Merge branch 'dev' into feature-remote-ocr-2

[ci skip]

docs/configuration.md

@@ -1759,6 +1759,11 @@ started by the container.
 
 : Path to an image file in the /media/logo directory, must include 'logo', e.g. `/logo/Atari_logo.svg`
 
+!!! note
+
+    The logo file will be viewable by anyone with access to the Paperless instance login page,
+    so consider your choice of logo carefully and removing exif data from images before uploading.
+
 #### [`PAPERLESS_ENABLE_UPDATE_CHECK=<bool>`](#PAPERLESS_ENABLE_UPDATE_CHECK) {#PAPERLESS_ENABLE_UPDATE_CHECK}
 
 !!! note
@@ -1800,3 +1805,23 @@ 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

@@ -25,9 +25,10 @@ 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.
+-   _Your_ data is stored locally on _your_ server and is never transmitted or shared in any way, unless you explicitly choose to do so.
 -   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.
+    -   Utilizes the open-source Tesseract engine to recognize more than 100 languages.
+    -   _New!_ Supports remote OCR with Azure AI (opt-in).
 -   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

@@ -878,6 +878,21 @@ 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

@@ -15,6 +15,7 @@ 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",
@@ -233,6 +234,7 @@ 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/manage/tag-list/tag-list.component.spec.ts

@@ -71,4 +71,20 @@ describe('TagListComponent', () => {
       'Do you really want to delete the tag "Tag1"?'
     )
   })
+
+  it('should filter out child tags if name filter is empty, otherwise show all', () => {
+    const tags = [
+      { id: 1, name: 'Tag1', parent: null },
+      { id: 2, name: 'Tag2', parent: 1 },
+      { id: 3, name: 'Tag3', parent: null },
+    ]
+    component['_nameFilter'] = null // Simulate empty name filter
+    const filtered = component.filterData(tags as any)
+    expect(filtered.length).toBe(2)
+    expect(filtered.find((t) => t.id === 2)).toBeUndefined()
+
+    component['_nameFilter'] = 'Tag2' // Simulate non-empty name filter
+    const filteredWithName = component.filterData(tags as any)
+    expect(filteredWithName.length).toBe(3)
+  })
 })

src-ui/src/app/components/manage/tag-list/tag-list.component.ts

@@ -62,6 +62,8 @@ export class TagListComponent extends ManagementListComponent<Tag> {
   }
 
   filterData(data: Tag[]) {
-    return data.filter((tag) => !tag.parent)
+    return this.nameFilter?.length
+      ? [...data]
+      : data.filter((tag) => !tag.parent)
   }
 }

src/documents/management/commands/document_consumer.py

@@ -82,6 +82,13 @@ def _is_ignored(filepath: Path) -> bool:
 
 
 def _consume(filepath: Path) -> None:
+    # Check permissions early
+    try:
+        filepath.stat()
+    except (PermissionError, OSError):
+        logger.warning(f"Not consuming file {filepath}: Permission denied.")
+        return
+
     if filepath.is_dir() or _is_ignored(filepath):
         return
 
@@ -323,7 +330,12 @@ class Command(BaseCommand):
 
                         # Also make sure the file exists still, some scanners might write a
                         # temporary file first
-                        file_still_exists = filepath.exists() and filepath.is_file()
+                        try:
+                            file_still_exists = filepath.exists() and filepath.is_file()
+                        except (PermissionError, OSError):  # pragma: no cover
+                            # If we can't check, let it fail in the _consume function
+                            file_still_exists = True
+                            continue
 
                         if waited_long_enough and file_still_exists:
                             _consume(filepath)

src/documents/tests/test_api_app_config.py

@@ -1,6 +1,4 @@
 import json
-from fractions import Fraction
-from io import BytesIO
 from pathlib import Path
 
 from django.contrib.auth.models import User
@@ -8,11 +6,6 @@ from django.core.files.uploadedfile import SimpleUploadedFile
 from rest_framework import status
 from rest_framework.test import APITestCase
 
