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test: replace indexing_technique string literals with IndexTechnique (#34042)

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tmimmanuel
2026-03-25 04:39:58 +01:00
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parent cb28885205
commit a946015ebf
15 changed files with 120 additions and 114 deletions
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13
api/tests/unit_tests/core/rag/indexing/processor/test_paragraph_index_processor.py
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@ -4,6 +4,7 @@ from unittest.mock import Mock, patch
import pytest
from core.entities.knowledge_entities import PreviewDetail
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from core.rag.index_processor.processor.paragraph_index_processor import ParagraphIndexProcessor
from core.rag.models.document import AttachmentDocument, Document
from dify_graph.model_runtime.entities.llm_entities import LLMResult, LLMUsage
@ -21,7 +22,7 @@ class TestParagraphIndexProcessor:
dataset = Mock()
dataset.id = "dataset-1"
dataset.tenant_id = "tenant-1"
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.is_multimodal = True
return dataset
@ -167,7 +168,7 @@ class TestParagraphIndexProcessor:
def test_load_uses_keyword_add_texts_with_keywords_when_economy(
self, processor: ParagraphIndexProcessor, dataset: Mock
) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
docs = [Document(page_content="chunk", metadata={})]
with patch("core.rag.index_processor.processor.paragraph_index_processor.Keyword") as mock_keyword_cls:
@ -178,7 +179,7 @@ class TestParagraphIndexProcessor:
def test_load_uses_keyword_add_texts_without_keywords_when_economy(
self, processor: ParagraphIndexProcessor, dataset: Mock
) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
docs = [Document(page_content="chunk", metadata={})]
with patch("core.rag.index_processor.processor.paragraph_index_processor.Keyword") as mock_keyword_cls:
@ -208,7 +209,7 @@ class TestParagraphIndexProcessor:
def test_clean_economy_deletes_summaries_and_keywords(
self, processor: ParagraphIndexProcessor, dataset: Mock
) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
with (
patch(
@ -222,7 +223,7 @@ class TestParagraphIndexProcessor:
mock_keyword_cls.return_value.delete.assert_called_once()
def test_clean_deletes_keywords_by_ids(self, processor: ParagraphIndexProcessor, dataset: Mock) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
with patch("core.rag.index_processor.processor.paragraph_index_processor.Keyword") as mock_keyword_cls:
processor.clean(dataset, ["node-2"], with_keywords=True)
@ -267,7 +268,7 @@ class TestParagraphIndexProcessor:
def test_index_list_chunks_economy(
self, processor: ParagraphIndexProcessor, dataset: Mock, dataset_document: Mock
) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
with (
patch(
"core.rag.index_processor.processor.paragraph_index_processor.helper.generate_text_hash",

3
api/tests/unit_tests/core/rag/indexing/processor/test_parent_child_index_processor.py
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@ -4,6 +4,7 @@ from unittest.mock import MagicMock, Mock, patch
import pytest
from core.entities.knowledge_entities import PreviewDetail
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from core.rag.index_processor.processor.parent_child_index_processor import ParentChildIndexProcessor
from core.rag.models.document import AttachmentDocument, ChildDocument, Document
from services.entities.knowledge_entities.knowledge_entities import ParentMode
@ -19,7 +20,7 @@ class TestParentChildIndexProcessor:
dataset = Mock()
dataset.id = "dataset-1"
dataset.tenant_id = "tenant-1"
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.is_multimodal = True
return dataset

7
api/tests/unit_tests/core/rag/indexing/processor/test_qa_index_processor.py
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@ -6,6 +6,7 @@ import pytest
from werkzeug.datastructures import FileStorage
from core.entities.knowledge_entities import PreviewDetail
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from core.rag.index_processor.processor.qa_index_processor import QAIndexProcessor
from core.rag.models.document import AttachmentDocument, Document
@ -33,7 +34,7 @@ class TestQAIndexProcessor:
dataset = Mock()
dataset.id = "dataset-1"
dataset.tenant_id = "tenant-1"
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.is_multimodal = True
return dataset
@ -207,7 +208,7 @@ class TestQAIndexProcessor:
vector.create_multimodal.assert_called_once_with(multimodal_docs)
def test_load_skips_vector_for_non_high_quality(self, processor: QAIndexProcessor, dataset: Mock) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
docs = [Document(page_content="Q1", metadata={"answer": "A1"})]
with patch("core.rag.index_processor.processor.qa_index_processor.Vector") as mock_vector_cls:
@ -298,7 +299,7 @@ class TestQAIndexProcessor:
def test_index_requires_high_quality(
self, processor: QAIndexProcessor, dataset: Mock, dataset_document: Mock
) -> None:
dataset.indexing_technique = "economy"
dataset.indexing_technique = IndexTechniqueType.ECONOMY
qa_chunks = SimpleNamespace(qa_chunks=[SimpleNamespace(question="Q1", answer="A1")])
with (

