diff --git a/litellm/__init__.py b/litellm/__init__.py
index 4ad362d509..8b7a13e4ff 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -369,7 +369,7 @@ from .llms.vertex_ai import VertexAIConfig
 from .llms.sagemaker import SagemakerConfig
 from .llms.ollama import OllamaConfig
 from .llms.maritalk import MaritTalkConfig
-from .llms.bedrock import AmazonTitanConfig, AmazonAI21Config, AmazonAnthropicConfig, AmazonCohereConfig
+from .llms.bedrock import AmazonTitanConfig, AmazonAI21Config, AmazonAnthropicConfig, AmazonCohereConfig, AmazonLlamaConfig
 from .llms.openai import OpenAIConfig, OpenAITextCompletionConfig
 from .llms.azure import AzureOpenAIConfig
 from .main import *  # type: ignore
diff --git a/litellm/llms/openai.py b/litellm/llms/openai.py
index efc8808212..6bfd1aad3c 100644
--- a/litellm/llms/openai.py
+++ b/litellm/llms/openai.py
@@ -154,8 +154,8 @@ class OpenAITextCompletionConfig():
                 and v is not None}
 
 class OpenAIChatCompletion(BaseLLM):
-    openai_client: Optional[openai.Client] = None
-    openai_aclient: Optional[openai.AsyncClient] = None
+    openai_client: openai.Client
+    openai_aclient: openai.AsyncClient
 
     def __init__(self) -> None:
         super().__init__()
@@ -232,13 +232,13 @@ class OpenAIChatCompletion(BaseLLM):
                 try: 
                     if acompletion is True: 
                         if optional_params.get("stream", False):
-                            return self.async_streaming(logging_obj=logging_obj, api_base=api_base, data=data, headers=headers, model_response=model_response, model=model)
+                            return self.async_streaming(logging_obj=logging_obj, data=data, model=model)
                         else:
-                            return self.acompletion(api_base=api_base, data=data, headers=headers, model_response=model_response)
+                            return self.acompletion(data=data, model_response=model_response)
                     elif optional_params.get("stream", False):
-                        return self.streaming(logging_obj=logging_obj, api_base=api_base, data=data, headers=headers, model_response=model_response, model=model)
+                        return self.streaming(logging_obj=logging_obj, data=data, model=model)
                     else:
-                        response = self.openai_client.chat.completions.create(**data)
+                        response = self.openai_client.chat.completions.create(**data) # type: ignore
                         return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
                 except Exception as e:
                     if "Conversation roles must alternate user/assistant" in str(e) or "user and assistant roles should be alternating" in str(e): 
@@ -266,8 +266,7 @@ class OpenAIChatCompletion(BaseLLM):
             raise e
     
     async def acompletion(self, 
-                          api_base: str, 
-                          data: dict, headers: dict, 
+                          data: dict, 
                           model_response: ModelResponse): 
         response = None
         try: 
@@ -281,10 +280,7 @@ class OpenAIChatCompletion(BaseLLM):
 
     def streaming(self,
                   logging_obj,
-                  api_base: str, 
                   data: dict, 
-                  headers: dict, 
-                  model_response: ModelResponse, 
                   model: str
     ):
         response = self.openai_client.chat.completions.create(**data)
@@ -294,10 +290,7 @@ class OpenAIChatCompletion(BaseLLM):
 
     async def async_streaming(self, 
                           logging_obj,
-                          api_base: str, 
                           data: dict, 
-                          headers: dict, 
-                          model_response: ModelResponse, 
                           model: str):
         response = await self.openai_aclient.chat.completions.create(**data)
         streamwrapper = CustomStreamWrapper(completion_stream=response, model=model, custom_llm_provider="openai",logging_obj=logging_obj)
@@ -315,10 +308,8 @@ class OpenAIChatCompletion(BaseLLM):
                 optional_params=None,):
         super().embedding()
         exception_mapping_worked = False
-        if self._client_session is None:
-            self._client_session = self.create_client_session()
         try: 
-            headers = self.validate_environment(api_key)
+            headers = self.validate_environment(api_key, api_base=api_base, headers=None)
             api_base = f"{api_base}/embeddings"
             model = model
             data = {
@@ -334,9 +325,7 @@ class OpenAIChatCompletion(BaseLLM):
                     additional_args={"complete_input_dict": data},
                 )
             ## COMPLETION CALL
-            response = requests.post(
-                api_base, headers=headers, json=data, timeout=litellm.request_timeout
-            )
+            response = self.openai_client.embeddings.create(**data) # type: ignore
             ## LOGGING
             logging_obj.post_call(
                     input=input,
@@ -344,10 +333,8 @@ class OpenAIChatCompletion(BaseLLM):
                     additional_args={"complete_input_dict": data},
                     original_response=response,
                 )
-
-            if response.status_code!=200:
-                raise OpenAIError(message=response.text, status_code=response.status_code)
-            embedding_response = response.json() 
+            
+            embedding_response = json.loads(response.model_dump_json())
             output_data = []
             for idx, embedding in enumerate(embedding_response["data"]):
                 output_data.append(
diff --git a/litellm/tests/test_async_fn.py b/litellm/tests/test_async_fn.py
index 80981a62e9..8bd0b2daa5 100644
--- a/litellm/tests/test_async_fn.py
+++ b/litellm/tests/test_async_fn.py
@@ -50,7 +50,7 @@ def test_async_response():
             pytest.fail(f"An exception occurred: {e}")
 
     asyncio.run(test_get_response())
-
+test_async_response()
 def test_async_anyscale_response():
     import asyncio
     litellm.set_verbose = True
diff --git a/litellm/tests/test_embedding.py b/litellm/tests/test_embedding.py
index d533b7c42e..d9f1c9f673 100644
--- a/litellm/tests/test_embedding.py
+++ b/litellm/tests/test_embedding.py
@@ -20,7 +20,7 @@ def test_openai_embedding():
         # print(f"response: {str(response)}")
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
-# test_openai_embedding()
+test_openai_embedding()
 
 def test_openai_azure_embedding_simple():
     try: