Chore(deps): Bump the development group with 2 updates

Bumps the development group with 2 updates: [mkdocs-material](https://github.com/squidfunk/mkdocs-material) and [ruff](https://github.com/astral-sh/ruff).


Updates `mkdocs-material` from 9.6.20 to 9.6.21
- [Release notes](https://github.com/squidfunk/mkdocs-material/releases)
- [Changelog](https://github.com/squidfunk/mkdocs-material/blob/master/CHANGELOG)
- [Commits](https://github.com/squidfunk/mkdocs-material/compare/9.6.20...9.6.21)

Updates `ruff` from 0.13.2 to 0.13.3
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.13.2...0.13.3)

---
updated-dependencies:
- dependency-name: mkdocs-material
  dependency-version: 9.6.21
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: development
- dependency-name: ruff
  dependency-version: 0.13.3
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: development
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/cleanup-tags.yml

@@ -6,10 +6,9 @@
 # This workflow will not trigger runs on forked repos.
 name: Cleanup Image Tags
 on:
-  delete:
-  push:
-    paths:
-      - ".github/workflows/cleanup-tags.yml"
+  workflow_dispatch:
+  schedule:
+    - cron: '0 0 * * 0'
 concurrency:
   group: registry-tags-cleanup
   cancel-in-progress: false

docs/configuration.md

@@ -170,11 +170,11 @@ Available options are `postgresql` and `mariadb`.
 
     !!! note
 
-    A small pool is typically sufficient — for example, a size of 4.
-    Make sure your PostgreSQL server's max_connections setting is large enough to handle:
-    ```(Paperless workers + Celery workers) × pool size + safety margin```
-    For example, with 4 Paperless workers and 2 Celery workers, and a pool size of 4:
-    (4 + 2) × 4 + 10 = 34 connections required.
+        A small pool is typically sufficient — for example, a size of 4.
+        Make sure your PostgreSQL server's max_connections setting is large enough to handle:
+        ```(Paperless workers + Celery workers) × pool size + safety margin```
+        For example, with 4 Paperless workers and 2 Celery workers, and a pool size of 4:
+        (4 + 2) × 4 + 10 = 34 connections required.
 
 #### [`PAPERLESS_DB_READ_CACHE_ENABLED=<bool>`](#PAPERLESS_DB_READ_CACHE_ENABLED) {#PAPERLESS_DB_READ_CACHE_ENABLED}
 
@@ -184,9 +184,9 @@ Available options are `postgresql` and `mariadb`.
 
     !!! danger
 
-    **Do not modify the database outside the application while it is running.**
-    This includes actions such as restoring a backup, upgrading the database, or performing manual inserts. All external modifications must be done **only when the application is stopped**.
-    After making any such changes, you **must invalidate the DB read cache** using the `invalidate_cachalot` management command.
+        **Do not modify the database outside the application while it is running.**
+        This includes actions such as restoring a backup, upgrading the database, or performing manual inserts. All external modifications must be done **only when the application is stopped**.
+        After making any such changes, you **must invalidate the DB read cache** using the `invalidate_cachalot` management command.
 
 #### [`PAPERLESS_READ_CACHE_TTL=<int>`](#PAPERLESS_READ_CACHE_TTL) {#PAPERLESS_READ_CACHE_TTL}
 
@@ -196,7 +196,7 @@ Available options are `postgresql` and `mariadb`.
 
     !!! warning
 
-    A high TTL increases memory usage over time. Memory may be used until end of TTL, even if the cache is invalidated with the `invalidate_cachalot` command.
+        A high TTL increases memory usage over time. Memory may be used until end of TTL, even if the cache is invalidated with the `invalidate_cachalot` command.
 
