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Author SHA1 Message Date
stumpylogandClaude Sonnet 5 631c521827 Fix: address code review feedback on table gateways
- Document sqlite3.Row row_factory precondition in module docstring
- Strengthen test_create_is_idempotent to verify populated table survives
- Collapse three roundtrip tests into one @pytest.mark.parametrize

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-30 14:29:34 -07:00
stumpylogandClaude Sonnet 5 22b4ce7938 Feature: add table-gateway module for document_chunks/document_meta/index_meta
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-30 14:29:34 -07:00
Trenton H 424a148482 Refactor: extract migration infrastructure, add has_pending_migration() (#13410) 2026-07-30 14:28:21 -07:00
Trenton HandGitHub e79f0d4106 Performance: Use server side iterators during LLM index updating (#13430) 2026-07-30 08:53:01 -07:00
GitHub Actions c29c9178f0 Auto translate strings 2026-07-30 14:39:47 +00:00
shamoonandGitHub baae99eb49 Fix: normalize monetary decimal symbol by locale (#13427) 2026-07-30 07:37:52 -07:00
Trenton HandGitHub f50a021ef6 Fix: fold overflowing path text in sanity checker (#13426) 2026-07-30 14:35:19 +00:00
shamoonandGitHub c8e00dca04 Fix: correct missing add field button for custom fields (#13424) 2026-07-30 07:16:25 -07:00
shamoonandGitHub 0a56018d6b Fix: hide attributes collapse / show button without UI settings (#13425) 2026-07-30 07:08:50 -07:00
350684cd6b Fix: consolidate born-digital PDF detection between archive decision and OCR (#13409)
* Fix: unify born-digital PDF detection between archive decision and OCR

should_produce_archive() and RasterisedDocumentParser.parse() each
reimplemented the "does this PDF have real text" check independently,
using different normalization of pdftotext output. Raw pdftotext output
can be non-empty (whitespace/form-feed layout padding) even when there
is no real content, so the two checks could disagree: consumer.py
treated a tagged-but-textless PDF as born-digital and skipped the
archive, while the parser's own (stricter, normalized) check found no
text and ran OCR anyway, leaving the document with no archive despite
real OCR text (GH #13387).

Both call sites now share one predicate, pdf_born_digital_text() in
paperless/parsers/utils.py, so they can no longer drift apart.

* Fix: restore extract_text seam for born-digital detection in parse()

parse() had switched to calling pdf_born_digital_text() directly for
its initial text/born-digital check, bypassing the parser's own
extract_text instance method. That broke test mockability (tests patch
tesseract_parser.extract_text to control the born-digital decision)
and caused CI failures with mismatched OCR call counts and text.

Split pdf_born_digital_text() into is_born_digital_text(text, path,
log) - a pure decision function - and a thin pdf_born_digital_text()
wrapper for callers without text in hand (consumer.should_produce_archive).
parse() now extracts via self.extract_text(None, document_path) and
passes the result to is_born_digital_text(), restoring the seam with
no change to production behavior.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

* Cleanup: simplify born-digital detection, close #13387 test gap

Simplification pass over the born-digital detection consolidation:
- is_born_digital_text(): drop the has_text temp for an early return.
- consumer.py: standardize the archive-decision log lines on plain
  hyphens (was a mix of em-dash and hyphen) and hoist the duplicated
  text_length computation.
- Parametrize TestPdfBornDigitalText instead of four near-identical
  tests.

Code review follow-up: the existing tests only ever exercised
pdf_born_digital_text() through mocks, so the actual #13387 scenario
(a tagged PDF whose only "text" is layout padding) was never checked
against real pdftotext/pikepdf output - a regression in the
normalize-before-decide logic itself would have gone undetected.
Moved tagged_no_text_pdf_file from parsers/conftest.py up to the
shared paperless/tests/conftest.py (it was previously only visible to
tests under parsers/) and added a non-mocked regression test against
the real sample file.

Also fixed two stale comments in test_consumer.py referencing a
_extract_text_for_archive_check helper that no longer exists.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-29 12:41:09 -07:00
45 changed files with 1352 additions and 1510 deletions
@@ -1,187 +0,0 @@
---
name: paperless-benchmarking
description: Use when profiling paperless-ngx performance, running `manage.py benchmark`, investigating a slow query or endpoint, or deciding whether a profiling finding should become a permanent registered scenario. Covers command reference, the fork/merge-back branch workflow for perf investigations, and how to read query-plan output.
---
# Paperless-ngx Benchmarking
This repo has a built-in benchmarking/profiling tool: `manage.py benchmark`, in
the `paperless_benchmark` Django app. It replaces ad hoc standalone scripts —
use it instead of writing new one-off seed/timing scripts.
## Command reference
```
manage.py benchmark seed --tier {home,medium,large} [--reset --yes-i-know-this-wipes-the-database] [--seed N]
manage.py benchmark run --repeat 5 [--label baseline]
manage.py benchmark profile <scenario_name> [--repeat 5] [--explain]
manage.py benchmark list-scenarios
```
- **`seed`** builds a realistic dataset at one of three scales: `home` (500
documents — fast, use this for iteration), `medium` (20,000 — the default
when `--tier` is omitted; a multi-minute seed), `large` (360,000 — matches
the scale reported in real large-install bug reports; slow, only use it
when a finding needs confirming at real scale). `--reset` wipes any
previously-seeded benchmark data first — but it is destructive and
irreversible: it deletes **all** users, **all** groups, and **all**
documents/tags/correspondents/document types/storage paths in the target
database, not just benchmark-created rows. Only run it against a disposable
benchmark database, never a real install. Because of that, `--reset` also
requires passing `--yes-i-know-this-wipes-the-database` in the same
invocation, or the command raises an error and does nothing. Omit both
flags if you want to layer more data onto an existing seed instead. `seed`
creates two named users, `perf_target` (mixed owned/shared documents,
realistic guardian permission grants) and `perf_admin` (superuser), plus a
general user/group pool with realistic permission-row ratios.
- **`run`** times the 3 built-in API endpoint benchmarks
(`/api/documents/`, `/api/documents/?page_size=50`, `/api/tags/?page_size=100000`) for both
`perf_target` and `perf_admin`, reporting min/median/max wall-clock and SQL
query count. Requires `seed` to have already run — it reuses that data, it
does not seed its own.
- **`profile`** times one named scenario from the registry (see
`list-scenarios`) via best-of-N repeat timing and SQL query count, against
`perf_target`. `--explain` additionally captures and prints the query plan:
real `EXPLAIN ANALYZE` execution stats on PostgreSQL/MariaDB, or
`EXPLAIN QUERY PLAN` (plan only, no real timing/row counts — clearly labeled
as such) on SQLite. Like `run`, `profile` requires `seed` to have already
run — it does not seed its own data either.
- Every `run`/`profile` invocation appends a JSON line to
`benchmark_results/history.jsonl` at the repo root (local-only, gitignored —
never commit this file). Use it to compare a `before`/`after` pair across
two invocations without hand-copying numbers.
- Full chain example: `seed --reset` once, then `run` and `profile` as many
times as you want against that same seeded data — no need to reseed between
them.
## Adding a new scenario
A "scenario" is a named, registered query/operation that `profile` can time
and explain. To add one, edit `src/paperless_benchmark/scenarios.py`: write a
`_<name>_run(user)` function (returns whatever `run_profile` should time) and
optionally a `_<name>_queryset(user)` function (returns the `QuerySet` for
`--explain` to analyze), then `register(Scenario(name=..., describe=...,
run=..., queryset_for_explain=...))` at module level. Both functions receive
the already-seeded `perf_target` user — they should not seed their own data.
## Branch workflow
`tools/benchmark-management-commands` is a **long-lived tooling branch**, not
a feature branch that gets merged and closed:
1. It is periodically brought up to date with `dev` (merge `dev` into it) so
the tooling doesn't drift from the schema/codebase it profiles. Do this
before starting a new investigation if it's been a while since the last
sync.
2. **Every performance investigation forks its own branch from
`tools/benchmark-management-commands`** (not from `dev`). Do the
investigation there: write throwaway profiling code, try fixes, capture
before/after numbers.
3. **That investigation branch never merges into `dev` or production.** Its
only job is to produce evidence and, optionally, a reusable scenario.
4. If the investigation turns up a scenario worth keeping permanently (see
"When to graduate a scenario" below), open a PR that adds **just that
scenario** back into `tools/benchmark-management-commands` — not the rest
of the investigation branch's throwaway code.
5. Any actual production fix the investigation motivates (e.g. an ORM query
change) goes into its own normal feature branch off `dev`, following the
project's regular contribution process — profiling evidence informs that
PR's description, but the profiling code itself does not travel with it.
## Reading query-plan output
- **PostgreSQL** `EXPLAIN ANALYZE`: look for `Seq Scan` on a large table
(missing index), a large gap between `rows=N` (planner's estimate) and the
actual row count in parentheses (stale statistics or a bad cardinality
estimate), and nested-loop joins driven by an outer relation with many
rows (usually the N+1 pattern this tool exists to catch).
- **MariaDB**: verified against a real MariaDB 12.3 container that MariaDB
does NOT accept MySQL 8.0.18+'s `EXPLAIN ANALYZE` syntax (it's a 1064
syntax error) -- `capture_explain()` instead runs MariaDB's own
`ANALYZE <statement>` form (no `EXPLAIN` keyword), which returns a
tabular plan with real per-row execution columns: `rows` (estimate) vs.
`r_rows` (actual), and `filtered` vs. `r_filtered`. A large gap between
`rows` and `r_rows`, or `type: ALL` (full table scan) on a large table,
are the signals to look for -- the same underlying concerns as Postgres's
`Seq Scan`/estimate-vs-actual gap, just in MariaDB's column-based output
instead of Postgres's nested-tree text format.
- **SQLite** `EXPLAIN QUERY PLAN`: no real timing/row-count data, only the
chosen access path (`SCAN` vs `SEARCH`, which index if any). Useful for
confirming an index is even being considered, not for judging real-world
cost — corroborate any SQLite finding against Postgres/MariaDB before
trusting it, since planner behavior differs meaningfully between them.
- Compare query **count**, not just timing, between before/after: a fix that
keeps the same wall-clock time but drops query count from O(n) to O(1) is
still a real, durable improvement — timing alone is noisy and
environment-dependent, query count is not.
## Cleaning up after an interrupted run
If a `seed`/`run`/`profile` invocation gets killed mid-run (Ctrl-C, `kill -9`,
a timed-out SSH session, etc.), check whether it left anything behind before
trusting the next benchmark's numbers. This was verified for real: a
`benchmark seed --tier large --reset ...` was started against both a fresh
PostgreSQL 18 container and a fresh MariaDB 12.3 container and `kill -9`'d a
few seconds into document seeding. In both cases, the database-side
connection disappeared immediately -- no stuck backend, no lingering query,
no held lock was observed in either backend once the killed process's PID
was confirmed gone. That said, this was one interruption point (mid
bulk-seed, between chunks); a run killed mid-query, or a driver/network
hiccup that doesn't cleanly close the socket, could behave differently, so
still check before trusting a number if any run in the session was
interrupted:
- **PostgreSQL**: look for leftover connections against the benchmark
database:
```sql
SELECT pid, state, query, query_start
FROM pg_stat_activity
WHERE datname = current_database() AND pid <> pg_backend_pid();
```
If a stuck backend shows up, clear it with:
```sql
SELECT pg_terminate_backend(pid)
FROM pg_stat_activity
WHERE datname = current_database() AND pid <> pg_backend_pid();
```
- **MariaDB**: look for leftover connections/queries:
```sql
SHOW FULL PROCESSLIST;
```
If a stuck connection shows up (anything other than your current admin
session), clear it with:
```sql
KILL <id>;
```
A stray connection left running concurrently with a subsequent benchmark run
would add real, contaminating load (extra queries competing for the same
rows, possibly held locks slowing the next run's timings) -- cheap to rule
out, expensive to silently trust a number that was actually measured
alongside a zombie connection.
## When to graduate a one-off finding into a permanent scenario
Register a scenario (rather than leaving it as throwaway code on the
investigation branch) when **both** are true:
- The query pattern is one this codebase is likely to regress on again (e.g.
it involves a permission-check join, a bulk operation, or anything else
with an easy-to-reintroduce N+1) — not a one-time fluke specific to this
investigation.
- Re-running it later, against a fresh seed, would still produce a
meaningful signal (it doesn't depend on investigation-specific throwaway
data or a fix that's already permanently landed and can't regress the same
way).
If a finding doesn't meet both bars, keep it as disposable code on the
investigation branch and let the branch's evidence (captured in the PR
description of whatever production fix it motivates) be the permanent
record instead.
-3
View File
@@ -115,6 +115,3 @@ celerybeat-schedule*
# Git worktree local folder
.worktrees
# Benchmark tooling output (local only, never committed)
/benchmark_results/
@@ -0,0 +1,12 @@
#!/command/with-contenv /usr/bin/bash
# shellcheck shell=bash
declare -r log_prefix="[init-llmindex-migrate]"
echo "${log_prefix} Checking for pending LLM index migrations..."
cd "${PAPERLESS_SRC_DIR}"
if [[ -n "${USER_IS_NON_ROOT}" ]]; then
python3 manage.py document_llmindex migrate
else
s6-setuidgid paperless python3 manage.py document_llmindex migrate
fi
@@ -0,0 +1 @@
oneshot
@@ -0,0 +1 @@
/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/run
+11 -1
View File
@@ -212,6 +212,16 @@ following:
This is a no-op if the index is already up to date, so it is safe to
run on every upgrade.
