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https://github.com/paperless-ngx/paperless-ngx.git
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Test views, caching
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commit
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@ -1,6 +1,8 @@
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import tempfile
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from datetime import timedelta
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from pathlib import Path
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from unittest.mock import MagicMock
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from unittest.mock import patch
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from django.conf import settings
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from django.contrib.auth.models import Permission
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@ -10,8 +12,15 @@ from django.test import override_settings
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from django.utils import timezone
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from rest_framework import status
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from documents.caching import get_llm_suggestion_cache
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from documents.caching import set_llm_suggestions_cache
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from documents.models import Correspondent
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from documents.models import Document
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from documents.models import DocumentType
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from documents.models import ShareLink
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from documents.models import StoragePath
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from documents.models import Tag
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from documents.signals.handlers import update_llm_suggestions_cache
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from documents.tests.utils import DirectoriesMixin
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from paperless.models import ApplicationConfiguration
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@ -154,3 +163,104 @@ class TestViews(DirectoriesMixin, TestCase):
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response.render()
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self.assertEqual(response.request["PATH_INFO"], "/accounts/login/")
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self.assertContains(response, b"Share link has expired")
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class TestAISuggestions(DirectoriesMixin, TestCase):
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def setUp(self):
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self.user = User.objects.create_superuser(username="testuser")
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self.document = Document.objects.create(
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title="Test Document",
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filename="test.pdf",
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mime_type="application/pdf",
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)
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self.tag1 = Tag.objects.create(name="tag1")
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self.correspondent1 = Correspondent.objects.create(name="correspondent1")
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self.document_type1 = DocumentType.objects.create(name="type1")
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self.path1 = StoragePath.objects.create(name="path1")
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super().setUp()
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@patch("documents.views.get_llm_suggestion_cache")
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@patch("documents.views.refresh_suggestions_cache")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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)
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def test_suggestions_with_cached_llm(self, mock_refresh_cache, mock_get_cache):
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mock_get_cache.return_value = MagicMock(suggestions={"tags": ["tag1", "tag2"]})
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self.client.force_login(user=self.user)
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response = self.client.get(f"/api/documents/{self.document.pk}/suggestions/")
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self.assertEqual(response.status_code, status.HTTP_200_OK)
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self.assertEqual(response.json(), {"tags": ["tag1", "tag2"]})
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mock_refresh_cache.assert_called_once_with(self.document.pk)
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@patch("documents.views.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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)
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def test_suggestions_with_ai_enabled(
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self,
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mock_get_ai_classification,
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):
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mock_get_ai_classification.return_value = {
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"title": "AI Title",
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"tags": ["tag1", "tag2"],
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"correspondents": ["correspondent1"],
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"document_types": ["type1"],
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"storage_paths": ["path1"],
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"dates": ["2023-01-01"],
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}
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self.client.force_login(user=self.user)
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response = self.client.get(f"/api/documents/{self.document.pk}/suggestions/")
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self.assertEqual(response.status_code, status.HTTP_200_OK)
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self.assertEqual(
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response.json(),
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{
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"title": "AI Title",
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"tags": [self.tag1.pk],
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"suggested_tags": ["tag2"],
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"correspondents": [self.correspondent1.pk],
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"suggested_correspondents": [],
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"document_types": [self.document_type1.pk],
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"suggested_document_types": [],
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"storage_paths": [self.path1.pk],
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"suggested_storage_paths": [],
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"dates": ["2023-01-01"],
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},
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)
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def test_invalidate_suggestions_cache(self):
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self.client.force_login(user=self.user)
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suggestions = {
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"title": "AI Title",
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"tags": ["tag1", "tag2"],
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"correspondents": ["correspondent1"],
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"document_types": ["type1"],
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"storage_paths": ["path1"],
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"dates": ["2023-01-01"],
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}
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set_llm_suggestions_cache(
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self.document.pk,
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suggestions,
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backend="mock_backend",
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)
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self.assertEqual(
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get_llm_suggestion_cache(
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self.document.pk,
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backend="mock_backend",
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).suggestions,
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suggestions,
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)
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# post_save signal triggered
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update_llm_suggestions_cache(
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sender=None,
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instance=self.document,
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)
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self.assertIsNone(
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get_llm_suggestion_cache(
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self.document.pk,
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backend="mock_backend",
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),
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)
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@ -739,51 +739,57 @@ class DocumentViewSet(
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return HttpResponseForbidden("Insufficient permissions")
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if settings.AI_ENABLED:
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cached = get_llm_suggestion_cache(doc.pk, backend=settings.LLM_BACKEND)
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cached_llm_suggestions = get_llm_suggestion_cache(
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doc.pk,
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backend=settings.LLM_BACKEND,
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)
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if cached:
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if cached_llm_suggestions:
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refresh_suggestions_cache(doc.pk)
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return Response(cached.suggestions)
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return Response(cached_llm_suggestions.suggestions)
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llm_resp = get_ai_document_classification(doc)
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llm_suggestions = get_ai_document_classification(doc)
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matched_tags = match_tags_by_name(llm_resp.get("tags", []), request.user)
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matched_tags = match_tags_by_name(
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llm_suggestions.get("tags", []),
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request.user,
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)
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matched_correspondents = match_correspondents_by_name(
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llm_resp.get("correspondents", []),
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llm_suggestions.get("correspondents", []),
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request.user,
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)
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matched_types = match_document_types_by_name(
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llm_resp.get("document_types", []),
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llm_suggestions.get("document_types", []),
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request.user,
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)
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matched_paths = match_storage_paths_by_name(
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llm_resp.get("storage_paths", []),
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llm_suggestions.get("storage_paths", []),
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request.user,
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)
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resp_data = {
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"title": llm_resp.get("title"),
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"title": llm_suggestions.get("title"),
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"tags": [t.id for t in matched_tags],
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"suggested_tags": extract_unmatched_names(
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llm_resp.get("tags", []),
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llm_suggestions.get("tags", []),
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matched_tags,
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),
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"correspondents": [c.id for c in matched_correspondents],
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"suggested_correspondents": extract_unmatched_names(
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llm_resp.get("correspondents", []),
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llm_suggestions.get("correspondents", []),
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matched_correspondents,
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),
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"document_types": [d.id for d in matched_types],
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"suggested_document_types": extract_unmatched_names(
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llm_resp.get("document_types", []),
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llm_suggestions.get("document_types", []),
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matched_types,
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),
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"storage_paths": [s.id for s in matched_paths],
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"suggested_storage_paths": extract_unmatched_names(
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llm_resp.get("storage_paths", []),
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llm_suggestions.get("storage_paths", []),
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matched_paths,
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),
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"dates": llm_resp.get("dates", []),
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"dates": llm_suggestions.get("dates", []),
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}
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set_llm_suggestions_cache(doc.pk, resp_data, backend=settings.LLM_BACKEND)
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