18
api/tests/unit_tests/core/rag/indexing/test_indexing_runner.py
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@ -61,7 +61,7 @@ from core.indexing_runner import (
DocumentIsPausedError,
IndexingRunner,
)
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from core.rag.models.document import ChildDocument, Document
from dify_graph.model_runtime.entities.model_entities import ModelType
from libs.datetime_utils import naive_utc_now
@ -76,7 +76,7 @@ from models.dataset import Document as DatasetDocument
def create_mock_dataset(
dataset_id: str | None = None,
tenant_id: str | None = None,
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_provider: str = "openai",
embedding_model: str = "text-embedding-ada-002",
) -> Mock:
@ -458,7 +458,7 @@ class TestIndexingRunnerTransform:
dataset = Mock(spec=Dataset)
dataset.id = str(uuid.uuid4())
dataset.tenant_id = str(uuid.uuid4())
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.embedding_model_provider = "openai"
dataset.embedding_model = "text-embedding-ada-002"
return dataset
@ -521,7 +521,7 @@ class TestIndexingRunnerTransform:
"""Test transformation with economy indexing (no embeddings)."""
# Arrange
runner = IndexingRunner()
sample_dataset.indexing_technique = "economy"
sample_dataset.indexing_technique = IndexTechniqueType.ECONOMY
mock_processor = MagicMock()
transformed_docs = [
@ -605,7 +605,7 @@ class TestIndexingRunnerLoad:
dataset = Mock(spec=Dataset)
dataset.id = str(uuid.uuid4())
dataset.tenant_id = str(uuid.uuid4())
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.embedding_model_provider = "openai"
dataset.embedding_model = "text-embedding-ada-002"
return dataset
@ -674,7 +674,7 @@ class TestIndexingRunnerLoad:
"""Test loading with economy indexing (keyword only)."""
# Arrange
runner = IndexingRunner()
sample_dataset.indexing_technique = "economy"
sample_dataset.indexing_technique = IndexTechniqueType.ECONOMY
mock_processor = MagicMock()
@ -701,7 +701,7 @@ class TestIndexingRunnerLoad:
# Arrange
runner = IndexingRunner()
sample_dataset_document.doc_form = IndexStructureType.PARENT_CHILD_INDEX
sample_dataset.indexing_technique = "high_quality"
sample_dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
# Add child documents
for doc in sample_documents:
@ -795,7 +795,7 @@ class TestIndexingRunnerRun:
mock_dataset = Mock(spec=Dataset)
mock_dataset.id = doc.dataset_id
mock_dataset.tenant_id = doc.tenant_id
mock_dataset.indexing_technique = "economy"
mock_dataset.indexing_technique = IndexTechniqueType.ECONOMY
mock_dependencies["db"].session.query.return_value.filter_by.return_value.first.return_value = mock_dataset
mock_process_rule = Mock(spec=DatasetProcessRule)
@ -949,7 +949,7 @@ class TestIndexingRunnerRun:
mock_dependencies["db"].session.get.side_effect = get_side_effect
mock_dataset = Mock(spec=Dataset)
mock_dataset.indexing_technique = "economy"
mock_dataset.indexing_technique = IndexTechniqueType.ECONOMY
mock_dependencies["db"].session.query.return_value.filter_by.return_value.first.return_value = mock_dataset
mock_process_rule = Mock(spec=DatasetProcessRule)

3
api/tests/unit_tests/core/workflow/nodes/knowledge_index/test_knowledge_index_node.py
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@ -5,6 +5,7 @@ from unittest.mock import Mock
import pytest
from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from core.workflow.nodes.knowledge_index.entities import KnowledgeIndexNodeData
from core.workflow.nodes.knowledge_index.exc import KnowledgeIndexNodeError
from core.workflow.nodes.knowledge_index.knowledge_index_node import KnowledgeIndexNode
@ -78,7 +79,7 @@ def sample_node_data():
type="knowledge-index",
chunk_structure="general_structure",
index_chunk_variable_selector=["start", "chunks"],
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
summary_index_setting=None,
)