 In case of an out-of-memory (OOM) situation, Redis may stop accepting new data — including cache entries, scheduled tasks, and documents to consume.
 If your system has limited RAM, consider configuring a dedicated Redis instance for the read cache, with a memory limit and the eviction policy set to `allkeys-lru`.
@@ -1805,23 +1805,3 @@ password. All of these options come from their similarly-named [Django settings]
 #### [`PAPERLESS_EMAIL_USE_SSL=<bool>`](#PAPERLESS_EMAIL_USE_SSL) {#PAPERLESS_EMAIL_USE_SSL}
 
 : Defaults to false.
-
-## Remote OCR
-
-#### [`PAPERLESS_REMOTE_OCR_ENGINE=<str>`](#PAPERLESS_REMOTE_OCR_ENGINE) {#PAPERLESS_REMOTE_OCR_ENGINE}
-
-: The remote OCR engine to use. Currently only Azure AI is supported as "azureai".
-
-    Defaults to None, which disables remote OCR.
-
-#### [`PAPERLESS_REMOTE_OCR_API_KEY=<str>`](#PAPERLESS_REMOTE_OCR_API_KEY) {#PAPERLESS_REMOTE_OCR_API_KEY}
-
-: The API key to use for the remote OCR engine.
-
-    Defaults to None.
-
-#### [`PAPERLESS_REMOTE_OCR_ENDPOINT=<str>`](#PAPERLESS_REMOTE_OCR_ENDPOINT) {#PAPERLESS_REMOTE_OCR_ENDPOINT}
-
-: The endpoint to use for the remote OCR engine. This is required for Azure AI.
-
-    Defaults to None.

docs/index.md

@@ -25,10 +25,9 @@ physical documents into a searchable online archive so you can keep, well, _less
 ## Features
 
 -   **Organize and index** your scanned documents with tags, correspondents, types, and more.
--   _Your_ data is stored locally on _your_ server and is never transmitted or shared in any way, unless you explicitly choose to do so.
+-   _Your_ data is stored locally on _your_ server and is never transmitted or shared in any way.
 -   Performs **OCR** on your documents, adding searchable and selectable text, even to documents scanned with only images.
-    -   Utilizes the open-source Tesseract engine to recognize more than 100 languages.
-    -   _New!_ Supports remote OCR with Azure AI (opt-in).
+-   Utilizes the open-source Tesseract engine to recognize more than 100 languages.
 -   Documents are saved as PDF/A format which is designed for long term storage, alongside the unaltered originals.
 -   Uses machine-learning to automatically add tags, correspondents and document types to your documents.
 -   Supports PDF documents, images, plain text files, Office documents (Word, Excel, PowerPoint, and LibreOffice equivalents)[^1] and more.

docs/usage.md

@@ -414,7 +414,7 @@ fields and permissions, which will be merged.
 
 #### Types {#workflow-trigger-types}
 
-Currently, there are three events that correspond to workflow trigger 'types':
+Currently, there are four events that correspond to workflow trigger 'types':
 
 1. **Consumption Started**: _before_ a document is consumed, so events can include filters by source (mail, consumption
    folder or API), file path, file name, mail rule
@@ -427,7 +427,7 @@ Currently, there are three events that correspond to workflow trigger 'types':
    added, created, updated date or you can specify a (date) custom field. You can also specify a day offset from the date (positive
    offsets will trigger after the date, negative offsets will trigger before).
 
