mirror of
https://github.com/paperless-ngx/paperless-ngx.git
synced 2026-07-28 23:04:56 +00:00
Compare commits
6
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 GitHub Actions
|
09c9fa03cf | ||
  shamoonandGitHub
|
04779d72bb | ||
 Trenton HandGitHub
|
1b32b9d678 | ||
|
Trenton HandGitHub
|
12d318deff | ||
  |
9c98f30d3f | ||
|
shamoonandGitHub
|
6a1d7b1bca |
@@ -1,12 +0,0 @@
|
||||
#!/command/with-contenv /usr/bin/bash
|
||||
# shellcheck shell=bash
|
||||
|
||||
declare -r log_prefix="[init-llmindex-migrate]"
|
||||
|
||||
echo "${log_prefix} Checking LLM index schema..."
|
||||
cd "${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
|
||||
@@ -1 +0,0 @@
|
||||
oneshot
|
||||
@@ -1 +0,0 @@
|
||||
/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/run
|
||||
+1
-20
@@ -212,16 +212,6 @@ following:
|
||||
This is a no-op if the index is already up to date, so it is safe to
|
||||
run on every upgrade.
|
||||
|
||||
5. Apply any pending LLM index schema migrations.
|
||||
|
||||
```shell-session
|
||||
cd src
|
||||
python3 manage.py document_llmindex migrate
|
||||
```
|
||||
|
||||
This is a no-op if the index is already up to date, or if the LLM index
|
||||
is disabled, 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
|
||||
@@ -542,7 +532,7 @@ index is updated automatically on the schedule set by
|
||||
can manage it manually:
|
||||
|
||||
```
|
||||
document_llmindex {rebuild,update,compact,migrate}
|
||||
document_llmindex {rebuild,update,compact}
|
||||
```
|
||||
|
||||
Specify `rebuild` to build the index from scratch from all documents in the database. Use
|
||||
@@ -554,15 +544,6 @@ scheduled task runs.
|
||||
|
||||
Specify `compact` to reclaim space and optimize the on-disk vector store.
|
||||
|
||||
Specify `migrate` to apply any pending index schema migrations without a full reindex.
|
||||
This is a no-op if the index is already up to date, so it is safe to run on every
|
||||
startup or upgrade; the container's startup sequence runs it automatically, and the
|
||||
[bare-metal upgrade steps](#bare-metal-updating) include it as a manual step. If a
|
||||
pending migration would require re-embedding every document, `migrate` only logs a
|
||||
warning and leaves the index as-is -- re-embedding can be slow and, for a metered
|
||||
embedding backend, cost money, so it is never triggered automatically. Run `rebuild`
|
||||
yourself when you are ready.
|
||||
|
||||
!!! note
|
||||
|
||||
These commands have no effect unless AI is enabled and an embedding backend is
|
||||
|
||||
@@ -620,6 +620,34 @@ no other workflow will be executed on the document.
|
||||
If a "Move to Trash" action is executed in a consume pipeline, the consumption
|
||||
will be aborted and the file will be deleted.
|
||||
|
||||
##### Password Removal {#workflow-action-password-removal}
|
||||
|
||||
"Password Removal" actions attempt to remove password protection from encrypted PDF documents. You can specify:
|
||||
|
||||
- One or more passwords to try, separated by commas or new lines
|
||||
- Each password is tried in order until one successfully unlocks the document
|
||||
|
||||
Password removal never modifies a file in place. Instead, once a working password is found, the
|
||||
decrypted content is consumed as a new [document version](#document-file-versions), leaving the
|
||||
original (still encrypted) version in the document's version history.
|
||||
|
||||
**Consumption Started**: because this trigger fires before the document exists yet, the password
|
||||
removal itself is deferred until after the initial consumption of the encrypted file has completed.
|
||||
OCR engines cannot process an encrypted PDF, so this first version is typically stored with no
|
||||
extracted text (unless the file already contained extractable text outside of OCR). Immediately
|
||||
afterwards, the password is removed and the decrypted file is automatically re-consumed as a second,
|
||||
new version of the same document, this time with normal OCR/text extraction applied. In other words,
|
||||
a password-protected file added with this trigger will briefly exist as an un-OCR'd version before
|
||||
the properly processed version is created.
|
||||
|
||||
**Document Added**, **Document Updated**, **Scheduled**: these triggers run against a document that
|
||||
already exists, so password removal happens immediately: the decrypted content is queued for
|
||||
consumption as a new version right away. Note that if the document's initial consumption also
|
||||
happened while it was still encrypted, that original version will likewise be missing OCR text.
|
||||
|
||||
**Current limitation**: Passwords are stored as a simple list without descriptions. To handle
|
||||
multiple PDF types with different passwords, create separate workflows for each use case.
|
||||
|
||||
#### Workflow placeholders
|
||||
|
||||
Titles and webhook payloads can be generated by workflows using [Jinja templates](https://jinja.palletsprojects.com/en/3.1.x/templates/).
|
||||
|
||||
+35
-35
@@ -659,7 +659,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">445</context>
|
||||
<context context-type="linenumber">449</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/bulk-editor/custom-fields-bulk-edit-dialog/custom-fields-bulk-edit-dialog.component.html</context>
|
||||
@@ -831,7 +831,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">464</context>
|
||||
<context context-type="linenumber">468</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/document-list.component.html</context>
|
||||
@@ -1355,7 +1355,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">390</context>
|
||||
<context context-type="linenumber">394</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/bulk-editor/bulk-editor.component.html</context>
|
||||
@@ -1596,7 +1596,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">165</context>
|
||||
<context context-type="linenumber">169</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="2691296884221415710" datatype="html">
|
||||
@@ -1607,7 +1607,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">170</context>
|
||||
<context context-type="linenumber">174</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/bulk-editor/bulk-editor.component.html</context>
|
||||
@@ -1638,7 +1638,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">174</context>
|
||||
<context context-type="linenumber">178</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/bulk-editor/bulk-editor.component.html</context>
|
||||
@@ -1669,7 +1669,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">178</context>
|
||||
<context context-type="linenumber">182</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/bulk-editor/bulk-editor.component.html</context>
|
||||
@@ -4914,7 +4914,7 @@
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">356</context>
|
||||
<context context-type="linenumber">360</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="8057014866157903311" datatype="html">
|
||||
@@ -7760,14 +7760,14 @@
|
||||
<source>Details</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">160</context>
|
||||
<context context-type="linenumber">164</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="5701618810648052610" datatype="html">
|
||||
<source>Title</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">163</context>
|
||||
<context context-type="linenumber">167</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-list/document-list.component.html</context>
|
||||
@@ -7790,14 +7790,14 @@
|
||||
<source>Date created</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">167</context>
|
||||
<context context-type="linenumber">171</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="5607669932062416162" datatype="html">
|
||||
<source>Default</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">179</context>
|
||||
<context context-type="linenumber">183</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/manage/saved-views/saved-views.component.html</context>
|
||||
@@ -7808,14 +7808,14 @@
|
||||
<source>Content</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">286</context>
|
||||
<context context-type="linenumber">290</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="218403386307979629" datatype="html">
|
||||
<source>Metadata</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">295</context>
|
||||
<context context-type="linenumber">299</context>
|
||||
</context-group>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/metadata-collapse/metadata-collapse.component.ts</context>
|
||||
@@ -7826,147 +7826,147 @@
|
||||
<source>Date modified</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">302</context>
|
||||
<context context-type="linenumber">306</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="6392918669949841614" datatype="html">
|
||||
<source>Date added</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">306</context>
|
||||
<context context-type="linenumber">310</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="146828917013192897" datatype="html">
|
||||
<source>Media filename</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">310</context>
|
||||
<context context-type="linenumber">314</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="4500855521601039868" datatype="html">
|
||||
<source>Original filename</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">314</context>
|
||||
<context context-type="linenumber">318</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="2659735245739197634" datatype="html">
|
||||
<source>Original SHA256 checksum</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">318</context>
|
||||
<context context-type="linenumber">322</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="5888243105821763422" datatype="html">
|
||||
<source>Original file size</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">322</context>
|
||||
<context context-type="linenumber">326</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="2696647325713149563" datatype="html">
|
||||
<source>Original mime type</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">326</context>
|
||||
<context context-type="linenumber">330</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="6714358112223607756" datatype="html">
|
||||
<source>Archive SHA256 checksum</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">331</context>
|
||||
<context context-type="linenumber">335</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="6033581412811562084" datatype="html">
|
||||
<source>Archive file size</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">337</context>
|
||||
<context context-type="linenumber">341</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="6992781481378431874" datatype="html">