21
api/tests/unit_tests/models/test_dataset_models.py
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@ -15,6 +15,7 @@ from datetime import UTC, datetime
from unittest.mock import patch
from uuid import uuid4
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from models.dataset import (
AppDatasetJoin,
ChildChunk,
@ -67,14 +68,14 @@ class TestDatasetModelValidation:
data_source_type=DataSourceType.UPLOAD_FILE,
created_by=str(uuid4()),
description="Test description",
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model="text-embedding-ada-002",
embedding_model_provider="openai",
)
# Assert
assert dataset.description == "Test description"
assert dataset.indexing_technique == "high_quality"
assert dataset.indexing_technique == IndexTechniqueType.HIGH_QUALITY
assert dataset.embedding_model == "text-embedding-ada-002"
assert dataset.embedding_model_provider == "openai"
@ -86,21 +87,21 @@ class TestDatasetModelValidation:
name="High Quality Dataset",
data_source_type=DataSourceType.UPLOAD_FILE,
created_by=str(uuid4()),
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
dataset_economy = Dataset(
tenant_id=str(uuid4()),
name="Economy Dataset",
data_source_type=DataSourceType.UPLOAD_FILE,
created_by=str(uuid4()),
indexing_technique="economy",
indexing_technique=IndexTechniqueType.ECONOMY,
)
# Assert
assert dataset_high_quality.indexing_technique == "high_quality"
assert dataset_economy.indexing_technique == "economy"
assert "high_quality" in Dataset.INDEXING_TECHNIQUE_LIST
assert "economy" in Dataset.INDEXING_TECHNIQUE_LIST
assert dataset_high_quality.indexing_technique == IndexTechniqueType.HIGH_QUALITY
assert dataset_economy.indexing_technique == IndexTechniqueType.ECONOMY
assert IndexTechniqueType.HIGH_QUALITY in Dataset.INDEXING_TECHNIQUE_LIST
assert IndexTechniqueType.ECONOMY in Dataset.INDEXING_TECHNIQUE_LIST
def test_dataset_provider_validation(self):
"""Test dataset provider values."""
@ -983,7 +984,7 @@ class TestModelIntegration:
name="Test Dataset",
data_source_type=DataSourceType.UPLOAD_FILE,
created_by=created_by,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
dataset.id = dataset_id
@ -1019,7 +1020,7 @@ class TestModelIntegration:
assert document.dataset_id == dataset_id
assert segment.dataset_id == dataset_id
assert segment.document_id == document_id
assert dataset.indexing_technique == "high_quality"
assert dataset.indexing_technique == IndexTechniqueType.HIGH_QUALITY
assert document.word_count == 100
assert segment.status == SegmentStatus.COMPLETED

19
api/tests/unit_tests/services/dataset_service_update_delete.py
View File

@ -97,6 +97,7 @@ from unittest.mock import Mock, create_autospec, patch
import pytest
from sqlalchemy.orm import Session
from core.rag.index_processor.constant.index_type import IndexTechniqueType
from models import Account, TenantAccountRole
from models.dataset import (
AppDatasetJoin,
@ -149,7 +150,7 @@ class DatasetUpdateDeleteTestDataFactory:
name: str = "Test Dataset",
description: str = "Test description",
tenant_id: str = "tenant-123",
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider: str | None = "openai",
embedding_model: str | None = "text-embedding-ada-002",
collection_binding_id: str | None = "binding-123",
@ -237,7 +238,7 @@ class DatasetUpdateDeleteTestDataFactory:
@staticmethod
def create_knowledge_configuration_mock(
chunk_structure: str = "tree",
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider: str = "openai",
embedding_model: str = "text-embedding-ada-002",
keyword_number: int = 10,
@ -630,12 +631,12 @@ class TestDatasetServiceUpdateRagPipelineDatasetSettings:
dataset_id="dataset-123",
runtime_mode="rag_pipeline",
chunk_structure="tree",
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
knowledge_config = DatasetUpdateDeleteTestDataFactory.create_knowledge_configuration_mock(
chunk_structure="list",
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider="openai",
embedding_model="text-embedding-ada-002",
)
@ -671,7 +672,7 @@ class TestDatasetServiceUpdateRagPipelineDatasetSettings:
# Assert
assert dataset.chunk_structure == "list"
assert dataset.indexing_technique == "high_quality"
assert dataset.indexing_technique == IndexTechniqueType.HIGH_QUALITY
assert dataset.embedding_model == "text-embedding-ada-002"
assert dataset.embedding_model_provider == "openai"
assert dataset.collection_binding_id == "binding-123"
@ -698,12 +699,12 @@ class TestDatasetServiceUpdateRagPipelineDatasetSettings:
dataset_id="dataset-123",
runtime_mode="rag_pipeline",
chunk_structure="tree", # Existing structure
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
knowledge_config = DatasetUpdateDeleteTestDataFactory.create_knowledge_configuration_mock(
chunk_structure="list", # Different structure
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
mock_session.merge.return_value = dataset
@ -735,11 +736,11 @@ class TestDatasetServiceUpdateRagPipelineDatasetSettings:
dataset = DatasetUpdateDeleteTestDataFactory.create_dataset_mock(
dataset_id="dataset-123",
runtime_mode="rag_pipeline",
indexing_technique="high_quality", # Current technique
indexing_technique=IndexTechniqueType.HIGH_QUALITY, # Current technique
)
knowledge_config = DatasetUpdateDeleteTestDataFactory.create_knowledge_configuration_mock(
indexing_technique="economy", # Trying to change to economy
indexing_technique=IndexTechniqueType.ECONOMY, # Trying to change to economy
)
mock_session.merge.return_value = dataset