-try:
-    from PIL import Image
-except ModuleNotFoundError:  # pragma: no cover - Pillow is required in production
-    Image = None  # type: ignore[assignment]
-
 from documents.tests.utils import DirectoriesMixin
 from paperless.models import ApplicationConfiguration
 from paperless.models import ColorConvertChoices
@@ -197,74 +190,6 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
         )
         self.assertFalse(Path(old_logo.path).exists())
 
-    def test_api_strips_metadata_from_logo_upload(self):
-        """
-        GIVEN:
-            - An image file containing EXIF metadata including GPS coordinates
-        WHEN:
-            - Uploaded via PATCH to app config
-        THEN:
-            - Stored logo no longer contains EXIF metadata
-        """
-        if Image is None:
-            self.skipTest("Pillow is not installed")
-
-        if not hasattr(Image, "Exif"):
-            self.skipTest("Current Pillow version cannot create EXIF metadata")
-
-        assert Image is not None
-
-        exif = Image.Exif()
-        exif[0x010E] = "Test description"  # ImageDescription
-        exif[0x8825] = {
-            1: "N",  # GPSLatitudeRef
-            2: (Fraction(51, 1), Fraction(30, 1), Fraction(0, 1)),
-            3: "E",  # GPSLongitudeRef
-            4: (Fraction(0, 1), Fraction(7, 1), Fraction(0, 1)),
-        }
-
-        buffer = BytesIO()
-        Image.new("RGB", (8, 8), "white").save(buffer, format="JPEG", exif=exif)
-        buffer.seek(0)
-
-        with Image.open(BytesIO(buffer.getvalue())) as uploaded_image:
-            self.assertGreater(len(uploaded_image.getexif()), 0)
-
-        response = self.client.patch(
-            f"{self.ENDPOINT}1/",
-            {
-                "app_logo": SimpleUploadedFile(
-                    name="with_exif.jpg",
-                    content=buffer.getvalue(),
-                    content_type="image/jpeg",
-                ),
-            },
-        )
-
-        self.assertEqual(response.status_code, status.HTTP_200_OK)
-
-        config = ApplicationConfiguration.objects.first()
-        stored_logo = Path(config.app_logo.path)
-        self.assertTrue(stored_logo.exists())
-
-        with Image.open(stored_logo) as sanitized:
-            sanitized_exif = sanitized.getexif()
-            self.assertNotEqual(sanitized_exif.get(0x010E), "Test description")
-
-            gps_ifd = None
-            if hasattr(sanitized_exif, "get_ifd"):
-                try:
-                    gps_ifd = sanitized_exif.get_ifd(0x8825)
-                except KeyError:
-                    gps_ifd = None
-            else:
-                gps_ifd = sanitized_exif.get(0x8825)
-
-            if gps_ifd is not None:
-                self.assertEqual(len(gps_ifd), 0, "GPS metadata should be cleared")
-
-            self.assertNotIn("exif", sanitized.info)
-
     def test_api_rejects_malicious_svg_logo(self):
         """
         GIVEN:

src/documents/tests/test_management_consumer.py

@@ -209,6 +209,26 @@ class TestConsumer(DirectoriesMixin, ConsumerThreadMixin, TransactionTestCase):
         # assert that we have an error logged with this invalid file.
         error_logger.assert_called_once()
 
+    @mock.patch("documents.management.commands.document_consumer.logger.warning")
+    def test_permission_error_on_prechecks(self, warning_logger):
+        filepath = Path(self.dirs.consumption_dir) / "selinux.txt"
+        filepath.touch()
+
+        original_stat = Path.stat
+
+        def raising_stat(self, *args, **kwargs):
+            if self == filepath:
+                raise PermissionError("Permission denied")
+            return original_stat(self, *args, **kwargs)
+
+        with mock.patch("pathlib.Path.stat", new=raising_stat):
+            document_consumer._consume(filepath)
+
+        warning_logger.assert_called_once()
+        (args, _) = warning_logger.call_args
+        self.assertIn("Permission denied", args[0])
+        self.consume_file_mock.assert_not_called()
+
     @override_settings(CONSUMPTION_DIR="does_not_exist")
     def test_consumption_directory_invalid(self):
         self.assertRaises(CommandError, call_command, "document_consumer", "--oneshot")

