Just messing around

[ci skip]

.codecov.yml

@@ -10,8 +10,10 @@ component_management:
       paths:
         - src-ui/**
 # https://docs.codecov.com/docs/pull-request-comments
+# codecov will only comment if coverage changes
 comment:
   layout: "header, diff, components, flags, files"
+  require_changes: true
   # https://docs.codecov.com/docs/javascript-bundle-analysis
   require_bundle_changes: true
   bundle_change_threshold: "50Kb"

docs/configuration.md

@@ -1800,23 +1800,3 @@ 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/troubleshooting.md

@@ -33,7 +33,7 @@ warns that
 `OCR for XX failed, but we're going to stick with what we've got since FORGIVING_OCR is enabled`,
 then you might need to install the [Tesseract language
 files](https://packages.ubuntu.com/search?keywords=tesseract-ocr)
-matching your document's languages.
+marching your document's languages.
 
 As an example, if you are running Paperless-ngx from any Ubuntu or
 Debian box, and your documents are written in Spanish you may need to

docs/usage.md

@@ -850,21 +850,6 @@ 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",
@@ -240,7 +239,6 @@ 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/dates-dropdown/dates-dropdown.component.html

@@ -11,7 +11,7 @@
         <div class="selected-icon">
           @if (createdRelativeDate) {
             <a class="text-light focus-variants" href="javascript:void(0)" (click)="clearCreatedRelativeDate()">
-              <i-bs width="1em" height="1em" name="check" class="variant-unfocused text-dark"></i-bs>
+              <i-bs width="1em" height="1em" name="check" class="variant-unfocused"></i-bs>
               <i-bs width="1em" height="1em" name="x" class="variant-focused text-primary"></i-bs>
             </a>
           }

src-ui/src/app/services/settings.service.ts

@@ -444,6 +444,12 @@ export class SettingsService {
       )
     }
 
+    this._renderer.setAttribute(
+      this.document.documentElement,
+      'data-bs-theme',
+      'dark-flat'
+    )
+
     if (themeColor?.length) {
       const hsl = hexToHsl(themeColor)
       const bgBrightnessEstimate = estimateBrightnessForColor(themeColor)

src-ui/src/theme.scss

@@ -349,3 +349,52 @@ $form-check-radio-checked-bg-image-dark: url("data:image/svg+xml,<svg xmlns='htt
   }
 
 }
+
+[data-bs-theme="dark-flat"] {
+  body:not(.primary-light):not(.primary-dark) {
+    @include paperless-green-dark-mode;
+
+    .navbar.bg-primary {
+      // navbar is og green in dark mode
+      @include paperless-green;
+    }
+  }
+
+  @include dark-mode;
+
+  .btn-outline-primary, .btn-outline-secondary {
+    border-color: var(--pngx-bg-alt) !important;
+    background-color: var(--pngx-bg-alt) !important;
+    color: var(--bs-body-color) !important;
+  }
+
+  .btn-outline-secondary:hover, .btn-outline-secondary:focus, .btn-outline-secondary:active, .btn-outline-secondary.active {
+    background-color: var(--pngx-bg-darker) !important;
+    color: var(--pngx-body-color-accent) !important;
+  }
+
+  .btn-outline-danger {
+    border-color: var(--pngx-bg-alt) !important;
+    background-color: var(--pngx-bg-alt) !important;
+    color: var(--bs-danger) !important;
+
+    &:hover, &:focus, &.active, &:active {
+      background-color: var(--pngx-bg-darker) !important;
+      color: var(--bs-danger) !important;
+    }
+  }
+
+  .form-control:not(.btn), input, select, textarea,
+  .form-select:not(.is-invalid):not(:disabled), .form-check-input,
+  .ng-select .ng-select-container {
+    background-color: var(--pngx-bg-darker) !important;
+    color: var(--bs-body-color) !important;
+    border-color: var(--pngx-bg-alt) !important;
+  }
+
+  .input-group .input-group-text {
+    background-color: var(--pngx-bg-alt);
+    color: var(--bs-body-color);
+    border-color: var(--pngx-bg-alt);
+  }
+}

