diff --git a/rag/llm/embedding_model.py b/rag/llm/embedding_model.py
index e460de6e2..7e8494b96 100644
--- a/rag/llm/embedding_model.py
+++ b/rag/llm/embedding_model.py
@@ -291,7 +291,7 @@ class OllamaEmbed(Base):
         arr = []
         tks_num = 0
         for txt in texts:
-            # remove special tokens if they exist
+            # remove special tokens if they exist base on regex in one request
             for token in OllamaEmbed._special_tokens:
                 txt = txt.replace(token, "")
             res = self.client.embeddings(prompt=txt, model=self.model_name, options={"use_mmap": True}, keep_alive=self.keep_alive)
@@ -487,6 +487,8 @@ class BedrockEmbed(Base):
         self.bedrock_sk = json.loads(key).get("bedrock_sk", "")
         self.bedrock_region = json.loads(key).get("bedrock_region", "")
         self.model_name = model_name
+        self.is_amazon = self.model_name.split(".")[0] == "amazon"
+        self.is_cohere = self.model_name.split(".")[0] == "cohere"
 
         if self.bedrock_ak == "" or self.bedrock_sk == "" or self.bedrock_region == "":
             # Try to create a client using the default credentials (AWS_PROFILE, AWS_DEFAULT_REGION, etc.)
@@ -499,9 +501,9 @@ class BedrockEmbed(Base):
         embeddings = []
         token_count = 0
         for text in texts:
-            if self.model_name.split(".")[0] == "amazon":
+            if self.is_amazon:
                 body = {"inputText": text}
-            elif self.model_name.split(".")[0] == "cohere":
+            elif self.is_cohere:
                 body = {"texts": [text], "input_type": "search_document"}
 
             response = self.client.invoke_model(modelId=self.model_name, body=json.dumps(body))
@@ -517,9 +519,9 @@ class BedrockEmbed(Base):
     def encode_queries(self, text):
         embeddings = []
         token_count = num_tokens_from_string(text)
-        if self.model_name.split(".")[0] == "amazon":
+        if self.is_amazon:
             body = {"inputText": truncate(text, 8196)}
-        elif self.model_name.split(".")[0] == "cohere":
+        elif self.is_cohere:
             body = {"texts": [truncate(text, 8196)], "input_type": "search_query"}
 
         response = self.client.invoke_model(modelId=self.model_name, body=json.dumps(body))