ollama too

src/documents/bulk_edit.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 import logging
 import tempfile
-import uuid
 from pathlib import Path
 from typing import TYPE_CHECKING
 from typing import Literal
@@ -380,7 +379,7 @@ def delete(doc_ids: list[int]) -> Literal["OK"]:
         )
         delete_ids = list({*doc_ids, *version_ids})
 
-        Document.objects.filter(id__in=delete_ids).delete(transaction_id=uuid.uuid4())
+        Document.objects.filter(id__in=delete_ids).delete()
 
         from documents.search import get_backend
 

src/documents/models.py

@@ -1,5 +1,4 @@
 import datetime
-import uuid
 from pathlib import Path
 from typing import Final
 
@@ -515,20 +514,13 @@ class Document(SoftDeleteModel, ModelWithOwner):  # type: ignore[django-manager-
     def delete(
         self,
         *args,
-        transaction_id=None,
         **kwargs,
     ):
-        # Versions must share the root's transaction ID so they are restored
-        # together by django-softdelete.
-        if transaction_id is None:
-            transaction_id = uuid.uuid4()
+        # If deleting a root document, move all its versions to trash as well.
         if self.root_document_id is None:
-            Document.objects.filter(root_document=self).delete(
-                transaction_id=transaction_id,
-            )
+            Document.objects.filter(root_document=self).delete()
         return super().delete(
             *args,
-            transaction_id=transaction_id,
             **kwargs,
         )
 

src/documents/tests/test_api_trash.py

@@ -207,65 +207,3 @@ class TestTrashAPI(DirectoriesMixin, APITestCase):
         )
         self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
         self.assertIn("have not yet been deleted", resp.data["documents"][0])
-
-    def _make_versioned_document(self) -> tuple[Document, list[Document]]:
-        root = Document.objects.create(
-            title="root",
-            content="root-content",
-            checksum="root",
-            mime_type="application/pdf",
-        )
-        versions = [
-            Document.objects.create(
-                title=f"v{index}",
-                content=f"v{index}-content",
-                checksum=f"v{index}",
-                mime_type="application/pdf",
-                root_document=root,
-                version_index=index,
-            )
-            for index in range(1, 3)
-        ]
-        return root, versions
-
-    def test_api_trash_restore_document_restores_its_versions(self) -> None:
-        """
-        GIVEN:
-            - Existing document with two versions
-        WHEN:
-            - API request to delete the document
-            - API request to restore it from the trash
-        THEN:
-            - Only the document itself is listed in the trash
-            - A version cannot be restored without its root
-            - The document is restored together with all of its versions
-        """
-        root, versions = self._make_versioned_document()
-
-        self.client.force_login(user=self.user)
-        self.client.delete(f"/api/documents/{root.pk}/")
-        self.assertEqual(Document.deleted_objects.count(), 3)
-
-        resp = self.client.get("/api/trash/")
-        self.assertEqual(resp.status_code, status.HTTP_200_OK)
-        self.assertEqual(resp.data["count"], 1)
-        self.assertEqual(resp.data["results"][0]["id"], root.pk)
-
-        # A version cannot be restored while its root remains in the trash.
-        resp = self.client.post(
-            "/api/trash/",
-            {"action": "restore", "documents": [versions[0].pk]},
-        )
-        self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
-        self.assertIn("Restore the root document", resp.data["documents"][0])
-
-        resp = self.client.post(
-            "/api/trash/",
-            {"action": "restore", "documents": [root.pk]},
-        )
-        self.assertEqual(resp.status_code, status.HTTP_200_OK)
-        self.assertEqual(Document.deleted_objects.count(), 0)
-        self.assertCountEqual(
-            Document.objects.filter(root_document=root).values_list("id", flat=True),
-            [version.pk for version in versions],
-        )

src/documents/tests/test_bulk_edit.py

@@ -392,11 +392,6 @@ class TestBulkEdit(DirectoriesMixin, TestCase):
         self.assertFalse(Document.objects.filter(id=self.doc1.id).exists())
         self.assertFalse(Document.objects.filter(id=version.id).exists())
 
-        Document.deleted_objects.get(id=self.doc1.id).restore(strict=False)
-
-        self.assertTrue(Document.objects.filter(id=self.doc1.id).exists())
-        self.assertTrue(Document.objects.filter(id=version.id).exists())
-
     def test_delete_version_document_keeps_root(self) -> None:
         version = Document.objects.create(
             checksum="A-v1",

src/documents/tests/test_document_model.py

@@ -110,7 +110,7 @@ class TestDocument(TestCase):
             checksum="checksum",
             mime_type="application/pdf",
         )
-        version = Document.objects.create(
+        Document.objects.create(
             root_document=root,
             correspondent=root.correspondent,
             title="Version",
@@ -124,10 +124,6 @@ class TestDocument(TestCase):
         self.assertEqual(Document.objects.count(), 0)
         self.assertEqual(Document.deleted_objects.count(), 2)
 