-The following flow diagram illustrates the three document trigger types:
+The following flow diagram illustrates the four document trigger types:
 
 ```mermaid
 flowchart TD
@@ -882,21 +882,6 @@ how regularly you intend to scan documents and use paperless.
     performed the task associated with the document, move it to the
     inbox.
 
-## Remote OCR
-
-!!! important
-
-    This feature is disabled by default and will always remain strictly "opt-in".
-
-Paperless-ngx supports performing OCR on documents using remote services. At the moment, this is limited to
-[Microsoft's Azure "Document Intelligence" service](https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence).
-This is of course a paid service (with a free tier) which requires an Azure account and subscription. Azure AI is not affiliated with
-Paperless-ngx in any way. When enabled, Paperless-ngx will automatically send appropriate documents to Azure for OCR processing, bypassing
-the local OCR engine. See the [configuration](configuration.md#PAPERLESS_REMOTE_OCR_ENGINE) options for more details.
-
-Additionally, when using a commercial service with this feature, consider both potential costs as well as any associated file size
-or page limitations (e.g. with a free tier).
-
 ## Architecture
 
 Paperless-ngx consists of the following components:

pyproject.toml

@@ -15,7 +15,6 @@ classifiers = [
 # This will allow testing to not install a webserver, mysql, etc
 
 dependencies = [
-  "azure-ai-documentintelligence>=1.0.2",
   "babel>=2.17",
   "bleach~=6.2.0",
   "celery[redis]~=5.5.1",
@@ -233,7 +232,6 @@ testpaths = [
   "src/paperless_tesseract/tests/",
   "src/paperless_tika/tests",
   "src/paperless_text/tests/",
-  "src/paperless_remote/tests/",
 ]
 addopts = [
   "--pythonwarnings=all",

src-ui/src/app/components/common/input/color/color.component.html

@@ -1,19 +1,18 @@
 <div class="mb-3">
   @if (title) {
-    <label [for]="inputId">{{title}}</label>
+    <label class="form-label" [for]="inputId">{{title}}</label>
   }
 
   <div class="input-group" [class.is-invalid]="error">
-    <span class="input-group-text" [style.background-color]="value">&nbsp;&nbsp;&nbsp;</span>
+    <button type="button" class="input-group-text" [style.background-color]="value" (click)="colorPicker.toggle()">&nbsp;&nbsp;&nbsp;</button>
 
     <ng-template #popContent>
       <div style="min-width: 200px;" class="pb-3">
         <color-slider [color]="value" (onChangeComplete)="colorChanged($event.color.hex)"></color-slider>
       </div>
-
     </ng-template>
 
-    <input #inputField class="form-control" [class.is-invalid]="error" [id]="inputId" [(ngModel)]="value" (change)="onChange(value)" [autoClose]="'outside'" [ngbPopover]="popContent" placement="bottom" popoverClass="shadow">
+    <input #inputField class="form-control" [class.is-invalid]="error" [id]="inputId" [(ngModel)]="value" (change)="onChange(value)" [autoClose]="'outside'" [ngbPopover]="popContent" #colorPicker="ngbPopover" placement="bottom" popoverClass="shadow">
 
     <button class="btn btn-outline-secondary" type="button" (click)="randomize()">
       <i-bs name="dice5"></i-bs>

src-ui/src/app/components/common/input/color/color.component.spec.ts

@@ -42,8 +42,8 @@ describe('ColorComponent', () => {
   })
 
   it('should set swatch color', () => {
-    const swatch: HTMLSpanElement = fixture.nativeElement.querySelector(
-      'span.input-group-text'
+    const swatch: HTMLButtonElement = fixture.nativeElement.querySelector(
+      'button.input-group-text'
     )
     expect(swatch.style.backgroundColor).toEqual('')
     component.value = '#ff0000'

src/documents/sanity_checker.py

@@ -76,7 +76,9 @@ def check_sanity(*, progress=False, scheduled=True) -> SanityCheckMessages:
     messages = SanityCheckMessages()
 
     present_files = {
-        x.resolve() for x in Path(settings.MEDIA_ROOT).glob("**/*") if not x.is_dir()
+        x.resolve()
+        for x in Path(settings.MEDIA_ROOT).glob("**/*")
+        if not x.is_dir() and x.name not in settings.IGNORABLE_FILES
     }
 
     lockfile = Path(settings.MEDIA_LOCK).resolve()

src/documents/tests/test_sanity_check.py

@@ -169,6 +169,13 @@ class TestSanityCheck(DirectoriesMixin, TestCase):
         messages = check_sanity()
         self.assertFalse(messages.has_warning)
 
+    def test_ignore_ignorable_files(self):
+        self.make_test_data()