14
api/tests/unit_tests/services/document_service_validation.py
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@ -111,7 +111,7 @@ from unittest.mock import Mock, patch
import pytest
from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from dify_graph.model_runtime.entities.model_entities import ModelType
from models.dataset import Dataset, DatasetProcessRule, Document
from services.dataset_service import DatasetService, DocumentService
@ -154,7 +154,7 @@ class DocumentValidationTestDataFactory:
dataset_id: str = "dataset-123",
tenant_id: str = "tenant-123",
doc_form: str | None = None,
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider: str = "openai",
embedding_model: str = "text-embedding-ada-002",
**kwargs,
@ -190,7 +190,7 @@ class DocumentValidationTestDataFactory:
data_source: DataSource | None = None,
process_rule: ProcessRule | None = None,
doc_form: str = IndexStructureType.PARAGRAPH_INDEX,
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
**kwargs,
) -> Mock:
"""
@ -448,7 +448,7 @@ class TestDatasetServiceCheckDatasetModelSetting:
"""
# Arrange
dataset = DocumentValidationTestDataFactory.create_dataset_mock(
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider="openai",
embedding_model="text-embedding-ada-002",
)
@ -481,7 +481,7 @@ class TestDatasetServiceCheckDatasetModelSetting:
- No errors are raised
"""
# Arrange
dataset = DocumentValidationTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = DocumentValidationTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
# Act (should not raise)
DatasetService.check_dataset_model_setting(dataset)
@ -503,7 +503,7 @@ class TestDatasetServiceCheckDatasetModelSetting:
"""
# Arrange
dataset = DocumentValidationTestDataFactory.create_dataset_mock(
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider="openai",
embedding_model="invalid-model",
)
@ -533,7 +533,7 @@ class TestDatasetServiceCheckDatasetModelSetting:
"""
# Arrange
dataset = DocumentValidationTestDataFactory.create_dataset_mock(
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider="openai",
embedding_model="text-embedding-ada-002",
)