5. Migrate the LLM index if needed.
```shell-session
cd src
python3 manage.py document_llmindex migrate
```
This is a no-op if the index schema is already current, so it is safe
to run on every upgrade.
### Database Upgrades
Paperless-ngx is compatible with Django-supported versions of PostgreSQL and MariaDB and it is generally
@@ -532,7 +542,7 @@ index is updated automatically on the schedule set by
can manage it manually:
```
document_llmindex {rebuild,update,compact}
document_llmindex {rebuild,update,compact,migrate}
```
Specify `rebuild` to build the index from scratch from all documents in the database. Use
+10 -10
View File
@@ -1849,7 +1849,7 @@
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">154</context>
<context context-type="linenumber">159</context>
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/filterable-dropdown/filterable-dropdown.component.html</context>
@@ -3972,11 +3972,11 @@
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">96</context>
<context context-type="linenumber">101</context>
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">102</context>
<context context-type="linenumber">107</context>
</context-group>
</trans-unit>
<trans-unit id="3800326155195149498" datatype="html">
@@ -3987,11 +3987,11 @@
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">97</context>
<context context-type="linenumber">102</context>
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">103</context>
<context context-type="linenumber">108</context>
</context-group>
</trans-unit>
<trans-unit id="7551700625201096185" datatype="html">
@@ -4002,14 +4002,14 @@
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">119</context>
<context context-type="linenumber">124</context>
</context-group>
</trans-unit>
<trans-unit id="3184700926171002527" datatype="html">
<source>Any</source>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">152</context>
<context context-type="linenumber">157</context>
</context-group>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/filterable-dropdown/filterable-dropdown.component.html</context>
@@ -4020,21 +4020,21 @@
<source>Not</source>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">157</context>
<context context-type="linenumber">162</context>
</context-group>
</trans-unit>
<trans-unit id="6548676277933116532" datatype="html">
<source>Add query</source>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">176</context>
<context context-type="linenumber">181</context>
</context-group>
</trans-unit>
<trans-unit id="5599577087865387184" datatype="html">
<source>Add expression</source>
<context-group purpose="location">
<context context-type="sourcefile">src/app/components/common/custom-fields-query-dropdown/custom-fields-query-dropdown.component.html</context>
<context context-type="linenumber">179</context>
<context context-type="linenumber">184</context>
</context-group>
</trans-unit>
<trans-unit id="6312759212949884929" datatype="html">
@@ -182,7 +182,7 @@
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="stack"></i-bs><span><ng-container i18n>Attributes</ng-container></span>
</a>
@if (!slimSidebarEnabled) {
@if (!slimSidebarEnabled && canSaveSettings) {
<button
type="button"
class="btn btn-link btn-sm text-muted p-0 me-3 attributes-expand-btn"
@@ -68,6 +68,11 @@
></ng-select>
} @else if (getCustomFieldByID(atom.field)?.data_type === CustomFieldDataType.DocumentLink) {
<pngx-input-document-link [(ngModel)]="atom.value" class="w-25 form-select doc-link-select p-0" placeholder="Search docs..." i18n-placeholder [minimal]="true"></pngx-input-document-link>
} @else if (getCustomFieldByID(atom.field)?.data_type === CustomFieldDataType.Monetary) {
<input class="w-25 form-control rounded-end" type="text" inputmode="decimal"
[ngModel]="atom.value"
(ngModelChange)="setMonetaryValue(atom, $event)"
[disabled]="disabled">
} @else {
<input class="w-25 form-control rounded-end" type="text" [(ngModel)]="atom.value" [disabled]="disabled">
}
@@ -1,5 +1,6 @@
import { provideHttpClient, withInterceptorsFromDi } from '@angular/common/http'
import { provideHttpClientTesting } from '@angular/common/http/testing'
import { LOCALE_ID } from '@angular/core'
import { ComponentFixture, TestBed } from '@angular/core/testing'
import { FormsModule, ReactiveFormsModule } from '@angular/forms'
import { NgbDropdownModule } from '@ng-bootstrap/ng-bootstrap'
@@ -41,6 +42,12 @@ const customFields = [
],
},
},
{
id: 3,
name: 'Test Monetary Field',
data_type: CustomFieldDataType.Monetary,
extra_data: { default_currency: 'EUR' },
},
]
describe('CustomFieldsQueryDropdownComponent', () => {
@@ -61,6 +68,7 @@ describe('CustomFieldsQueryDropdownComponent', () => {
providers: [
provideHttpClient(withInterceptorsFromDi()),
provideHttpClientTesting(),
{ provide: LOCALE_ID, useValue: 'de' },
],
}).compileComponents()
@@ -150,6 +158,22 @@ describe('CustomFieldsQueryDropdownComponent', () => {
expect(options2).toEqual([])
})
it('should normalize localized monetary comparison values', () => {
const atom = new CustomFieldQueryAtom([3, 'exact', null])
component.setMonetaryValue(atom, '1.234,56')
expect(atom.value).toEqual('1234.56')
})
it('should preserve API-formatted monetary comparison values', () => {
const atom = new CustomFieldQueryAtom([3, 'exact', null])
component.setMonetaryValue(atom, '1234.56')
expect(atom.value).toEqual('1234.56')
})
it('should remove an element from the selection model', () => {
const expression = new CustomFieldQueryExpression()
const atom = new CustomFieldQueryAtom()
@@ -1,9 +1,14 @@
import { NgTemplateOutlet } from '@angular/common'
import {
getLocaleNumberSymbol,
NgTemplateOutlet,
NumberSymbol,
} from '@angular/common'
import {
Component,
EventEmitter,
inject,
Input,
LOCALE_ID,
Output,
QueryList,
signal,
@@ -212,6 +217,7 @@ export class CustomFieldQueriesModel {
})
export class CustomFieldsQueryDropdownComponent extends LoadingComponentWithPermissions {
protected customFieldsService = inject(CustomFieldsService)
private readonly locale = inject(LOCALE_ID)
public CustomFieldQueryComponentType = CustomFieldQueryElementType
public CustomFieldQueryOperator = CustomFieldQueryOperator
@@ -376,4 +382,18 @@ export class CustomFieldsQueryDropdownComponent extends LoadingComponentWithPerm
}
return []
}
setMonetaryValue(atom: CustomFieldQueryAtom, value: string) {
// Normalize the decimal symbol e.g. . vs , by locale
const decimalSymbol = getLocaleNumberSymbol(
this.locale,
NumberSymbol.Decimal
)
if (decimalSymbol !== '.' && value.includes(decimalSymbol)) {
const groupSymbol = getLocaleNumberSymbol(this.locale, NumberSymbol.Group)
value = value.split(groupSymbol).join('').split(decimalSymbol).join('.')
}
atom.value = value
}
}
@@ -51,8 +51,8 @@
*pngxIfPermissions="{ action: PermissionAction.Add, type: activeManagementList.permissionType }">
<i-bs name="plus-circle" class="me-1"></i-bs><ng-container i18n>Create</ng-container>
</button>
} @else if (activeCustomFields) {
<button type="button" class="btn btn-sm btn-outline-primary" (click)="activeCustomFields.editField()"
} @else if (customFieldsActive) {
<button type="button" class="btn btn-sm btn-outline-primary" (click)="addCustomField()"
*pngxIfPermissions="{ action: PermissionAction.Add, type: PermissionType.CustomField }">
<i-bs name="plus-circle" class="me-1"></i-bs><ng-container i18n>Add Field</ng-container>
</button>
@@ -18,6 +18,7 @@ import {
DocumentAttributesComponent,
DocumentAttributesSectionKind,
} from './document-attributes.component'
import { CustomFieldsComponent } from './custom-fields/custom-fields.component'
import { ManagementListComponent } from './management-list/management-list.component'
@Component({
@@ -207,6 +208,29 @@ describe('DocumentAttributesComponent', () => {
expect(component.activeSection.kind).toBe(
DocumentAttributesSectionKind.CustomFields
)
expect(component.activeCustomFields).toBeDefined()
const customFields = Object.create(CustomFieldsComponent.prototype)
customFields.editField = jest.fn()
component.activeOutlet = {
componentInstance: customFields,
} as any
expect(component.activeCustomFields).toBe(customFields)
component.addCustomField()
expect(customFields.editField).toHaveBeenCalled()
})
it('should show the add field button before the custom fields instance is available', async () => {
jest.spyOn(permissionsService, 'currentUserCan').mockReturnValue(true)
fixture.detectChanges()
component.activeNavID.set(2)
await fixture.whenStable()
expect(component.activeCustomFields).toBeNull()
expect(
fixture.nativeElement.querySelector(
'pngx-page-header .btn-outline-primary'
)?.textContent
).toContain('Add Field')
})
})
@@ -163,12 +163,17 @@ export class DocumentAttributesComponent implements OnInit, OnDestroy {
}
get activeCustomFields(): CustomFieldsComponent | null {
if (this.activeSection?.kind !== DocumentAttributesSectionKind.CustomFields)
return null
if (!this.customFieldsActive) return null
const instance = this.activeOutlet?.componentInstance
return instance instanceof CustomFieldsComponent ? instance : null
}
get customFieldsActive(): boolean {
return (
this.activeSection?.kind === DocumentAttributesSectionKind.CustomFields
)
}
get activeTabLabel(): string {
return this.activeSection?.label ?? ''
}
@@ -224,6 +229,10 @@ export class DocumentAttributesComponent implements OnInit, OnDestroy {
this.router.navigate(['attributes', nextSection])
}
addCustomField(): void {
this.activeCustomFields?.editField(null)
}
private getDefaultNavID(): DocumentAttributesNavIDs | null {
return this.visibleSections[0]?.id ?? null
}
+15 -25
View File
@@ -57,9 +57,7 @@ from paperless.models import ArchiveFileGenerationChoices
from paperless.parsers import ParserContext
from paperless.parsers import ParserProtocol
from paperless.parsers.registry import get_parser_registry
from paperless.parsers.utils import PDF_TEXT_MIN_LENGTH
from paperless.parsers.utils import extract_pdf_text
from paperless.parsers.utils import is_tagged_pdf
from paperless.parsers.utils import pdf_born_digital_text
LOGGING_NAME: Final[str] = "paperless.consumer"
@@ -138,53 +136,45 @@ def should_produce_archive(
# Must produce a PDF so the frontend can display the original format at all.
if parser.requires_pdf_rendition:
_log.debug("Archive: yes parser requires PDF rendition for frontend display")
_log.debug("Archive: yes - parser requires PDF rendition for frontend display")
return True
# Parser cannot produce an archive (e.g. TextDocumentParser).
if not parser.can_produce_archive:
_log.debug("Archive: no parser cannot produce archives")
_log.debug("Archive: no - parser cannot produce archives")
return False
generation = OcrConfig().archive_file_generation
if generation == ArchiveFileGenerationChoices.ALWAYS:
_log.debug("Archive: yes ARCHIVE_FILE_GENERATION=always")
_log.debug("Archive: yes - ARCHIVE_FILE_GENERATION=always")
return True
if generation == ArchiveFileGenerationChoices.NEVER:
_log.debug("Archive: no ARCHIVE_FILE_GENERATION=never")
_log.debug("Archive: no - ARCHIVE_FILE_GENERATION=never")
