diff --git a/api/tests/unit_tests/core/rag/indexing/processor/test_paragraph_index_processor.py b/api/tests/unit_tests/core/rag/indexing/processor/test_paragraph_index_processor.py
index e6cc582398..2c234edd9a 100644
--- a/api/tests/unit_tests/core/rag/indexing/processor/test_paragraph_index_processor.py
+++ b/api/tests/unit_tests/core/rag/indexing/processor/test_paragraph_index_processor.py
@@ -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",
diff --git a/api/tests/unit_tests/core/rag/indexing/processor/test_parent_child_index_processor.py b/api/tests/unit_tests/core/rag/indexing/processor/test_parent_child_index_processor.py
index 5c78cae7c1..b1ed735ee7 100644
--- a/api/tests/unit_tests/core/rag/indexing/processor/test_parent_child_index_processor.py
+++ b/api/tests/unit_tests/core/rag/indexing/processor/test_parent_child_index_processor.py
@@ -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
 
diff --git a/api/tests/unit_tests/core/rag/indexing/processor/test_qa_index_processor.py b/api/tests/unit_tests/core/rag/indexing/processor/test_qa_index_processor.py
index 99323eeec9..98c47bec8f 100644
--- a/api/tests/unit_tests/core/rag/indexing/processor/test_qa_index_processor.py
+++ b/api/tests/unit_tests/core/rag/indexing/processor/test_qa_index_processor.py
@@ -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 (
diff --git a/api/tests/unit_tests/core/rag/indexing/test_indexing_runner.py b/api/tests/unit_tests/core/rag/indexing/test_indexing_runner.py
index b011ade884..b54a74b69c 100644
--- a/api/tests/unit_tests/core/rag/indexing/test_indexing_runner.py
+++ b/api/tests/unit_tests/core/rag/indexing/test_indexing_runner.py
@@ -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)
diff --git a/api/tests/unit_tests/core/workflow/nodes/knowledge_index/test_knowledge_index_node.py b/api/tests/unit_tests/core/workflow/nodes/knowledge_index/test_knowledge_index_node.py
index 33f7ace5ab..feb560bbc3 100644
--- a/api/tests/unit_tests/core/workflow/nodes/knowledge_index/test_knowledge_index_node.py
+++ b/api/tests/unit_tests/core/workflow/nodes/knowledge_index/test_knowledge_index_node.py
@@ -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,
     )
 
diff --git a/api/tests/unit_tests/models/test_dataset_models.py b/api/tests/unit_tests/models/test_dataset_models.py
index 98dd07907a..6c8a91129b 100644
--- a/api/tests/unit_tests/models/test_dataset_models.py
+++ b/api/tests/unit_tests/models/test_dataset_models.py
@@ -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
 
diff --git a/api/tests/unit_tests/services/dataset_service_update_delete.py b/api/tests/unit_tests/services/dataset_service_update_delete.py
index c805dd98e2..424ac18870 100644
--- a/api/tests/unit_tests/services/dataset_service_update_delete.py
+++ b/api/tests/unit_tests/services/dataset_service_update_delete.py
@@ -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
diff --git a/api/tests/unit_tests/services/document_service_validation.py b/api/tests/unit_tests/services/document_service_validation.py
index 1f68ff6b3d..49fdc5cc9b 100644
--- a/api/tests/unit_tests/services/document_service_validation.py
+++ b/api/tests/unit_tests/services/document_service_validation.py
@@ -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",
         )
diff --git a/api/tests/unit_tests/services/segment_service.py b/api/tests/unit_tests/services/segment_service.py
index 5e625fa0cd..14af7f7119 100644
--- a/api/tests/unit_tests/services/segment_service.py
+++ b/api/tests/unit_tests/services/segment_service.py
@@ -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
diff --git a/api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py b/api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py
index d2287e8982..9a513c3fe6 100644
--- a/api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py
+++ b/api/tests/unit_tests/services/test_dataset_service_lock_not_owned.py
@@ -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"
diff --git a/api/tests/unit_tests/services/test_summary_index_service.py b/api/tests/unit_tests/services/test_summary_index_service.py
index c4285c73a0..ef53df9350 100644
--- a/api/tests/unit_tests/services/test_summary_index_service.py
+++ b/api/tests/unit_tests/services/test_summary_index_service.py
@@ -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
diff --git a/api/tests/unit_tests/services/test_vector_service.py b/api/tests/unit_tests/services/test_vector_service.py
index d3a98dd4bb..16d3011810 100644
--- a/api/tests/unit_tests/services/test_vector_service.py
+++ b/api/tests/unit_tests/services/test_vector_service.py
@@ -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()
diff --git a/api/tests/unit_tests/services/vector_service.py b/api/tests/unit_tests/services/vector_service.py
index e180063041..33a5607ef4 100644
--- a/api/tests/unit_tests/services/vector_service.py
+++ b/api/tests/unit_tests/services/vector_service.py
@@ -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()
 
diff --git a/api/tests/unit_tests/tasks/test_clean_dataset_task.py b/api/tests/unit_tests/tasks/test_clean_dataset_task.py
index c0a4d2f113..936a10d6c5 100644
--- a/api/tests/unit_tests/tasks/test_clean_dataset_task.py
+++ b/api/tests/unit_tests/tasks/test_clean_dataset_task.py
@@ -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
diff --git a/api/tests/unit_tests/tasks/test_dataset_indexing_task.py b/api/tests/unit_tests/tasks/test_dataset_indexing_task.py
index 027cd3b1ec..0b189ebae2 100644
--- a/api/tests/unit_tests/tasks/test_dataset_indexing_task.py
+++ b/api/tests/unit_tests/tasks/test_dataset_indexing_task.py
@@ -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