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Author SHA1 Message Date
shamoon
d960aa2699
Use output_content_format poller.result to get clean content 2025-06-17 14:51:49 -07:00
shamoon
0fd6d40b37
Some docs 2025-06-17 14:51:49 -07:00
shamoon
c9f724d417
Test 2025-06-17 14:51:48 -07:00
shamoon
4b2c986cb3
This actually works
[ci skip]
2025-06-17 14:51:48 -07:00
shamoon
e2a2705d23
Basic parse 2025-06-17 14:51:48 -07:00
shamoon
ea63481cd4
Ok, restart implementing this with just azure
[ci skip]
2025-06-17 14:51:45 -07:00
14 changed files with 336 additions and 0 deletions

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@ -1708,3 +1708,23 @@ 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.

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@ -841,6 +841,18 @@ how regularly you intend to scan documents and use paperless.
performed the task associated with the document, move it to the
inbox.
## Remove 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.
## Architecture
Paperless-ngx consists of the following components:

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@ -15,6 +15,7 @@ classifiers = [
# This will allow testing to not install a webserver, mysql, etc
dependencies = [
"azure-ai-documentintelligence>=1.0.2",
"bleach~=6.2.0",
"celery[redis]~=5.5.1",
"channels~=4.2",

View File

@ -317,6 +317,7 @@ 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",
@ -1277,3 +1278,11 @@ OUTLOOK_OAUTH_ENABLED = bool(
and OUTLOOK_OAUTH_CLIENT_ID
and OUTLOOK_OAUTH_CLIENT_SECRET,
)
###############################################################################
# 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")

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@ -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"]

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@ -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)

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@ -0,0 +1,15 @@
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 []

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@ -0,0 +1,108 @@
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
"""
logging_name = "paperless.parsing.remote"
def get_settings(self) -> RemoteEngineConfig:
"""
This parser uses the OCR configuration settings to parse documents
"""
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",
"image/png",
"image/jpeg",
"image/tiff",
"image/bmp",
"image/gif",
"image/webp",
]
else:
return []
def azure_ai_vision_parse(
self,
file: Path,
) -> str | None:
"""
This method uses the Azure AI Vision API to parse documents
"""
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)

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@ -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(),
}

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@ -0,0 +1,29 @@
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 Vision 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)

View File

@ -0,0 +1,67 @@
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
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_remote.parsers.subprocess.run")
@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
# 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 = RemoteDocumentParser(uuid.uuid4())
parser.parse(
self.SAMPLE_FILES / "simple-digital.pdf",
"application/pdf",
)
self.assertContainsStrings(
parser.text.strip(),
["This is a test document."],
)

39
uv.lock generated
View File

@ -93,6 +93,34 @@ 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"
@ -1355,6 +1383,15 @@ 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"
@ -1883,6 +1920,7 @@ name = "paperless-ngx"
version = "2.16.3"
source = { virtual = "." }
dependencies = [
{ name = "azure-ai-documentintelligence", 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'" },
{ name = "channels", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
@ -2013,6 +2051,7 @@ typing = [
[package.metadata]
requires-dist = [
{ name = "azure-ai-documentintelligence", specifier = ">=1.0.2" },
{ name = "bleach", specifier = "~=6.2.0" },
{ name = "celery", extras = ["redis"], specifier = "~=5.5.1" },
{ name = "channels", specifier = "~=4.2" },