|
||||
<source>Original document metadata</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">346</context>
|
||||
<context context-type="linenumber">350</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="2846565152091361585" datatype="html">
|
||||
<source>Archived document metadata</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">349</context>
|
||||
<context context-type="linenumber">353</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="7206723502037428235" datatype="html">
|
||||
<source>Notes <x id="START_BLOCK_IF" equiv-text="@if (document()?.notes.length) {"/><x id="START_TAG_SPAN" ctype="x-span" equiv-text="<span class="badge text-bg-secondary ms-1">"/><x id="INTERPOLATION" equiv-text="length}}"/><x id="CLOSE_TAG_SPAN" ctype="x-span"/><x id="CLOSE_BLOCK_IF" equiv-text="}"/></source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">368,371</context>
|
||||
<context context-type="linenumber">372,375</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="186236568870281953" datatype="html">
|
||||
<source>History</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">379</context>
|
||||
<context context-type="linenumber">383</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="8236092845697214347" datatype="html">
|
||||
<source> Duplicates <x id="START_TAG_SPAN" ctype="x-span" equiv-text="<span class="badge text-bg-secondary ms-1">"/><x id="INTERPOLATION" equiv-text="cate_documents.length }}"/><x id="CLOSE_TAG_SPAN" ctype="x-span"/></source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">401,405</context>
|
||||
<context context-type="linenumber">405,409</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="6449374629822973702" datatype="html">
|
||||
<source>Duplicate documents detected:</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">407</context>
|
||||
<context context-type="linenumber">411</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="14058600336670816" datatype="html">
|
||||
<source>In trash</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">418</context>
|
||||
<context context-type="linenumber">422</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="5129524307369213584" datatype="html">
|
||||
<source>Save & next</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">447</context>
|
||||
<context context-type="linenumber">451</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="4910102545766233758" datatype="html">
|
||||
<source>Save & close</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">449</context>
|
||||
<context context-type="linenumber">453</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="3823219296477075982" datatype="html">
|
||||
<source>Discard</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">451</context>
|
||||
<context context-type="linenumber">455</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="1309556917227148591" datatype="html">
|
||||
<source>Document loading...</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">459</context>
|
||||
<context context-type="linenumber">463</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="8191371354890763172" datatype="html">
|
||||
<source>Enter Password</source>
|
||||
<context-group purpose="location">
|
||||
<context context-type="sourcefile">src/app/components/document-detail/document-detail.component.html</context>
|
||||
<context context-type="linenumber">513</context>
|
||||
<context context-type="linenumber">517</context>
|
||||
</context-group>
|
||||
</trans-unit>
|
||||
<trans-unit id="5758784066858623886" datatype="html">
|
||||
|
||||
@@ -113,8 +113,8 @@
|
||||
|
||||
<form [formGroup]='documentForm' (ngSubmit)="save()">
|
||||
|
||||
<div class="btn-toolbar mb-1 border-bottom">
|
||||
<div class="btn-group pb-3">
|
||||
<div class="btn-toolbar justify-content-end mb-1 pb-3 gap-2 row-gap-2 border-bottom">
|
||||
<div class="btn-group me-auto">
|
||||
<button type="button" class="btn btn-sm btn-outline-secondary" i18n-title title="Close" (click)="close()">
|
||||
<i-bs width="1.2em" height="1.2em" name="x"></i-bs>
|
||||
</button>
|
||||
@@ -127,32 +127,36 @@
|
||||
</div>
|
||||
|
||||
<ng-container *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.Document }">
|
||||
<div class="btn-group pb-3 ms-auto">
|
||||
<pngx-suggestions-dropdown *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.Document }"
|
||||
[disabled]="!userCanEdit || suggestionsLoading()"
|
||||
[loading]="suggestionsLoading()"
|
||||
[suggestions]="suggestions()"
|
||||
[aiEnabled]="aiEnabled"
|
||||
(getSuggestions)="getSuggestions()"
|
||||
(addTag)="createTag($event)"
|
||||
(addDocumentType)="createDocumentType($event)"
|
||||
(addCorrespondent)="createCorrespondent($event)">
|
||||
</pngx-suggestions-dropdown>
|
||||
<div class="d-flex gap-2">
|
||||
<div class="btn-group">
|
||||
<pngx-suggestions-dropdown *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.Document }"
|
||||
[disabled]="!userCanEdit || suggestionsLoading()"
|
||||
[loading]="suggestionsLoading()"
|
||||
[suggestions]="suggestions()"
|
||||
[aiEnabled]="aiEnabled"
|
||||
(getSuggestions)="getSuggestions()"
|
||||
(addTag)="createTag($event)"
|
||||
(addDocumentType)="createDocumentType($event)"
|
||||
(addCorrespondent)="createCorrespondent($event)">
|
||||
</pngx-suggestions-dropdown>
|
||||
</div>
|
||||
|
||||
<div class="btn-group">
|
||||
<pngx-custom-fields-dropdown
|
||||
*pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.CustomField }"
|
||||
[documentId]="documentId()"
|
||||
[disabled]="!userCanEdit"
|
||||
[existingFields]="document()?.custom_fields"
|
||||
(created)="refreshCustomFields()"
|
||||
(added)="addField($event)">
|
||||
</pngx-custom-fields-dropdown>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="btn-group pb-3 ms-2">
|
||||
<pngx-custom-fields-dropdown
|
||||
*pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.CustomField }"
|
||||
[documentId]="documentId()"
|
||||
[disabled]="!userCanEdit"
|
||||
[existingFields]="document()?.custom_fields"
|
||||
(created)="refreshCustomFields()"
|
||||
(added)="addField($event)">
|
||||
</pngx-custom-fields-dropdown>
|
||||
<div class="ps-3">
|
||||
<ng-container *ngTemplateOutlet="saveButtons"></ng-container>
|
||||
</div>
|
||||
</ng-container>
|
||||
|
||||
<ng-container *ngTemplateOutlet="saveButtons"></ng-container>
|
||||
</div>
|
||||
|
||||
<ul ngbNav #nav="ngbNav" class="nav-underline flex-nowrap flex-md-wrap overflow-auto" (navChange)="onNavChange($event)" [activeId]="activeNavID()" (activeIdChange)="activeNavID.set($event)">
|
||||
@@ -276,7 +280,7 @@
|
||||
}
|
||||
</div>
|
||||
|
||||
<div class="d-flex border-top pt-3">
|
||||
<div class="d-flex justify-content-end border-top pt-3">
|
||||
<ng-container *ngTemplateOutlet="saveButtons"></ng-container>
|
||||
</div>
|
||||
</ng-template>
|
||||
@@ -440,7 +444,7 @@
|
||||
</div>
|
||||
|
||||
<ng-template #saveButtons>
|
||||
<div class="btn-group pb-3 ms-4">
|
||||
<div class="btn-group">
|
||||
<ng-container *pngxIfPermissions="{ action: PermissionAction.Change, type: PermissionType.Document }">
|
||||
<button type="submit" class="order-3 btn btn-sm btn-primary" i18n [disabled]="!userCanEdit || networkActive() || (isDirty$ | async) !== true">Save</button>
|
||||
@if (hasNext()) {
|
||||
|
||||
@@ -3,7 +3,6 @@ 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):
|
||||
@@ -14,18 +13,12 @@ class Command(PaperlessCommand):
|
||||
|
||||
def add_arguments(self, parser: Any) -> None:
|
||||
super().add_arguments(parser)
|
||||
parser.add_argument(
|
||||
"command",
|
||||
choices=["rebuild", "update", "compact", "migrate"],
|
||||
)
|
||||
parser.add_argument("command", choices=["rebuild", "update", "compact"])
|
||||
|
||||
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(
|
||||
|
||||
@@ -43,8 +43,16 @@ def _fmt(dt: datetime) -> str:
|
||||
|
||||
|
||||
def _iso_range(lo: datetime, hi: datetime) -> str:
|
||||
"""Format a [lo TO hi] range string in ISO 8601 for Tantivy query syntax."""
|
||||
return f"[{_fmt(lo)} TO {_fmt(hi)}]"
|
||||
"""
|
||||
Format a half-open ``[lo TO hi)`` range in ISO 8601 for Tantivy query syntax.
|
||||
|
||||
``hi`` is always the exclusive ceiling of a computed period (the start of
|
||||
the *next* day/week/month/quarter/year), so the closing bracket must be
|
||||
the Tantivy exclusive-range brace ``}`` rather than ``]`` — otherwise the
|
||||
first instant of the following period (e.g. the 1st of next month) is
|
||||
incorrectly included in the match.
|
||||
"""
|
||||
return f"[{_fmt(lo)} TO {_fmt(hi)}}}"
|
||||
|
||||
|
||||
def _quarter_start(d: date) -> date:
|
||||
|
||||
@@ -566,6 +566,17 @@ def translate_range(field: str, lo: str, hi: str, tz: tzinfo) -> str:
|
||||
lo_pair, hi_pair = hi_pair, lo_pair
|
||||
|
||||
lo_iso = _fmt(lo_pair[0]) if lo_pair is not None else OPEN_LO
|
||||
hi_iso = _fmt(hi_pair[1]) if hi_pair is not None else OPEN_HI
|
||||
|
||||
return f"{field}:[{lo_iso} TO {hi_iso}]"
|
||||
# A bound resolves to (floor, ceil) where floor == ceil for an exact instant
|
||||
# (a full ISO datetime, "now", or a "+/-N unit" offset) and floor != ceil for
|
||||
# a coarser period token (year/month/day precision). Only the latter needs a
|
||||
# half-open close: its ceil is the start of the *next* period and must be
|
||||
# excluded, or that instant (e.g. the 1st of next month) wrongly matches.
|
||||
if hi_pair is not None:
|
||||
hi_iso = _fmt(hi_pair[1])
|
||||
hi_close = "]" if hi_pair[0] == hi_pair[1] else "}"
|
||||
else:
|
||||
hi_iso = OPEN_HI
|
||||
hi_close = "]"
|
||||
|
||||
return f"{field}:[{lo_iso} TO {hi_iso}{hi_close}"
|
||||
|
||||
@@ -1134,6 +1134,11 @@ def before_task_publish_handler(
|
||||
return
|
||||
|
||||
try:
|
||||
# Close stale connections without disrupting a transaction publishing a task
|
||||
for connection in connections.all(initialized_only=True):
|
||||
if not connection.in_atomic_block:
|
||||
connection.close_if_unusable_or_obsolete()
|
||||
|
||||
_, task_kwargs, _ = body
|
||||
task_id = headers["id"]
|
||||
|
||||
|
||||
@@ -8,7 +8,6 @@ if TYPE_CHECKING:
|
||||
from pytest_mock import MockerFixture
|
||||
|
||||
_COMPACT = "documents.management.commands.document_llmindex.llm_index_compact"
|
||||
_MIGRATE = "documents.management.commands.document_llmindex.llm_index_migrate"
|
||||
_INDEX = "documents.management.commands.document_llmindex.llmindex_index"
|
||||
|
||||
|
||||
@@ -18,11 +17,6 @@ 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,
|
||||
|
||||
@@ -32,7 +32,9 @@ AUCKLAND = ZoneInfo("Pacific/Auckland") # UTC+13 in southern-hemisphere summer
|
||||
|
||||
|
||||
def _range(result: str, field: str) -> tuple[str, str]:
|
||||
m = re.search(rf"{field}:\[(.+?) TO (.+?)\]", result)
