chore: extract retrival method literal values into enum (#5060)

api/core/rag/datasource/retrieval_service.py

@@ -6,11 +6,12 @@ from flask import Flask, current_app
 from core.rag.data_post_processor.data_post_processor import DataPostProcessor
 from core.rag.datasource.keyword.keyword_factory import Keyword
 from core.rag.datasource.vdb.vector_factory import Vector
+from core.rag.retrieval.retrival_methods import RetrievalMethod
 from extensions.ext_database import db
 from models.dataset import Dataset
 
 default_retrieval_model = {
-    'search_method': 'semantic_search',
+    'search_method': RetrievalMethod.SEMANTIC_SEARCH,
     'reranking_enable': False,
     'reranking_model': {
         'reranking_provider_name': '',
@@ -47,7 +48,7 @@ class RetrievalService:
             threads.append(keyword_thread)
             keyword_thread.start()
         # retrieval_model source with semantic
-        if retrival_method == 'semantic_search' or retrival_method == 'hybrid_search':
+        if RetrievalMethod.is_support_semantic_search(retrival_method):
             embedding_thread = threading.Thread(target=RetrievalService.embedding_search, kwargs={
                 'flask_app': current_app._get_current_object(),
                 'dataset_id': dataset_id,
@@ -63,7 +64,7 @@ class RetrievalService:
             embedding_thread.start()
 
         # retrieval source with full text
-        if retrival_method == 'full_text_search' or retrival_method == 'hybrid_search':
+        if RetrievalMethod.is_support_fulltext_search(retrival_method):
             full_text_index_thread = threading.Thread(target=RetrievalService.full_text_index_search, kwargs={
                 'flask_app': current_app._get_current_object(),
                 'dataset_id': dataset_id,
@@ -85,7 +86,7 @@ class RetrievalService:
             exception_message = ';\n'.join(exceptions)
             raise Exception(exception_message)
 
-        if retrival_method == 'hybrid_search':
+        if retrival_method == RetrievalMethod.HYBRID_SEARCH:
             data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
             all_documents = data_post_processor.invoke(
                 query=query,
@@ -141,7 +142,7 @@ class RetrievalService:
                 )
 
                 if documents:
-                    if reranking_model and retrival_method == 'semantic_search':
+                    if reranking_model and retrival_method == RetrievalMethod.SEMANTIC_SEARCH:
                         data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
                         all_documents.extend(data_post_processor.invoke(
                             query=query,
@@ -173,7 +174,7 @@ class RetrievalService:
                     top_k=top_k
                 )
                 if documents:
-                    if reranking_model and retrival_method == 'full_text_search':
+                    if reranking_model and retrival_method == RetrievalMethod.FULL_TEXT_SEARCH:
                         data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
                         all_documents.extend(data_post_processor.invoke(
                             query=query,

api/core/rag/retrieval/dataset_retrieval.py

@@ -15,6 +15,7 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 from core.rag.datasource.retrieval_service import RetrievalService
 from core.rag.models.document import Document
 from core.rag.rerank.rerank import RerankRunner
+from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.rag.retrieval.router.multi_dataset_function_call_router import FunctionCallMultiDatasetRouter
 from core.rag.retrieval.router.multi_dataset_react_route import ReactMultiDatasetRouter
 from core.tools.tool.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool
@@ -25,7 +26,7 @@ from models.dataset import Dataset, DatasetQuery, DocumentSegment
 from models.dataset import Document as DatasetDocument
 
 default_retrieval_model = {
-    'search_method': 'semantic_search',
+    'search_method': RetrievalMethod.SEMANTIC_SEARCH,
     'reranking_enable': False,
     'reranking_model': {
         'reranking_provider_name': '',
@@ -419,7 +420,7 @@ class DatasetRetrieval:
         if retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE:
             # get retrieval model config
             default_retrieval_model = {
-                'search_method': 'semantic_search',
+                'search_method': RetrievalMethod.SEMANTIC_SEARCH,
                 'reranking_enable': False,
                 'reranking_model': {
                     'reranking_provider_name': '',

api/core/rag/retrieval/retrival_methods.py

@@ -0,0 +1,15 @@
+from enum import Enum
+
+
+class RetrievalMethod(str, Enum):
+    SEMANTIC_SEARCH = 'semantic_search'
+    FULL_TEXT_SEARCH = 'full_text_search'
+    HYBRID_SEARCH = 'hybrid_search'
+
+    @staticmethod
+    def is_support_semantic_search(retrieval_method: str) -> bool:
+        return retrieval_method in {RetrievalMethod.SEMANTIC_SEARCH, RetrievalMethod.HYBRID_SEARCH}
+
+    @staticmethod
+    def is_support_fulltext_search(retrieval_method: str) -> bool:
+        return retrieval_method in {RetrievalMethod.FULL_TEXT_SEARCH, RetrievalMethod.HYBRID_SEARCH}

api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py

@@ -8,12 +8,13 @@ from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.rag.datasource.retrieval_service import RetrievalService
 from core.rag.rerank.rerank import RerankRunner
+from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
 from models.dataset import Dataset, Document, DocumentSegment
 
 default_retrieval_model = {
-    'search_method': 'semantic_search',
+    'search_method': RetrievalMethod.SEMANTIC_SEARCH,
     'reranking_enable': False,
     'reranking_model': {
         'reranking_provider_name': '',

api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py

@@ -2,12 +2,13 @@
 from pydantic import BaseModel, Field
 
 from core.rag.datasource.retrieval_service import RetrievalService
+from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
 from models.dataset import Dataset, Document, DocumentSegment
 
 default_retrieval_model = {
-    'search_method': 'semantic_search',
+    'search_method': RetrievalMethod.SEMANTIC_SEARCH,
     'reranking_enable': False,
     'reranking_model': {
         'reranking_provider_name': '',

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -11,6 +11,7 @@ from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities.model_entities import ModelFeature, ModelType
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
+from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.workflow.entities.base_node_data_entities import BaseNodeData
 from core.workflow.entities.node_entities import NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
@@ -21,7 +22,7 @@ from models.dataset import Dataset, Document, DocumentSegment
 from models.workflow import WorkflowNodeExecutionStatus
 
 default_retrieval_model = {
-    'search_method': 'semantic_search',
+    'search_method': RetrievalMethod.SEMANTIC_SEARCH,
     'reranking_enable': False,
     'reranking_model': {
         'reranking_provider_name': '',