return False
# auto: produce archives for scanned/image documents; skip for born-digital PDFs.
if mime_type.startswith("image/"):
_log.debug("Archive: yes image document, ARCHIVE_FILE_GENERATION=auto")
_log.debug("Archive: yes - image document, ARCHIVE_FILE_GENERATION=auto")
return True
if mime_type == "application/pdf":
text = extract_pdf_text(document_path)
has_text = text is not None and len(text) > 0
if has_text and is_tagged_pdf(document_path):
text, born_digital = pdf_born_digital_text(document_path, log=_log)
text_length = len(text) if text else 0
if born_digital:
_log.debug(
"Archive: no born-digital PDF (structure tags detected),"
"Archive: no - born-digital PDF (text_length=%d),"
" ARCHIVE_FILE_GENERATION=auto",
text_length,
)
return False
if text is None or len(text) <= PDF_TEXT_MIN_LENGTH:
_log.debug(
"Archive: yes — scanned PDF (text_length=%d%d),"
" ARCHIVE_FILE_GENERATION=auto",
len(text) if text else 0,
PDF_TEXT_MIN_LENGTH,
)
return True
_log.debug(
"Archive: no — born-digital PDF (text_length=%d > %d),"
"Archive: yes - scanned/textless PDF (text_length=%d),"
" ARCHIVE_FILE_GENERATION=auto",
len(text),
PDF_TEXT_MIN_LENGTH,
text_length,
)
return False
return True
_log.debug(
"Archive: no MIME type %r not eligible for auto archive generation",
"Archive: no - MIME type %r not eligible for auto archive generation",
mime_type,
)
return False
@@ -3,6 +3,7 @@ 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
from paperless_ai.indexing import llm_index_migrate
class Command(PaperlessCommand):
@@ -13,12 +14,18 @@ class Command(PaperlessCommand):
def add_arguments(self, parser: Any) -> None:
super().add_arguments(parser)
parser.add_argument("command", choices=["rebuild", "update", "compact"])
parser.add_argument(
"command",
choices=["rebuild", "update", "compact", "migrate"],
)
def handle(self, *args: Any, **options: Any) -> None:
if options["command"] == "compact":
llm_index_compact()
return
if options["command"] == "migrate":
llm_index_migrate()
return
llmindex_index(
rebuild=options["command"] == "rebuild",
iter_wrapper=lambda docs: self.track(
@@ -61,7 +61,7 @@ class Command(PaperlessCommand):
)
table.add_column("Level", width=7, no_wrap=True)
table.add_column("Document", min_width=20)
table.add_column("Issue", ratio=1)
table.add_column("Issue", ratio=1, overflow="fold")
for doc_pk, doc_messages in messages.iter_messages():
if doc_pk is not None:
@@ -9,6 +9,7 @@ if TYPE_CHECKING:
_COMPACT = "documents.management.commands.document_llmindex.llm_index_compact"
_INDEX = "documents.management.commands.document_llmindex.llmindex_index"
_MIGRATE = "documents.management.commands.document_llmindex.llm_index_migrate"
class TestDocumentLlmindexCommand:
@@ -17,6 +18,11 @@ class TestDocumentLlmindexCommand:
call_command("document_llmindex", "compact")
mock_compact.assert_called_once_with()
def test_migrate_calls_llm_index_migrate(self, mocker: MockerFixture) -> None:
mock_migrate = mocker.patch(_MIGRATE)
call_command("document_llmindex", "migrate")
mock_migrate.assert_called_once_with()
def test_rebuild_calls_llmindex_index_with_rebuild_true(
self,
mocker: MockerFixture,
+2 -2
View File
@@ -1329,7 +1329,7 @@ class PreConsumeTestCase(DirectoriesMixin, GetConsumerMixin, TestCase):
with self.get_consumer(self.test_file) as c:
c.run()
# Verify no pre-consume script subprocess was invoked
# (run_subprocess may still be called by _extract_text_for_archive_check)
# (run_subprocess may still be called by pdf_born_digital_text via pdftotext)
script_calls = [
call
for call in m.call_args_list
@@ -1354,7 +1354,7 @@ class PreConsumeTestCase(DirectoriesMixin, GetConsumerMixin, TestCase):
self.assertTrue(m.called)
# Find the call that invoked the pre-consume script
# (run_subprocess may also be called by _extract_text_for_archive_check)
# (run_subprocess may also be called by pdf_born_digital_text via pdftotext)
script_call = next(
call
for call in m.call_args_list
+14 -42
View File
@@ -134,60 +134,32 @@ class TestShouldProduceArchive:
assert should_produce_archive(parser, mime, Path("/tmp/doc")) is expected
@pytest.mark.parametrize(
("extracted_text", "expected"),
("born_digital", "expected"),
[
pytest.param(
"This is a born-digital PDF with lots of text content. " * 10,
False,
id="born-digital-long-text-skips-archive",
),
pytest.param(None, True, id="no-text-scanned-produces-archive"),
pytest.param("tiny", True, id="short-text-treated-as-scanned"),
pytest.param(True, False, id="born-digital-skips-archive"),
pytest.param(False, True, id="not-born-digital-produces-archive"),
],
)
def test_auto_pdf_archive_decision(
self,
mocker: MockerFixture,
settings,
extracted_text: str | None,
born_digital: bool, # noqa: FBT001
expected: bool, # noqa: FBT001
) -> None:
"""Archive decision tracks pdf_born_digital_text()'s verdict exactly.
should_produce_archive() defers entirely to pdf_born_digital_text()
for the has-real-text decision, so both callers of that predicate
(this function and RasterisedDocumentParser.parse()) always agree.
"""
settings.ARCHIVE_FILE_GENERATION = "auto"
mocker.patch("documents.consumer.is_tagged_pdf", return_value=False)
mocker.patch("documents.consumer.extract_pdf_text", return_value=extracted_text)
mocker.patch(
"documents.consumer.pdf_born_digital_text",
return_value=("some text", born_digital),
)
parser = _parser_instance(can_produce=True, requires_rendition=False)
assert (
should_produce_archive(parser, "application/pdf", Path("/tmp/doc.pdf"))
is expected
)
def test_tagged_pdf_skips_archive_in_auto_mode(
self,
mocker: MockerFixture,
settings,
) -> None:
"""Tagged PDFs (e.g. Word exports) with real text are treated as born-digital, even below PDF_TEXT_MIN_LENGTH."""
settings.ARCHIVE_FILE_GENERATION = "auto"
mocker.patch("documents.consumer.is_tagged_pdf", return_value=True)
mocker.patch("documents.consumer.extract_pdf_text", return_value="tiny")
parser = _parser_instance(can_produce=True, requires_rendition=False)
assert (
should_produce_archive(parser, "application/pdf", Path("/tmp/doc.pdf"))
is False
)
def test_tagged_pdf_without_text_produces_archive(
self,
mocker: MockerFixture,
settings,
) -> None:
"""A tagged PDF with no actual extractable text (e.g. some scanner firmware) is not
trusted as born-digital — the tag alone must not bypass OCR."""
settings.ARCHIVE_FILE_GENERATION = "auto"
mocker.patch("documents.consumer.is_tagged_pdf", return_value=True)
mocker.patch("documents.consumer.extract_pdf_text", return_value=None)
parser = _parser_instance(can_produce=True, requires_rendition=False)
assert (
should_produce_archive(parser, "application/pdf", Path("/tmp/doc.pdf"))
is True
)
+6 -21
View File
@@ -3,7 +3,6 @@ from __future__ import annotations
import importlib.resources
import logging
import os
import re
import shutil
import tempfile
from pathlib import Path
@@ -25,9 +24,9 @@ from paperless.config import OcrConfig
from paperless.models import CleanChoices
from paperless.models import ModeChoices
from paperless.models import OutputTypeChoices
from paperless.parsers.utils import PDF_TEXT_MIN_LENGTH
from paperless.parsers.utils import extract_pdf_text
from paperless.parsers.utils import is_tagged_pdf
from paperless.parsers.utils import is_born_digital_text
from paperless.parsers.utils import post_process_text
from paperless.parsers.utils import read_file_handle_unicode_errors
from paperless.version import __full_version_str__
@@ -510,10 +509,10 @@ class RasterisedDocumentParser:
if mime_type == "application/pdf":
text_original = self.extract_text(None, document_path)
has_text = text_original is not None and len(text_original) > 0
original_has_text = has_text and (
is_tagged_pdf(document_path, log=self.log)
or len(text_original) > PDF_TEXT_MIN_LENGTH
original_has_text = is_born_digital_text(
text_original,
document_path,
log=self.log,
)
else:
text_original = None
@@ -658,17 +657,3 @@ class RasterisedDocumentParser:
f"No text was found in {document_path}, the content will be empty.",
)
self.text = ""
def post_process_text(text: str | None) -> str | None:
if not text:
return None
collapsed_spaces = re.sub(r"([^\S\r\n]+)", " ", text)
no_leading_whitespace = re.sub(r"([\n\r]+)([^\S\n\r]+)", "\\1", collapsed_spaces)
no_trailing_whitespace = re.sub(r"([^\S\n\r]+)$", "", no_leading_whitespace)
# TODO: this needs a rework
# replace \0 prevents issues with saving to postgres.
# text may contain \0 when this character is present in PDF files.
return no_trailing_whitespace.strip().replace("\0", " ")
+82
View File
@@ -111,6 +111,88 @@ def extract_pdf_text(
return None
def post_process_text(text: str | None) -> str | None:
"""Normalize extracted PDF/OCR text: collapse whitespace, strip padding.
Returns ``None`` for ``None`` or whitespace-only input, so callers can
treat "no text" and "only layout padding" the same way.
"""
if not text:
return None
collapsed_spaces = re.sub(r"([^\S\r\n]+)", " ", text)
no_leading_whitespace = re.sub(r"([\n\r]+)([^\S\n\r]+)", "\\1", collapsed_spaces)
no_trailing_whitespace = re.sub(r"([^\S\n\r]+)$", "", no_leading_whitespace)
# replace \0 prevents issues with saving to postgres.
# text may contain \0 when this character is present in PDF files.
result = no_trailing_whitespace.strip().replace("\0", " ")
return result or None
def is_born_digital_text(
text: str | None,
path: Path,
log: logging.Logger | None = None,
) -> bool:
"""Decide whether already-extracted, normalized PDF text counts as born-digital.
This is the single source of truth for "does this PDF already have real
text", used both to decide whether to produce an archive file and to
decide whether OCR can be skipped. Both decisions must agree, or a
tagged-but-textless PDF can end up with no archive AND a forced OCR pass
(see GH #13387): raw ``pdftotext -layout`` output can be non-empty
(whitespace/form-feed padding) even when there is no real content, so
*text* must already be normalized via :func:`post_process_text`, not the
raw extraction.
Parameters
----------
text:
The normalized extracted text (or ``None``) to evaluate.
path:
Absolute path to the PDF file, used for the tagged-PDF check.
log:
Logger for warnings. Falls back to the module-level logger when omitted.
Returns
-------
bool
Whether the PDF counts as born-digital (has real text, and is either
tagged or exceeds ``PDF_TEXT_MIN_LENGTH``).
"""
if not text:
return False
return is_tagged_pdf(path, log=log) or len(text) > PDF_TEXT_MIN_LENGTH
def pdf_born_digital_text(
path: Path,
log: logging.Logger | None = None,
) -> tuple[str | None, bool]:
"""Extract a PDF's text and decide whether it should be treated as born-digital.
Convenience wrapper around :func:`is_born_digital_text` for callers that
don't already have the PDF's text extracted (e.g. the archive-generation
decision, which runs before any parser has touched the file).
Parameters
----------
path:
Absolute path to the PDF file.
log:
Logger for warnings. Falls back to the module-level logger when omitted.
Returns
-------
tuple[str | None, bool]
The normalized extracted text (or ``None``), and whether the PDF
counts as born-digital.
"""
text = post_process_text(extract_pdf_text(path, log=log))
return text, is_born_digital_text(text, path, log=log)
def read_file_handle_unicode_errors(
filepath: Path,
log: logging.Logger | None = None,
-1
View File
@@ -150,7 +150,6 @@ INSTALLED_APPS = [
"drf_spectacular",
"drf_spectacular_sidecar",
"treenode",
"paperless_benchmark.apps.PaperlessBenchmarkConfig",
*env_apps,
]
+17
View File
@@ -36,6 +36,23 @@ def samples_dir() -> Path:
return (Path(__file__).parent / "samples").resolve()
@pytest.fixture(scope="session")
def tagged_no_text_pdf_file(samples_dir: Path) -> Path:
"""Path to a tagged PDF whose only "text" is pdftotext layout padding.
Reproduces GH #13387: ``/MarkInfo /Marked true`` is set, but the only
extractable content is a form-feed byte, not real text. Lives here
rather than in parsers/conftest.py so both parser tests and
paperless/tests/test_parser_utils.py can use it.
Returns
-------
Path
Absolute path to ``tesseract/tagged-but-no-text.pdf``.
"""
return samples_dir / "tesseract" / "tagged-but-no-text.pdf"
@pytest.fixture(autouse=True)
def clean_registry() -> Generator[None, None, None]:
"""Reset the parser registry before and after every test.
@@ -21,7 +21,7 @@ from documents.parsers import run_convert
from paperless.models import ModeChoices
from paperless.parsers import ParserProtocol
from paperless.parsers.tesseract import RasterisedDocumentParser
from paperless.parsers.tesseract import post_process_text
from paperless.parsers.utils import is_tagged_pdf
if TYPE_CHECKING:
from pathlib import Path
@@ -151,36 +151,6 @@ class TestRasterisedDocumentParserLifecycle:
assert tempdir is not None and not tempdir.exists()
# ---------------------------------------------------------------------------
# post_process_text
# ---------------------------------------------------------------------------
class TestPostProcessText:
@pytest.mark.parametrize(
("source", "expected"),
[
pytest.param(
"simple string",
"simple string",
id="collapse-spaces",
),
pytest.param(
"simple newline\n testing string",
"simple newline\ntesting string",
id="preserve-newline",
),
pytest.param(
"utf-8 строка с пробелами в конце ", # noqa: RUF001
"utf-8 строка с пробелами в конце", # noqa: RUF001
id="utf8-trailing-spaces",
),
],
)
def test_post_process_text(self, source: str, expected: str) -> None:
assert post_process_text(source) == expected
# ---------------------------------------------------------------------------
# Page count
# ---------------------------------------------------------------------------
@@ -910,25 +880,25 @@ class TestSkipArchive:
self,
mocker: MockerFixture,
tesseract_parser: RasterisedDocumentParser,
tesseract_samples_dir: Path,
tagged_no_text_pdf_file: Path,
) -> None:
"""
GIVEN:
- A PDF that reports itself as tagged (/MarkInfo /Marked true) but
has no actual extractable text (some scanner firmware produces
this see GitHub issue #13349)
- A real PDF that reports itself as tagged (/MarkInfo /Marked
true) but whose only pdftotext output is layout padding (a
lone form-feed byte), not real text (see GitHub issue #13387,
originally reported against #13349's tagged-PDF handling)
- Mode: auto, produce_archive=False
WHEN:
- Document is parsed
THEN:
- The tag alone is not trusted as "has text"; OCRmyPDF still runs
"""
assert is_tagged_pdf(tagged_no_text_pdf_file) is True
tesseract_parser.settings.mode = ModeChoices.AUTO
mocker.patch("paperless.parsers.tesseract.is_tagged_pdf", return_value=True)
mocker.patch.object(tesseract_parser, "extract_text", return_value=None)
mock_ocr = mocker.patch("ocrmypdf.ocr")
tesseract_parser.parse(
tesseract_samples_dir / "multi-page-images.pdf",
tagged_no_text_pdf_file,
"application/pdf",
produce_archive=False,
)
+110
View File
@@ -4,10 +4,18 @@ from __future__ import annotations
import codecs
from pathlib import Path
from typing import TYPE_CHECKING
import pytest
from paperless.parsers.utils import is_tagged_pdf
from paperless.parsers.utils import pdf_born_digital_text
from paperless.parsers.utils import post_process_text
from paperless.parsers.utils import read_file_handle_unicode_errors
if TYPE_CHECKING:
from pytest_mock import MockerFixture
SAMPLES = Path(__file__).parent / "samples" / "tesseract"
@@ -60,3 +68,105 @@ class TestIsTaggedPdf:
bad = tmp_path / "bad.pdf"
bad.write_bytes(b"not a pdf")
assert is_tagged_pdf(bad) is False
class TestPostProcessText:
@pytest.mark.parametrize(
("source", "expected"),
[
pytest.param(
"simple string",
"simple string",
id="collapse-spaces",
),
pytest.param(
"simple newline\n testing string",
"simple newline\ntesting string",
id="preserve-newline",
),
pytest.param(
"utf-8 строка с пробелами в конце ", # noqa: RUF001
"utf-8 строка с пробелами в конце", # noqa: RUF001
id="utf8-trailing-spaces",
),
pytest.param(None, None, id="none-input"),
pytest.param("", None, id="empty-string"),
pytest.param(" \n\x0c \n ", None, id="whitespace-and-formfeed-only"),
],
)
def test_post_process_text(
self,
source: str | None,
expected: str | None,
) -> None:
assert post_process_text(source) == expected
class TestPdfBornDigitalText:
"""Regression coverage for GH #13387.
should_produce_archive() and RasterisedDocumentParser.parse() must agree
on whether a PDF has real text, so both go through this one function.