|
||||
# Half-open period ranges close with "}" (exclusive); exact-instant ranges
|
||||
# (full ISO datetimes, "now", relative offsets) close with "]" (inclusive).
|
||||
m = re.search(rf"{field}:\[(.+?) TO (.+?)[\]}}]", result)
|
||||
assert m, f"No range for {field!r} in: {result!r}"
|
||||
return m.group(1), m.group(2)
|
||||
|
||||
|
||||
@@ -214,27 +214,27 @@ class TestTranslateScalar:
|
||||
(
|
||||
"created",
|
||||
"2020",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"202003",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z]",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"20200115",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z]",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"2020-01-15",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z]",
|
||||
"created:[2020-01-15T00:00:00Z TO 2020-01-16T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"created",
|
||||
"2020-03",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z]",
|
||||
"created:[2020-03-01T00:00:00Z TO 2020-04-01T00:00:00Z}",
|
||||
),
|
||||
],
|
||||
)
|
||||
@@ -248,9 +248,9 @@ class TestTranslateScalar:
|
||||
assert exc_info.value.value == "202023"
|
||||
|
||||
def test_keyword_delegates(self) -> None:
|
||||
# keyword path produces a range; just assert it is a created range
|
||||
# keyword path produces a half-open range; just assert it is a created range
|
||||
out = translate_scalar("created", "today", UTC)
|
||||
assert out.startswith("created:[") and out.endswith("]")
|
||||
assert out.startswith("created:[") and out.endswith("}")
|
||||
|
||||
def test_14digit_compact_datetime(self) -> None:
|
||||
out = translate_scalar("created", "20240115120000", UTC)
|
||||
@@ -279,21 +279,21 @@ class TestTranslateRange:
|
||||
@pytest.mark.parametrize(
|
||||
("lo", "hi", "expected"),
|
||||
[
|
||||
("2005", "2009", "created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z]"),
|
||||
("2005", "2009", "created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z}"),
|
||||
(
|
||||
"202001",
|
||||
"202006",
|
||||
"created:[2020-01-01T00:00:00Z TO 2020-07-01T00:00:00Z]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2020-07-01T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"20200101",
|
||||
"20201231",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z}",
|
||||
),
|
||||
(
|
||||
"2020-01-01",
|
||||
"2020-12-31",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z}",
|
||||
),
|
||||
],
|
||||
)
|
||||
@@ -302,7 +302,7 @@ class TestTranslateRange:
|
||||
|
||||
def test_reversed_swaps(self):
|
||||
assert translate_range("created", "2009", "2005", UTC) == (
|
||||
"created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z]"
|
||||
"created:[2005-01-01T00:00:00Z TO 2010-01-01T00:00:00Z}"
|
||||
)
|
||||
|
||||
def test_open_upper(self):
|
||||
@@ -311,7 +311,7 @@ class TestTranslateRange:
|
||||
|
||||
def test_open_lower(self):
|
||||
out = translate_range("created", "", "2020", UTC)
|
||||
assert out == f"created:[{OPEN_LO} TO 2021-01-01T00:00:00Z]"
|
||||
assert out == f"created:[{OPEN_LO} TO 2021-01-01T00:00:00Z}}"
|
||||
|
||||
def test_invalid_bound_raises(self):
|
||||
with pytest.raises(InvalidDateQuery) as exc_info:
|
||||
@@ -334,16 +334,16 @@ class TestTranslateQuery:
|
||||
[
|
||||
(
|
||||
"created:2020",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z}",
|
||||
),
|
||||
("tag:foo,bar", "tag:foo AND tag:bar"),
|
||||
# 'type' is a user-facing alias rewritten to 'document_type' (the real schema field)
|
||||
("tag:foo,type:bar", "tag:foo AND document_type:bar"),
|
||||
(
|
||||
"created:[2020 TO 2021],added:[2022 TO 2023]",
|
||||
"created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z]"
|
||||
"created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z}"
|
||||
" AND "
|
||||
"added:[2022-01-01T00:00:00Z TO 2024-01-01T00:00:00Z]",
|
||||
"added:[2022-01-01T00:00:00Z TO 2024-01-01T00:00:00Z}",
|
||||
),
|
||||
# correspondent is not multi-value: comma stays literal inside the value
|
||||
("correspondent:foo,bar", "correspondent:foo,bar"),
|
||||
@@ -506,7 +506,7 @@ class TestOperatorNormalization:
|
||||
def test_date_range_preserved(self) -> None:
|
||||
out = translate_query("created:[2020 TO 2021]", UTC)
|
||||
# Must not corrupt the ISO range
|
||||
assert out == "created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z]"
|
||||
assert out == "created:[2020-01-01T00:00:00Z TO 2022-01-01T00:00:00Z}"
|
||||
|
||||
def test_date_scalar_with_or(self) -> None:
|
||||
out = translate_query("created:2020 OR foo", UTC)
|
||||
@@ -581,42 +581,42 @@ class TestKeywordDateResolution:
|
||||
[
|
||||
pytest.param(
|
||||
"today",
|
||||
"created:[2026-03-28T00:00:00Z TO 2026-03-29T00:00:00Z]",
|
||||
"created:[2026-03-28T00:00:00Z TO 2026-03-29T00:00:00Z}",
|
||||
id="today",
|
||||
),
|
||||
pytest.param(
|
||||
"yesterday",
|
||||
"created:[2026-03-27T00:00:00Z TO 2026-03-28T00:00:00Z]",
|
||||
"created:[2026-03-27T00:00:00Z TO 2026-03-28T00:00:00Z}",
|
||||
id="yesterday",
|
||||
),
|
||||
pytest.param(
|
||||
"previous week",
|
||||
"created:[2026-03-16T00:00:00Z TO 2026-03-23T00:00:00Z]",
|
||||
"created:[2026-03-16T00:00:00Z TO 2026-03-23T00:00:00Z}",
|
||||
id="previous-week",
|
||||
),
|
||||
pytest.param(
|
||||
"this month",
|
||||
"created:[2026-03-01T00:00:00Z TO 2026-04-01T00:00:00Z]",
|
||||
"created:[2026-03-01T00:00:00Z TO 2026-04-01T00:00:00Z}",
|
||||
id="this-month",
|
||||
),
|
||||
pytest.param(
|
||||
"previous month",
|
||||
"created:[2026-02-01T00:00:00Z TO 2026-03-01T00:00:00Z]",
|
||||
"created:[2026-02-01T00:00:00Z TO 2026-03-01T00:00:00Z}",
|
||||
id="previous-month",
|
||||
),
|
||||
pytest.param(
|
||||
"this year",
|
||||
"created:[2026-01-01T00:00:00Z TO 2027-01-01T00:00:00Z]",
|
||||
"created:[2026-01-01T00:00:00Z TO 2027-01-01T00:00:00Z}",
|
||||
id="this-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous year",
|
||||
"created:[2025-01-01T00:00:00Z TO 2026-01-01T00:00:00Z]",
|
||||
"created:[2025-01-01T00:00:00Z TO 2026-01-01T00:00:00Z}",
|
||||
id="previous-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous quarter",
|
||||
"created:[2025-10-01T00:00:00Z TO 2026-01-01T00:00:00Z]",
|
||||
"created:[2025-10-01T00:00:00Z TO 2026-01-01T00:00:00Z}",
|
||||
id="previous-quarter",
|
||||
),
|
||||
],
|
||||
@@ -637,42 +637,42 @@ class TestKeywordDateResolution:
|
||||
[
|
||||
pytest.param(
|
||||
"today",
|
||||
"added:[2026-03-27T15:00:00Z TO 2026-03-28T15:00:00Z]",
|
||||
"added:[2026-03-27T15:00:00Z TO 2026-03-28T15:00:00Z}",
|
||||
id="today",
|
||||
),
|
||||
pytest.param(
|
||||
"yesterday",
|
||||
"added:[2026-03-26T15:00:00Z TO 2026-03-27T15:00:00Z]",
|
||||
"added:[2026-03-26T15:00:00Z TO 2026-03-27T15:00:00Z}",
|
||||
id="yesterday",
|
||||
),
|
||||
pytest.param(
|
||||
"previous week",
|
||||
"added:[2026-03-15T15:00:00Z TO 2026-03-22T15:00:00Z]",
|
||||
"added:[2026-03-15T15:00:00Z TO 2026-03-22T15:00:00Z}",
|
||||
id="previous-week",
|
||||
),
|
||||
pytest.param(
|
||||
"this month",
|
||||
"added:[2026-02-28T15:00:00Z TO 2026-03-31T15:00:00Z]",
|
||||
"added:[2026-02-28T15:00:00Z TO 2026-03-31T15:00:00Z}",
|
||||
id="this-month",
|
||||
),
|
||||
pytest.param(
|
||||
"previous month",
|
||||
"added:[2026-01-31T15:00:00Z TO 2026-02-28T15:00:00Z]",
|
||||
"added:[2026-01-31T15:00:00Z TO 2026-02-28T15:00:00Z}",
|
||||
id="previous-month",
|
||||
),
|
||||
pytest.param(
|
||||
"this year",
|
||||
"added:[2025-12-31T15:00:00Z TO 2026-12-31T15:00:00Z]",
|
||||
"added:[2025-12-31T15:00:00Z TO 2026-12-31T15:00:00Z}",
|
||||
id="this-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous year",
|
||||
"added:[2024-12-31T15:00:00Z TO 2025-12-31T15:00:00Z]",
|
||||
"added:[2024-12-31T15:00:00Z TO 2025-12-31T15:00:00Z}",
|
||||
id="previous-year",
|
||||
),
|
||||
pytest.param(
|
||||
"previous quarter",
|
||||
"added:[2025-09-30T15:00:00Z TO 2025-12-31T15:00:00Z]",
|
||||
"added:[2025-09-30T15:00:00Z TO 2025-12-31T15:00:00Z}",
|
||||
id="previous-quarter",
|
||||
),
|
||||
],
|
||||
@@ -719,7 +719,7 @@ class TestISODatetimeBounds:
|
||||
def test_translate_query_text_before_comma_separated_date_clause(self) -> None:
|
||||
result = translate_query("schäfersee,created:previous year", UTC)
|
||||
assert result == (
|
||||
"schäfersee AND created:[2025-01-01T00:00:00Z TO 2026-01-01T00:00:00Z]"
|
||||
"schäfersee AND created:[2025-01-01T00:00:00Z TO 2026-01-01T00:00:00Z}"
|
||||
)
|
||||
|
||||
def test_invalid_iso_datetime_raises(self) -> None:
|
||||
|
||||
@@ -720,6 +720,48 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
|
||||
self.assertEqual(results[0]["id"], 3)
|
||||
self.assertEqual(results[0]["title"], "bank statement 3")
|
||||
|
||||
def test_search_added_previous_month_excludes_next_period_start(self) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- One document added at the last instant of last month
|
||||
- One document added exactly at the first instant of this month
|
||||
WHEN:
|
||||
- Query for documents added in the previous month
|
||||
THEN:
|
||||
- Only the document from last month is returned; the document dated
|
||||
exactly at the start of this month (the exclusive upper bound of
|
||||
the range) is not
|
||||
"""
|
||||
d1 = DocumentFactory.create(
|
||||
title="end of last month",
|
||||
content="last instant of last month",
|
||||
checksum="A",
|
||||
pk=1,
|
||||
added=timezone.make_aware(datetime.datetime(2024, 1, 31, 23, 59, 59)),
|
||||
)
|
||||
d2 = DocumentFactory.create(
|
||||
title="start of this month",
|
||||
content="first instant of this month",
|
||||
checksum="B",
|
||||
pk=2,
|
||||
added=timezone.make_aware(datetime.datetime(2024, 2, 1, 0, 0, 0)),
|
||||
)
|
||||
|
||||
backend = get_backend()
|
||||
backend.add_or_update(d1)
|
||||
backend.add_or_update(d2)
|
||||
|
||||
with time_machine.travel(
|
||||
timezone.make_aware(datetime.datetime(2024, 2, 15, 12, 0, 0)),
|
||||
tick=False,
|
||||
):
|
||||
response = self.client.get("/api/documents/?query=added:previous month")
|
||||
results = response.data["results"]
|
||||
|
||||
self.assertEqual(len(results), 1)
|
||||
self.assertEqual(results[0]["id"], 1)
|
||||
self.assertEqual(results[0]["title"], "end of last month")
|
||||
|
||||
def test_search_added_invalid_date(self) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
|
||||
@@ -56,6 +56,32 @@ def send_publish(
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestBeforeTaskPublishHandler:
|
||||
@mock.patch("documents.signals.handlers.connections.all")
|
||||
def test_closes_old_connections_outside_atomic_blocks(
|
||||
self,
|
||||
connections_all,
|
||||
) -> None:
|
||||
connection = mock.Mock(in_atomic_block=False)
|
||||
connections_all.return_value = [connection]
|
||||
|
||||
task_id = send_publish("documents.tasks.train_classifier", (), {})
|
||||
|
||||
connection.close_if_unusable_or_obsolete.assert_called_once_with()
|
||||
assert PaperlessTask.objects.filter(task_id=task_id).exists()
|
||||
|
||||
@mock.patch("documents.signals.handlers.connections.all")
|
||||
def test_keeps_connections_open_inside_atomic_blocks(
|
||||
self,
|
||||
connections_all,
|
||||
) -> None:
|
||||
connection = mock.Mock(in_atomic_block=True)
|
||||
connections_all.return_value = [connection]
|
||||
|
||||
task_id = send_publish("documents.tasks.train_classifier", (), {})
|
||||
|
||||
connection.close_if_unusable_or_obsolete.assert_not_called()
|
||||
assert PaperlessTask.objects.filter(task_id=task_id).exists()
|
||||
|
||||
def test_creates_task_for_consume_file(
|
||||
self,
|
||||
consume_input_doc,
|
||||
|
||||
@@ -144,24 +144,6 @@ 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.
