(fix) router: azure/embedding support

litellm/router.py

@@ -327,7 +327,7 @@ class Router:
             data["model"] = original_model_string[:index_of_model_id]
         else:
             data["model"] = original_model_string
-        model_client = deployment.get("async_client", None)
+        model_client = deployment.get("client", None)
         
         return await litellm.aembedding(**{**data, "input": input, "caching": self.cache_responses, "client": model_client, **kwargs})
 
@@ -830,6 +830,7 @@ class Router:
                 or custom_llm_provider == "openai"
                 or custom_llm_provider == "azure"
                 or "ft:gpt-3.5-turbo" in model_name
+                or model_name in litellm.open_ai_embedding_models
             ):
                 # glorified / complicated reading of configs
                 # user can pass vars directly or they can pas os.environ/AZURE_API_KEY, in which case we will read the env

litellm/tests/test_router.py

@@ -299,3 +299,34 @@ def test_aembedding_on_router():
 		traceback.print_exc()
 		pytest.fail(f"Error occurred: {e}")
 # test_aembedding_on_router()
+
+
+def test_azure_aembedding_on_router():
+	litellm.set_verbose = True
+	try:
+		model_list = [
+			{
+				"model_name": "text-embedding-ada-002",
+				"litellm_params": {
+					"model": "azure/azure-embedding-model",
+					"api_key":os.environ['AZURE_API_KEY'],
+					"api_base": os.environ['AZURE_API_BASE']
+				},
+				"tpm": 100000,
+				"rpm": 10000,
+			},
+		]
+
+		async def embedding_call():
+			router = Router(model_list=model_list)
+			response = await router.aembedding(
+				model="text-embedding-ada-002",
+				input=["good morning from litellm"]
+			)
+			print(response)
+			router.reset()
+		asyncio.run(embedding_call())
+	except Exception as e:
+		traceback.print_exc()
+		pytest.fail(f"Error occurred: {e}")
+# test_azure_aembedding_on_router()