Fix pr-bot timing

.github/workflows/issue-bot.yml

@@ -72,7 +72,7 @@ jobs:
                 'You are welcome to open a new issue that describes the problem you observed in your own words.'
               : 'This issue was automatically closed because it was not opened using our bug report form. ' +
                 'Issues have to be created through the form so that the details we need to investigate are included.\n\n' +
-                `If the problem is still there, please [open a new issue](${newIssue}) using the form. No other action is needed here.\n\n' +
+                `If the problem is still there, please [open a new issue](${newIssue}) using the form. No other action is needed here.\n\n` +
                 'If any part of your report was written by an AI tool or agent, you must say so: undisclosed AI-generated ' +
                 `contributions are a violation of our [Code of Conduct](${codeOfConduct}).`;
 

.github/workflows/pr-bot.yml

@@ -25,6 +25,10 @@ jobs:
   pr-bot:
     name: Automated PR Bot
     runs-on: ubuntu-latest
+    # Runs after Anti-slop so the welcome comment can see whether the PR was closed
+    # instead of racing it. Still runs if that job fails, so labeling is not lost.
+    needs: Anti-slop
+    if: ${{ !cancelled() }}
     permissions:
       contents: read
       pull-requests: write
@@ -99,8 +103,25 @@ jobs:
         uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
         with:
           script: |
-            const pr = context.payload.pull_request;
-            const user = pr.user.login;
+            const user = context.payload.pull_request.user.login;
+
+            // Re-read the PR: Anti-slop may have closed and labeled it after the webhook
+            const { data: pr } = await github.rest.pulls.get({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              pull_number: context.payload.pull_request.number,
+            });
+
+            if (pr.state === 'closed') {
+              core.info('Skipping comment: PR is already closed');
+              return;
+            }
+
+            const labels = pr.labels.map((label) => (typeof label === 'string' ? label : label.name));
+            if (labels.includes('ai')) {
+              core.info('Skipping comment: PR is labeled ai');
+              return;
+            }
 
             const { data: members } = await github.rest.orgs.listMembers({
               org: 'paperless-ngx',

src/documents/tests/test_views.py

@@ -32,7 +32,6 @@ 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
 
 
@@ -738,38 +737,6 @@ 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

@@ -251,7 +251,6 @@ 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
@@ -1603,22 +1602,6 @@ 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,

src/paperless_ai/client.py

@@ -22,7 +22,6 @@ 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")
@@ -133,7 +132,7 @@ class AIClient:
         from llama_index.core.llms import ChatMessage
 
         if self.settings.llm_backend == LLMBackend.OLLAMA:
-            with self._normalize_errors():
+            with self._normalize_timeouts():
                 result = self.llm.chat(
                     [ChatMessage(role="user", content=prompt)],
                     format=DocumentClassifierSchema.model_json_schema(),
@@ -154,7 +153,7 @@ 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_errors():
+        with self._normalize_timeouts():
             result = self.llm.chat_with_tools(
                 tools=[tool],
                 user_msg=user_msg,
@@ -174,7 +173,7 @@ class AIClient:
         )
 
     @contextmanager
-    def _normalize_errors(self) -> Iterator[None]:
+    def _normalize_timeouts(self) -> Iterator[None]:
         try:
             yield
         except httpx.TimeoutException as exc:
@@ -182,23 +181,8 @@ 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

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

src/paperless_ai/tests/test_client.py

@@ -4,7 +4,6 @@ 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
@@ -12,7 +11,6 @@ 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
 
 
@@ -216,52 +214,6 @@ 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,