diff --git a/api/core/model_manager.py b/api/core/model_manager.py
index 86d042de3e..d3d4d25940 100644
--- a/api/core/model_manager.py
+++ b/api/core/model_manager.py
@@ -115,7 +115,7 @@ class ModelInstance:
     def invoke_llm(
         self,
         prompt_messages: Sequence[PromptMessage],
-        model_parameters: dict | None = None,
+        model_parameters: dict[str, Any] | None = None,
         tools: Sequence[PromptMessageTool] | None = None,
         stop: list[str] | None = None,
         stream: Literal[True] = True,
@@ -126,7 +126,7 @@ class ModelInstance:
     def invoke_llm(
         self,
         prompt_messages: list[PromptMessage],
-        model_parameters: dict | None = None,
+        model_parameters: dict[str, Any] | None = None,
         tools: Sequence[PromptMessageTool] | None = None,
         stop: list[str] | None = None,
         stream: Literal[False] = False,
@@ -137,7 +137,7 @@ class ModelInstance:
     def invoke_llm(
         self,
         prompt_messages: list[PromptMessage],
-        model_parameters: dict | None = None,
+        model_parameters: dict[str, Any] | None = None,
         tools: Sequence[PromptMessageTool] | None = None,
         stop: list[str] | None = None,
         stream: bool = True,
@@ -147,7 +147,7 @@ class ModelInstance:
     def invoke_llm(
         self,
         prompt_messages: Sequence[PromptMessage],
-        model_parameters: dict | None = None,
+        model_parameters: dict[str, Any] | None = None,
         tools: Sequence[PromptMessageTool] | None = None,
         stop: Sequence[str] | None = None,
         stream: bool = True,
@@ -528,7 +528,7 @@ class LBModelManager:
         model_type: ModelType,
         model: str,
         load_balancing_configs: list[ModelLoadBalancingConfiguration],
-        managed_credentials: dict | None = None,
+        managed_credentials: dict[str, Any] | None = None,
     ):
         """
         Load balancing model manager
diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py
index b681ff5db1..8ebc840b99 100644
--- a/api/core/rag/retrieval/dataset_retrieval.py
+++ b/api/core/rag/retrieval/dataset_retrieval.py
@@ -875,7 +875,11 @@ class DatasetRetrieval:
         return retrieval_resource_list
 
     def _on_retrieval_end(
-        self, flask_app: Flask, documents: list[Document], message_id: str | None = None, timer: dict | None = None
+        self,
+        flask_app: Flask,
+        documents: list[Document],
+        message_id: str | None = None,
+        timer: dict[str, Any] | None = None,
     ):
         """Handle retrieval end."""
         with flask_app.app_context():
@@ -980,7 +984,7 @@ class DatasetRetrieval:
 
             self._send_trace_task(message_id, documents, timer)
 
-    def _send_trace_task(self, message_id: str | None, documents: list[Document], timer: dict | None):
+    def _send_trace_task(self, message_id: str | None, documents: list[Document], timer: dict[str, Any] | None):
         """Send trace task if trace manager is available."""
         trace_manager: TraceQueueManager | None = (
             self.application_generate_entity.trace_manager if self.application_generate_entity else None
@@ -1142,7 +1146,7 @@ class DatasetRetrieval:
         invoke_from: InvokeFrom,
         hit_callback: DatasetIndexToolCallbackHandler,
         user_id: str,
-        inputs: dict,
+        inputs: dict[str, Any],
     ) -> list[DatasetRetrieverBaseTool] | None:
         """
         A dataset tool is a tool that can be used to retrieve information from a dataset
@@ -1337,7 +1341,7 @@ class DatasetRetrieval:
         metadata_filtering_mode: str,
         metadata_model_config: ModelConfig,
         metadata_filtering_conditions: MetadataFilteringCondition | None,
-        inputs: dict,
+        inputs: dict[str, Any],
     ) -> tuple[dict[str, list[str]] | None, MetadataFilteringCondition | None]:
         document_query = select(DatasetDocument).where(
             DatasetDocument.dataset_id.in_(dataset_ids),
@@ -1417,7 +1421,7 @@ class DatasetRetrieval:
             metadata_filter_document_ids[document.dataset_id].append(document.id)  # type: ignore
         return metadata_filter_document_ids, metadata_condition
 
-    def _replace_metadata_filter_value(self, text: str, inputs: dict) -> str:
+    def _replace_metadata_filter_value(self, text: str, inputs: dict[str, Any]) -> str:
         if not inputs:
             return text