16
api/tests/unit_tests/services/segment_service.py
View File

@ -2,7 +2,7 @@ from unittest.mock import MagicMock, Mock, patch
import pytest
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from models.account import Account
from models.dataset import ChildChunk, Dataset, Document, DocumentSegment
from models.enums import SegmentType
@ -111,7 +111,7 @@ class SegmentTestDataFactory:
def create_dataset_mock(
dataset_id: str = "dataset-123",
tenant_id: str = "tenant-123",
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_model: str = "text-embedding-ada-002",
embedding_model_provider: str = "openai",
**kwargs,
@ -163,7 +163,7 @@ class TestSegmentServiceCreateSegment:
"""Test successful creation of a segment."""
# Arrange
document = SegmentTestDataFactory.create_document_mock(word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
args = {"content": "New segment content", "keywords": ["test", "segment"]}
mock_query = MagicMock()
@ -212,7 +212,7 @@ class TestSegmentServiceCreateSegment:
"""Test creation of segment with QA model (requires answer)."""
# Arrange
document = SegmentTestDataFactory.create_document_mock(doc_form=IndexStructureType.QA_INDEX, word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
args = {"content": "What is AI?", "answer": "AI is Artificial Intelligence", "keywords": ["ai"]}
mock_query = MagicMock()
@ -247,7 +247,7 @@ class TestSegmentServiceCreateSegment:
"""Test creation of segment with high quality indexing technique."""
# Arrange
document = SegmentTestDataFactory.create_document_mock(word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
args = {"content": "New segment content", "keywords": ["test"]}
mock_query = MagicMock()
@ -289,7 +289,7 @@ class TestSegmentServiceCreateSegment:
"""Test segment creation when vector indexing fails."""
# Arrange
document = SegmentTestDataFactory.create_document_mock(word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
args = {"content": "New segment content", "keywords": ["test"]}
mock_query = MagicMock()
@ -342,7 +342,7 @@ class TestSegmentServiceUpdateSegment:
# Arrange
segment = SegmentTestDataFactory.create_segment_mock(enabled=True, word_count=10)
document = SegmentTestDataFactory.create_document_mock(word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
args = SegmentUpdateArgs(content="Updated content", keywords=["updated"])
mock_db_session.query.return_value.where.return_value.first.return_value = segment
@ -431,7 +431,7 @@ class TestSegmentServiceUpdateSegment:
# Arrange
segment = SegmentTestDataFactory.create_segment_mock(enabled=True, word_count=10)
document = SegmentTestDataFactory.create_document_mock(doc_form=IndexStructureType.QA_INDEX, word_count=100)
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = SegmentTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
args = SegmentUpdateArgs(content="Updated question", answer="Updated answer", keywords=["qa"])
mock_db_session.query.return_value.where.return_value.first.return_value = segment

10
api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py
View File

@ -4,7 +4,7 @@ from unittest.mock import Mock, create_autospec
import pytest
from redis.exceptions import LockNotOwnedError
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from models.account import Account
from models.dataset import Dataset, Document
from services.dataset_service import DocumentService, SegmentService
@ -71,7 +71,7 @@ def test_save_document_with_dataset_id_ignores_lock_not_owned(
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
dataset.indexing_technique = IndexTechniqueType.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")
