamespace(metadata={"document_id": str(document_id)}, score=score)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
@@ -169,9 +170,9 @@ class TestBuildTaxonomyCandidates:
|
||||
doc_a.tags.add(tag)
|
||||
doc_b = DocumentFactory.create()
|
||||
doc_b.tags.add(tag)
|
||||
similar_documents = [make_similar(doc_a.pk, 0.9), make_similar(doc_b.pk, 0.4)]
|
||||
nodes = [make_node(doc_a.pk, 0.9), make_node(doc_b.pk, 0.4)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["tags"]) == 1
|
||||
assert result["tags"][0]["id"] == tag.pk
|
||||
@@ -196,9 +197,9 @@ class TestBuildTaxonomyCandidates:
|
||||
document.tags.add(tag)
|
||||
tag.name = "New Name"
|
||||
tag.save()
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert result["tags"][0]["name"] == "New Name"
|
||||
|
||||
@@ -218,9 +219,9 @@ class TestBuildTaxonomyCandidates:
|
||||
document = DocumentFactory.create()
|
||||
document.tags.add(tag)
|
||||
tag.delete()
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert result["tags"] == []
|
||||
|
||||
@@ -239,12 +240,9 @@ class TestBuildTaxonomyCandidates:
|
||||
strong_doc.tags.add(strong_tag)
|
||||
weak_doc = DocumentFactory.create()
|
||||
weak_doc.tags.add(weak_tag)
|
||||
similar_documents = [
|
||||
make_similar(strong_doc.pk, 0.9),
|
||||
make_similar(weak_doc.pk, 0.1),
|
||||
]
|
||||
nodes = [make_node(strong_doc.pk, 0.9), make_node(weak_doc.pk, 0.1)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert [c["name"] for c in result["tags"]] == ["Strong", "Weak"]
|
||||
|
||||
@@ -260,9 +258,9 @@ class TestBuildTaxonomyCandidates:
|
||||
document = DocumentFactory.create()
|
||||
for i in range(15):
|
||||
document.tags.add(TagFactory.create(name=f"Tag{i}"))
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["tags"]) == 10
|
||||
|
||||
@@ -276,12 +274,12 @@ class TestBuildTaxonomyCandidates:
|
||||
- Only 5 correspondents are returned
|
||||
"""
|
||||
correspondents = CorrespondentFactory.create_batch(7)
|
||||
similar_documents = [
|
||||
make_similar(DocumentFactory.create(correspondent=c).pk, 0.5)
|
||||
nodes = [
|
||||
make_node(DocumentFactory.create(correspondent=c).pk, 0.5)
|
||||
for c in correspondents
|
||||
]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["correspondents"]) == 5
|
||||
|
||||
@@ -296,9 +294,9 @@ class TestBuildTaxonomyCandidates:
|
||||
"""
|
||||
document_type = DocumentTypeFactory.create(name="Invoice")
|
||||
document = DocumentFactory.create(document_type=document_type)
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["document_types"]) == 1
|
||||
assert result["document_types"][0]["id"] == document_type.pk
|
||||
@@ -314,12 +312,12 @@ class TestBuildTaxonomyCandidates:
|
||||
- Only 5 document_types are returned
|
||||
"""
|
||||
document_types = DocumentTypeFactory.create_batch(7)
|
||||
similar_documents = [
|
||||
make_similar(DocumentFactory.create(document_type=dt).pk, 0.5)
|
||||
nodes = [
|
||||
make_node(DocumentFactory.create(document_type=dt).pk, 0.5)
|
||||
for dt in document_types
|
||||
]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["document_types"]) == 5
|
||||
|
||||
@@ -334,9 +332,9 @@ class TestBuildTaxonomyCandidates:
|
||||
"""
|
||||
storage_path = StoragePathFactory.create(name="Invoices")
|
||||
document = DocumentFactory.create(storage_path=storage_path)
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["storage_paths"]) == 1
|
||||
assert result["storage_paths"][0]["id"] == storage_path.pk
|
||||
@@ -352,12 +350,12 @@ class TestBuildTaxonomyCandidates:
|
||||
- Only 5 storage_paths are returned
|
||||
"""
|
||||
storage_paths = StoragePathFactory.create_batch(7)
|
||||
similar_documents = [
|
||||
make_similar(DocumentFactory.create(storage_path=sp).pk, 0.5)
|
||||
nodes = [
|
||||
make_node(DocumentFactory.create(storage_path=sp).pk, 0.5)
|
||||
for sp in storage_paths
|
||||
]
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert len(result["storage_paths"]) == 5
|
||||
|
||||
@@ -377,14 +375,14 @@ class TestBuildTaxonomyCandidates:
|
||||
tag = TagFactory.create(name="Restricted")
|
||||
document = DocumentFactory.create()
|
||||
document.tags.add(tag)
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
user = UserFactory.create()
|
||||
mocker.patch(
|
||||
"documents.permissions.permitted_object_ids",
|
||||
return_value=[], # user cannot see this tag
|
||||
)
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=user)
|
||||
result = build_taxonomy_candidates(nodes, user=user)
|
||||
|
||||
assert result["tags"] == []
|
||||
|
||||
@@ -414,10 +412,10 @@ class TestBuildTaxonomyCandidates:
|
||||
tag.save()
|
||||
document = DocumentFactory.create()
|
||||
document.tags.add(tag)
|
||||
similar_documents = [make_similar(document.pk, 0.5)]
|
||||
nodes = [make_node(document.pk, 0.5)]
|
||||
spy = mocker.patch("documents.permissions.permitted_object_ids")
|
||||
|
||||
result = build_taxonomy_candidates(similar_documents, user=None)
|
||||
result = build_taxonomy_candidates(nodes, user=None)
|
||||
|
||||
assert result["tags"][0]["name"] == "Owned"
|
||||
spy.assert_not_called()
|
||||
|
||||
Reference in New Issue
Block a user