diff --git a/litellm/llms/vertex_ai.py b/litellm/llms/vertex_ai.py
index 5457ee40d13..f555752273a 100644
--- a/litellm/llms/vertex_ai.py
+++ b/litellm/llms/vertex_ai.py
@@ -181,6 +181,7 @@ def completion(
         from vertexai.preview.language_models import ChatModel, CodeChatModel, InputOutputTextPair
         from vertexai.language_models import TextGenerationModel, CodeGenerationModel
         from vertexai.preview.generative_models import GenerativeModel, Part, GenerationConfig
+        from google.cloud.aiplatform_v1beta1.types import content as gapic_content_types
 
 
         vertexai.init(
@@ -193,6 +194,15 @@ def completion(
             if k not in optional_params: 
                 optional_params[k] = v
 
+        ## Process safety settings into format expected by vertex AI    
+        if "safety_settings" in optional_params:
+            safety_settings = optional_params.pop("safety_settings")
+            if not isinstance(safety_settings, list):
+                raise ValueError("safety_settings must be a list")
+            if len(safety_settings) > 0 and not isinstance(safety_settings[0], dict):
+                raise ValueError("safety_settings must be a list of dicts")
+            safety_settings=[gapic_content_types.SafetySetting(x) for x in safety_settings]
+
         # vertexai does not use an API key, it looks for credentials.json in the environment
 
         prompt = " ".join([message["content"] for message in messages if isinstance(message["content"], str)])
@@ -238,16 +248,16 @@ def completion(
 
             if "stream" in optional_params and optional_params["stream"] == True:
                 stream = optional_params.pop("stream")
-                request_str += f"chat.send_message({prompt}, generation_config=GenerationConfig(**{optional_params}), stream={stream})\n"
+                request_str += f"chat.send_message({prompt}, generation_config=GenerationConfig(**{optional_params}), safety_settings={safety_settings}, stream={stream})\n"
                 ## LOGGING
                 logging_obj.pre_call(input=prompt, api_key=None, additional_args={"complete_input_dict": optional_params, "request_str": request_str})
-                model_response = chat.send_message(prompt, generation_config=GenerationConfig(**optional_params), stream=stream)
+                model_response = chat.send_message(prompt, generation_config=GenerationConfig(**optional_params), safety_settings=safety_settings, stream=stream)
                 optional_params["stream"] = True
                 return model_response
-            request_str += f"chat.send_message({prompt}, generation_config=GenerationConfig(**{optional_params})).text\n"
+            request_str += f"chat.send_message({prompt}, generation_config=GenerationConfig(**{optional_params}), safety_settings={safety_settings}).text\n"
             ## LOGGING
             logging_obj.pre_call(input=prompt, api_key=None, additional_args={"complete_input_dict": optional_params, "request_str": request_str})
-            response_obj = chat.send_message(prompt, generation_config=GenerationConfig(**optional_params))
+            response_obj = chat.send_message(prompt, generation_config=GenerationConfig(**optional_params), safety_settings=safety_settings)
             completion_response = response_obj.text
             response_obj = response_obj._raw_response
         elif mode == "vision":
@@ -258,12 +268,13 @@ def completion(
             content = [prompt] + images
             if "stream" in optional_params and optional_params["stream"] == True:
                 stream = optional_params.pop("stream")
-                request_str += f"response = llm_model.generate_content({content}, generation_config=GenerationConfig(**{optional_params}), stream={stream})\n"
+                request_str += f"response = llm_model.generate_content({content}, generation_config=GenerationConfig(**{optional_params}), safety_settings={safety_settings}, stream={stream})\n"
                 logging_obj.pre_call(input=prompt, api_key=None, additional_args={"complete_input_dict": optional_params, "request_str": request_str})
                 
                 model_response = llm_model.generate_content(
                     contents=content,
                     generation_config=GenerationConfig(**optional_params),
+                    safety_settings=safety_settings,
                     stream=True
                 )
                 optional_params["stream"] = True
@@ -276,7 +287,8 @@ def completion(
             ## LLM Call
             response = llm_model.generate_content(
                 contents=content,
-                generation_config=GenerationConfig(**optional_params)
+                generation_config=GenerationConfig(**optional_params),
+                safety_settings=safety_settings,
             )
             completion_response = response.text
             response_obj = response._raw_response