+        Path(self.dirs.media_dir, ".DS_Store").touch()
+        Path(self.dirs.media_dir, "desktop.ini").touch()
+        messages = check_sanity()
+        self.assertFalse(messages.has_warning)
+
     def test_archive_filename_no_checksum(self):
         doc = self.make_test_data()
         doc.archive_checksum = None

src/paperless/settings.py

@@ -322,7 +322,6 @@ INSTALLED_APPS = [
     "paperless_tesseract.apps.PaperlessTesseractConfig",
     "paperless_text.apps.PaperlessTextConfig",
     "paperless_mail.apps.PaperlessMailConfig",
-    "paperless_remote.apps.PaperlessRemoteParserConfig",
     "django.contrib.admin",
     "rest_framework",
     "rest_framework.authtoken",
@@ -1004,6 +1003,18 @@ THREADS_PER_WORKER = os.getenv(
 # Paperless Specific Settings                                                 #
 ###############################################################################
 
+IGNORABLE_FILES: Final[list[str]] = [
+    ".DS_Store",
+    ".DS_STORE",
+    "._*",
+    ".stfolder/*",
+    ".stversions/*",
+    ".localized/*",
+    "desktop.ini",
+    "@eaDir/*",
+    "Thumbs.db",
+]
+
 CONSUMER_POLLING = int(os.getenv("PAPERLESS_CONSUMER_POLLING", 0))
 
 CONSUMER_POLLING_DELAY = int(os.getenv("PAPERLESS_CONSUMER_POLLING_DELAY", 5))
@@ -1026,7 +1037,7 @@ CONSUMER_IGNORE_PATTERNS = list(
     json.loads(
         os.getenv(
             "PAPERLESS_CONSUMER_IGNORE_PATTERNS",
-            '[".DS_Store", ".DS_STORE", "._*", ".stfolder/*", ".stversions/*", ".localized/*", "desktop.ini", "@eaDir/*", "Thumbs.db"]',
+            json.dumps(IGNORABLE_FILES),
         ),
     ),
 )
@@ -1390,10 +1401,3 @@ WEBHOOKS_ALLOW_INTERNAL_REQUESTS = __get_boolean(
     "PAPERLESS_WEBHOOKS_ALLOW_INTERNAL_REQUESTS",
     "true",
 )
-
-###############################################################################
-# Remote Parser                                                               #
-###############################################################################
-REMOTE_OCR_ENGINE = os.getenv("PAPERLESS_REMOTE_OCR_ENGINE")
-REMOTE_OCR_API_KEY = os.getenv("PAPERLESS_REMOTE_OCR_API_KEY")
-REMOTE_OCR_ENDPOINT = os.getenv("PAPERLESS_REMOTE_OCR_ENDPOINT")

src/paperless_remote/__init__.py

@@ -1,4 +0,0 @@
-# this is here so that django finds the checks.
-from paperless_remote.checks import check_remote_parser_configured
-
-__all__ = ["check_remote_parser_configured"]

src/paperless_remote/apps.py

@@ -1,14 +0,0 @@
-from django.apps import AppConfig
-
-from paperless_remote.signals import remote_consumer_declaration
-
-
-class PaperlessRemoteParserConfig(AppConfig):
-    name = "paperless_remote"
-
-    def ready(self):
-        from documents.signals import document_consumer_declaration
-
-        document_consumer_declaration.connect(remote_consumer_declaration)
-
-        AppConfig.ready(self)

src/paperless_remote/checks.py

@@ -1,17 +0,0 @@
-from django.conf import settings
-from django.core.checks import Error
-from django.core.checks import register
-
-
-@register()
-def check_remote_parser_configured(app_configs, **kwargs):
-    if settings.REMOTE_OCR_ENGINE == "azureai" and not (
-        settings.REMOTE_OCR_ENDPOINT and settings.REMOTE_OCR_API_KEY
-    ):
-        return [
-            Error(
-                "Azure AI remote parser requires endpoint and API key to be configured.",
-            ),
-        ]
-
-    return []

src/paperless_remote/parsers.py

@@ -1,113 +0,0 @@
-from pathlib import Path
-
-from django.conf import settings
-
-from paperless_tesseract.parsers import RasterisedDocumentParser
-
-
-class RemoteEngineConfig:
-    def __init__(
-        self,
-        engine: str,
-        api_key: str | None = None,
-        endpoint: str | None = None,
-    ):
-        self.engine = engine
-        self.api_key = api_key
-        self.endpoint = endpoint
-
-    def engine_is_valid(self):
-        valid = self.engine in ["azureai"] and self.api_key is not None
-        if self.engine == "azureai":
-            valid = valid and self.endpoint is not None
-        return valid
-
-
-class RemoteDocumentParser(RasterisedDocumentParser):
-    """
-    This parser uses a remote OCR engine to parse documents. Currently, it supports Azure AI Vision
-    as this is the only service that provides a remote OCR API with text-embedded PDF output.
-    """
-
-    logging_name = "paperless.parsing.remote"
-