"""
@pytest.mark.parametrize(
("extracted", "tagged", "expected_text", "expected_born_digital"),
[
pytest.param("tiny", True, "tiny", True, id="tagged-with-real-text"),
pytest.param("tiny", False, "tiny", False, id="untagged-below-min-length"),
pytest.param(
"x" * 51,
False,
"x" * 51,
True,
id="untagged-above-min-length",
),
pytest.param(None, True, None, False, id="tagged-but-no-text"),
],
)
def test_born_digital_decision(
self,
mocker: MockerFixture,
tmp_path: Path,
extracted: str | None,
tagged: bool, # noqa: FBT001
expected_text: str | None,
expected_born_digital: bool, # noqa: FBT001
) -> None:
"""
GIVEN:
- A PDF whose pdftotext output and /MarkInfo tag status vary
WHEN:
- pdf_born_digital_text() is called
THEN:
- The normalized text and born-digital verdict match; the tag
alone never counts as "has text"
"""
mocker.patch(
"paperless.parsers.utils.extract_pdf_text",
return_value=extracted,
)
mocker.patch("paperless.parsers.utils.is_tagged_pdf", return_value=tagged)
text, born_digital = pdf_born_digital_text(tmp_path / "doc.pdf")
assert text == expected_text
assert born_digital is expected_born_digital
def test_tagged_but_textless_pdf_is_not_born_digital(
self,
tagged_no_text_pdf_file: Path,
) -> None:
"""
GIVEN:
- A real PDF that is tagged (/MarkInfo /Marked true) but whose
only "text" is layout padding (a stray form-feed byte)
WHEN:
- pdf_born_digital_text() is called with no mocking
THEN:
- The normalized text is None and the PDF is not treated as
born-digital. The raw, unnormalized pdftotext output is
non-empty for this file, which is exactly what caused the
archive decision to disagree with the OCR decision in #13387.
"""
text, born_digital = pdf_born_digital_text(tagged_no_text_pdf_file)
assert text is None
assert born_digital is False
+111 -27
View File
@@ -1,5 +1,6 @@
import logging
from collections.abc import Iterable
from collections.abc import Iterator
from contextlib import contextmanager
from datetime import timedelta
from typing import TYPE_CHECKING
@@ -22,6 +23,7 @@ from paperless_ai.embedding import get_configured_model_name
from paperless_ai.embedding import get_embedding_model
if TYPE_CHECKING:
from django.db.models import QuerySet
from llama_index.core.schema import BaseNode
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
@@ -32,6 +34,35 @@ logger = logging.getLogger("paperless_ai.indexing")
RAG_NUM_OUTPUT = 512
RAG_CHUNK_OVERLAP = 200
# update_llm_index(): row count per .iterator() batch when streaming
# documents for a rebuild/update, matching _DocumentViewerStream's chunk
# size in documents/search/_backend.py.
_INDEX_STREAM_CHUNK_SIZE = 1000
class _StreamedDocuments:
"""A thin QuerySet wrapper that streams via ``.iterator()`` instead of
materializing every row (plus its ``content`` and prefetch caches) into
memory at once, while still supporting ``len()`` so ``iter_wrapper``'s
progress bar shows a real total instead of falling back to indeterminate.
Same shape as ``documents/search/_backend.py``'s ``_DocumentViewerStream``,
just without that class's extra per-batch permission lookup -- nothing
here needs one.
"""
def __init__(self, documents: "QuerySet[Document]") -> None:
self._documents = documents
def __len__(self) -> int:
return self._documents.count()
def __iter__(self) -> Iterator[Document]:
# iterator(chunk_size=...) streams from a server-side cursor instead
# of materializing the whole queryset in memory; since Django 4.1 it
# still honours prefetch_related, running the prefetches one batch
# at a time.
return iter(self._documents.iterator(chunk_size=_INDEX_STREAM_CHUNK_SIZE))
def queue_llm_index_update_if_needed(*, rebuild: bool, reason: str) -> bool:
# NOTE: The check-then-enqueue sequence below is non-atomic (TOCTOU): two
@@ -144,6 +175,24 @@ def _exclude_readers():
lock.close()
def _with_exclusive_access(operation: str, fn):
"""Run ``fn()`` with exclusive index access (see ``_exclude_readers()``),
for compaction/migration file swaps that must not run while readers are
active. Returns ``fn()``'s result, or None (after logging) if active
readers do not drain within ``LLM_INDEX_COMPACTION_LOCK_TIMEOUT`` --
callers skip the operation this run; it retries next time.
"""
try:
with _exclude_readers():
return fn()
except Timeout:
logger.info(
"Skipping LLM index %s: index readers are active; will retry next run.",
operation,
)
return None
@contextmanager
def write_store(embed_model_name: str | None = None):
"""Acquire the write lock and yield the vector store.
@@ -168,6 +217,21 @@ def write_store(embed_model_name: str | None = None):
yield store
def _check_and_run_migrations(store: "PaperlessSqliteVecVectorStore") -> bool:
"""Run any pending structural migrations, returning True if a pending
re-embed migration needs the caller to force a rebuild -- never
triggered automatically here. Safe to call before any write, including
delete()/upsert_document(): has_pending_migration() (see its docstring)
keeps this a no-op, with no exclusive access taken, once the store is
current.
"""
if not store.has_pending_migration():
return False
return bool(
_with_exclusive_access("migration check", store.check_and_run_migrations),
)
def _safe_related_name(document: Document, field: str) -> str | None:
"""
Returns the ``name`` of a related object (correspondent, document_type,
@@ -339,15 +403,7 @@ def update_llm_index(
happens, since a rebuild always covers the whole library regardless.
"""
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
needs_reembed = _check_and_run_migrations(store)
if needs_reembed:
logger.warning(
"LLM index migration requires re-embedding; forcing rebuild.",
@@ -385,7 +441,7 @@ def update_llm_index(
if rebuild or not store.table_exists():
logger.info("Rebuilding LLM index.")
store.drop_table()
for document in iter_wrapper(documents):
for document in iter_wrapper(_StreamedDocuments(documents)):
nodes = build_document_node(document, chunk_size=chunk_size)
_embed_nodes(nodes, embed_model)
store.add(nodes)
@@ -398,7 +454,7 @@ def update_llm_index(
)
existing = store.get_modified_times()
changed = 0
for document in iter_wrapper(scoped_documents):
for document in iter_wrapper(_StreamedDocuments(scoped_documents)):
doc_id = str(document.id)
if existing.get(doc_id) == document.modified.isoformat():
continue
@@ -412,14 +468,7 @@ def update_llm_index(
else "No changes detected in LLM index."
)
try:
with _exclude_readers():
store.compact()
except Timeout:
logger.info(
"Skipping LLM index compaction: index readers are active; "
"will retry next run.",
)
_with_exclusive_access("compaction", store.compact)
return msg
@@ -434,25 +483,60 @@ def llm_index_add_or_update_document(document: Document):
_embed_nodes(new_nodes, get_embedding_model(config))
with write_store(embed_model_name=get_configured_model_name(config)) as store:
needs_reembed = _check_and_run_migrations(store)
if needs_reembed:
logger.warning(
"Skipping incremental LLM index update for document %s: the "
"index requires re-embedding first. Run 'document_llmindex "
"rebuild' to resolve.",
document.id,
)
return
store.upsert_document(str(document.id), new_nodes)
def llm_index_migrate() -> None:
"""Apply any pending LLM index schema migrations, with no reindex.
Intended to run unconditionally on every startup (see the
init-llmindex-migrate container step and the bare-metal upgrade docs):
has_pending_migration() short-circuits to a metadata-only read once the
store is current, so a healthy install pays almost nothing here. Only
ever applies structural migrations -- a pending re-embed migration is
left for the explicit, deliberate rebuild path (``document_llmindex
update``/``rebuild``) to resolve, since re-embedding can be slow and,
for a metered embedding backend, cost money.
"""
if not AIConfig().llm_index_enabled:
return
with write_store() as store:
needs_reembed = _check_and_run_migrations(store)
if needs_reembed:
logger.warning(
"LLM index requires re-embedding, which this automatic migration "
"check will not do on its own -- it can be slow and, for a "
"metered embedding backend, cost money. Run "
"'document_llmindex rebuild' manually when ready.",
)
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.",
)
_with_exclusive_access("compaction", lambda: store.compact(force=True))
def llm_index_remove_document(document: Document):
"""Remove a document's chunks from the LLM index."""
with write_store() as store:
if _check_and_run_migrations(store):
logger.warning(
"Skipping removal of document %s from the LLM index: the "
"index requires re-embedding first. Run 'document_llmindex "
"rebuild' to resolve.",
document.id,
)
return
store.delete(str(document.id))
+60
View File
@@ -0,0 +1,60 @@
"""Schema migrations for the sqlite-vec vector store.
Each migration lives in its own module here, named ``mNNNN_description.py``
(e.g. ``m0001_v1_to_v2.py`` -- a leading digit isn't a valid Python
identifier, hence the ``m`` prefix, unlike Django's own numbered migrations,
which load via a dynamic ``importlib.import_module()`` call rather than a
static import statement), and registers itself into ``MIGRATIONS`` at import
time. ``vector_store.py`` imports those modules at the bottom of the file,
purely for that registration side effect, after ``PaperlessSqliteVecVectorStore``
is fully defined -- migrations need it to implement ``apply()`` (see
``Migration`` below).
To add a new migration: add a new ``mNNNN_description.py`` module here that
imports ``PaperlessSqliteVecVectorStore`` from ``paperless_ai.vector_store``,
defines its ``apply()``, and appends a ``Migration`` to ``MIGRATIONS``; then
import that module at the bottom of ``vector_store.py`` and bump
``SCHEMA_VERSION`` there. A migration must freeze its own historical DDL for
any side table its target version depends on (``DROP TABLE IF EXISTS`` +
its own literal ``CREATE TABLE``/``CREATE INDEX`` statements) rather than
delegating to any "current schema" helper -- see ``m0001_v1_to_v2.py`` for
why and the worked example.
"""
import sqlite3
from collections.abc import Callable
from dataclasses import dataclass
from dataclasses import field
from typing import Literal
@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 every table its target schema needs in ``dst_conn`` and copy
``src_conn``'s rows and relevant ``index_meta`` keys into it.
``schema_version`` is written by the migration runner after ``apply``
returns, not by ``apply`` itself.
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, populated by each migration
# module's import-time registration (see the module docstring above).
MIGRATIONS: list[Migration] = []
+229
View File
@@ -0,0 +1,229 @@
"""Thin gateways over the plain relational side tables that sit alongside the
vec0 table. Each method takes the sqlite3.Connection to operate on
explicitly, rather than owning one -- the store swaps connections during
compact()/migration, and migrations always work across two connections
(src_conn, dst_conn) at once.
PRECONDITION: Callers must set conn.row_factory = sqlite3.Row before passing a
connection to any of these gateways' read methods. The read methods across all
three classes (DocumentChunksTable.chunk_ids_for_document, IndexMetaTable._get,
DocumentMetaTable.all_modified_times, DocumentMetaTable.copy_all) use
row["column_name"] dictionary-style indexing, which requires sqlite3.Row as the
row factory -- without it, sqlite3.Row is not set, rows are returned as plain
tuples, and tuple indices must be integers, raising TypeError.
"""
import sqlite3
from collections.abc import Iterable
from typing import NamedTuple
class ChunkRow(NamedTuple):
chunk_id: str
document_id: int
class DocumentMetaRow(NamedTuple):
document_id: int
modified: str
class DocumentChunksTable:
"""chunk_id -> document_id, indexed by document_id. Gives O(1)
per-document chunk lookup that vec0's own document_id metadata column
cannot (see PaperlessSqliteVecVectorStore._delete_chunks_by_document_id).