src/documents/views.py

@@ -2836,11 +2836,6 @@ class SystemStatusView(PassUserMixin):
         last_trained_task = (
             PaperlessTask.objects.filter(
                 task_name=PaperlessTask.TaskName.TRAIN_CLASSIFIER,
-                status__in=[
-                    states.SUCCESS,
-                    states.FAILURE,
-                    states.REVOKED,
-                ],  # ignore running tasks
             )
             .order_by("-date_done")
             .first()
@@ -2850,7 +2845,7 @@ class SystemStatusView(PassUserMixin):
         if last_trained_task is None:
             classifier_status = "WARNING"
             classifier_error = "No classifier training tasks found"
-        elif last_trained_task and last_trained_task.status != states.SUCCESS:
+        elif last_trained_task and last_trained_task.status == states.FAILURE:
             classifier_status = "ERROR"
             classifier_error = last_trained_task.result
         classifier_last_trained = (
@@ -2860,11 +2855,6 @@ class SystemStatusView(PassUserMixin):
         last_sanity_check = (
             PaperlessTask.objects.filter(
                 task_name=PaperlessTask.TaskName.CHECK_SANITY,
-                status__in=[
-                    states.SUCCESS,
-                    states.FAILURE,
-                    states.REVOKED,
-                ],  # ignore running tasks
             )
             .order_by("-date_done")
             .first()
@@ -2874,7 +2864,7 @@ class SystemStatusView(PassUserMixin):
         if last_sanity_check is None:
             sanity_check_status = "WARNING"
             sanity_check_error = "No sanity check tasks found"
-        elif last_sanity_check and last_sanity_check.status != states.SUCCESS:
+        elif last_sanity_check and last_sanity_check.status == states.FAILURE:
             sanity_check_status = "ERROR"
             sanity_check_error = last_sanity_check.result
         sanity_check_last_run = (

src/paperless/settings.py

@@ -324,7 +324,6 @@ 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",
@@ -1206,8 +1205,8 @@ def _ocr_to_dateparser_languages(ocr_languages: str) -> list[str]:
 
             language_part = ocr_to_dateparser.get(ocr_lang_part)
             if language_part is None:
-                logger.debug(
-                    f'Unable to map OCR language "{ocr_lang_part}" to dateparser locale. ',
+                logger.warning(
+                    f'Skipping unknown OCR language "{ocr_language}" — no dateparser equivalent.',
                 )
                 continue
 
@@ -1220,7 +1219,7 @@ def _ocr_to_dateparser_languages(ocr_languages: str) -> list[str]:
                 try:
                     loader.get_locale_map(locales=[dateparser_language])
                 except Exception:
-                    logger.info(
+                    logger.warning(
                         f"Language variant '{dateparser_language}' not supported by dateparser; falling back to base language '{language_part}'. You can manually set PAPERLESS_DATE_PARSER_LANGUAGES if needed.",
                     )
                     dateparser_language = language_part
@@ -1230,12 +1229,12 @@ def _ocr_to_dateparser_languages(ocr_languages: str) -> list[str]:
                 result.append(dateparser_language)
     except Exception as e:
         logger.warning(
-            f"Error auto-configuring dateparser languages. Set PAPERLESS_DATE_PARSER_LANGUAGES parameter to avoid this. Detail: {e}",
+            f"Could not configure dateparser languages. Set PAPERLESS_DATE_PARSER_LANGUAGES parameter to avoid this. Detail: {e}",
         )
         return []
     if not result:
-        logger.info(
-            "Unable to automatically determine dateparser languages from OCR_LANGUAGE, falling back to multi-language support.",
+        logger.warning(
+            "Could not configure any dateparser languages from OCR_LANGUAGE — fallback to autodetection.",
         )
     return result
 
@@ -1444,10 +1443,3 @@ 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

@@ -1,15 +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:
-        return [
-            Error(
-                "Azure AI remote parser requires endpoint 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 = 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)
-
-        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 = ""
-            return
-        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

@@ -1,29 +0,0 @@
-from django.test 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 to be configured.",
-            ),
-        )
-
-    @override_settings(REMOTE_OCR_ENGINE="something")
-    @override_settings(REMOTE_OCR_API_KEY="somekey")
-    def test_valid_configuration(self):
-        msgs = check_remote_parser_configured(None)
-        self.assertEqual(len(msgs), 0)

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, strings):
-        # 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/af/cc/55a32a2c98022d88812b5986d2a92c4ff3ee087e83b712ebc703bba452bf/Automat-24.8.1-py3-none-any.whl", hash = "sha256:bf029a7bc3da1e2c24da2343e7598affaa9f10bf0ab63ff808566ce90551e02a", size = 42585, upload-time = "2024-08-19T17:31:56.729Z" },
 ]
 
-[[package]]
-name = "azure-ai-documentintelligence"
-version = "1.0.2"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "azure-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
-    { name = "isodate", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
-    { name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/44/7b/8115cd713e2caa5e44def85f2b7ebd02a74ae74d7113ba20bdd41fd6dd80/azure_ai_documentintelligence-1.0.2.tar.gz", hash = "sha256:4d75a2513f2839365ebabc0e0e1772f5601b3a8c9a71e75da12440da13b63484", size = 170940 }
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