@ -80,7 +80,7 @@ def test_save_document_with_dataset_id_ignores_lock_not_owned(
doc_form=IndexStructureType.QA_INDEX,
original_document_id=None, # go into "new document" branch
data_source=data_source,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
embedding_model=None,
embedding_model_provider=None,
retrieval_model=None,
@ -126,7 +126,7 @@ def test_add_segment_ignores_lock_not_owned(
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
dataset.indexing_technique = IndexTechniqueType.ECONOMY # skip embedding/token calculation branch
document = create_autospec(Document, instance=True)
document.id = "doc-1"
@ -169,7 +169,7 @@ def test_multi_create_segment_ignores_lock_not_owned(
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
dataset.indexing_technique = IndexTechniqueType.ECONOMY # again, skip high_quality path
document = create_autospec(Document, instance=True)
document.id = "doc-1"

16
api/tests/unit_tests/services/test_summary_index_service.py
View File

@ -11,7 +11,7 @@ from unittest.mock import MagicMock
import pytest
import services.summary_index_service as summary_module
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from models.enums import SegmentStatus, SummaryStatus
from services.summary_index_service import SummaryIndexService
@ -27,7 +27,7 @@ class _SessionContext:
return None
def _dataset(*, indexing_technique: str = "high_quality") -> MagicMock:
def _dataset(*, indexing_technique: str = IndexTechniqueType.HIGH_QUALITY) -> MagicMock:
dataset = MagicMock(name="dataset")
dataset.id = "dataset-1"
dataset.tenant_id = "tenant-1"
@ -169,7 +169,8 @@ def test_create_summary_record_creates_new(monkeypatch: pytest.MonkeyPatch) -> N
def test_vectorize_summary_skips_non_high_quality(monkeypatch: pytest.MonkeyPatch) -> None:
vector_cls = MagicMock()
monkeypatch.setattr(summary_module, "Vector", vector_cls)
SummaryIndexService.vectorize_summary(_summary_record(), _segment(), _dataset(indexing_technique="economy"))
dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY)
SummaryIndexService.vectorize_summary(_summary_record(), _segment(), dataset)
vector_cls.assert_not_called()
@ -621,7 +622,7 @@ def test_generate_and_vectorize_summary_creates_missing_record_and_logs_usage(mo
def test_generate_summaries_for_document_skip_conditions(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _dataset(indexing_technique="economy")
dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY)
document = MagicMock(spec=summary_module.DatasetDocument)
document.id = "doc-1"
document.doc_form = IndexStructureType.PARAGRAPH_INDEX
@ -778,7 +779,7 @@ def test_disable_summaries_for_segments_no_summaries_noop(monkeypatch: pytest.Mo
def test_enable_summaries_for_segments_skips_non_high_quality() -> None:
SummaryIndexService.enable_summaries_for_segments(_dataset(indexing_technique="economy"))
SummaryIndexService.enable_summaries_for_segments(_dataset(indexing_technique=IndexTechniqueType.ECONOMY))
def test_enable_summaries_for_segments_revectorizes_and_enables(monkeypatch: pytest.MonkeyPatch) -> None:
@ -932,9 +933,8 @@ def test_delete_summaries_for_segments_no_summaries_noop(monkeypatch: pytest.Mon
def test_update_summary_for_segment_skip_conditions() -> None:
assert (
SummaryIndexService.update_summary_for_segment(_segment(), _dataset(indexing_technique="economy"), "x") is None
)
economy_dataset = _dataset(indexing_technique=IndexTechniqueType.ECONOMY)
assert SummaryIndexService.update_summary_for_segment(_segment(), economy_dataset, "x") is None
seg = _segment(has_document=True)
seg.document.doc_form = IndexStructureType.QA_INDEX
assert SummaryIndexService.update_summary_for_segment(seg, _dataset(), "x") is None