"""
@staticmethod
def create(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE IF NOT EXISTS document_chunks "
"(chunk_id TEXT PRIMARY KEY, document_id INTEGER NOT NULL)",
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_document_chunks_document_id "
"ON document_chunks (document_id)",
)
@staticmethod
def insert_many(conn: sqlite3.Connection, rows: Iterable[ChunkRow]) -> None:
"""rows must already be batch-bounded by the caller (e.g. vec0's own
fetchmany() loop) -- this never reads, so it can't itself introduce
an unbounded scan, but a whole-table iterable defeats the point."""
conn.executemany(
"INSERT INTO document_chunks (chunk_id, document_id) VALUES (?, ?)",
rows,
)
@staticmethod
def chunk_ids_for_document(
conn: sqlite3.Connection,
document_id: int,
) -> list[str]:
return [
row["chunk_id"]
for row in conn.execute(
"SELECT chunk_id FROM document_chunks WHERE document_id = ?",
(document_id,),
).fetchall()
]
@staticmethod
def delete_for_document(conn: sqlite3.Connection, document_id: int) -> None:
conn.execute(
"DELETE FROM document_chunks WHERE document_id = ?",
(document_id,),
)
@staticmethod
def delete_all(conn: sqlite3.Connection) -> None:
conn.execute("DELETE FROM document_chunks")
@staticmethod
def count(conn: sqlite3.Connection) -> int:
"""Cheap stand-in for vec0's own row count -- see compact()."""
return conn.execute("SELECT count(*) FROM document_chunks").fetchone()[0]
class DocumentMetaTable:
"""document_id -> modified, one row per document. Lives outside vec0
because vec0 only inlines TEXT metadata up to 12 bytes and `modified`
(an ISO timestamp) is always longer.
"""
@staticmethod
def create(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE IF NOT EXISTS document_meta "
"(document_id INTEGER PRIMARY KEY, modified TEXT NOT NULL)",
)
@staticmethod
def upsert_many(
conn: sqlite3.Connection,
rows: Iterable[DocumentMetaRow],
) -> None:
conn.executemany(
"INSERT INTO document_meta (document_id, modified) VALUES (?, ?) "
"ON CONFLICT(document_id) DO UPDATE SET modified = excluded.modified",
rows,
)
@staticmethod
def delete_for_document(conn: sqlite3.Connection, document_id: int) -> None:
conn.execute(
"DELETE FROM document_meta WHERE document_id = ?",
(document_id,),
)
@staticmethod
def delete_all(conn: sqlite3.Connection) -> None:
conn.execute("DELETE FROM document_meta")
@staticmethod
def copy_all(
src_conn: sqlite3.Connection,
dst_conn: sqlite3.Connection,
batch_size: int,
) -> None:
"""Stream document_meta from src_conn into dst_conn in bounded
batches. The *only* sanctioned way to move this table across
connections (compact()/migrations) -- an unbounded fetchall here
would defeat the same OOM-avoidance the vec0 row copy already relies
on. batch_size has no default: forces the call site to think about
it (pass COMPACT_BATCH_SIZE)."""
cursor = src_conn.execute(
"SELECT document_id, modified FROM document_meta",
)
while batch := cursor.fetchmany(batch_size):
DocumentMetaTable.upsert_many(
dst_conn,
(DocumentMetaRow(r["document_id"], r["modified"]) for r in batch),
)
@staticmethod
def all_modified_times(conn: sqlite3.Connection) -> dict[str, str]:
"""Full document_id -> modified map, for get_modified_times()'s
public API only. One unbounded read by design (existing behavior).
Never use this for cross-connection copying; see copy_all()."""
return {
str(row["document_id"]): str(row["modified"] or "")
for row in conn.execute(
"SELECT document_id, modified FROM document_meta",
)
}
class IndexMetaTable:
"""Typed accessors over index_meta's key/value rows -- replaces
PaperlessSqliteVecVectorStore._meta_get_on/_meta_set_on, which returned
untyped str | None regardless of whether the key held an int (dim,
schema_version, total_inserts) or a string (embed_model).
"""
@staticmethod
def create(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
)
@staticmethod
def _get(conn: sqlite3.Connection, key: str) -> str | None:
row = conn.execute(
"SELECT value FROM index_meta WHERE key = ?",
(key,),
).fetchone()
return row["value"] if row else None
@staticmethod
def _set(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),
)
@staticmethod
def get_dim(conn: sqlite3.Connection) -> int | None:
value = IndexMetaTable._get(conn, "dim")
return int(value) if value is not None else None
@staticmethod
def set_dim(conn: sqlite3.Connection, dim: int) -> None:
IndexMetaTable._set(conn, "dim", str(dim))
@staticmethod
def get_embed_model(conn: sqlite3.Connection) -> str | None:
return IndexMetaTable._get(conn, "embed_model")
@staticmethod
def set_embed_model(conn: sqlite3.Connection, name: str) -> None:
IndexMetaTable._set(conn, "embed_model", name)
@staticmethod
def get_schema_version(conn: sqlite3.Connection) -> int | None:
value = IndexMetaTable._get(conn, "schema_version")
return int(value) if value is not None else None
@staticmethod
def set_schema_version(conn: sqlite3.Connection, version: int) -> None:
IndexMetaTable._set(conn, "schema_version", str(version))
@staticmethod
def get_total_inserts(conn: sqlite3.Connection) -> int:
value = IndexMetaTable._get(conn, "total_inserts")
return int(value) if value is not None else 0
@staticmethod
def increment_total_inserts(conn: sqlite3.Connection, count: int) -> None:
current = IndexMetaTable.get_total_inserts(conn)
IndexMetaTable._set(conn, "total_inserts", str(current + count))
@staticmethod
def reset_total_inserts(conn: sqlite3.Connection, count: int) -> None:
"""Set total_inserts to an absolute value -- distinct from
increment_total_inserts(): used by compact()'s rebuild and by
m0001_v1_to_v2 after copying live rows into a fresh file, where
total_inserts must become exactly the live row count, not add to
whatever the source file's counter held."""
IndexMetaTable._set(conn, "total_inserts", str(count))
+169
View File
@@ -1,3 +1,4 @@
import logging
from pathlib import Path
from unittest.mock import MagicMock
from unittest.mock import patch
@@ -186,6 +187,45 @@ def test_truncate_embedding_query_returns_single_chunk() -> None:
assert "word199" not in result
class TestStreamedDocuments:
"""_StreamedDocuments streams via .iterator() instead of materializing
the whole queryset (plus its content and prefetch caches) in memory at
once, while still supporting len() so a progress bar wrapped around it
shows a real total.
"""
def test_len_and_iter_delegate_to_streaming_queryset_methods(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- A mock queryset
WHEN:
- A _StreamedDocuments wrapping it is measured and iterated
THEN:
- len() uses count() (not a materializing len()), and iteration
uses .iterator(chunk_size=...) (not plain iteration, which
would materialize prefetches for the whole queryset at once)
"""
mock_queryset = mocker.MagicMock()
mock_queryset.count.return_value = 42
mock_queryset.iterator.return_value = iter(["doc-1", "doc-2"])
streamed = indexing._StreamedDocuments(mock_queryset)
assert len(streamed) == 42
assert list(streamed) == ["doc-1", "doc-2"]
# count.call_count isn't asserted exactly: list()'s own size-hint
# optimization calls len(streamed) again internally, on top of the
# explicit len() call above -- both legitimately delegate to
# count(), so only the delegation itself (not the call count) is
# the thing being verified here.
mock_queryset.count.assert_called_with()
mock_queryset.iterator.assert_called_once_with(
chunk_size=indexing._INDEX_STREAM_CHUNK_SIZE,
)
@pytest.mark.django_db
def test_update_llm_index(
temp_llm_index_dir: Path,
@@ -737,6 +777,7 @@ class TestLlmIndexLocking:
mocker: pytest_mock.MockerFixture,
) -> None:
mock_store = MagicMock()
mock_store.has_pending_migration.return_value = False
mocker.patch(
"paperless_ai.indexing.write_store",
return_value=mocker.MagicMock(
@@ -757,12 +798,45 @@ class TestLlmIndexLocking:
mock_store.upsert_document.assert_called_once()
def test_add_or_update_document_skips_write_when_reembed_pending(
self,
temp_llm_index_dir: Path,
mock_embed_model: FakeEmbedding,
mocker: pytest_mock.MockerFixture,
) -> None:
"""A pending re-embed migration must block the incremental write,
not let it proceed against a schema that just changed underneath it.
"""
mock_store = MagicMock()
mock_store.has_pending_migration.return_value = True
mock_store.check_and_run_migrations.return_value = True
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=[mock_node],
)
doc = MagicMock(spec=Document)
doc.id = 1
indexing.llm_index_add_or_update_document(doc)
mock_store.upsert_document.assert_not_called()
def test_remove_document_uses_write_store(
self,
temp_llm_index_dir: Path,
mocker: pytest_mock.MockerFixture,
) -> None:
mock_store = MagicMock()
mock_store.has_pending_migration.return_value = False
mocker.patch(
"paperless_ai.indexing.write_store",
return_value=mocker.MagicMock(
@@ -777,6 +851,31 @@ class TestLlmIndexLocking:
mock_store.delete.assert_called_once_with("1")
def test_remove_document_skips_write_when_reembed_pending(
self,
temp_llm_index_dir: Path,
mocker: pytest_mock.MockerFixture,
) -> None:
"""A pending re-embed migration must block the delete too, for the
same consistency reason as the incremental-update path.
"""
mock_store = MagicMock()
mock_store.has_pending_migration.return_value = True
mock_store.check_and_run_migrations.return_value = True
mocker.patch(
"paperless_ai.indexing.write_store",
return_value=mocker.MagicMock(
__enter__=mocker.MagicMock(return_value=mock_store),
__exit__=mocker.MagicMock(return_value=False),
),
)
doc = MagicMock(spec=Document)
doc.id = 1
indexing.llm_index_remove_document(doc)
mock_store.delete.assert_not_called()
def test_update_llm_index_rebuild_uses_write_store(
self,
temp_llm_index_dir: Path,
@@ -849,6 +948,76 @@ class TestVectorStoreIndexing:
assert rows >= 1
class TestLlmIndexMigrate:
def test_noop_when_ai_disabled(self, mocker: pytest_mock.MockerFixture) -> None:
"""
GIVEN:
- AI/LLM index support is disabled in configuration
WHEN:
- llm_index_migrate() is called
THEN:
- No store is opened and no migration check runs
"""
mocker.patch(
"paperless_ai.indexing.AIConfig",
return_value=mocker.Mock(llm_index_enabled=False),
)
write_store_mock = mocker.patch("paperless_ai.indexing.write_store")
indexing.llm_index_migrate()
write_store_mock.assert_not_called()
def test_runs_pending_migration_when_enabled(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- AI/LLM index support is enabled
WHEN:
- llm_index_migrate() is called
THEN:
- The store is opened for write and a migration check runs
"""
mocker.patch(
"paperless_ai.indexing.AIConfig",
return_value=mocker.Mock(llm_index_enabled=True),
)
store_mock = mocker.MagicMock()
store_mock.has_pending_migration.return_value = False
write_store_cm = mocker.patch("paperless_ai.indexing.write_store")
write_store_cm.return_value.__enter__.return_value = store_mock
indexing.llm_index_migrate()
store_mock.has_pending_migration.assert_called_once()
def test_logs_warning_when_reembed_needed(
self,
mocker: pytest_mock.MockerFixture,
caplog: pytest.LogCaptureFixture,
) -> None:
"""
GIVEN:
- AI/LLM index support is enabled
- A pending migration requires re-embedding
WHEN:
- llm_index_migrate() is called
THEN:
- A warning directs the operator to run a manual rebuild, since
this automatic check must never re-embed on its own
"""
mocker.patch(
"paperless_ai.indexing.AIConfig",
return_value=mocker.Mock(llm_index_enabled=True),
)
store_mock = mocker.MagicMock()
store_mock.has_pending_migration.return_value = True
store_mock.check_and_run_migrations.return_value = True
write_store_cm = mocker.patch("paperless_ai.indexing.write_store")
write_store_cm.return_value.__enter__.return_value = store_mock
with caplog.at_level(logging.WARNING, logger="paperless_ai.indexing"):
indexing.llm_index_migrate()
assert "requires re-embedding" in caplog.text
@pytest.mark.django_db
class TestQuerySimilarDocuments:
def test_query_similar_documents_respects_allowed_ids(
+306
View File
@@ -0,0 +1,306 @@
import sqlite3
from collections.abc import Generator
import pytest
from paperless_ai.tables import ChunkRow
from paperless_ai.tables import DocumentChunksTable
from paperless_ai.tables import DocumentMetaRow
from paperless_ai.tables import DocumentMetaTable
from paperless_ai.tables import IndexMetaTable
@pytest.fixture
def conn() -> Generator[sqlite3.Connection, None, None]:
connection = sqlite3.connect(":memory:")
connection.row_factory = sqlite3.Row
try:
yield connection
finally:
connection.close()
class TestDocumentChunksTable:
def test_create_is_idempotent(self, conn: sqlite3.Connection) -> None:
"""
GIVEN:
- A bare sqlite3 connection
WHEN:
- create() is called, a row is inserted, then create() is called again
THEN:
- No error is raised and the row survives uncorrupted
"""
DocumentChunksTable.create(conn)
DocumentChunksTable.insert_many(conn, [ChunkRow("c1", 1)])
DocumentChunksTable.create(conn)
assert DocumentChunksTable.chunk_ids_for_document(conn, 1) == ["c1"]
def test_insert_many_then_lookup_by_document_id(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- An empty document_chunks table
WHEN:
- Two chunks for document 1 and one for document 2 are inserted
THEN:
- chunk_ids_for_document returns exactly the matching chunk ids
"""
DocumentChunksTable.create(conn)
DocumentChunksTable.insert_many(
conn,
[ChunkRow("c1", 1), ChunkRow("c2", 1), ChunkRow("c3", 2)],
)
assert sorted(DocumentChunksTable.chunk_ids_for_document(conn, 1)) == [
"c1",
"c2",
]
assert DocumentChunksTable.chunk_ids_for_document(conn, 2) == ["c3"]
assert DocumentChunksTable.chunk_ids_for_document(conn, 999) == []
def test_delete_for_document_removes_only_that_document(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- Chunks for two different documents
WHEN:
- delete_for_document() is called for one of them
THEN:
- Only that document's chunks are removed
"""
DocumentChunksTable.create(conn)
