chore: ignore redis lock not owned error (#29064)

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py

@@ -0,0 +1,177 @@
+import types
+from unittest.mock import Mock, create_autospec
+
+import pytest
+from redis.exceptions import LockNotOwnedError
+
+from models.account import Account
+from models.dataset import Dataset, Document
+from services.dataset_service import DocumentService, SegmentService
+
+
+class FakeLock:
+    """Lock that always fails on enter with LockNotOwnedError."""
+
+    def __enter__(self):
+        raise LockNotOwnedError("simulated")
+
+    def __exit__(self, exc_type, exc, tb):
+        # Normal contextmanager signature; return False so exceptions propagate
+        return False
+
+
+@pytest.fixture
+def fake_current_user(monkeypatch):
+    user = create_autospec(Account, instance=True)
+    user.id = "user-1"
+    user.current_tenant_id = "tenant-1"
+    monkeypatch.setattr("services.dataset_service.current_user", user)
+    return user
+
+
+@pytest.fixture
+def fake_features(monkeypatch):
+    """Features.billing.enabled == False to skip quota logic."""
+    features = types.SimpleNamespace(
+        billing=types.SimpleNamespace(enabled=False, subscription=types.SimpleNamespace(plan="ENTERPRISE")),
+        documents_upload_quota=types.SimpleNamespace(limit=10_000, size=0),
+    )
+    monkeypatch.setattr(
+        "services.dataset_service.FeatureService.get_features",
+        lambda tenant_id: features,
+    )
+    return features
+
+
+@pytest.fixture
+def fake_lock(monkeypatch):
+    """Patch redis_client.lock to always raise LockNotOwnedError on enter."""
+
+    def _fake_lock(name, timeout=None, *args, **kwargs):
+        return FakeLock()
+
+    # DatasetService imports redis_client directly from extensions.ext_redis
+    monkeypatch.setattr("services.dataset_service.redis_client.lock", _fake_lock)
+
+
+# ---------------------------------------------------------------------------
+# 1. Knowledge Pipeline document creation (save_document_with_dataset_id)
+# ---------------------------------------------------------------------------
+
+
+def test_save_document_with_dataset_id_ignores_lock_not_owned(
+    monkeypatch,
+    fake_current_user,
+    fake_features,
+    fake_lock,
+):
+    # Arrange
+    dataset = create_autospec(Dataset, instance=True)
+    dataset.id = "ds-1"
+    dataset.tenant_id = fake_current_user.current_tenant_id
+    dataset.data_source_type = "upload_file"
+    dataset.indexing_technique = "high_quality"  # so we skip re-initialization branch
+
+    # Minimal knowledge_config stub that satisfies pre-lock code
+    info_list = types.SimpleNamespace(data_source_type="upload_file")
+    data_source = types.SimpleNamespace(info_list=info_list)
+    knowledge_config = types.SimpleNamespace(
+        doc_form="qa_model",
+        original_document_id=None,  # go into "new document" branch
+        data_source=data_source,
+        indexing_technique="high_quality",
+        embedding_model=None,
+        embedding_model_provider=None,
+        retrieval_model=None,
+        process_rule=None,
+        duplicate=False,
+        doc_language="en",
+    )
+
+    account = fake_current_user
+
+    # Avoid touching real doc_form logic
+    monkeypatch.setattr("services.dataset_service.DatasetService.check_doc_form", lambda *a, **k: None)
+    # Avoid real DB interactions
+    monkeypatch.setattr("services.dataset_service.db", Mock())
+
+    # Act: this would hit the redis lock, whose __enter__ raises LockNotOwnedError.
+    # Our implementation should catch it and still return (documents, batch).
+    documents, batch = DocumentService.save_document_with_dataset_id(
+        dataset=dataset,
+        knowledge_config=knowledge_config,
+        account=account,
+    )
+
+    # Assert
+    # We mainly care that:
+    # - No exception is raised
+    # - The function returns a sensible tuple
+    assert isinstance(documents, list)
+    assert isinstance(batch, str)
+
+
+# ---------------------------------------------------------------------------
+# 2. Single-segment creation (add_segment)
+# ---------------------------------------------------------------------------
+
+
+def test_add_segment_ignores_lock_not_owned(
+    monkeypatch,
+    fake_current_user,
+    fake_lock,
+):
+    # Arrange
+    dataset = create_autospec(Dataset, instance=True)
+    dataset.id = "ds-1"
+    dataset.tenant_id = fake_current_user.current_tenant_id
+    dataset.indexing_technique = "economy"  # skip embedding/token calculation branch
+
+    document = create_autospec(Document, instance=True)
+    document.id = "doc-1"
+    document.dataset_id = dataset.id
+    document.word_count = 0
+    document.doc_form = "qa_model"
+
+    # Minimal args required by add_segment
+    args = {
+        "content": "question text",
+        "answer": "answer text",
+        "keywords": ["k1", "k2"],
+    }
+
+    # Avoid real DB operations
+    db_mock = Mock()
+    db_mock.session = Mock()
+    monkeypatch.setattr("services.dataset_service.db", db_mock)
+    monkeypatch.setattr("services.dataset_service.VectorService", Mock())
+
+    # Act
+    result = SegmentService.create_segment(args=args, document=document, dataset=dataset)
+
+    # Assert
+    # Under LockNotOwnedError except, add_segment should swallow the error and return None.
+    assert result is None
+
+
+# ---------------------------------------------------------------------------
+# 3. Multi-segment creation (multi_create_segment)
+# ---------------------------------------------------------------------------
+
+
+def test_multi_create_segment_ignores_lock_not_owned(
+    monkeypatch,
+    fake_current_user,
+    fake_lock,
+):
+    # Arrange
+    dataset = create_autospec(Dataset, instance=True)
+    dataset.id = "ds-1"
+    dataset.tenant_id = fake_current_user.current_tenant_id
+    dataset.indexing_technique = "economy"  # again, skip high_quality path
+
+    document = create_autospec(Document, instance=True)
+    document.id = "doc-1"
+    document.dataset_id = dataset.id
+    document.word_count = 0
+    document.doc_form = "qa_model"