diff --git a/api/core/rag/datasource/retrieval_service.py b/api/core/rag/datasource/retrieval_service.py
index 7f6ecc3d3f..d7ea03efee 100644
--- a/api/core/rag/datasource/retrieval_service.py
+++ b/api/core/rag/datasource/retrieval_service.py
@@ -68,9 +68,12 @@ class SegmentRecord(TypedDict):
 
 
 class DefaultRetrievalModelDict(TypedDict):
-    search_method: RetrievalMethod | str
+    search_method: RetrievalMethod
     reranking_enable: bool
     reranking_model: RerankingModelDict
+    reranking_mode: NotRequired[str]
+    weights: NotRequired[WeightsDict | None]
+    score_threshold: NotRequired[float]
     top_k: int
     score_threshold_enabled: bool
 
diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py
index c44e9b847b..1096c69041 100644
--- a/api/core/rag/retrieval/dataset_retrieval.py
+++ b/api/core/rag/retrieval/dataset_retrieval.py
@@ -33,7 +33,7 @@ from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, Comp
 from core.prompt.simple_prompt_transform import ModelMode
 from core.rag.data_post_processor.data_post_processor import DataPostProcessor, RerankingModelDict, WeightsDict
 from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler
-from core.rag.datasource.retrieval_service import RetrievalService
+from core.rag.datasource.retrieval_service import DefaultRetrievalModelDict, RetrievalService
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
 from core.rag.entities.context_entities import DocumentContext
 from core.rag.entities.metadata_entities import Condition, MetadataCondition
@@ -87,7 +87,7 @@ from models.enums import CreatorUserRole, DatasetQuerySource
 from services.external_knowledge_service import ExternalDatasetService
 from services.feature_service import FeatureService
 
-default_retrieval_model: dict[str, Any] = {
+default_retrieval_model: DefaultRetrievalModelDict = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
@@ -666,7 +666,11 @@ class DatasetRetrieval:
                             document_ids_filter = document_ids
                         else:
                             return []
-                    retrieval_model_config = dataset.retrieval_model or default_retrieval_model
+                    retrieval_model_config: DefaultRetrievalModelDict = (
+                        cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                        if dataset.retrieval_model
+                        else default_retrieval_model
+                    )
 
                     # get top k
                     top_k = retrieval_model_config["top_k"]
@@ -1058,7 +1062,11 @@ class DatasetRetrieval:
                     all_documents.append(document)
             else:
                 # get retrieval model , if the model is not setting , using default
-                retrieval_model = dataset.retrieval_model or default_retrieval_model
+                retrieval_model: DefaultRetrievalModelDict = (
+                    cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                    if dataset.retrieval_model
+                    else default_retrieval_model
+                )
 
                 if dataset.indexing_technique == "economy":
                     # use keyword table query
@@ -1132,7 +1140,7 @@ class DatasetRetrieval:
 
         if retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE:
             # get retrieval model config
-            default_retrieval_model = {
+            default_retrieval_model: DefaultRetrievalModelDict = {
                 "search_method": RetrievalMethod.SEMANTIC_SEARCH,
                 "reranking_enable": False,
                 "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
@@ -1141,7 +1149,11 @@ class DatasetRetrieval:
             }
 
             for dataset in available_datasets:
-                retrieval_model_config = dataset.retrieval_model or default_retrieval_model
+                retrieval_model_config: DefaultRetrievalModelDict = (
+                    cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                    if dataset.retrieval_model
+                    else default_retrieval_model
+                )
 
                 # get top k
                 top_k = retrieval_model_config["top_k"]