DocumentChunksTable.insert_many(
conn,
[ChunkRow("c1", 1), ChunkRow("c2", 2)],
)
DocumentChunksTable.delete_for_document(conn, 1)
assert DocumentChunksTable.chunk_ids_for_document(conn, 1) == []
assert DocumentChunksTable.chunk_ids_for_document(conn, 2) == ["c2"]
def test_delete_all_clears_every_row(self, conn: sqlite3.Connection) -> None:
"""
GIVEN:
- Chunks for multiple documents
WHEN:
- delete_all() is called
THEN:
- count() returns 0
"""
DocumentChunksTable.create(conn)
DocumentChunksTable.insert_many(
conn,
[ChunkRow("c1", 1), ChunkRow("c2", 2)],
)
DocumentChunksTable.delete_all(conn)
assert DocumentChunksTable.count(conn) == 0
def test_count_reflects_live_rows(self, conn: sqlite3.Connection) -> None:
"""
GIVEN:
- An empty document_chunks table
WHEN:
- Rows are inserted then one document's rows are deleted
THEN:
- count() reflects the remaining row count
"""
DocumentChunksTable.create(conn)
DocumentChunksTable.insert_many(
conn,
[ChunkRow("c1", 1), ChunkRow("c2", 1), ChunkRow("c3", 2)],
)
assert DocumentChunksTable.count(conn) == 3
DocumentChunksTable.delete_for_document(conn, 1)
assert DocumentChunksTable.count(conn) == 1
class TestDocumentMetaTable:
def test_upsert_many_then_all_modified_times(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- An empty document_meta table
WHEN:
- Two documents' modified timestamps are upserted
THEN:
- all_modified_times() returns both, keyed by str(document_id)
"""
DocumentMetaTable.create(conn)
DocumentMetaTable.upsert_many(
conn,
[
DocumentMetaRow(1, "2026-01-01T00:00:00"),
DocumentMetaRow(2, "2026-02-02T00:00:00"),
],
)
assert DocumentMetaTable.all_modified_times(conn) == {
"1": "2026-01-01T00:00:00",
"2": "2026-02-02T00:00:00",
}
def test_upsert_many_overwrites_existing_value(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- A document_meta row for document 1
WHEN:
- upsert_many() is called again with a new modified value for
the same document_id
THEN:
- The stored value is replaced, not duplicated
"""
DocumentMetaTable.create(conn)
DocumentMetaTable.upsert_many(conn, [DocumentMetaRow(1, "old")])
DocumentMetaTable.upsert_many(conn, [DocumentMetaRow(1, "new")])
assert DocumentMetaTable.all_modified_times(conn) == {"1": "new"}
def test_delete_for_document_removes_only_that_row(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- document_meta rows for two documents
WHEN:
- delete_for_document() is called for one of them
THEN:
- Only that document's row is removed
"""
DocumentMetaTable.create(conn)
DocumentMetaTable.upsert_many(
conn,
[DocumentMetaRow(1, "a"), DocumentMetaRow(2, "b")],
)
DocumentMetaTable.delete_for_document(conn, 1)
assert DocumentMetaTable.all_modified_times(conn) == {"2": "b"}
def test_delete_all_clears_every_row(self, conn: sqlite3.Connection) -> None:
"""
GIVEN:
- document_meta rows for multiple documents
WHEN:
- delete_all() is called
THEN:
- all_modified_times() returns an empty dict
"""
DocumentMetaTable.create(conn)
DocumentMetaTable.upsert_many(
conn,
[DocumentMetaRow(1, "a"), DocumentMetaRow(2, "b")],
)
DocumentMetaTable.delete_all(conn)
assert DocumentMetaTable.all_modified_times(conn) == {}
def test_copy_all_streams_every_row_to_destination(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- A source connection with document_meta rows for 5 documents
- A separate, empty destination connection
WHEN:
- copy_all() is called with a batch size smaller than the row
count, forcing multiple fetchmany() cycles
THEN:
- Every row is present on the destination connection
"""
DocumentMetaTable.create(conn)
DocumentMetaTable.upsert_many(
conn,
[DocumentMetaRow(i, f"modified-{i}") for i in range(5)],
)
dst_conn = sqlite3.connect(":memory:")
dst_conn.row_factory = sqlite3.Row
try:
DocumentMetaTable.create(dst_conn)
DocumentMetaTable.copy_all(conn, dst_conn, batch_size=2)
assert DocumentMetaTable.all_modified_times(dst_conn) == {
str(i): f"modified-{i}" for i in range(5)
}
finally:
dst_conn.close()
class TestIndexMetaTable:
@pytest.mark.parametrize(
("setter_name", "getter_name", "value"),
[
("set_dim", "get_dim", 384),
("set_embed_model", "get_embed_model", "model-a"),
("set_schema_version", "get_schema_version", 2),
],
)
def test_typed_accessor_roundtrip(
self,
conn: sqlite3.Connection,
setter_name: str,
getter_name: str,
value: int | str,
) -> None:
"""
GIVEN:
- An empty index_meta table
WHEN:
- A typed accessor's setter is called then the getter is read back
THEN:
- The same value is returned, correctly typed (int or str)
"""
IndexMetaTable.create(conn)
getter = getattr(IndexMetaTable, getter_name)
setter = getattr(IndexMetaTable, setter_name)
assert getter(conn) is None
setter(conn, value)
assert getter(conn) == value
def test_total_inserts_starts_at_zero(self, conn: sqlite3.Connection) -> None:
"""
GIVEN:
- An empty index_meta table
WHEN:
- get_total_inserts() is read before anything is set
THEN:
- 0 is returned
"""
IndexMetaTable.create(conn)
assert IndexMetaTable.get_total_inserts(conn) == 0
def test_increment_total_inserts_accumulates(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- An empty index_meta table
WHEN:
- increment_total_inserts() is called twice
THEN:
- get_total_inserts() returns the running sum
"""
IndexMetaTable.create(conn)
IndexMetaTable.increment_total_inserts(conn, 5)
IndexMetaTable.increment_total_inserts(conn, 3)
assert IndexMetaTable.get_total_inserts(conn) == 8
def test_reset_total_inserts_sets_absolute_value(
self,
conn: sqlite3.Connection,
) -> None:
"""
GIVEN:
- A total_inserts counter already at a high value
WHEN:
- reset_total_inserts() is called with a lower value
THEN:
- get_total_inserts() returns exactly that value, not a sum
"""
IndexMetaTable.create(conn)
IndexMetaTable.increment_total_inserts(conn, 100)
IndexMetaTable.reset_total_inserts(conn, 7)
assert IndexMetaTable.get_total_inserts(conn) == 7
+49 -2
View File
@@ -9,11 +9,11 @@ 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.migrations import MIGRATIONS
from paperless_ai.migrations import Migration
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
@@ -646,3 +646,50 @@ class TestMigrations:
assert result is True
assert self._schema_version(store) == 2
def test_has_pending_migration_false_when_no_table(
self,
store: PaperlessSqliteVecVectorStore,
) -> None:
"""
GIVEN:
- A vector store with no table created yet
WHEN:
- has_pending_migration() is checked
THEN:
- False is returned (nothing to migrate before anything exists)
"""
assert store.has_pending_migration() is False
def test_has_pending_migration_false_at_current_version(
self,
store: PaperlessSqliteVecVectorStore,
) -> None:
"""
GIVEN:
- A store at the current SCHEMA_VERSION
WHEN:
- has_pending_migration() is checked
THEN:
- False is returned
"""
store.add([make_node("a1", "1")])
assert store.has_pending_migration() is False
def test_has_pending_migration_true_when_behind(
self,
store: PaperlessSqliteVecVectorStore,
) -> None:
"""
GIVEN:
- A store whose schema_version has been forced behind SCHEMA_VERSION
WHEN:
- has_pending_migration() is checked
THEN:
- True is returned
"""
store.add([make_node("a1", "1")])
store.client.execute(
"UPDATE index_meta SET value = '0' WHERE key = 'schema_version'",
)
assert store.has_pending_migration() is True
+35 -45
View File
@@ -2,16 +2,12 @@ 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
@@ -26,6 +22,9 @@ 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
from paperless_ai.migrations import MIGRATIONS
from paperless_ai.migrations import Migration
logger = logging.getLogger("paperless_ai.vector_store")
DB_FILENAME = "llmindex.db"
@@ -53,38 +52,6 @@ COMPACT_BATCH_SIZE = 500
_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)
@@ -551,6 +518,31 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
Path(compact_path).replace(db_path)
self._conn = self._open_connection(db_path)
def _stored_schema_version(self) -> int | None:
"""The schema_version recorded in index_meta, or None if no table
exists. A missing key (a store predating version tracking) is
treated as SCHEMA_VERSION -- i.e. already current -- since no
migration in MIGRATIONS targets a version before tracking began.
"""
if not self.table_exists():
return None
raw = self._meta_get("schema_version")
return int(raw) if raw is not None else SCHEMA_VERSION
def has_pending_migration(self) -> bool:
"""Cheaply check whether a migration is pending, with no exclusive
access needed -- just a metadata read under the connection callers
already hold via the write FileLock.
Callers should only pay for check_and_run_migrations()'s exclusive
access (a structural migration's file swap must not run while
readers are active) when this returns True, so that the common
case -- already at SCHEMA_VERSION -- never contends with readers
or a concurrent compaction.
"""
current = self._stored_schema_version()
return current is not None and current < SCHEMA_VERSION
def check_and_run_migrations(self) -> bool:
"""Apply any pending schema migrations to the store.
@@ -559,15 +551,13 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
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.
Must be called under the write FileLock, with readers excluded (see
has_pending_migration() for a cheap pre-check that avoids paying for
that exclusion in the common case). 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:
current = self._stored_schema_version()
if current is None or current >= SCHEMA_VERSION:
return False
pending = sorted(
@@ -579,7 +569,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
if migration.kind == "re-embed":
logger.warning(
"LLM index schema v%d -> v%d requires re-embedding (%s); "
"forcing full rebuild.",
"the caller must force a rebuild.",
migration.from_version,
migration.to_version,
migration.description,
-8
View File
@@ -1,8 +0,0 @@
from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class PaperlessBenchmarkConfig(AppConfig):
name = "paperless_benchmark"
verbose_name = _("Paperless benchmark")
-136
View File
@@ -1,136 +0,0 @@
from __future__ import annotations
from typing import TYPE_CHECKING
from django.db import connection
if TYPE_CHECKING:
from django.db.models import QuerySet
def _reset_table_names() -> list[str]:
from guardian.models import GroupObjectPermission
from guardian.models import UserObjectPermission
from documents.models import Correspondent
from documents.models import Document
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
return [
Document.tags.through._meta.db_table,
Document._meta.db_table,
Tag._meta.db_table,
Correspondent._meta.db_table,
DocumentType._meta.db_table,
StoragePath._meta.db_table,
UserObjectPermission._meta.db_table,
GroupObjectPermission._meta.db_table,
]
def _delete_all_users_and_groups() -> None:
# ASSUMPTION: this tool assumes a disposable benchmark database, never
# point it at a real install. This deletes EVERY user and group in the
# database (not just benchmark-created ones) -- there is no way to
# distinguish "real" users from seeded ones, so this is only safe against
# a database that exists solely to run this benchmarking tool. The
# `benchmark seed --reset` CLI path requires an explicit
# `--yes-i-know-this-wipes-the-database` flag before reaching here; do
# not remove that guard.
from django.contrib.auth import get_user_model
from django.contrib.auth.models import Group
get_user_model().objects.all().delete()
Group.objects.all().delete()
def _reset_postgresql() -> None:
tables = _reset_table_names()
with connection.cursor() as cursor:
cursor.execute(f"TRUNCATE TABLE {', '.join(tables)} RESTART IDENTITY CASCADE;")
_delete_all_users_and_groups()
def _reset_mariadb() -> None:
# MariaDB's TRUNCATE has no CASCADE clause and refuses to truncate a
# table referenced by a foreign key while checks are enabled, so
# checks are disabled for the duration of the reset.
tables = _reset_table_names()
with connection.cursor() as cursor:
cursor.execute("SET FOREIGN_KEY_CHECKS = 0;")
try:
for table in tables:
cursor.execute(f"TRUNCATE TABLE {table};")
finally:
cursor.execute("SET FOREIGN_KEY_CHECKS = 1;")
_delete_all_users_and_groups()
def _reset_sqlite() -> None:
from documents.models import Correspondent
from documents.models import Document
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
Document.global_objects.all().delete()
Tag.objects.all().delete()
Correspondent.objects.all().delete()
DocumentType.objects.all().delete()
StoragePath.objects.all().delete()
_delete_all_users_and_groups()
def reset_benchmark_data() -> None:
"""
Remove all previously-seeded benchmark data (documents, tags,
correspondents, document types, storage paths, guardian permission
rows, users, and groups) so a fresh `benchmark seed` run starts
from an empty slate. Dispatches per-backend because TRUNCATE syntax
and cascade behavior differ across the 3 supported databases.
"""
if connection.vendor == "postgresql":
_reset_postgresql()
elif connection.vendor == "mysql":
# MariaDB also reports vendor == "mysql" under Django's mysql backend.
_reset_mariadb()
else:
_reset_sqlite()
def capture_explain(queryset: QuerySet) -> str:
"""
Return the query plan for `queryset` using the current backend's
explain facility. PostgreSQL supports `EXPLAIN ANALYZE {sql}` (real
execution stats). MariaDB does NOT accept that syntax -- verified
against a real MariaDB 12.3 container: `EXPLAIN ANALYZE {sql}` raises a
1064 syntax error, while MariaDB's own `ANALYZE {sql}` form (no
`EXPLAIN` keyword) works and returns real per-row execution stats
(`r_rows`, `r_filtered`, etc. columns) -- this is MariaDB's
EXPLAIN-ANALYZE-equivalent, distinct from MySQL 8.0.18+'s
`EXPLAIN ANALYZE` syntax, which MariaDB does not implement. SQLite only
supports EXPLAIN QUERY PLAN (the chosen plan, not real timing/row
counts) -- that output is clearly labeled rather than silently looking
equivalent to the other two backends' output.