-        root.restore(strict=False)
-
-        self.assertTrue(Document.objects.filter(pk=version.pk).exists())
-
     def test_file_name(self) -> None:
         doc = Document(
             mime_type="application/pdf",

src/documents/tests/test_views.py

@@ -32,6 +32,7 @@ from documents.signals.handlers import update_llm_suggestions_cache
 from documents.tests.utils import DirectoriesMixin
 from documents.tests.utils import read_streaming_response
 from paperless.models import ApplicationConfiguration
+from paperless_ai.exceptions import LLMProviderError
 from paperless_ai.exceptions import LLMTimeoutError
 
 
@@ -737,6 +738,38 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
             get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
         )
 
+    @patch("documents.views.get_ai_document_classification")
+    @override_settings(
+        AI_ENABLED=True,
+        LLM_BACKEND="openai-like",
+    )
+    def test_ai_suggestions_with_llm_provider_error(
+        self,
+        mock_get_ai_classification,
+    ) -> None:
+        mock_get_ai_classification.side_effect = LLMProviderError(
+            "confidential provider response",
+        )
+
+        self.client.force_login(user=self.user)
+        response = self.client.get(
+            f"/api/documents/{self.document.pk}/ai_suggestions/",
+        )
+
+        self.assertEqual(response.status_code, status.HTTP_502_BAD_GATEWAY)
+        self.assertEqual(
+            response.json(),
+            {
+                "ai": [
+                    "AI backend rejected the request. Check logs for details.",
+                ],
+            },
+        )
+        self.assertNotIn("confidential provider response", response.content.decode())
+        self.assertIsNone(
+            get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
+        )
+
     @patch("documents.views.get_ai_document_classification")
     @override_settings(
         AI_ENABLED=True,

src/documents/views.py

@@ -251,6 +251,7 @@ from paperless.views import StandardPagination
 from paperless_ai.ai_classifier import get_ai_document_classification
 from paperless_ai.ai_classifier import get_llm_output_language
 from paperless_ai.chat import stream_chat_with_documents
+from paperless_ai.exceptions import LLMProviderError
 from paperless_ai.exceptions import LLMTimeoutError
 from paperless_ai.matching import extract_unmatched_names
 from paperless_ai.matching import match_correspondents_by_name
@@ -1602,6 +1603,22 @@ class DocumentViewSet(
                     {"ai": [_("AI backend request timed out.")]},
                     status=status.HTTP_503_SERVICE_UNAVAILABLE,
                 )
+            except LLMProviderError:
+                logger.exception(
+                    "AI backend rejected the request for document %s",
+                    doc.pk,
+                )
+                return Response(
+                    {
+                        "ai": [
+                            _(
+                                "AI backend rejected the request. "
+                                "Check logs for details.",
+                            ),
+                        ],
+                    },
+                    status=status.HTTP_502_BAD_GATEWAY,
+                )
             set_llm_suggestions_cache(
                 doc.pk,
                 llm_suggestions,
@@ -5431,10 +5448,7 @@ class TrashView(ListModelMixin, PassUserMixin):
 
     model = Document
 
-    # A version is listed separately only when its root is not in the trash.
-    queryset = Document.deleted_objects.exclude(
-        root_document_id__in=Document.deleted_objects.values("id"),
-    )
+    queryset = Document.deleted_objects.all()
 
     def get(self, request: Request, format: str | None = None) -> Response:
         self.serializer_class = DocumentSerializer
@@ -5465,15 +5479,7 @@ class TrashView(ListModelMixin, PassUserMixin):
             return HttpResponseForbidden("Insufficient permissions")
         action = serializer.validated_data.get("action")
         if action == "restore":
-            restored = list(self.get_queryset().filter(id__in=doc_ids))
-            if len(restored) != len(doc_ids):
-                raise ValidationError(
-                    {
-                        "documents": [
-                            "Restore the root document instead of one of its versions.",
-                        ],
-                    },
-                )
+            restored = list(Document.deleted_objects.filter(id__in=doc_ids))
             for doc in restored:
                 doc.restore(strict=False)
             if restored:

src/paperless_ai/client.py

@@ -22,6 +22,7 @@ from paperless.network import validate_outbound_http_url
 from paperless_ai.base_model import ClassificationSuggestions
 from paperless_ai.base_model import DocumentClassifierSchema
 from paperless_ai.base_model import model_to_classification_suggestions
+from paperless_ai.exceptions import LLMProviderError
 from paperless_ai.exceptions import LLMTimeoutError
 