38
api/tests/unit_tests/services/test_vector_service.py
View File

@ -9,7 +9,7 @@ from unittest.mock import MagicMock
import pytest
import services.vector_service as vector_service_module
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from services.vector_service import VectorService
@ -32,7 +32,7 @@ class _ParentDocStub:
def _make_dataset(
*,
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
doc_form: str = IndexStructureType.PARAGRAPH_INDEX,
tenant_id: str = "tenant-1",
dataset_id: str = "dataset-1",
@ -192,7 +192,7 @@ def test_create_segments_vector_parent_child_calls_generate_child_chunks_with_ex
dataset = _make_dataset(
doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX,
embedding_model_provider="openai",
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
segment = _make_segment()
@ -241,7 +241,7 @@ def test_create_segments_vector_parent_child_uses_default_embedding_model_when_p
dataset = _make_dataset(
doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX,
embedding_model_provider=None,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
)
segment = _make_segment()
@ -329,7 +329,7 @@ def test_create_segments_vector_parent_child_missing_processing_rule_raises(monk
def test_create_segments_vector_parent_child_non_high_quality_raises(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(
doc_form=vector_service_module.IndexStructureType.PARENT_CHILD_INDEX,
indexing_technique="economy",
indexing_technique=IndexTechniqueType.ECONOMY,
)
segment = _make_segment()
dataset_document = MagicMock()
@ -348,7 +348,7 @@ def test_create_segments_vector_parent_child_non_high_quality_raises(monkeypatch
def test_update_segment_vector_high_quality_uses_vector(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
segment = _make_segment()
vector_instance = MagicMock()
@ -364,7 +364,7 @@ def test_update_segment_vector_high_quality_uses_vector(monkeypatch: pytest.Monk
def test_update_segment_vector_economy_uses_keyword_with_keywords_list(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="economy")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY)
segment = _make_segment()
keyword_instance = MagicMock()
@ -380,7 +380,7 @@ def test_update_segment_vector_economy_uses_keyword_with_keywords_list(monkeypat
def test_update_segment_vector_economy_uses_keyword_without_keywords_list(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="economy")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY)
segment = _make_segment()
keyword_instance = MagicMock()
@ -473,7 +473,7 @@ def test_generate_child_chunks_commits_even_when_no_children(monkeypatch: pytest
def test_create_child_chunk_vector_high_quality_adds_texts(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
child_chunk = MagicMock()
child_chunk.content = "child"
child_chunk.index_node_id = "id"
@ -489,7 +489,7 @@ def test_create_child_chunk_vector_high_quality_adds_texts(monkeypatch: pytest.M
def test_create_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="economy")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY)
vector_cls = MagicMock()
monkeypatch.setattr(vector_service_module, "Vector", vector_cls)
@ -505,7 +505,7 @@ def test_create_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch)
def test_update_child_chunk_vector_high_quality_updates_vector(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
new_chunk = MagicMock()
new_chunk.content = "n"
@ -536,7 +536,7 @@ def test_update_child_chunk_vector_high_quality_updates_vector(monkeypatch: pyte
def test_update_child_chunk_vector_economy_noop(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="economy")
dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY)
vector_cls = MagicMock()
monkeypatch.setattr(vector_service_module, "Vector", vector_cls)
VectorService.update_child_chunk_vector([], [], [], dataset)
@ -561,7 +561,7 @@ def test_delete_child_chunk_vector_deletes_by_id(monkeypatch: pytest.MonkeyPatch
def test_update_multimodel_vector_returns_when_not_high_quality(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="economy", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.ECONOMY, is_multimodal=True)
segment = _make_segment(tenant_id="t", attachments=[{"id": "a"}])
vector_cls = MagicMock()
@ -575,7 +575,7 @@ def test_update_multimodel_vector_returns_when_not_high_quality(monkeypatch: pyt
def test_update_multimodel_vector_returns_when_no_actual_change(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True)
segment = _make_segment(tenant_id="t", attachments=[{"id": "a"}, {"id": "b"}])
vector_cls = MagicMock()
@ -591,7 +591,7 @@ def test_update_multimodel_vector_returns_when_no_actual_change(monkeypatch: pyt
def test_update_multimodel_vector_deletes_bindings_and_commits_on_empty_new_ids(
monkeypatch: pytest.MonkeyPatch,
) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True)
segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}, {"id": "old-2"}])
vector_instance = MagicMock(name="vector_instance")
@ -612,7 +612,7 @@ def test_update_multimodel_vector_deletes_bindings_and_commits_on_empty_new_ids(
def test_update_multimodel_vector_commits_when_no_upload_files_found(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True)
segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}])
vector_instance = MagicMock()
@ -630,7 +630,7 @@ def test_update_multimodel_vector_commits_when_no_upload_files_found(monkeypatch
def test_update_multimodel_vector_adds_bindings_and_vectors_and_skips_missing_upload_files(
monkeypatch: pytest.MonkeyPatch,
) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True)
segment = _make_segment(segment_id="seg-1", tenant_id="tenant-1", attachments=[{"id": "old-1"}])
vector_instance = MagicMock()
@ -663,7 +663,7 @@ def test_update_multimodel_vector_adds_bindings_and_vectors_and_skips_missing_up
def test_update_multimodel_vector_updates_bindings_without_multimodal_vector_ops(
monkeypatch: pytest.MonkeyPatch,
) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=False)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=False)
segment = _make_segment(tenant_id="tenant-1", attachments=[{"id": "old-1"}])
vector_instance = MagicMock()
@ -683,7 +683,7 @@ def test_update_multimodel_vector_updates_bindings_without_multimodal_vector_ops
def test_update_multimodel_vector_rolls_back_and_reraises_on_error(monkeypatch: pytest.MonkeyPatch) -> None:
dataset = _make_dataset(indexing_technique="high_quality", is_multimodal=True)
dataset = _make_dataset(indexing_technique=IndexTechniqueType.HIGH_QUALITY, is_multimodal=True)
segment = _make_segment(segment_id="seg-1", tenant_id="tenant-1", attachments=[{"id": "old-1"}])
vector_instance = MagicMock()