src/paperless/serialisers.py

@@ -1,5 +1,4 @@
 import logging
-from io import BytesIO
 
 import magic
 from allauth.mfa.adapter import get_adapter as get_mfa_adapter
@@ -10,10 +9,6 @@ from allauth.socialaccount.models import SocialApp
 from django.contrib.auth.models import Group
 from django.contrib.auth.models import Permission
 from django.contrib.auth.models import User
-from django.core.files.uploadedfile import SimpleUploadedFile
-from PIL import Image
-from PIL import ImageOps
-from PIL import UnidentifiedImageError
 from rest_framework import serializers
 from rest_framework.authtoken.serializers import AuthTokenSerializer
 
@@ -24,102 +19,6 @@ from paperless_mail.serialisers import ObfuscatedPasswordField
 logger = logging.getLogger("paperless.settings")
 
 
-def strip_image_metadata(uploaded_file, mime_type: str | None):
-    """Return a copy of ``uploaded_file`` with EXIF/ICC metadata removed."""
-
-    if uploaded_file is None:
-        return uploaded_file
-
-    original_position = uploaded_file.tell() if hasattr(uploaded_file, "tell") else None
-    image = None
-
-    sanitized = None
-
-    try:
-        if hasattr(uploaded_file, "seek"):
-            uploaded_file.seek(0)
-        image = Image.open(uploaded_file)
-        image.load()
-    except (UnidentifiedImageError, OSError):
-        if hasattr(uploaded_file, "seek") and original_position is not None:
-            uploaded_file.seek(original_position)
-        return uploaded_file
-
-    try:
-        image_format = (image.format or "").upper()
-        image = ImageOps.exif_transpose(image)
-
-        if image_format not in {"JPEG", "JPG", "PNG"}:
-            if hasattr(uploaded_file, "seek") and original_position is not None:
-                uploaded_file.seek(original_position)
-            return uploaded_file
-
-        if hasattr(image, "info"):
-            image.info.pop("exif", None)
-            image.info.pop("icc_profile", None)
-            image.info.pop("comment", None)
-
-        if image_format in {"JPEG", "JPG"}:
-            sanitized = image.convert("RGB")
-            save_kwargs = {
-                "format": "JPEG",
-                "quality": 95,
-                "subsampling": 0,
-                "optimize": True,
-                "exif": b"",
-            }
-        else:  # PNG
-            target_mode = (
-                "RGBA"
-                if ("A" in image.mode or image.info.get("transparency"))
-                else "RGB"
-            )
-            sanitized = image.convert(target_mode)
-            save_kwargs = {
-                "format": "PNG",
-                "optimize": True,
-            }
-
-        buffer = BytesIO()
-        try:
-            sanitized.save(buffer, **save_kwargs)
-        except (OSError, ValueError):
-            buffer = BytesIO()
-            if image_format in {"JPEG", "JPG"}:
-                sanitized.save(
-                    buffer,
-                    format="JPEG",
-                    quality=90,
-                    subsampling=0,
-                    exif=b"",
-                )
-            else:
-                sanitized.save(
-                    buffer,
-                    format="PNG",
-                )
-
-        buffer.seek(0)
-
-        if hasattr(uploaded_file, "close"):
-            try:
-                uploaded_file.close()
-            except Exception:
-                pass
-
-        content_type = getattr(uploaded_file, "content_type", None) or mime_type
-        return SimpleUploadedFile(
-            name=getattr(uploaded_file, "name", "logo"),
-            content=buffer.getvalue(),
-            content_type=content_type,
-        )
-    finally:
-        if sanitized is not None:
-            sanitized.close()
-        if image is not None:
-            image.close()
-
-
 class PaperlessAuthTokenSerializer(AuthTokenSerializer):
     code = serializers.CharField(
         label="MFA Code",
@@ -310,22 +209,9 @@ class ApplicationConfigurationSerializer(serializers.ModelSerializer):
         return super().update(instance, validated_data)
 