 logger = logging.getLogger("paperless_ai.client")
@@ -132,7 +133,7 @@ class AIClient:
         from llama_index.core.llms import ChatMessage
 
         if self.settings.llm_backend == LLMBackend.OLLAMA:
-            with self._normalize_timeouts():
+            with self._normalize_errors():
                 result = self.llm.chat(
                     [ChatMessage(role="user", content=prompt)],
                     format=DocumentClassifierSchema.model_json_schema(),
@@ -153,7 +154,7 @@ class AIClient:
             content=f"{prompt}\n\n"
             f"Answer by calling the {tool.metadata.name} tool. Do not write the answer as text.",
         )
-        with self._normalize_timeouts():
+        with self._normalize_errors():
             result = self.llm.chat_with_tools(
                 tools=[tool],
                 user_msg=user_msg,
@@ -173,7 +174,7 @@ class AIClient:
         )
 
     @contextmanager
-    def _normalize_timeouts(self) -> Iterator[None]:
+    def _normalize_errors(self) -> Iterator[None]:
         try:
             yield
         except httpx.TimeoutException as exc:
@@ -181,8 +182,23 @@ class AIClient:
         except Exception as exc:
             if self._is_openai_timeout(exc):
                 raise LLMTimeoutError from exc
+            if self._is_provider_error(exc):
+                raise LLMProviderError from exc
             raise
 
+    def _is_provider_error(self, exc: Exception) -> bool:
+        if self.settings.llm_backend == LLMBackend.OLLAMA:
+            from ollama import ResponseError
+
+            return isinstance(exc, ResponseError)
+
+        if self.settings.llm_backend == LLMBackend.OPENAI_LIKE:
+            from openai import APIStatusError
+
+            return isinstance(exc, APIStatusError)
+
+        return False
+
     def _is_openai_timeout(self, exc: Exception) -> bool:
         if self.settings.llm_backend != LLMBackend.OPENAI_LIKE:
             return False

src/paperless_ai/exceptions.py

@@ -1,2 +1,6 @@
 class LLMTimeoutError(Exception):
     pass
+
+
+class LLMProviderError(Exception):
+    """The LLM backend rejected the request."""

src/paperless_ai/tests/test_client.py

@@ -4,6 +4,7 @@ from unittest.mock import MagicMock
 from unittest.mock import patch
 
 import httpx
+import ollama
 import openai
 import pytest
 from llama_index.core.llms.llm import ToolSelection
@@ -11,6 +12,7 @@ from llama_index.core.llms.llm import ToolSelection
 from paperless_ai.client import LLM_SYSTEM_PROMPT
 from paperless_ai.client import PLACEHOLDER_API_KEY
 from paperless_ai.client import AIClient
+from paperless_ai.exceptions import LLMProviderError
 from paperless_ai.exceptions import LLMTimeoutError
 
 
@@ -214,6 +216,52 @@ def test_run_llm_query_openai_timeout_raises_local_error(
         client.run_llm_query("test_prompt")
 
 
+def test_run_llm_query_openai_status_error_raises_provider_error(
+    mock_ai_config,
+    mock_openai_llm,
+):
+    mock_ai_config.llm_backend = "openai-like"
+    mock_ai_config.llm_model = "test_model"
+    mock_ai_config.llm_endpoint = "http://test-url"
+
+    request = httpx.Request("POST", "http://test-url/v1/chat/completions")
+    body = {"error": {"message": "Thinking mode does not support this tool_choice"}}
+    mock_openai_llm.return_value.chat_with_tools.side_effect = openai.BadRequestError(
+        "Error code: 400",
+        response=httpx.Response(400, request=request, json=body),
+        body=body,
+    )
+
+    client = AIClient()
+
+    with pytest.raises(LLMProviderError) as exc_info:
+        client.run_llm_query("test_prompt")
+    assert str(exc_info.value) == ""
+    assert isinstance(exc_info.value.__cause__, openai.BadRequestError)
+
+
+def test_run_llm_query_ollama_response_error_raises_provider_error(
+    mock_ai_config,
+    mock_ollama_llm,
+):
+    mock_ai_config.llm_backend = "ollama"
+    mock_ai_config.llm_model = "test_model"
+    mock_ai_config.llm_endpoint = "http://test-url"
+
+    response_error = ollama.ResponseError(
+        "confidential provider response",
+        status_code=400,
+    )
+    mock_ollama_llm.return_value.chat.side_effect = response_error
+
+    client = AIClient()
+
+    with pytest.raises(LLMProviderError) as exc_info:
+        client.run_llm_query("test_prompt")
+    assert str(exc_info.value) == ""
+    assert exc_info.value.__cause__ is response_error
+
+
 def test_run_llm_query_httpx_timeout_raises_local_error(
     mock_ai_config,
     mock_ollama_llm,