"""
sql, params = queryset.query.sql_with_params()
with connection.cursor() as cursor:
if connection.vendor == "postgresql":
cursor.execute(f"EXPLAIN ANALYZE {sql}", params)
return "\n".join(str(row[0]) for row in cursor.fetchall())
if connection.vendor == "mysql":
# MariaDB also reports vendor == "mysql" under Django's mysql
# backend. Unlike MySQL 8.0.18+, MariaDB has no `EXPLAIN
# ANALYZE` syntax -- its equivalent is `ANALYZE <statement>`.
cursor.execute(f"ANALYZE {sql}", params)
columns = [c[0] for c in cursor.description]
header = " | ".join(columns)
rows = "\n".join(
" | ".join(str(c) for c in row) for row in cursor.fetchall()
)
return f"{header}\n{rows}"
cursor.execute(f"EXPLAIN QUERY PLAN {sql}", params)
rows = "\n".join(" | ".join(str(c) for c in row) for row in cursor.fetchall())
return f"(plan only -- no execution stats on SQLite)\n{rows}"
-81
View File
@@ -1,81 +0,0 @@
# src/paperless_benchmark/endpoints.py
from __future__ import annotations
import statistics
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from django.contrib.auth.models import User
from rest_framework.test import APIClient
ENDPOINTS: tuple[tuple[str, str], ...] = (
("documents_default", "/api/documents/"),
("documents_page50", "/api/documents/?page_size=50"),
("tags_all", "/api/tags/?page_size=100000"),
)
@dataclass(frozen=True, slots=True)
class EndpointTiming:
user_label: str
endpoint_name: str
query_count: int
min_ms: float
median_ms: float
max_ms: float
def _timed_requests(client: APIClient, url: str, n: int) -> list[float]:
times = []
for _ in range(n):
t0 = time.perf_counter()
resp = client.get(url)
t1 = time.perf_counter()
if resp.status_code != 200:
raise RuntimeError(
f"GET {url} -> {resp.status_code}: {resp.content[:300]!r}",
)
times.append(t1 - t0)
return times
def _query_count(client: APIClient, url: str) -> int:
from django.db import connection
from django.test.utils import CaptureQueriesContext
with CaptureQueriesContext(connection) as ctx:
resp = client.get(url)
if resp.status_code != 200:
raise RuntimeError(f"GET {url} -> {resp.status_code}: {resp.content[:300]!r}")
return len(ctx.captured_queries)
def run_endpoint_benchmarks(
*,
perf_target: User,
perf_admin: User,
repeat: int,
) -> list[EndpointTiming]:
from rest_framework.test import APIClient
results: list[EndpointTiming] = []
for user_label, user in (("target", perf_target), ("admin", perf_admin)):
client = APIClient()
client.force_authenticate(user=user)
for name, url in ENDPOINTS:
client.get(url) # warm-up request, not counted
qcount = _query_count(client, url)
times_ms = [t * 1000 for t in _timed_requests(client, url, repeat)]
results.append(
EndpointTiming(
user_label=user_label,
endpoint_name=name,
query_count=qcount,
min_ms=min(times_ms),
median_ms=statistics.median(times_ms),
max_ms=max(times_ms),
),
)
return results
-56
View File
@@ -1,56 +0,0 @@
# src/paperless_benchmark/harness.py
from __future__ import annotations
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Generic
from typing import TypeVar
from django.db import connection
from django.test.utils import CaptureQueriesContext
if TYPE_CHECKING:
from collections.abc import Callable
T = TypeVar("T")
@dataclass(frozen=True, slots=True)
class ProfileResult(Generic[T]):
best_seconds: float
all_seconds: tuple[float, ...]
query_count: int
result: T
def run_profile(fn: Callable[[], T], *, repeat: int = 5) -> ProfileResult[T]:
"""
Call `fn` `repeat` times, capturing wall-clock time for every call and
the SQL query count for the final call. Returns the best (minimum)
time across all repeats, since the first call(s) can be skewed by
connection warm-up or cold caches.
"""
if repeat < 1:
raise ValueError("repeat must be >= 1")
all_seconds: list[float] = []
result: T | None = None
query_count = 0
for i in range(repeat):
with CaptureQueriesContext(connection) as ctx:
start = time.perf_counter()
result = fn()
all_seconds.append(time.perf_counter() - start)
if i == repeat - 1:
query_count = len(ctx.captured_queries)
# Purely a type-narrowing aid for the type checker: the `repeat < 1`
# guard above already turns the one case that could leave `result`
# unset into a clear ValueError, so this is unreachable in practice.
assert result is not None
return ProfileResult(
best_seconds=min(all_seconds),
all_seconds=tuple(all_seconds),
query_count=query_count,
result=result,
)
@@ -1,222 +0,0 @@
# src/paperless_benchmark/management/commands/benchmark.py
from __future__ import annotations
from typing import Any
from django.core.management.base import BaseCommand
from django.core.management.base import CommandError
from django.core.management.base import CommandParser
class Command(BaseCommand):
help = "Seed, run, and profile paperless-ngx performance benchmarks."
def add_arguments(self, parser: CommandParser) -> None:
parser.add_argument(
"action",
choices=["seed", "run", "profile", "list-scenarios"],
help="Which benchmark action to perform.",
)
parser.add_argument(
"scenario",
nargs="?",
default=None,
help="Scenario name (required for `profile`; see `list-scenarios`).",
)
parser.add_argument(
"--tier",
choices=["home", "medium", "large"],
default="medium",
help="Dataset scale tier for `seed` (default: medium).",
)
parser.add_argument(
"--reset",
action="store_true",
default=False,
help="For `seed`: truncate existing benchmark data first.",
)
parser.add_argument(
"--yes-i-know-this-wipes-the-database",
action="store_true",
default=False,
help=(
"Required alongside --reset: confirms you understand `seed "
"--reset` deletes ALL users, ALL groups, and ALL documents/"
"tags/correspondents/document types/storage paths in this "
"database, not just benchmark-created ones."
),
)
parser.add_argument(
"--seed",
type=int,
default=42,
help="RNG seed for reproducible datasets (default: 42).",
)
parser.add_argument(
"--repeat",
type=int,
default=5,
help="Number of timed repetitions for `run`/`profile` (default: 5).",
)
parser.add_argument(
"--label",
default="baseline",
help="Free-text tag for a `run`, printed and recorded in history only.",
)
parser.add_argument(
"--explain",
action="store_true",
default=False,
help="For `profile`: also capture and print the query plan.",
)
def handle(self, *args: Any, **options: Any) -> None:
action = options["action"]
if action == "seed":
self._handle_seed(options)
elif action == "run":
self._handle_run(options)
elif action == "profile":
self._handle_profile(options)
else:
self._handle_list_scenarios()
def _handle_seed(self, options: dict[str, Any]) -> None:
from paperless_benchmark.db import reset_benchmark_data
from paperless_benchmark.seeding import seed_benchmark_dataset
if options["reset"]:
if not options["yes_i_know_this_wipes_the_database"]:
raise CommandError(
"--reset requires --yes-i-know-this-wipes-the-database. "
"This deletes ALL users, ALL groups, and ALL documents, "
"tags, correspondents, document types, and storage paths "
"in this database -- not just benchmark-created ones. "
"Only run this against a disposable benchmark database, "
"never a real install. Re-run with "
"--reset --yes-i-know-this-wipes-the-database to proceed.",
)
self.stdout.write("Resetting existing benchmark data...")
reset_benchmark_data()
data = seed_benchmark_dataset(options["tier"], seed=options["seed"])
self.stdout.write(
self.style.SUCCESS(
f"Seeded tier={options['tier']!r}: {data.documents} documents, "
f"{len(data.users)} users, {len(data.groups)} groups.",
),
)
def _handle_run(self, options: dict[str, Any]) -> None:
from django.contrib.auth import get_user_model
from django.db import connection
from documents.models import Document
from paperless_benchmark.endpoints import run_endpoint_benchmarks
from paperless_benchmark.results import append_history
user_model = get_user_model()
try:
perf_target = user_model.objects.get(username="perf_target")
perf_admin = user_model.objects.get(username="perf_admin")
except user_model.DoesNotExist as e:
raise CommandError(
"No benchmark dataset found. Run `manage.py benchmark seed` first.",
) from e
db_vendor = connection.vendor
document_count = Document.objects.count()
results = run_endpoint_benchmarks(
perf_target=perf_target,
perf_admin=perf_admin,
repeat=options["repeat"],
)
self.stdout.write(f"# label={options['label']} repeat={options['repeat']}")
self.stdout.write(
f"{'user':7s} {'endpoint':20s} {'queries':>8s} "
f"{'min_ms':>9s} {'median_ms':>10s} {'max_ms':>9s}",
)
for r in results:
self.stdout.write(
f"{r.user_label:7s} {r.endpoint_name:20s} {r.query_count:8d} "
f"{r.min_ms:9.1f} {r.median_ms:10.1f} {r.max_ms:9.1f}",
)
append_history(
{
"mode": "run",
"label": options["label"],
"user": r.user_label,
"endpoint": r.endpoint_name,
"query_count": r.query_count,
"min_ms": r.min_ms,
"median_ms": r.median_ms,
"max_ms": r.max_ms,
"db_vendor": db_vendor,
"document_count": document_count,
},
)
def _handle_profile(self, options: dict[str, Any]) -> None:
from django.contrib.auth import get_user_model
from django.db import connection
from documents.models import Document
from paperless_benchmark.db import capture_explain
from paperless_benchmark.harness import run_profile
from paperless_benchmark.results import append_history
from paperless_benchmark.scenarios import get as get_scenario
if not options["scenario"]:
raise CommandError(
"`profile` requires a scenario name; see `list-scenarios`.",
)
scenario = get_scenario(options["scenario"])
user_model = get_user_model()
try:
perf_target = user_model.objects.get(username="perf_target")
except user_model.DoesNotExist as e:
raise CommandError(
"No benchmark dataset found. Run `manage.py benchmark seed` first.",
) from e
profile = run_profile(
lambda: scenario.run(perf_target),
repeat=options["repeat"],
)
self.stdout.write(
f"{scenario.name}: best={profile.best_seconds:.4f}s "
f"queries={profile.query_count}",
)
if options["explain"]:
if scenario.queryset_for_explain is not None:
plan = capture_explain(scenario.queryset_for_explain(perf_target))
self.stdout.write(plan)
else:
self.stdout.write(
self.style.WARNING(
f"--explain was requested but scenario {scenario.name!r} "
"does not support it (no queryset_for_explain); skipping.",
),
)
append_history(
{
"mode": "profile",
"scenario": scenario.name,
"best_seconds": profile.best_seconds,
"query_count": profile.query_count,
"db_vendor": connection.vendor,
"document_count": Document.objects.count(),
},
)
def _handle_list_scenarios(self) -> None:
from paperless_benchmark.scenarios import all_scenarios
for scenario in all_scenarios():
self.stdout.write(f"{scenario.name}: {scenario.describe}")
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# src/paperless_benchmark/results.py
from __future__ import annotations
import json
import subprocess
from datetime import UTC
from datetime import datetime
from pathlib import Path
from typing import Any
RESULTS_DIR = Path(__file__).resolve().parent.parent.parent / "benchmark_results"
def _current_git_ref() -> str:
result = subprocess.run(
["git", "rev-parse", "--short", "HEAD"],
capture_output=True,
text=True,
check=False,
)
return result.stdout.strip() or "unknown"
def append_history(entry: dict[str, Any], *, code_ref: str | None = None) -> None:
"""
Append one line to benchmark_results/history.jsonl -- a local-only,
append-only, cross-session record of every `benchmark run`/`profile`
invocation. Unlike a single overwritten snapshot file, this survives
across sessions so a benchmarking effort picked back up days later has
a full timeline instead of only the most recent result.
"""
RESULTS_DIR.mkdir(exist_ok=True)
record = {
"timestamp": datetime.now(UTC).isoformat(),
"code_ref": code_ref or _current_git_ref(),
**entry,
}
with (RESULTS_DIR / "history.jsonl").open("a") as f:
f.write(json.dumps(record) + "\n")
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# src/paperless_benchmark/scenarios.py
from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Any
if TYPE_CHECKING:
from collections.abc import Callable
from django.contrib.auth.models import User
from django.db.models import QuerySet
@dataclass(frozen=True, slots=True)
class Scenario:
name: str
describe: str
run: Callable[[User], Any]
queryset_for_explain: Callable[[User], QuerySet] | None = None
_SCENARIOS: dict[str, Scenario] = {}
def register(scenario: Scenario) -> None:
_SCENARIOS[scenario.name] = scenario
def get(name: str) -> Scenario:
from django.core.management.base import CommandError
try:
return _SCENARIOS[name]
except KeyError:
available = ", ".join(sorted(_SCENARIOS)) or "(none registered)"
raise CommandError(
f"Unknown benchmark scenario {name!r}. Available: {available}",
) from None
def all_scenarios() -> tuple[Scenario, ...]:
return tuple(_SCENARIOS.values())
def _guardian_visibility_query_run(user: User) -> list[int]:
from documents.models import Document
from documents.permissions import get_objects_for_user_owner_aware
return list(
get_objects_for_user_owner_aware(
user,
"documents.view_document",
Document,
).values_list("id", flat=True),
)
def _guardian_visibility_query_queryset(user: User) -> QuerySet:
from documents.models import Document
from documents.permissions import get_objects_for_user_owner_aware
return get_objects_for_user_owner_aware(user, "documents.view_document", Document)
register(
Scenario(
name="guardian_visibility_query",
describe=(
"Document-visibility queryset for a user with mixed owned/shared "
"documents -- exercises documents.permissions."
