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This actually works
[ci skip]
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@ -317,6 +317,7 @@ INSTALLED_APPS = [
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"paperless_tesseract.apps.PaperlessTesseractConfig",
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"paperless_text.apps.PaperlessTextConfig",
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"paperless_mail.apps.PaperlessMailConfig",
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"paperless_remote.apps.PaperlessRemoteParserConfig",
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"django.contrib.admin",
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"rest_framework",
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"rest_framework.authtoken",
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@ -64,6 +64,7 @@ class RemoteDocumentParser(RasterisedDocumentParser):
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This method uses the Azure AI Vision API to parse documents
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"""
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from azure.ai.documentintelligence import DocumentIntelligenceClient
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from azure.ai.documentintelligence.models import AnalyzeDocumentRequest
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from azure.core.credentials import AzureKeyCredential
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client = DocumentIntelligenceClient(
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@ -72,19 +73,25 @@ class RemoteDocumentParser(RasterisedDocumentParser):
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)
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with file.open("rb") as f:
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analyze_request = AnalyzeDocumentRequest(bytes_source=f.read())
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poller = client.begin_analyze_document(
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model_id="prebuilt-read",
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analyze_request=f,
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content_type="application/octet-stream",
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output_format="pdf",
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body=analyze_request,
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output=["pdf"], # request searchable PDF output
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content_type="application/json",
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)
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result = poller.result()
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poller.wait()
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result_id = poller.details["operation_id"]
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# Download the PDF with embedded text
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pdf_bytes = client.get_analyze_result_pdf(result.result_id)
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self.archive_path = Path(self.tempdir) / "archive.pdf"
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self.archive_path.write_bytes(pdf_bytes)
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with self.archive_path.open("wb") as f:
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for chunk in client.get_analyze_result_pdf(
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model_id="prebuilt-read",
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result_id=result_id,
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):
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f.write(chunk)
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with tempfile.NamedTemporaryFile(delete=False, suffix=".txt") as tmp:
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subprocess.run(
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@ -96,7 +103,7 @@ class RemoteDocumentParser(RasterisedDocumentParser):
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tmp.name,
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],
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)
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with Path.open(tmp.name, encoding="utf-8") as t:
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with Path(tmp.name).open(encoding="utf-8") as t:
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return t.read()
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def parse(self, document_path: Path, mime_type, file_name=None):
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