|
||||
@@ -342,21 +324,6 @@ def _exclude_document_id_filter(document_id: int | str):
|
||||
)
|
||||
|
||||
|
||||
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 update_llm_index(
|
||||
*,
|
||||
iter_wrapper: IterWrapper[Document] = identity,
|
||||
@@ -372,7 +339,15 @@ def update_llm_index(
|
||||
happens, since a rebuild always covers the whole library regardless.
|
||||
"""
|
||||
with write_store() as store:
|
||||
needs_reembed = _check_and_run_migrations(store)
|
||||
try:
|
||||
with _exclude_readers():
|
||||
needs_reembed = store.check_and_run_migrations()
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index migration check: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
needs_reembed = False
|
||||
if needs_reembed:
|
||||
logger.warning(
|
||||
"LLM index migration requires re-embedding; forcing rebuild.",
|
||||
@@ -421,24 +396,12 @@ def update_llm_index(
|
||||
if document_ids is not None
|
||||
else documents
|
||||
)
|
||||
# When document_ids is given, the caller already knows exactly
|
||||
# which documents to reindex (e.g. a bulk edit) -- trust it and
|
||||
# skip the modified-time comparison entirely. Bulk edits (tags,
|
||||
# correspondent, document type, storage path, custom fields)
|
||||
# write via queryset.update()/M2M bulk operations, which bypass
|
||||
# Document.modified's auto_now, so comparing against
|
||||
# get_modified_times() here would silently skip reindexing
|
||||
# documents whose embedded metadata just changed. The comparison
|
||||
# is only meaningful for the unscoped, full-library scan, where
|
||||
# it avoids re-embedding documents that have not changed.
|
||||
existing = store.get_modified_times() if document_ids is None else None
|
||||
existing = store.get_modified_times()
|
||||
changed = 0
|
||||
for document in iter_wrapper(scoped_documents):
|
||||
doc_id = str(document.id)
|
||||
if existing is not None:
|
||||
stored_modified = existing.get(doc_id)
|
||||
if stored_modified == document.modified.isoformat():
|
||||
continue
|
||||
if existing.get(doc_id) == document.modified.isoformat():
|
||||
continue
|
||||
nodes = build_document_node(document, chunk_size=chunk_size)
|
||||
_embed_nodes(nodes, embed_model)
|
||||
store.upsert_document(doc_id, nodes)
|
||||
@@ -449,7 +412,14 @@ def update_llm_index(
|
||||
else "No changes detected in LLM index."
|
||||
)
|
||||
|
||||
_with_exclusive_access("compaction", store.compact)
|
||||
try:
|
||||
with _exclude_readers():
|
||||
store.compact()
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index compaction: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
return msg
|
||||
|
||||
|
||||
@@ -464,45 +434,25 @@ 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:
|
||||
_check_and_run_migrations(store)
|
||||
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:
|
||||
_with_exclusive_access("compaction", lambda: store.compact(force=True))
|
||||
try:
|
||||
with _exclude_readers():
|
||||
store.compact(force=True)
|
||||
except Timeout:
|
||||
logger.info(
|
||||
"Skipping LLM index compaction: index readers are active; "
|
||||
"will retry next run.",
|
||||
)
|
||||
|
||||
|
||||
def llm_index_remove_document(document: Document):
|
||||
"""Remove a document's chunks from the LLM index."""
|
||||
with write_store() as store:
|
||||
_check_and_run_migrations(store)
|
||||
store.delete(str(document.id))
|
||||
|
||||
|
||||
|
||||
@@ -1,58 +0,0 @@
|
||||
"""Schema migrations for the sqlite-vec vector store.
|
||||
|
||||
Each migration lives in its own module here, named ``mNNNN_description.py``
|
||||
(e.g. ``m0001_add_document_chunks.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()`` (most likely just a call to
|
||||
``PaperlessSqliteVecVectorStore._rebuild_into()``, see ``Migration`` below),
|
||||
and appends a ``Migration`` to ``MIGRATIONS``; then import that module at the
|
||||
bottom of ``vector_store.py`` and bump ``SCHEMA_VERSION`` there.
|
||||
"""
|
||||
|
||||
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 the vec0 table in ``dst_conn`` and copy ``src_conn``'s rows
|
||||
and index_meta into it -- usually just a call to
|
||||
``PaperlessSqliteVecVectorStore._rebuild_into(src_conn, dst_conn, dim)``.
|
||||
``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] = []
|
||||
@@ -1,95 +0,0 @@
|
||||
import sqlite3
|
||||
|
||||
from paperless_ai.migrations import MIGRATIONS
|
||||
from paperless_ai.migrations import Migration
|
||||
from paperless_ai.vector_store import COMPACT_BATCH_SIZE
|
||||
from paperless_ai.vector_store import DEFAULT_TABLE_NAME
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
|
||||
def _migrate_v1_to_v2_add_document_chunks(
|
||||
src_conn: sqlite3.Connection,
|
||||
dst_conn: sqlite3.Connection,
|
||||
dim: int,
|
||||
) -> None:
|
||||
"""v1 -> v2: backfill the document_chunks side table.
|
||||
|
||||
document_chunks (see PaperlessSqliteVecVectorStore._open_connection) lets
|
||||
delete()/upsert_document() find a document's chunk ids without a vec0
|
||||
full table scan on the document_id metadata column. Every row written
|
||||
before this migration predates that table, so without backfilling,
|
||||
deleting a pre-migration document would find zero chunk ids and leave its
|
||||
vec0 rows permanently orphaned.
|
||||
|
||||
Deliberately spells out its own v2-shaped vec0 table and row copy,
|
||||
rather than delegating to PaperlessSqliteVecVectorStore's
|
||||
_create_vec_table()/_rebuild_into()/_copy_rows(): those always reflect
|
||||
whatever the *current* schema is. If a later migration changes that
|
||||
schema (bumping SCHEMA_VERSION again), this migration must keep
|
||||
producing its own historical v2 shape regardless -- otherwise a user
|
||||
upgrading across multiple versions in one go (e.g. v1 straight to v4)
|
||||
would have this migration silently produce a v4-shaped table instead
|
||||
of v2, and the v2 -> v3 migration that runs right after it would find
|
||||
the columns it expects to migrate *from* already gone.
|
||||
"""
|
||||
dst_conn.execute( # nosemgrep: python.sqlalchemy.security.sqlalchemy-execute-raw-query.sqlalchemy-execute-raw-query
|
||||
"CREATE VIRTUAL TABLE "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " USING vec0("
|
||||
+ "id TEXT PRIMARY KEY,"
|
||||
+ " document_id TEXT,"
|
||||
+ " modified TEXT,"
|
||||
+ " +node_content TEXT,"
|
||||
+ " embedding float["
|
||||
+ str(int(dim))
|
||||
+ "] distance_metric=cosine"
|
||||
+ ")",
|
||||
)
|
||||
PaperlessSqliteVecVectorStore._meta_set_on(dst_conn, "dim", str(dim))
|
||||
embed_model = PaperlessSqliteVecVectorStore._meta_get_on(src_conn, "embed_model")
|
||||
if embed_model is not None:
|
||||
PaperlessSqliteVecVectorStore._meta_set_on(dst_conn, "embed_model", embed_model)
|
||||
|
||||
dst_conn.execute("BEGIN IMMEDIATE")
|
||||
src_cursor = src_conn.execute(
|
||||
"SELECT id, document_id, modified, node_content, embedding FROM "
|
||||
+ DEFAULT_TABLE_NAME,
|
||||
)
|
||||
live = 0
|
||||
while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
|
||||
dst_conn.executemany(
|
||||
"INSERT INTO "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " (id, document_id, modified, node_content, embedding) "
|
||||
"VALUES (?, ?, ?, ?, ?)",
|
||||
[
|
||||
(
|
||||
r["id"],
|
||||
r["document_id"],
|
||||
r["modified"],
|
||||
r["node_content"],
|
||||
bytes(r["embedding"]),
|
||||
)
|
||||
for r in batch
|
||||
],
|
||||
)
|
||||
dst_conn.executemany(
|
||||
"INSERT INTO document_chunks (chunk_id, document_id) VALUES (?, ?)",
|
||||
[(r["id"], r["document_id"]) for r in batch],
|
||||
)
|
||||
live += len(batch)