"get_objects_for_user_owner_aware's guardian permission join."
),
run=_guardian_visibility_query_run,
queryset_for_explain=_guardian_visibility_query_queryset,
),
)
def _permitted_document_ids_run(user: User) -> list[int]:
from documents.models import Document
from documents.permissions import permitted_document_ids
return list(
Document.objects.filter(id__in=permitted_document_ids(user)).values_list(
"id",
flat=True,
),
)
def _permitted_document_ids_queryset(user: User) -> QuerySet:
from documents.models import Document
from documents.permissions import permitted_document_ids
return Document.objects.filter(id__in=permitted_document_ids(user))
register(
Scenario(
name="permitted_document_ids",
describe=(
"Document-visibility query built from documents.permissions."
"permitted_document_ids -- the resolved-ID-set alternative to "
"guardian_visibility_query, for side-by-side comparison."
),
run=_permitted_document_ids_run,
queryset_for_explain=_permitted_document_ids_queryset,
),
)
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# src/paperless_benchmark/seeding.py
from __future__ import annotations
import datetime
import random
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Literal
if TYPE_CHECKING:
from django.contrib.auth.models import Group
from django.contrib.auth.models import User
Tier = Literal["home", "medium", "large"]
CHUNK_SIZE = 5_000
MIME_TYPES = (
"application/pdf",
"image/png",
"image/jpeg",
"text/plain",
)
# Ownership split for documents, mirroring the shape used in the #11950
# perf-benchmark dataset (owned-by-target / owned-by-other / unowned).
OWNED_BY_TARGET_FRACTION = 0.60
OWNED_BY_OTHER_FRACTION = 0.30
# remainder (0.10) is unowned
# Of documents owned by "other" users, the fraction explicitly shared
# (view, or view+change) with perf_target via guardian permissions --
# this is what exercises the get_user_can_change() per-row N+1 that the
# `run` endpoint benchmarks measure.
SHARED_WITH_TARGET_FRACTION = 0.5
SHARED_WITH_CHANGE_FRACTION = 0.5
# Guardian permission-row ratios measured from a real install (discussion
# #13276): 1,414 user-perm rows / 27,232 group-perm rows over 12,000
# documents. Layered across ALL owned documents for the general user/group
# pool (not just perf_target's shares), so `profile` scenarios exercise a
# realistic permission-join shape for arbitrary users, not only perf_target.
USER_PERM_ROWS_PER_DOC = 1_414 / 12_000
GROUP_PERM_ROWS_PER_DOC = 27_232 / 12_000
@dataclass(frozen=True, slots=True)
class _TierCounts:
documents: int
tags: int
correspondents: int
document_types: int
storage_paths: int
other_users: int
groups: int
tags_per_doc: tuple[int, int]
TIERS: dict[Tier, _TierCounts] = {
"home": _TierCounts(
documents=500,
tags=20,
correspondents=10,
document_types=8,
storage_paths=5,
other_users=3,
groups=2,
tags_per_doc=(1, 3),
),
"medium": _TierCounts(
documents=20_000,
tags=100,
correspondents=300,
document_types=50,
storage_paths=20,
other_users=10,
groups=5,
tags_per_doc=(2, 6),
),
"large": _TierCounts(
documents=360_000,
tags=1_000,
correspondents=5_000,
document_types=300,
storage_paths=50,
other_users=25,
groups=10,
tags_per_doc=(3, 7),
),
}
def log(msg: str) -> None:
print(f"[{time.strftime('%H:%M:%S')}] {msg}", flush=True) # noqa: T201
@dataclass(frozen=True, slots=True)
class SeededData:
"""
Summary of a completed seed run. `documents`/`tags`/`correspondents`/
`document_types`/`storage_paths` are counts, not the seeded ORM
instances: at the `large` tier (360,000 documents) holding every
instance in memory simultaneously is a real risk for zero benefit, since
no caller consumes anything but the counts. `perf_target`/`perf_admin`/
`users`/`groups` stay as real objects -- at most ~26 users/12 groups even
at `large` tier, and small enough to be useful to a future caller.
"""
perf_target: User
perf_admin: User
users: tuple[User, ...]
groups: tuple[Group, ...]
documents: int
tags: int
correspondents: int
document_types: int
storage_paths: int
def _grant_model_level_permissions(user: User) -> None:
"""
Grant perf_target Django model-level view/add/change permissions on
Document and Tag, on top of the per-object guardian grants seeding
creates elsewhere. DRF's PaperlessObjectPermissions checks model-level
permissions before guardian's object-level ones are ever consulted, so
without this perf_target gets a blanket 403 on /api/documents/ and
/api/tags/ regardless of which documents guardian says it can see.
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from documents.models import Document
from documents.models import Tag
for model in (Document, Tag):
content_type = ContentType.objects.get_for_model(model)
codenames = [
f"{action}_{model._meta.model_name}" for action in ("view", "add", "change")
]
perms = Permission.objects.filter(
content_type=content_type,
codename__in=codenames,
)
user.user_permissions.add(*perms)
def _create_users_and_groups(
counts: _TierCounts,
) -> tuple[User, User, tuple[User, ...], tuple[Group, ...]]:
from django.contrib.auth.models import Group
from documents.tests.factories import UserFactory
perf_target = UserFactory.create(username="perf_target")
_grant_model_level_permissions(perf_target)
perf_admin = UserFactory.create(username="perf_admin", superuser=True)
other_users = tuple(UserFactory.create_batch(counts.other_users))
groups = tuple(
Group.objects.create(name=f"benchmark_group_{i}") for i in range(counts.groups)
)
log(
f"Created users: 1 target, 1 superuser, {len(other_users)} other, "
f"{len(groups)} groups.",
)
return perf_target, perf_admin, other_users, groups
def _create_lookup_tables(counts: _TierCounts):
from documents.models import Correspondent
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
from documents.tests.factories import CorrespondentFactory
from documents.tests.factories import DocumentTypeFactory
from documents.tests.factories import StoragePathFactory
from documents.tests.factories import TagFactory
tags = tuple(Tag.objects.bulk_create(TagFactory.build_batch(counts.tags)))
correspondents = tuple(
Correspondent.objects.bulk_create(
CorrespondentFactory.build_batch(counts.correspondents),
),
)
document_types = tuple(
DocumentType.objects.bulk_create(
DocumentTypeFactory.build_batch(counts.document_types),
),
)
storage_paths = tuple(
StoragePath.objects.bulk_create(
StoragePathFactory.build_batch(counts.storage_paths),
),
)
log(
f"Created {len(tags)} tags, {len(correspondents)} correspondents, "
f"{len(document_types)} document types, {len(storage_paths)} storage paths.",
)
return tags, correspondents, document_types, storage_paths
def _assign_owner(rng: random.Random, perf_target: User, other_users: tuple[User, ...]):
roll = rng.random()
if roll < OWNED_BY_TARGET_FRACTION:
return perf_target, "target"
if roll < OWNED_BY_TARGET_FRACTION + OWNED_BY_OTHER_FRACTION:
return rng.choice(other_users), "other"
return None, "unowned"
def _seed_documents(
rng: random.Random,
counts: _TierCounts,
tags,
correspondents,
document_types,
storage_paths,
perf_target,
other_users,
) -> tuple[int, list[int]]:
"""
Bulk-create `counts.documents` documents in chunks. Returns the total
document count plus a lightweight list of pks for documents that ended
up with an owner (target or other) -- that's all
`_grant_general_permissions` needs to sample from, so full `Document`
instances aren't accumulated across chunks (a real memory concern at the
`large` tier's 360,000 documents).
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from guardian.models import UserObjectPermission
from documents.models import Document
from documents.tests.factories import DocumentFactory
tag_ids = [t.pk for t in tags]
correspondent_ids = [c.pk for c in correspondents]
document_type_ids = [d.pk for d in document_types]
storage_path_ids = [s.pk for s in storage_paths]
doc_content_type = ContentType.objects.get_for_model(Document)
view_perm = Permission.objects.get(
codename="view_document",
content_type=doc_content_type,
)
change_perm = Permission.objects.get(
codename="change_document",
content_type=doc_content_type,
)
through_model = Document.tags.through
document_count = 0
owned_document_pks: list[int] = []
remaining = counts.documents
while remaining > 0:
chunk_n = min(CHUNK_SIZE, remaining)
remaining -= chunk_n
batch = []
owner_buckets = []
for _ in range(chunk_n):
doc = DocumentFactory.build(
mime_type=rng.choice(MIME_TYPES),
page_count=rng.randint(1, 30),
correspondent_id=(
rng.choice(correspondent_ids)
if correspondent_ids and rng.random() < 0.8
else None
),
document_type_id=(
rng.choice(document_type_ids)
if document_type_ids and rng.random() < 0.6
else None
),
storage_path_id=(
rng.choice(storage_path_ids)
if storage_path_ids and rng.random() < 0.8
else None
),
# Document.created is a plain DateField (default: today).
# Leaving it unset would give every seeded document the same
# date, collapsing Document's ("-created",) ordering index
# into a single-valued sort key -- spread it over a
# realistic multi-year window instead.
created=datetime.date.today()
- datetime.timedelta(days=rng.randint(0, 365 * 3)),
)
owner, bucket = _assign_owner(rng, perf_target, other_users)
doc.owner_id = owner.pk if owner else None
batch.append(doc)
owner_buckets.append(bucket)
created = Document.objects.bulk_create(batch, batch_size=CHUNK_SIZE)
through_rows = []
for doc in created:
k = rng.randint(*counts.tags_per_doc)
for tag_id in rng.sample(tag_ids, min(k, len(tag_ids))):
through_rows.append(through_model(document_id=doc.pk, tag_id=tag_id))
if through_rows:
through_model.objects.bulk_create(through_rows, batch_size=CHUNK_SIZE)
perm_rows = []
for doc, bucket in zip(created, owner_buckets, strict=True):
if bucket == "unowned":
continue
owned_document_pks.append(doc.pk)
if bucket != "other":
continue
if rng.random() >= SHARED_WITH_TARGET_FRACTION:
continue
perm_rows.append(
UserObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(doc.pk),
user=perf_target,
),
)
if rng.random() < SHARED_WITH_CHANGE_FRACTION:
perm_rows.append(
UserObjectPermission(
permission=change_perm,
content_type=doc_content_type,
object_pk=str(doc.pk),
user=perf_target,
),
)
if perm_rows:
UserObjectPermission.objects.bulk_create(perm_rows, batch_size=CHUNK_SIZE)
document_count += len(created)
log(f" {document_count}/{counts.documents} documents seeded")
return document_count, owned_document_pks
def _grant_general_permissions(
rng: random.Random,
owned_document_pks: list[int],
users,
groups,
) -> None:
"""
Layer realistic (issue #13276-derived) guardian permission-row ratios
across owned documents for the general user/group pool, so `profile`
scenarios exercise the same permission-join shape regardless of which
user they check visibility for (not just perf_target).
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from guardian.models import GroupObjectPermission
from guardian.models import UserObjectPermission
from documents.models import Document
if not owned_document_pks or not users:
return
doc_content_type = ContentType.objects.get_for_model(Document)
view_perm = Permission.objects.get(
codename="view_document",
content_type=doc_content_type,
)
n_user_perms = round(len(owned_document_pks) * USER_PERM_ROWS_PER_DOC)
n_group_perms = (
round(len(owned_document_pks) * GROUP_PERM_ROWS_PER_DOC) if groups else 0
)
user_rows = [
UserObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(rng.choice(owned_document_pks)),
user=rng.choice(users),
)
for _ in range(n_user_perms)
]
if user_rows:
UserObjectPermission.objects.bulk_create(
user_rows,
batch_size=CHUNK_SIZE,
ignore_conflicts=True,
)
group_rows = [
GroupObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(rng.choice(owned_document_pks)),
group=rng.choice(groups),
)
for _ in range(n_group_perms)
]
if group_rows:
GroupObjectPermission.objects.bulk_create(
group_rows,
batch_size=CHUNK_SIZE,
ignore_conflicts=True,
)
log(f" Granted {len(user_rows)} user perms, {len(group_rows)} group perms.")
def seed_benchmark_dataset(tier: Tier, *, seed: int = 42) -> SeededData:
"""
Build a benchmark dataset at the given scale tier: a named perf_target
(mixed owned/shared documents) and perf_admin (superuser) for endpoint
benchmarking, plus a general user/group pool with realistic guardian
permission-row ratios for profile scenarios.
"""
counts = TIERS[tier]
rng = random.Random(seed)
log(f"Seeding tier={tier!r}")
perf_target, perf_admin, other_users, groups = _create_users_and_groups(counts)
tags, correspondents, document_types, storage_paths = _create_lookup_tables(counts)
document_count, owned_document_pks = _seed_documents(
rng,
counts,
tags,
correspondents,
document_types,
storage_paths,
perf_target,
other_users,
)
all_users = (perf_target, *other_users)
_grant_general_permissions(rng, owned_document_pks, all_users, groups)
log(f"Done. {document_count} documents seeded for tier={tier!r}.")
return SeededData(
perf_target=perf_target,
perf_admin=perf_admin,
users=all_users,
groups=groups,
documents=document_count,
tags=len(tags),
correspondents=len(correspondents),
document_types=len(document_types),
storage_paths=len(storage_paths),
)