diff --git a/litellm/main.py b/litellm/main.py
index 656fca89c..137b5b0d8 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -1357,14 +1357,17 @@ def batch_completion_models_all_responses(*args, **kwargs):
 def embedding(
     model, 
     input=[], 
-    api_key=None,
-    api_base=None,
     # Optional params
     azure=False, 
     force_timeout=60, 
     litellm_call_id=None, 
     litellm_logging_obj=None,
     logger_fn=None, 
+    # set api_base, api_version, api_key
+    api_base: Optional[str] = None,
+    api_version: Optional[str] = None,
+    api_key: Optional[str] = None,
+    api_type: Optional[str] = None,
     caching=False,
     custom_llm_provider=None,
 ):
@@ -1375,10 +1378,26 @@ def embedding(
         logging.update_environment_variables(model=model, user="", optional_params={}, litellm_params={"force_timeout": force_timeout, "azure": azure, "litellm_call_id": litellm_call_id, "logger_fn": logger_fn})
         if azure == True or custom_llm_provider == "azure":
             # azure configs
-            openai.api_type = get_secret("AZURE_API_TYPE") or "azure"
-            openai.api_base = get_secret("AZURE_API_BASE")
-            openai.api_version = get_secret("AZURE_API_VERSION")
-            openai.api_key = get_secret("AZURE_API_KEY")
+            api_type = get_secret("AZURE_API_TYPE") or "azure"
+
+            api_base = (
+                api_base
+                or litellm.api_base
+                or get_secret("AZURE_API_BASE")
+            )
+
+            api_version = (
+                api_version or
+                litellm.api_version or
+                get_secret("AZURE_API_VERSION")
+            )
+
+            api_key = (
+                api_key or
+                litellm.api_key or
+                litellm.azure_key or
+                get_secret("AZURE_API_KEY")
+            )
             ## LOGGING
             logging.pre_call(
                 input=input,
@@ -1390,30 +1409,61 @@ def embedding(
                 },
             )
             ## EMBEDDING CALL
-            response = openai.Embedding.create(input=input, engine=model)
+            response = openai.Embedding.create(
+                input=input, 
+                engine=model,
+                api_key=api_key,
+                api_base=api_base,
+                api_version=api_version,
+                api_type=api_type,
+            )
 
             ## LOGGING
             logging.post_call(input=input, api_key=openai.api_key, original_response=response)
         elif model in litellm.open_ai_embedding_models:
-            openai.api_type = "openai"
-            openai.api_base = "https://api.openai.com/v1"
-            openai.api_version = None
-            openai.api_key = get_secret("OPENAI_API_KEY")
+            api_base = (
+                api_base
+                or litellm.api_base
+                or get_secret("OPENAI_API_BASE")
+                or "https://api.openai.com/v1"
+            )
+            openai.organization = (
+                litellm.organization
+                or get_secret("OPENAI_ORGANIZATION")
+                or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
+            )
+            # set API KEY
+            api_key = (
+                api_key or
+                litellm.api_key or
+                litellm.openai_key or
+                get_secret("OPENAI_API_KEY")
+            )
+            api_type = "openai"
+            api_version = None
+
             ## LOGGING
             logging.pre_call(
                 input=input,
-                api_key=openai.api_key,
+                api_key=api_key,
                 additional_args={
-                    "api_type": openai.api_type,
-                    "api_base": openai.api_base,
-                    "api_version": openai.api_version,
+                    "api_type": api_type,
+                    "api_base": api_base,
+                    "api_version": api_version,
                 },
             )
             ## EMBEDDING CALL
-            response = openai.Embedding.create(input=input, model=model)
+            response = openai.Embedding.create(
+                input=input, 
+                model=model,
+                api_key=api_key,
+                api_base=api_base,
+                api_version=api_version,
+                api_type=api_type,
+            )
 
             ## LOGGING
-            logging.post_call(input=input, api_key=openai.api_key, original_response=response)
+            logging.post_call(input=input, api_key=api_key, original_response=response)
         elif model in litellm.cohere_embedding_models:
             cohere_key = (
                 api_key