-    def get_settings(self) -> RemoteEngineConfig:
-        """
-        Returns the configuration for the remote OCR engine, loaded from Django settings.
-        """
-        return RemoteEngineConfig(
-            engine=settings.REMOTE_OCR_ENGINE,
-            api_key=settings.REMOTE_OCR_API_KEY,
-            endpoint=settings.REMOTE_OCR_ENDPOINT,
-        )
-
-    def supported_mime_types(self):
-        if self.settings.engine_is_valid():
-            return {
-                "application/pdf": ".pdf",
-                "image/png": ".png",
-                "image/jpeg": ".jpg",
-                "image/tiff": ".tiff",
-                "image/bmp": ".bmp",
-                "image/gif": ".gif",
-                "image/webp": ".webp",
-            }
-        else:
-            return {}
-
-    def azure_ai_vision_parse(
-        self,
-        file: Path,
-    ) -> str | None:
-        """
-        Uses Azure AI Vision to parse the document and return the text content.
-        It requests a searchable PDF output with embedded text.
-        The PDF is saved to the archive_path attribute.
-        Returns the text content extracted from the document.
-        If the parsing fails, it returns None.
-        """
-        from azure.ai.documentintelligence import DocumentIntelligenceClient
-        from azure.ai.documentintelligence.models import AnalyzeDocumentRequest
-        from azure.ai.documentintelligence.models import AnalyzeOutputOption
-        from azure.ai.documentintelligence.models import DocumentContentFormat
-        from azure.core.credentials import AzureKeyCredential
-
-        client = DocumentIntelligenceClient(
-            endpoint=self.settings.endpoint,
-            credential=AzureKeyCredential(self.settings.api_key),
-        )
-
-        with file.open("rb") as f:
-            analyze_request = AnalyzeDocumentRequest(bytes_source=f.read())
-            poller = client.begin_analyze_document(
-                model_id="prebuilt-read",
-                body=analyze_request,
-                output_content_format=DocumentContentFormat.TEXT,
-                output=[AnalyzeOutputOption.PDF],  # request searchable PDF output
-                content_type="application/json",
-            )
-
-        poller.wait()
-        result_id = poller.details["operation_id"]
-        result = poller.result()
-
-        # Download the PDF with embedded text
-        self.archive_path = self.tempdir / "archive.pdf"
-        with self.archive_path.open("wb") as f:
-            for chunk in client.get_analyze_result_pdf(
-                model_id="prebuilt-read",
-                result_id=result_id,
-            ):
-                f.write(chunk)
-
-        client.close()
-        return result.content
-
-    def parse(self, document_path: Path, mime_type, file_name=None):
-        if not self.settings.engine_is_valid():
-            self.log.warning(
-                "No valid remote parser engine is configured, content will be empty.",
-            )
-            self.text = ""
-        elif self.settings.engine == "azureai":
-            self.text = self.azure_ai_vision_parse(document_path)

src/paperless_remote/signals.py

@@ -1,18 +0,0 @@
-def get_parser(*args, **kwargs):
-    from paperless_remote.parsers import RemoteDocumentParser
-
-    return RemoteDocumentParser(*args, **kwargs)
-
-
-def get_supported_mime_types():
-    from paperless_remote.parsers import RemoteDocumentParser
-
-    return RemoteDocumentParser(None).supported_mime_types()
-
-
-def remote_consumer_declaration(sender, **kwargs):
-    return {
-        "parser": get_parser,
-        "weight": 5,
-        "mime_types": get_supported_mime_types(),
-    }

src/paperless_remote/tests/test_checks.py

@@ -1,24 +0,0 @@
-from unittest import TestCase
-
-from django.test import override_settings
-
-from paperless_remote import check_remote_parser_configured
-
-
-class TestChecks(TestCase):
-    @override_settings(REMOTE_OCR_ENGINE=None)
-    def test_no_engine(self):
-        msgs = check_remote_parser_configured(None)
-        self.assertEqual(len(msgs), 0)
-
-    @override_settings(REMOTE_OCR_ENGINE="azureai")
-    @override_settings(REMOTE_OCR_API_KEY="somekey")
-    @override_settings(REMOTE_OCR_ENDPOINT=None)
-    def test_azure_no_endpoint(self):
-        msgs = check_remote_parser_configured(None)
-        self.assertEqual(len(msgs), 1)
