diff --git a/src/pai_rag/app/web/view_model.py b/src/pai_rag/app/web/view_model.py
index 55dd2901..667b2a60 100644
--- a/src/pai_rag/app/web/view_model.py
+++ b/src/pai_rag/app/web/view_model.py
@@ -218,7 +218,7 @@ def to_app_config(self):
         config["embedding"]["source"] = self.embed_source
         config["embedding"]["model_name"] = self.embed_model
         config["embedding"]["api_key"] = self.embed_api_key
-        config["embedding"]["embed_batch_size"] = self.embed_batch_size
+        config["embedding"]["embed_batch_size"] = int(self.embed_batch_size)
 
         config["llm"]["source"] = self.llm
         config["llm"]["endpoint"] = self.llm_eas_url
diff --git a/src/pai_rag/modules/embedding/embedding.py b/src/pai_rag/modules/embedding/embedding.py
index 0d15a743..8b8350aa 100644
--- a/src/pai_rag/modules/embedding/embedding.py
+++ b/src/pai_rag/modules/embedding/embedding.py
@@ -26,6 +26,9 @@ def _create_new_instance(self, new_params: Dict[str, Any]):
         source = config["source"].lower()
         embed_batch_size = config.get("embed_batch_size", DEFAULT_EMBED_BATCH_SIZE)
 
+        if not isinstance(embed_batch_size, int):
+            raise TypeError("embed_batch_size must be of type int")
+
         if source == "openai":
             embed_model = OpenAIEmbedding(
                 api_key=config.get("api_key", None),
@@ -52,6 +55,7 @@ def _create_new_instance(self, new_params: Dict[str, Any]):
             embed_model = HuggingFaceEmbedding(
                 model_name=model_path, embed_batch_size=embed_batch_size
             )
+
             logger.info(
                 f"Initialized HuggingFace embedding model {model_name} with {embed_batch_size} batch size."
             )