|
||||
# This migration only ever copies live rows (like compact()), so the
|
||||
# cumulative counter resets to match -- the new file has no bloat yet.
|
||||
PaperlessSqliteVecVectorStore._meta_set_on(dst_conn, "total_inserts", str(live))
|
||||
dst_conn.execute("COMMIT")
|
||||
|
||||
|
||||
MIGRATIONS.append(
|
||||
Migration(
|
||||
from_version=1,
|
||||
to_version=2,
|
||||
kind="structural",
|
||||
description="add document_chunks side table for O(1) per-document deletes",
|
||||
apply=_migrate_v1_to_v2_add_document_chunks,
|
||||
),
|
||||
)
|
||||
@@ -1,63 +0,0 @@
|
||||
import sqlite3
|
||||
|
||||
from paperless_ai.migrations import MIGRATIONS
|
||||
from paperless_ai.migrations import Migration
|
||||
from paperless_ai.vector_store import _UPSERT_DOCUMENT_META
|
||||
from paperless_ai.vector_store import COMPACT_BATCH_SIZE
|
||||
from paperless_ai.vector_store import DEFAULT_TABLE_NAME
|
||||
from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
|
||||
|
||||
|
||||
def _migrate_v2_to_v3_move_modified_to_document_meta(
|
||||
src_conn: sqlite3.Connection,
|
||||
dst_conn: sqlite3.Connection,
|
||||
dim: int,
|
||||
) -> None:
|
||||
"""v2 -> v3: move `modified` out of the vec0 metadata column into the
|
||||
document_meta side table.
|
||||
|
||||
vec0 only inlines TEXT metadata up to 12 bytes (sqlite-vec.c); `modified`
|
||||
is an ISO timestamp (e.g. "2026-07-28T12:34:56.789012+00:00", 32 chars),
|
||||
always over that, so every read of it took vec0's uncached long-value
|
||||
path -- a fresh SQL prepare/step/finalize per row, on every full scan
|
||||
(every compact(), every structural migration, every
|
||||
get_modified_times() call). It was also never filtered on inside a KNN
|
||||
query, so it never needed to be a vec0 column at all.
|
||||
|
||||
document_meta is one row per document (all of a document's chunks share
|
||||
the same modified value), not per chunk, so get_modified_times() also
|
||||
loses its old per-chunk dedup loop in the process.
|
||||
|
||||
dst_conn's document_meta table already exists, empty (created by
|
||||
_open_connection() the same as document_chunks), but so does
|
||||
src_conn's -- this migration is what starts populating it, so
|
||||
_rebuild_into()'s own document_meta copy (which assumes the source
|
||||
already has it right, true for compact() but not for this migration)
|
||||
would find nothing there. Backfill it explicitly here first, from the
|
||||
old vec0 table's modified column instead, before the generic rebuild.
|
||||
"""
|
||||
old_cursor = src_conn.execute(
|
||||
"SELECT DISTINCT document_id, modified FROM " + DEFAULT_TABLE_NAME,
|
||||
)
|
||||
while old_batch := old_cursor.fetchmany(COMPACT_BATCH_SIZE):
|
||||
dst_conn.executemany(
|
||||
_UPSERT_DOCUMENT_META,
|
||||
[(r["document_id"], r["modified"]) for r in old_batch],
|
||||
)
|
||||
PaperlessSqliteVecVectorStore._rebuild_into(
|
||||
src_conn,
|
||||
dst_conn,
|
||||
dim,
|
||||
meta_keys=("dim", "embed_model"),
|
||||
)
|
||||
|
||||
|
||||
MIGRATIONS.append(
|
||||
Migration(
|
||||
from_version=2,
|
||||
to_version=3,
|
||||
kind="structural",
|
||||
description="move modified out of the vec0 table into document_meta",
|
||||
apply=_migrate_v2_to_v3_move_modified_to_document_meta,
|
||||
),
|
||||
)
|
||||
@@ -21,7 +21,6 @@ from documents.signals import document_consumption_finished
|
||||
from documents.signals import document_updated
|
||||
from documents.tests.factories import DocumentFactory
|
||||
from documents.tests.factories import PaperlessTaskFactory
|
||||
from documents.tests.factories import TagFactory
|
||||
from paperless.models import ApplicationConfiguration
|
||||
from paperless_ai import indexing
|
||||
from paperless_ai.tests.conftest import FakeEmbedding
|
||||
@@ -37,23 +36,6 @@ def real_document(db: None) -> Document:
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_store(mocker: pytest_mock.MockerFixture) -> MagicMock:
|
||||
"""The MagicMock store yielded by every ``with write_store() as store:``
|
||||
block, for tests that only care what indexing.py does with the store,
|
||||
not what the store itself does.
|
||||
"""
|
||||
store = mocker.MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
return store
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_build_document_node(real_document: Document) -> None:
|
||||
nodes = indexing.build_document_node(real_document)
|
||||
@@ -365,62 +347,6 @@ def test_update_llm_index_partial_update(
|
||||
assert after[str(doc2.pk)] == before[str(doc2.pk)]
|
||||
|
||||
|
||||
class TestUpdateLlmIndexScopedDocumentIds:
|
||||
"""A document_ids-scoped update must trust the caller and reindex every scoped
|
||||
document, never gating on Document.modified.
|
||||
|
||||
bulk_edit.py's add_tag/remove_tag/modify_tags/set_correspondent/set_document_type/
|
||||
set_storage_path/modify_custom_fields all write via queryset.update() or direct
|
||||
M2M/through-model bulk operations -- none of which call Document.save(), so
|
||||
Document.modified's auto_now never fires. Comparing against
|
||||
get_modified_times() for a document_ids-scoped call would therefore skip
|
||||
reindexing documents whose embedded tags/correspondent/etc. just changed.
|
||||
"""
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_scoped_update_reindexes_despite_unchanged_modified(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
) -> None:
|
||||
"""A document_ids-scoped update must pick up a tag added via the M2M
|
||||
manager's bulk_create path, even though that leaves modified untouched.
|
||||
|
||||
Steps:
|
||||
1. Build an initial index for a document with no tags.
|
||||
2. Add a tag via a direct through-model bulk_create, mirroring
|
||||
bulk_edit.add_tag -- this does not call Document.save().
|
||||
3. Call update_llm_index(rebuild=False, document_ids=[doc.pk]).
|
||||
4. Assert the stored node metadata now includes the new tag.
|
||||
"""
|
||||
# Step 1
|
||||
tag = TagFactory.create(name="Important")
|
||||
doc = DocumentFactory.create(title="Test Document", added=timezone.now())
|
||||
indexing.update_llm_index(rebuild=True)
|
||||
modified_before = doc.modified
|
||||
|
||||
# Step 2: bulk-add the tag the way bulk_edit.add_tag does -- a direct
|
||||
# through-model insert, no Document.save().
|
||||
DocumentTagRelationship = Document.tags.through
|
||||
DocumentTagRelationship.objects.bulk_create(
|
||||
[DocumentTagRelationship(document_id=doc.pk, tag_id=tag.pk)],
|
||||
)
|
||||
doc.refresh_from_db()
|
||||
assert doc.modified == modified_before, (
|
||||
"Precondition failed: expected modified to be unchanged after a "
|
||||
"through-model bulk tag add"
|
||||
)
|
||||
|
||||
# Step 3
|
||||
result = indexing.update_llm_index(rebuild=False, document_ids=[doc.pk])
|
||||
assert result == "LLM index updated successfully."
|
||||
|
||||
# Step 4
|
||||
with indexing.get_vector_store() as store:
|
||||
nodes = store.get_nodes()
|
||||
assert any(tag.name in node.metadata.get("tags", []) for node in nodes)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
def test_add_or_update_document_updates_existing_entry(
|
||||
temp_llm_index_dir: Path,
|
||||
@@ -779,104 +705,23 @@ class TestLlmIndexAddOrUpdateDocumentEmptyContent:
|
||||
@pytest.mark.django_db
|
||||
def test_llm_index_compact_uses_force(
|
||||
temp_llm_index_dir: Path,
|
||||
mock_store: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""compact must use force=True to rebuild the table and reclaim space immediately."""
|
||||
mock_store = mocker.MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
|
||||
indexing.llm_index_compact()
|
||||
|
||||
mock_store.compact.assert_called_once_with(force=True)
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestLlmIndexMigrate:
|
||||
"""llm_index_migrate() is the cheap, startup-safe migration check -- see
|
||||
the init-llmindex-migrate container step and the bare-metal upgrade docs.
|
||||
"""
|
||||
|
||||
def test_skips_when_llm_index_disabled(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- The LLM index is disabled
|
||||
WHEN:
|
||||
- llm_index_migrate() is called
|
||||
THEN:
|
||||
- The store is never opened (no stray db file for users who
|
||||
never enabled AI features)
|
||||
"""
|
||||
mock_config = mocker.MagicMock()
|
||||
mock_config.llm_index_enabled = False
|
||||
mocker.patch("paperless_ai.indexing.AIConfig", return_value=mock_config)
|
||||
mock_write_store = mocker.patch("paperless_ai.indexing.write_store")
|
||||
|
||||
indexing.llm_index_migrate()
|
||||
|
||||
mock_write_store.assert_not_called()
|
||||
|
||||
def test_runs_pending_structural_migration(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
mock_store: MagicMock,
|
||||
caplog: pytest.LogCaptureFixture,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- The LLM index is enabled and a structural migration is pending
|
||||
WHEN:
|
||||
- llm_index_migrate() is called
|
||||
THEN:
|
||||
- check_and_run_migrations() runs, and no re-embed warning is
|
||||
logged (the pending migration was structural, not re-embed)
|
||||
"""
|
||||
mock_config = mocker.MagicMock()
|
||||
mock_config.llm_index_enabled = True
|
||||
mocker.patch("paperless_ai.indexing.AIConfig", return_value=mock_config)
|
||||
mock_store.has_pending_migration.return_value = True
|
||||
mock_store.check_and_run_migrations.return_value = False
|
||||
|
||||
with caplog.at_level("WARNING"):
|
||||
indexing.llm_index_migrate()
|
||||
|
||||
mock_store.check_and_run_migrations.assert_called_once()
|
||||
assert "re-embedding" not in caplog.text
|
||||
|
||||
def test_warns_without_rebuilding_when_reembed_pending(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
mock_store: MagicMock,
|
||||
caplog: pytest.LogCaptureFixture,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- The LLM index is enabled and a pending migration requires
|
||||
re-embedding
|
||||
WHEN:
|
||||
- llm_index_migrate() is called
|
||||
THEN:
|
||||
- A warning is logged telling the admin to rebuild manually, but
|
||||
no rebuild is triggered automatically -- re-embedding can be
|
||||
slow and, for a metered embedding backend, cost money, so it
|
||||
must be a deliberate user action, never an automatic one
|
||||
"""
|
||||
mock_config = mocker.MagicMock()
|
||||
mock_config.llm_index_enabled = True
|
||||
mocker.patch("paperless_ai.indexing.AIConfig", return_value=mock_config)
|
||||
mock_store.has_pending_migration.return_value = True
|
||||
mock_store.check_and_run_migrations.return_value = True
|
||||
|
||||
with caplog.at_level("WARNING"):
|
||||
indexing.llm_index_migrate()
|
||||
|
||||
assert "re-embedding" in caplog.text
|
||||
mock_store.drop_table.assert_not_called()
|
||||
mock_store.add.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.django_db
|
||||
class TestLlmIndexLocking:
|
||||
"""Index mutation functions must go through write_store(), which holds the lock.
