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Author SHA1 Message Date
shamoon
52c43cb1bd
Some docs 2025-06-04 08:32:14 -07:00
shamoon
569ce5d264
Test 2025-06-04 08:32:13 -07:00
shamoon
42abeced39
This actually works
[ci skip]
2025-06-04 08:32:13 -07:00
shamoon
5e495e716d
Basic parse 2025-06-04 08:32:12 -07:00
shamoon
b49113872f
Ok, restart implementing this with just azure
[ci skip]
2025-06-04 08:32:10 -07:00
14 changed files with 345 additions and 0 deletions

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@ -1706,3 +1706,23 @@ 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",
@ -1276,3 +1277,11 @@ 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 +1,117 @@
import subprocess
import tempfile
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.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=["pdf"], # request searchable PDF output
content_type="application/json",
)
poller.wait()
result_id = poller.details["operation_id"]
# 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)
with tempfile.NamedTemporaryFile(delete=False, suffix=".txt") as tmp:
subprocess.run(
[
"pdftotext",
"-q",
"-layout",
str(self.archive_path),
tmp.name,
],
)
with Path(tmp.name).open(encoding="utf-8") as t:
return t.read()
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 = "2.16.2"
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" },