     def validate_app_logo(self, file):
-        if not file:
+        if file and magic.from_buffer(file.read(2048), mime=True) == "image/svg+xml":
-            return file
-
-        if hasattr(file, "seek"):
-            file.seek(0)
-        mime_type = magic.from_buffer(file.read(2048), mime=True)
-        if hasattr(file, "seek"):
-            file.seek(0)
-
-        if mime_type == "image/svg+xml":
             reject_dangerous_svg(file)
-            if hasattr(file, "seek"):
+        return file
-                file.seek(0)
-            return file
-
-        return strip_image_metadata(file, mime_type)
 
     class Meta:
         model = ApplicationConfiguration

src/paperless/settings.py

@@ -322,6 +322,7 @@ 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",
@@ -1389,3 +1390,10 @@ 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

@@ -0,0 +1,4 @@
+# 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

@@ -0,0 +1,14 @@
+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

@@ -0,0 +1,17 @@
+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

@@ -0,0 +1,113 @@
+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

@@ -0,0 +1,18 @@
+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

@@ -0,0 +1,24 @@
+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

@@ -0,0 +1,101 @@
+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

@@ -95,6 +95,34 @@ 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 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d9/75/c9ec040f23082f54ffb1977ff8f364c2d21c79a640a13d1c1809e7fd6b1a/azure_ai_documentintelligence-1.0.2-py3-none-any.whl", hash = "sha256:e1fb446abbdeccc9759d897898a0fe13141ed29f9ad11fc705f951925822ed59", size = 106005 },
+]
+
+[[package]]
+name = "azure-core"
+version = "1.33.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "requests", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
+    { name = "six", 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/75/aa/7c9db8edd626f1a7d99d09ef7926f6f4fb34d5f9fa00dc394afdfe8e2a80/azure_core-1.33.0.tar.gz", hash = "sha256:f367aa07b5e3005fec2c1e184b882b0b039910733907d001c20fb08ebb8c0eb9", size = 295633 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/07/b7/76b7e144aa53bd206bf1ce34fa75350472c3f69bf30e5c8c18bc9881035d/azure_core-1.33.0-py3-none-any.whl", hash = "sha256:9b5b6d0223a1d38c37500e6971118c1e0f13f54951e6893968b38910bc9cda8f", size = 207071 },
+]
+
 [[package]]
 name = "babel"
 version = "2.17.0"
@@ -1412,6 +1440,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c7/fc/4e5a141c3f7c7bed550ac1f69e599e92b6be449dd4677ec09f325cad0955/inotifyrecursive-0.3.5-py3-none-any.whl", hash = "sha256:7e5f4a2e1dc2bef0efa3b5f6b339c41fb4599055a2b54909d020e9e932cc8d2f", size = 8009, upload-time = "2020-11-20T12:38:46.981Z" },
 ]
 
+[[package]]
+name = "isodate"
+version = "0.7.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/54/4d/e940025e2ce31a8ce1202635910747e5a87cc3a6a6bb2d00973375014749/isodate-0.7.2.tar.gz", hash = "sha256:4cd1aa0f43ca76f4a6c6c0292a85f40b35ec2e43e315b59f06e6d32171a953e6", size = 29705 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/15/aa/0aca39a37d3c7eb941ba736ede56d689e7be91cab5d9ca846bde3999eba6/isodate-0.7.2-py3-none-any.whl", hash = "sha256:28009937d8031054830160fce6d409ed342816b543597cece116d966c6d99e15", size = 22320 },
+]
+
 [[package]]
 name = "jinja2"
 version = "3.1.6"
@@ -2032,6 +2069,7 @@ name = "paperless-ngx"
 version = "2.18.4"
 source = { virtual = "." }
 dependencies = [
+    { name = "azure-ai-documentintelligence", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "babel", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "bleach", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "celery", extra = ["redis"], marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
@@ -2169,6 +2207,7 @@ typing = [
 
 [package.metadata]
 requires-dist = [
+    { name = "azure-ai-documentintelligence", specifier = ">=1.0.2" },
     { name = "babel", specifier = ">=2.17" },
     { name = "bleach", specifier = "~=6.2.0" },
     { name = "celery", extras = ["redis"], specifier = "~=5.5.1" },