|
||||
@@ -889,9 +734,16 @@ class TestLlmIndexLocking:
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
mock_store: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
mock_node = MagicMock()
|
||||
mock_node.get_content.return_value = "fake node text"
|
||||
mocker.patch(
|
||||
@@ -905,89 +757,40 @@ class TestLlmIndexLocking:
|
||||
|
||||
mock_store.upsert_document.assert_called_once()
|
||||
|
||||
@pytest.mark.parametrize("has_pending", [True, False])
|
||||
def test_add_or_update_document_runs_migration_check_only_when_pending(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
mock_store: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
*,
|
||||
has_pending: bool,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document to add/update, and a store reporting whether a
|
||||
migration is pending
|
||||
WHEN:
|
||||
- llm_index_add_or_update_document() is called
|
||||
THEN:
|
||||
- check_and_run_migrations() runs only when has_pending_migration()
|
||||
is True, so a normal upsert never pays for the exclusive access
|
||||
that check_and_run_migrations() requires
|
||||
- upsert_document() is called either way
|
||||
"""
|
||||
mock_store.has_pending_migration.return_value = has_pending
|
||||
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 = DocumentFactory.build(id=1)
|
||||
indexing.llm_index_add_or_update_document(doc)
|
||||
|
||||
assert mock_store.check_and_run_migrations.called is has_pending
|
||||
mock_store.upsert_document.assert_called_once()
|
||||
|
||||
def test_remove_document_uses_write_store(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_store: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
|
||||
doc = MagicMock(spec=Document)
|
||||
doc.id = 1
|
||||
indexing.llm_index_remove_document(doc)
|
||||
|
||||
mock_store.delete.assert_called_once_with("1")
|
||||
|
||||
@pytest.mark.parametrize("has_pending", [True, False])
|
||||
def test_remove_document_runs_migration_check_only_when_pending(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_store: MagicMock,
|
||||
*,
|
||||
has_pending: bool,
|
||||
) -> None:
|
||||
"""
|
||||
GIVEN:
|
||||
- A document to remove, and a store reporting whether a
|
||||
migration is pending
|
||||
WHEN:
|
||||
- llm_index_remove_document() is called
|
||||
THEN:
|
||||
- check_and_run_migrations() runs only when has_pending_migration()
|
||||
is True, so a normal delete never pays for the exclusive access
|
||||
that check_and_run_migrations() requires (see
|
||||
test_normal_write_is_not_gated_by_the_compaction_lock)
|
||||
- delete() is called either way
|
||||
"""
|
||||
mock_store.has_pending_migration.return_value = has_pending
|
||||
|
||||
doc = DocumentFactory.build(id=1)
|
||||
indexing.llm_index_remove_document(doc)
|
||||
|
||||
assert mock_store.check_and_run_migrations.called is has_pending
|
||||
mock_store.delete.assert_called_once_with("1")
|
||||
|
||||
def test_update_llm_index_rebuild_uses_write_store(
|
||||
self,
|
||||
temp_llm_index_dir: Path,
|
||||
mock_embed_model: FakeEmbedding,
|
||||
mock_store: MagicMock,
|
||||
mocker: pytest_mock.MockerFixture,
|
||||
) -> None:
|
||||
mock_store = MagicMock()
|
||||
mocker.patch(
|
||||
"paperless_ai.indexing.write_store",
|
||||
return_value=mocker.MagicMock(
|
||||
__enter__=mocker.MagicMock(return_value=mock_store),
|
||||
__exit__=mocker.MagicMock(return_value=False),
|
||||
),
|
||||
)
|
||||
mock_qs = MagicMock()
|
||||
mock_qs.exists.return_value = True
|
||||
mock_qs.__iter__ = MagicMock(return_value=iter([]))
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
+139
-311
@@ -2,13 +2,16 @@ 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 NamedTuple
|
||||
from typing import Literal
|
||||
|
||||
import sqlite_vec
|
||||
from llama_index.core.bridge.pydantic import PrivateAttr
|
||||
@@ -23,34 +26,15 @@ 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"
|
||||
DEFAULT_TABLE_NAME = "documents"
|
||||
|
||||
_INSERT = (
|
||||
"INSERT INTO "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " (id, document_id, node_content, embedding) VALUES (?, ?, ?, ?)"
|
||||
)
|
||||
|
||||
_INSERT_CHUNK_INDEX = (
|
||||
"INSERT INTO document_chunks (chunk_id, document_id) VALUES (?, ?)"
|
||||
)
|
||||
|
||||
# document_meta is document-scoped (one row per document), not chunk-scoped
|
||||
# like document_chunks -- see get_modified_times() and _row().
|
||||
_UPSERT_DOCUMENT_META = (
|
||||
"INSERT INTO document_meta (document_id, modified) VALUES (?, ?) "
|
||||
"ON CONFLICT(document_id) DO UPDATE SET modified = excluded.modified"
|
||||
)
|
||||
|
||||
# Current schema version. Bump when adding a migration -- see
|
||||
# paperless_ai/migrations/__init__.py for the full procedure.
|
||||
SCHEMA_VERSION = 3
|
||||
# Current schema version. Written to index_meta at table creation and bumped
|
||||
# whenever a Migration is added to MIGRATIONS. check_and_run_migrations() uses
|
||||
# this to decide which migrations to run on an existing store.
|
||||
SCHEMA_VERSION = 1
|
||||
|
||||
# compact(): rebuild when the cumulative rowid count exceeds this multiple of
|
||||
# the live row count. DELETEs on vec0 tables never reclaim space (upstream
|
||||
@@ -65,36 +49,40 @@ COMPACT_BATCH_SIZE = 500
|
||||
|
||||
# Filterable vec0 metadata columns. _build_where() only ever receives filter
|
||||
# keys we construct ourselves, but allowlisting keeps SQL identifiers safe by
|
||||
# construction. "modified" is deliberately not here: it is never filtered on
|
||||
# (see document_meta -- it isn't even a vec0 column anymore).
|
||||
_FILTER_COLUMNS = frozenset({"document_id"})
|
||||
# construction.
|
||||
_FILTER_COLUMNS = frozenset({"document_id", "modified"})
|
||||
|
||||
|
||||
class _Row(NamedTuple):
|
||||
"""One node, ready to write. ``modified`` is not a vec0 column (see
|
||||
document_meta / _open_connection) -- it rides along here because every
|
||||
row-producing call site needs both the vec0 insert values and the
|
||||
document_meta upsert value from the same node.
|
||||
@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).
|
||||
"""
|
||||
|
||||
chunk_id: str
|
||||
document_id: str
|
||||
modified: str
|
||||
node_content: str
|
||||
embedding: bytes
|
||||
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,
|
||||
)
|
||||
|
||||
|
||||
class _Vec0Params(NamedTuple):
|
||||
"""``_INSERT``'s bind parameters, in placeholder order -- a NamedTuple
|
||||
is still a plain positional tuple as far as sqlite3.executemany() is
|
||||
concerned, so this keeps the self-documenting field names without
|
||||
losing that.
|
||||
"""
|
||||
|
||||
chunk_id: str
|
||||
document_id: str
|
||||
node_content: str
|
||||
embedding: bytes
|
||||
# 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:
|
||||
@@ -105,49 +93,6 @@ def _unpack(blob: bytes) -> list[float]:
|
||||
return list(struct.unpack(f"{len(blob) // 4}f", blob))
|
||||
|
||||
|
||||
def _copy_rows(src_conn: sqlite3.Connection, dst_conn: sqlite3.Connection) -> int:
|
||||
"""Copy every live vec0 row from ``src_conn`` into ``dst_conn``, recording
|
||||
each one in ``dst_conn``'s document_chunks side table, then copy
|
||||
document_meta the same way. Returns the number of vec0 rows copied. The
|
||||
caller owns ``dst_conn``'s transaction.
|
||||
|
||||
Both are streamed from their source cursors in batches instead of being
|
||||
materialized all at once, so a large index does not cause an OOM during a
|
||||
routine compaction or migration. document_meta is one row per document,
|
||||
not per chunk, so in practice it is far smaller than the vec0 table --
|
||||
but the same discipline applies regardless of size.
|
||||
"""
|
||||
src_cursor = src_conn.execute(
|
||||
"SELECT id, document_id, node_content, embedding FROM " + DEFAULT_TABLE_NAME,
|
||||
)
|
||||
copied = 0
|
||||
while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
|
||||
dst_conn.executemany(
|
||||
_INSERT,
|
||||
[
|
||||
_Vec0Params(
|
||||
chunk_id=r["id"],
|
||||
document_id=r["document_id"],
|
||||
node_content=r["node_content"],
|
||||
embedding=bytes(r["embedding"]),
|
||||
)
|
||||
for r in batch
|
||||
],
|
||||
)
|
||||
dst_conn.executemany(
|
||||
_INSERT_CHUNK_INDEX,
|
||||
[(r["id"], r["document_id"]) for r in batch],
|
||||
)
|
||||
copied += len(batch)
|
||||
meta_cursor = src_conn.execute("SELECT document_id, modified FROM document_meta")
|
||||
while meta_batch := meta_cursor.fetchmany(COMPACT_BATCH_SIZE):
|
||||
dst_conn.executemany(
|
||||
_UPSERT_DOCUMENT_META,
|
||||
[(r["document_id"], r["modified"]) for r in meta_batch],
|
||||
)
|
||||
return copied
|
||||
|
||||
|
||||
def _build_where(filters: MetadataFilters | None) -> tuple[str, list[str]]:
|
||||
"""Translate the EQ / IN / NE filters we use into a parameterized SQL clause
|
||||
on vec0 metadata columns. Returns ("", []) when there is nothing to filter.