36
api/tests/unit_tests/services/vector_service.py
View File

@ -121,7 +121,7 @@ import pytest
from core.rag.datasource.vdb.vector_base import BaseVector
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.datasource.vdb.vector_type import VectorType
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from core.rag.models.document import Document
from models.dataset import ChildChunk, Dataset, DatasetDocument, DatasetProcessRule, DocumentSegment
from services.vector_service import VectorService
@ -153,7 +153,7 @@ class VectorServiceTestDataFactory:
dataset_id: str = "dataset-123",
tenant_id: str = "tenant-123",
doc_form: str = IndexStructureType.PARAGRAPH_INDEX,
indexing_technique: str = "high_quality",
indexing_technique: str = IndexTechniqueType.HIGH_QUALITY,
embedding_model_provider: str = "openai",
embedding_model: str = "text-embedding-ada-002",
index_struct_dict: dict | None = None,
@ -494,7 +494,7 @@ class TestVectorService:
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(
doc_form=IndexStructureType.PARAGRAPH_INDEX, indexing_technique="high_quality"
doc_form=IndexStructureType.PARAGRAPH_INDEX, indexing_technique=IndexTechniqueType.HIGH_QUALITY
)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -535,7 +535,7 @@ class TestVectorService:
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(
doc_form="parent_child_model", indexing_technique="high_quality"
doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY
)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -568,7 +568,7 @@ class TestVectorService:
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(
doc_form="parent_child_model", indexing_technique="high_quality"
doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY
)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -591,7 +591,7 @@ class TestVectorService:
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(
doc_form="parent_child_model", indexing_technique="high_quality"
doc_form="parent_child_model", indexing_technique=IndexTechniqueType.HIGH_QUALITY
)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -616,7 +616,7 @@ class TestVectorService:
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(
doc_form="parent_child_model", indexing_technique="economy"
doc_form="parent_child_model", indexing_technique=IndexTechniqueType.ECONOMY
)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -669,7 +669,7 @@ class TestVectorService:
store when using high_quality indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -695,7 +695,7 @@ class TestVectorService:
index when using economy indexing with keywords.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -731,7 +731,7 @@ class TestVectorService:
index when using economy indexing without keywords.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
segment = VectorServiceTestDataFactory.create_document_segment_mock()
@ -895,7 +895,7 @@ class TestVectorService:
when using high_quality indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -923,7 +923,7 @@ class TestVectorService:
using economy indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -951,7 +951,7 @@ class TestVectorService:
when there are new chunks, updated chunks, and deleted chunks.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock(chunk_id="new-chunk-1")
@ -993,7 +993,7 @@ class TestVectorService:
add_texts is called, not delete_by_ids.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -1019,7 +1019,7 @@ class TestVectorService:
delete_by_ids is called, not add_texts.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
delete_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -1045,7 +1045,7 @@ class TestVectorService:
using economy indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
new_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -1075,7 +1075,7 @@ class TestVectorService:
when using high_quality indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="high_quality")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.HIGH_QUALITY)
child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()
@ -1099,7 +1099,7 @@ class TestVectorService:
using economy indexing.
"""
# Arrange
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique="economy")
dataset = VectorServiceTestDataFactory.create_dataset_mock(indexing_technique=IndexTechniqueType.ECONOMY)
child_chunk = VectorServiceTestDataFactory.create_child_chunk_mock()

16
api/tests/unit_tests/tasks/test_clean_dataset_task.py
View File

@ -16,7 +16,7 @@ from unittest.mock import MagicMock, patch
import pytest
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from models.enums import DataSourceType
from tasks.clean_dataset_task import clean_dataset_task
@ -184,7 +184,7 @@ class TestErrorHandling:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -229,7 +229,7 @@ class TestPipelineAndWorkflowDeletion:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -265,7 +265,7 @@ class TestPipelineAndWorkflowDeletion:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -321,7 +321,7 @@ class TestSegmentAttachmentCleanup:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -366,7 +366,7 @@ class TestSegmentAttachmentCleanup:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -408,7 +408,7 @@ class TestEdgeCases:
clean_dataset_task(
dataset_id=dataset_id,
tenant_id=tenant_id,
indexing_technique="high_quality",
indexing_technique=IndexTechniqueType.HIGH_QUALITY,
index_struct='{"type": "paragraph"}',
collection_binding_id=collection_binding_id,
doc_form=IndexStructureType.PARAGRAPH_INDEX,
@ -445,7 +445,7 @@ class TestIndexProcessorParameters:
- Dataset object with correct attributes is passed
"""
# Arrange
indexing_technique = "high_quality"
indexing_technique = IndexTechniqueType.HIGH_QUALITY
index_struct = '{"type": "paragraph"}'
# Act

4
api/tests/unit_tests/tasks/test_dataset_indexing_task.py
View File

@ -15,7 +15,7 @@ from unittest.mock import MagicMock, Mock, patch
import pytest
from core.indexing_runner import DocumentIsPausedError
from core.rag.index_processor.constant.index_type import IndexStructureType
from core.rag.index_processor.constant.index_type import IndexStructureType, IndexTechniqueType
from core.rag.pipeline.queue import TenantIsolatedTaskQueue
from enums.cloud_plan import CloudPlan
from extensions.ext_redis import redis_client
@ -209,7 +209,7 @@ def mock_dataset(dataset_id, tenant_id):
dataset = Mock(spec=Dataset)
dataset.id = dataset_id
dataset.tenant_id = tenant_id
dataset.indexing_technique = "high_quality"
dataset.indexing_technique = IndexTechniqueType.HIGH_QUALITY
dataset.embedding_model_provider = "openai"
dataset.embedding_model = "text-embedding-ada-002"
return dataset