-        self.assertTrue(
-            msgs[0].msg.startswith(
-                "Azure AI remote parser requires endpoint and API key to be configured.",
-            ),
-        )

src/paperless_remote/tests/test_parser.py

@@ -1,101 +0,0 @@
-import uuid
-from pathlib import Path
-from unittest import mock
-
-from django.test import TestCase
-from django.test import override_settings
-
-from documents.tests.utils import DirectoriesMixin
-from documents.tests.utils import FileSystemAssertsMixin
-from paperless_remote.parsers import RemoteDocumentParser
-from paperless_remote.signals import get_parser
-
-
-class TestParser(DirectoriesMixin, FileSystemAssertsMixin, TestCase):
-    SAMPLE_FILES = Path(__file__).resolve().parent / "samples"
-
-    def assertContainsStrings(self, content: str, strings: list[str]):
-        # Asserts that all strings appear in content, in the given order.
-        indices = []
-        for s in strings:
-            if s in content:
-                indices.append(content.index(s))
-            else:
-                self.fail(f"'{s}' is not in '{content}'")
-        self.assertListEqual(indices, sorted(indices))
-
-    @mock.patch("paperless_tesseract.parsers.run_subprocess")
-    @mock.patch("azure.ai.documentintelligence.DocumentIntelligenceClient")
-    def test_get_text_with_azure(self, mock_client_cls, mock_subprocess):
-        # Arrange mock Azure client
-        mock_client = mock.Mock()
-        mock_client_cls.return_value = mock_client
-
-        # Simulate poller result and its `.details`
-        mock_poller = mock.Mock()
-        mock_poller.wait.return_value = None
-        mock_poller.details = {"operation_id": "fake-op-id"}
-        mock_client.begin_analyze_document.return_value = mock_poller
-        mock_poller.result.return_value.content = "This is a test document."
-
-        # Return dummy PDF bytes
-        mock_client.get_analyze_result_pdf.return_value = [
-            b"%PDF-",
-            b"1.7 ",
-            b"FAKEPDF",
-        ]
-
-        # Simulate pdftotext by writing dummy text to sidecar file
-        def fake_run(cmd, *args, **kwargs):
-            with Path(cmd[-1]).open("w", encoding="utf-8") as f:
-                f.write("This is a test document.")
-
-        mock_subprocess.side_effect = fake_run
-
-        with override_settings(
-            REMOTE_OCR_ENGINE="azureai",
-            REMOTE_OCR_API_KEY="somekey",
-            REMOTE_OCR_ENDPOINT="https://endpoint.cognitiveservices.azure.com",
-        ):
-            parser = get_parser(uuid.uuid4())
-            parser.parse(
-                self.SAMPLE_FILES / "simple-digital.pdf",
-                "application/pdf",
-            )
-
-            self.assertContainsStrings(
-                parser.text.strip(),
-                ["This is a test document."],
-            )
-
-    @override_settings(
-        REMOTE_OCR_ENGINE="azureai",
-        REMOTE_OCR_API_KEY="key",
-        REMOTE_OCR_ENDPOINT="https://endpoint.cognitiveservices.azure.com",
-    )
-    def test_supported_mime_types_valid_config(self):
-        parser = RemoteDocumentParser(uuid.uuid4())
-        expected_types = {
-            "application/pdf": ".pdf",
-            "image/png": ".png",
-            "image/jpeg": ".jpg",
-            "image/tiff": ".tiff",
-            "image/bmp": ".bmp",
-            "image/gif": ".gif",
-            "image/webp": ".webp",
-        }
-        self.assertEqual(parser.supported_mime_types(), expected_types)
-
-    def test_supported_mime_types_invalid_config(self):
-        parser = get_parser(uuid.uuid4())
-        self.assertEqual(parser.supported_mime_types(), {})
-
-    @override_settings(
-        REMOTE_OCR_ENGINE=None,
-        REMOTE_OCR_API_KEY=None,
-        REMOTE_OCR_ENDPOINT=None,
-    )
-    def test_parse_with_invalid_config(self):
-        parser = get_parser(uuid.uuid4())
-        parser.parse(self.SAMPLE_FILES / "simple-digital.pdf", "application/pdf")
-        self.assertEqual(parser.text, "")

uv.lock

@@ -95,34 +95,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/02/ff/1175b0b7371e46244032d43a56862d0af455823b5280a50c63d99cc50f18/automat-25.4.16-py3-none-any.whl", hash = "sha256:04e9bce696a8d5671ee698005af6e5a9fa15354140a87f4870744604dcdd3ba1", size = 42842, upload-time = "2025-04-16T20:12:14.447Z" },
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