|
||||
@@ -193,12 +138,10 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
|
||||
Stores one row per node: the node id (TEXT primary key), its document id
|
||||
(metadata column, used for EQ/IN filtering and per-document delete), the
|
||||
embedding (float32, cosine metric), and the serialized node (text +
|
||||
metadata) as JSON in an auxiliary column. Each document's modified
|
||||
timestamp lives in the separate document_meta table instead (see
|
||||
get_modified_times()), not as a vec0 column. ``stores_text`` lets
|
||||
llama-index run off this store alone, with no separate docstore or
|
||||
index store.
|
||||
document's modified timestamp, the embedding (float32, cosine metric), and
|
||||
the serialized node (text + metadata) as JSON in an auxiliary column.
|
||||
``stores_text`` lets llama-index run off this store alone, with no
|
||||
separate docstore or index store.
|
||||
|
||||
Everything lives in one SQLite database file (``DB_FILENAME``) inside the
|
||||
directory given as ``uri`` (kept as a directory for compatibility with the
|
||||
@@ -246,36 +189,6 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
conn.execute(
|
||||
"CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
|
||||
)
|
||||
# vec0 metadata columns only get an efficient lookup path inside a KNN
|
||||
# (MATCH) query; a plain `WHERE document_id = ?` is a full table scan
|
||||
# regardless of index size. This plain, indexed table is how delete()/
|
||||
# upsert_document() find a document's chunk ids without that scan.
|
||||
# document_id is INTEGER here (unlike vec0's own TEXT metadata
|
||||
# column): this is a normal SQLite table, so standard type affinity
|
||||
# correctly coerces the TEXT document ids written/looked-up
|
||||
# elsewhere in this module -- it does not share vec0's own
|
||||
# metadata-column comparison code, which silently mismatches
|
||||
# non-TEXT bound values instead of coercing them.
|
||||
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)",
|
||||
)
|
||||
# modified used to be a vec0 metadata column, but vec0 only inlines
|
||||
# TEXT metadata up to 12 bytes -- an ISO timestamp is always longer,
|
||||
# so every read recompiled and stepped a fresh SQL statement per row
|
||||
# (sqlite-vec's vec0Column long-value path). It was never filtered
|
||||
# on inside a KNN query either, so it never needed to be a vec0
|
||||
# column at all. One row per document here (not per chunk, like
|
||||
# document_chunks), since every chunk of a document shares the same
|
||||
# modified value -- see get_modified_times().
|
||||
conn.execute(
|
||||
"CREATE TABLE IF NOT EXISTS document_meta "
|
||||
"(document_id INTEGER PRIMARY KEY, modified TEXT NOT NULL)",
|
||||
)
|
||||
return conn
|
||||
|
||||
@property
|
||||
@@ -310,17 +223,13 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
else:
|
||||
self._conn.execute("COMMIT")
|
||||
|
||||
@staticmethod
|
||||
def _meta_get_on(conn: sqlite3.Connection, key: str) -> str | None:
|
||||
row = conn.execute(
|
||||
def _meta_get(self, key: str) -> str | None:
|
||||
row = self._conn.execute(
|
||||
"SELECT value FROM index_meta WHERE key = ?",
|
||||
(key,),
|
||||
).fetchone()
|
||||
return row["value"] if row else None
|
||||
|
||||
def _meta_get(self, key: str) -> str | None:
|
||||
return self._meta_get_on(self._conn, key)
|
||||
|
||||
@staticmethod
|
||||
def _meta_set_on(conn: sqlite3.Connection, key: str, value: str) -> None:
|
||||
conn.execute(
|
||||
@@ -350,8 +259,6 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
def drop_table(self) -> None:
|
||||
self._conn.execute("DROP TABLE IF EXISTS " + DEFAULT_TABLE_NAME)
|
||||
self._conn.execute("DELETE FROM index_meta")
|
||||
self._conn.execute("DELETE FROM document_chunks")
|
||||
self._conn.execute("DELETE FROM document_meta")
|
||||
|
||||
def stored_model_name(self) -> str | None:
|
||||
"""Return the embedding model name recorded at table creation, or None."""
|
||||
@@ -382,6 +289,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
+ " USING vec0("
|
||||
+ "id TEXT PRIMARY KEY,"
|
||||
+ " document_id TEXT,"
|
||||
+ " modified TEXT,"
|
||||
+ " +node_content TEXT,"
|
||||
+ " embedding float["
|
||||
+ str(int(dim))
|
||||
@@ -400,7 +308,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
if not self.table_exists():
|
||||
self._create_table(dim)
|
||||
|
||||
def _row(self, node: BaseNode) -> _Row:
|
||||
def _row(self, node: BaseNode) -> tuple[str, str, str, str, bytes]:
|
||||
meta = node_to_metadata_dict(
|
||||
node,
|
||||
remove_text=False,
|
||||
@@ -409,66 +317,19 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
# vec0 metadata columns reject NULL (asg017/sqlite-vec#141): coerce
|
||||
# every value to a string, with "" as the absent sentinel.
|
||||
document_id = node.ref_doc_id or node.metadata.get("document_id")
|
||||
return _Row(
|
||||
chunk_id=node.node_id,
|
||||
document_id=str(document_id or ""),
|
||||
modified=str(node.metadata.get("modified") or ""),
|
||||
node_content=json.dumps(meta),
|
||||
embedding=_pack(node.get_embedding()),
|
||||
return (
|
||||
node.node_id,
|
||||
str(document_id or ""),
|
||||
str(node.metadata.get("modified") or ""),
|
||||
json.dumps(meta),
|
||||
_pack(node.get_embedding()),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _vec0_params(rows: list[_Row]) -> list[_Vec0Params]:
|
||||
"""``rows``, minus the ``modified`` field vec0 no longer stores."""
|
||||
return [
|
||||
_Vec0Params(r.chunk_id, r.document_id, r.node_content, r.embedding)
|
||||
for r in rows
|
||||
]
|
||||
|
||||
def _index_chunks(self, rows: list[_Row]) -> None:
|
||||
"""Record each row's (chunk_id, document_id) in document_chunks, and
|
||||
each row's (document_id, modified) in document_meta -- deduped
|
||||
within the batch, since every chunk of a document shares the same
|
||||
modified value -- kept in lockstep with every insert into the vec0
|
||||
table.
|
||||
"""
|
||||
self._conn.executemany(
|
||||
_INSERT_CHUNK_INDEX,
|
||||
[(r.chunk_id, r.document_id) for r in rows],
|
||||
)
|
||||
modified_by_document = {r.document_id: r.modified for r in rows}
|
||||
self._conn.executemany(
|
||||
_UPSERT_DOCUMENT_META,
|
||||
list(modified_by_document.items()),
|
||||
)
|
||||
|
||||
def _delete_chunks_by_document_id(self, document_id: str) -> None:
|
||||
"""Delete all of a document's chunks via point-deletes on `id`.
|
||||
|
||||
vec0 has no efficient lookup on the document_id metadata column
|
||||
outside a KNN query (see _open_connection), so a plain
|
||||
`DELETE ... WHERE document_id = ?` is a full table scan regardless of
|
||||
index size. Looking the chunk ids up in document_chunks first (a real
|
||||
indexed lookup) and deleting each by its `id` primary key instead
|
||||
turns that scan into a handful of O(1) point deletes.
|
||||
"""
|
||||
doc_id = str(document_id)
|
||||
chunk_rows = self._conn.execute(
|
||||
"SELECT chunk_id FROM document_chunks WHERE document_id = ?",
|
||||
(doc_id,),
|
||||
).fetchall()
|
||||
self._conn.executemany(
|
||||
"DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE id = ?",
|
||||
[(row["chunk_id"],) for row in chunk_rows],
|
||||
)
|
||||
self._conn.execute(
|
||||
"DELETE FROM document_chunks WHERE document_id = ?",
|
||||
(doc_id,),
|
||||
)
|
||||
self._conn.execute(
|
||||
"DELETE FROM document_meta WHERE document_id = ?",
|
||||
(doc_id,),
|
||||
)
|
||||
_INSERT = (
|
||||
"INSERT INTO "
|
||||
+ DEFAULT_TABLE_NAME
|
||||
+ " (id, document_id, modified, node_content, embedding) VALUES (?, ?, ?, ?, ?)"
|
||||
)
|
||||
|
||||
def _increment_total_inserts(self, count: int) -> None:
|
||||
"""Increment the cumulative insert counter stored in index_meta.
|
||||
@@ -487,8 +348,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
rows = [self._row(node) for node in nodes]
|
||||
with self._transaction():
|
||||
self._ensure_table(len(nodes[0].get_embedding()))
|
||||
self._conn.executemany(_INSERT, self._vec0_params(rows))
|
||||
self._index_chunks(rows)
|
||||
self._conn.executemany(self._INSERT, rows)
|
||||
self._increment_total_inserts(len(rows))
|
||||
return [node.node_id for node in nodes]
|
||||
|
||||
@@ -505,17 +365,22 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
if nodes:
|
||||
self._ensure_table(len(nodes[0].get_embedding()))
|
||||
if self.table_exists():
|
||||
self._delete_chunks_by_document_id(document_id)
|
||||
self._conn.execute(
|
||||
"DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
|
||||
(str(document_id),),
|
||||
)
|
||||
if rows:
|
||||
self._conn.executemany(_INSERT, self._vec0_params(rows))
|
||||
self._index_chunks(rows)
|
||||
self._conn.executemany(self._INSERT, rows)
|
||||
self._increment_total_inserts(len(rows))
|
||||
return [node.node_id for node in nodes]
|
||||
|
||||
def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
|
||||
if self.table_exists():
|
||||
with self._transaction():
|
||||
self._delete_chunks_by_document_id(ref_doc_id)
|
||||
self._conn.execute(
|
||||
"DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
|
||||
(str(ref_doc_id),),
|
||||
)
|
||||
|
||||
def _rows_to_nodes(self, rows: list[sqlite3.Row]) -> list[BaseNode]:
|
||||
nodes: list[BaseNode] = []
|
||||
@@ -585,78 +450,19 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
def get_modified_times(self) -> dict[str, str]:
|
||||
"""Return {document_id: stored_modified_isoformat} for all indexed documents.
