fix: Invalid expected metadata value type error (#22793)

api/core/tools/utils/dataset_retriever/dataset_retriever_base_tool.py

@@ -1,5 +1,5 @@
 from abc import abstractmethod
-from typing import Any, Optional
+from typing import Optional
 
 from msal_extensions.persistence import ABC  # type: ignore
 from pydantic import BaseModel, ConfigDict
@@ -21,11 +21,7 @@ class DatasetRetrieverBaseTool(BaseModel, ABC):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @abstractmethod
-    def _run(
-        self,
-        *args: Any,
-        **kwargs: Any,
-    ) -> Any:
+    def _run(self, query: str) -> str:
         """Use the tool.
 
         Add run_manager: Optional[CallbackManagerForToolRun] = None

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

@@ -462,7 +462,7 @@ class KnowledgeRetrievalNode(BaseNode):
                                 expected_value = self.graph_runtime_state.variable_pool.convert_template(
                                     expected_value
                                 ).value[0]
-                                if expected_value.value_type == "number":  # type: ignore
+                                if expected_value.value_type in {"number", "integer", "float"}:  # type: ignore
                                     expected_value = expected_value.value  # type: ignore
                                 elif expected_value.value_type == "string":  # type: ignore
                                     expected_value = re.sub(r"[\r\n\t]+", " ", expected_value.text).strip()  # type: ignore

api/core/workflow/nodes/llm/node.py

@@ -565,7 +565,7 @@ class LLMNode(BaseNode):
                     retriever_resources=original_retriever_resource, context=context_str.strip()
                 )
 
-    def _convert_to_original_retriever_resource(self, context_dict: dict):
+    def _convert_to_original_retriever_resource(self, context_dict: dict) -> RetrievalSourceMetadata | None:
         if (
             "metadata" in context_dict
             and "_source" in context_dict["metadata"]