add cohere embedding models

litellm/main.py

@@ -54,6 +54,7 @@ from litellm.utils import (
     get_secret,
     CustomStreamWrapper,
     ModelResponse,
+    EmbeddingResponse,
     read_config_args,
 )
 
@@ -1352,7 +1353,15 @@ def batch_completion_models_all_responses(*args, **kwargs):
     60
 )  ## set timeouts, in case calls hang (e.g. Azure) - default is 60s, override with `force_timeout`
 def embedding(
-    model, input=[], azure=False, force_timeout=60, litellm_call_id=None, litellm_logging_obj=None, logger_fn=None, caching=False,
+    model, 
+    input=[], 
+    azure=False, 
+    force_timeout=60, 
+    litellm_call_id=None, 
+    litellm_logging_obj=None,
+    logger_fn=None, 
+    caching=False,
+    api_key=None,
 ):
     try:
         response = None
@@ -1393,6 +1402,23 @@ def embedding(
             )
             ## EMBEDDING CALL
             response = openai.Embedding.create(input=input, model=model)
+        elif model in litellm.cohere_embedding_models:
+            cohere_key = (
+                api_key
+                or litellm.cohere_key
+                or get_secret("COHERE_API_KEY")
+                or get_secret("CO_API_KEY")
+                or litellm.api_key
+            )
+            response = cohere.embedding(
+                model=model,
+                input=input,
+                encoding=encoding,
+                api_key=cohere_key,
+                logging_obj=logging,
+                model_response= EmbeddingResponse()
+
+            )
         else:
             args = locals()
             raise ValueError(f"No valid embedding model args passed in - {args}")