|
||||
|
||||
document_meta already has exactly one row per document (not per
|
||||
chunk, unlike the vec0 table), so no dedup is needed here.
|
||||
All chunks of a document share the same ``modified`` value, so the
|
||||
first row seen per document is sufficient.
|
||||
"""
|
||||
if not self.table_exists():
|
||||
return {}
|
||||
return {
|
||||
str(row["document_id"]): str(row["modified"] or "")
|
||||
for row in self._conn.execute(
|
||||
"SELECT document_id, modified FROM document_meta",
|
||||
)
|
||||
}
|
||||
|
||||
@property
|
||||
def _db_path(self) -> str:
|
||||
return str(Path(self._uri) / DB_FILENAME)
|
||||
|
||||
@contextmanager
|
||||
def _rebuild_file(self) -> Iterator[sqlite3.Connection]:
|
||||
"""Open a fresh temp database file for a file-swap rebuild (compact
|
||||
or structural migration), yielding its connection for the caller to
|
||||
populate.
|
||||
|
||||
On success, swaps the temp file in as the live database (closing
|
||||
this store's current connection first -- see _swap_in_compact()).
|
||||
On any exception, discards the temp file, including its -wal/-shm,
|
||||
instead, and this store's own connection is left untouched.
|
||||
"""
|
||||
compact_path = self._db_path + ".compact"
|
||||
new_conn = self._open_connection(compact_path)
|
||||
try:
|
||||
yield new_conn
|
||||
except BaseException:
|
||||
new_conn.close()
|
||||
for suffix in ["", "-wal", "-shm"]:
|
||||
Path(compact_path + suffix).unlink(missing_ok=True)
|
||||
raise
|
||||
else:
|
||||
new_conn.close()
|
||||
self._swap_in_compact(compact_path, self._db_path)
|
||||
|
||||
@staticmethod
|
||||
def _rebuild_into(
|
||||
src_conn: sqlite3.Connection,
|
||||
dst_conn: sqlite3.Connection,
|
||||
dim: int,
|
||||
meta_keys: tuple[str, ...] = ("dim", "embed_model", "schema_version"),
|
||||
) -> int:
|
||||
"""Create the vec0 table in ``dst_conn``, copy ``meta_keys`` from
|
||||
``src_conn``'s index_meta, and stream every live row across
|
||||
(populating document_chunks as it goes -- see _copy_rows()).
|
||||
Returns the number of rows copied.
|
||||
|
||||
Used by both compact() (default meta_keys: the schema is unchanged)
|
||||
and structural migrations (meta_keys minus "schema_version", which
|
||||
the migration sets to its own target version instead of preserving
|
||||
the source's).
|
||||
"""
|
||||
PaperlessSqliteVecVectorStore._create_vec_table(dst_conn, dim)
|
||||
for key in meta_keys:
|
||||
value = PaperlessSqliteVecVectorStore._meta_get_on(src_conn, key)
|
||||
if value is not None:
|
||||
PaperlessSqliteVecVectorStore._meta_set_on(dst_conn, key, value)
|
||||
dst_conn.execute("BEGIN IMMEDIATE")
|
||||
copied = _copy_rows(src_conn, dst_conn)
|
||||
# Reset the cumulative counter: after a rebuild, total_inserts == live.
|
||||
PaperlessSqliteVecVectorStore._meta_set_on(
|
||||
dst_conn,
|
||||
"total_inserts",
|
||||
str(copied),
|
||||
)
|
||||
dst_conn.execute("COMMIT")
|
||||
return copied
|
||||
result: dict[str, str] = {}
|
||||
for row in self._conn.execute(
|
||||
"SELECT document_id, modified FROM " + DEFAULT_TABLE_NAME,
|
||||
):
|
||||
doc_id = str(row["document_id"])
|
||||
if doc_id not in result:
|
||||
result[doc_id] = str(row["modified"] or "")
|
||||
return result
|
||||
|
||||
def compact(self, *, force: bool = False) -> None:
|
||||
"""Rebuild the database file to reclaim space left behind by DELETEs.
|
||||
@@ -690,8 +496,50 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
live,
|
||||
total,
|
||||
)
|
||||
with self._rebuild_file() as new_conn:
|
||||
self._rebuild_into(self._conn, new_conn, dim)
|
||||
db_path = str(Path(self._uri) / DB_FILENAME)
|
||||
compact_path = db_path + ".compact"
|
||||
|
||||
# Copy all live rows into a fresh database file.
|
||||
new_conn = self._open_connection(compact_path)
|
||||
try:
|
||||
self._create_vec_table(new_conn, dim)
|
||||
self._meta_set_on(new_conn, "dim", str(dim))
|
||||
for key in ("embed_model", "schema_version"):
|
||||
value = self._meta_get(key)
|
||||
if value is not None:
|
||||
self._meta_set_on(new_conn, key, value)
|
||||
src_cursor = self._conn.execute(
|
||||
"SELECT id, document_id, modified, node_content, embedding "
|
||||
"FROM " + DEFAULT_TABLE_NAME,
|
||||
)
|
||||
new_conn.execute("BEGIN IMMEDIATE")
|
||||
# Stream rows from the source cursor in batches instead of
|
||||
# materializing the whole table in memory, so a large index does
|
||||
# not cause an OOM during routine maintenance compactions.
|
||||
while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
|
||||
new_conn.executemany(
|
||||
self._INSERT,
|
||||
[
|
||||
(
|
||||
r["id"],
|
||||
r["document_id"],
|
||||
r["modified"],
|
||||
r["node_content"],
|
||||
bytes(r["embedding"]),
|
||||
)
|
||||
for r in batch
|
||||
],
|
||||
)
|
||||
# Reset the cumulative counter: after compact, total_inserts == live.
|
||||
self._meta_set_on(new_conn, "total_inserts", str(live))
|
||||
new_conn.execute("COMMIT")
|
||||
except BaseException:
|
||||
new_conn.close()
|
||||
for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
|
||||
Path(p).unlink(missing_ok=True)
|
||||
raise
|
||||
new_conn.close()
|
||||
self._swap_in_compact(compact_path, db_path)
|
||||
|
||||
def _swap_in_compact(self, compact_path: str, db_path: str) -> None:
|
||||
"""Atomically replace the live database with the compacted copy."""
|
||||
@@ -703,31 +551,6 @@ 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.
|
||||
|
||||
@@ -736,13 +559,15 @@ 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, 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.
|
||||
Must be called under the write FileLock. No-op when the table does
|
||||
not exist or is already at SCHEMA_VERSION.
|
||||
"""
|
||||
current = self._stored_schema_version()
|
||||
if current is None or current >= SCHEMA_VERSION:
|
||||
if not self.table_exists():
|
||||
return False
|
||||
|
||||
raw = self._meta_get("schema_version")
|
||||
current = int(raw) if raw is not None else SCHEMA_VERSION
|
||||
if current >= SCHEMA_VERSION:
|
||||
return False
|
||||
|
||||
pending = sorted(
|
||||
@@ -754,7 +579,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
if migration.kind == "re-embed":
|
||||
logger.warning(
|
||||
"LLM index schema v%d -> v%d requires re-embedding (%s); "
|
||||
"the caller must force a rebuild.",
|
||||
"forcing full rebuild.",
|
||||
migration.from_version,
|
||||
migration.to_version,
|
||||
migration.description,
|
||||
@@ -776,13 +601,16 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
|
||||
dim = self.vector_dim()
|
||||
if dim is None: # pragma: no cover
|
||||
raise RuntimeError("Cannot migrate: no stored vector dimension")
|
||||
with self._rebuild_file() as new_conn:
|
||||
db_path = str(Path(self._uri) / DB_FILENAME)
|
||||
compact_path = db_path + ".compact"
|
||||
new_conn = self._open_connection(compact_path)
|
||||
try:
|
||||
migration.apply(self._conn, new_conn, dim)
|
||||
self._meta_set_on(new_conn, "schema_version", str(migration.to_version))
|
||||
|
||||
|
||||
# Registers m0001/m0002 into MIGRATIONS; must be at the bottom (needs
|
||||
# PaperlessSqliteVecVectorStore fully defined) -- see
|
||||
# paperless_ai/migrations/__init__.py for the full procedure.
|
||||
from paperless_ai.migrations import m0001_add_document_chunks # noqa
|
||||
from paperless_ai.migrations import m0002_move_modified_to_document_meta # noqa
|
||||
except BaseException: # pragma: no cover
|
||||
new_conn.close()
|
||||
for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
|
||||
Path(p).unlink(missing_ok=True)
|
||||
raise
|
||||
new_conn.close()
|
||||
self._swap_in_compact(compact_path, db_path)
|
||||
|
||||
@@ -3735,15 +3735,15 @@ crypto = [
|
||||
|
||||
[[package]]
|
||||
name = "pymdown-extensions"
|
||||
version = "10.21.3"
|
||||
version = "11.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "markdown", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
{ name = "pyyaml", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/9e/26/d1015444da4d952a1ca487a236b522eb979766f0295a0bd0c5fc089989a9/pymdown_extensions-10.21.3.tar.gz", hash = "sha256:72cfcf55f07aea0d4af2c4f11dd4e52466ddfb1bb819673146398e0bd3a77354", size = 854140, upload-time = "2026-05-13T12:57:32.267Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/47/67/f1e79672a5f91985577c7984c9709ca110e4fd37fe7fd167b60422e6ccc2/pymdown_extensions-11.0.tar.gz", hash = "sha256:8269cef0247f9e2d0a62fcea10860aba05c1cbab5470fd4b63230b96434dc589", size = 857049, upload-time = "2026-06-23T02:27:45.146Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/7e/85/545a951eecc270fcd688288c600017e2050a1aacb56c711d208586d3e470/pymdown_extensions-10.21.3-py3-none-any.whl", hash = "sha256:d7a5d08014fc571e80ca21dd6f854e31f94c489800350564d55d15b3c41e76b6", size = 269002, upload-time = "2026-05-13T12:57:30.296Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/af/b6/1ae53367e28b9cffa3be7574e13fbe4589694272fd47710fbdbafd3d63c6/pymdown_extensions-11.0-py3-none-any.whl", hash = "sha256:fbc4acb641814fa9d17521bbd21a5240ef739a662f11c06330c4b78c93e954d6", size = 269415, upload-time = "2026-06-23T02:27:43.826Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Reference in New Issue
Block a user