proxy - add azure/command r

litellm/router.py

@@ -1767,6 +1767,11 @@ class Router:
             or "ft:gpt-3.5-turbo" in model_name
             or model_name in litellm.open_ai_embedding_models
         ):
+            if custom_llm_provider == "azure":
+                if litellm.utils._is_non_openai_azure_model(model_name):
+                    custom_llm_provider = "openai"
+                    # remove azure prefx from model_name
+                    model_name = model_name.replace("azure/", "")
             # 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
             # we do this here because we init clients for Azure, OpenAI and we need to set the right key

litellm/tests/test_router_init.py

@@ -440,3 +440,46 @@ def test_openai_with_organization():
 
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+
+
+def test_init_clients_azure_command_r_plus():
+    # This tests that the router uses the OpenAI client for Azure/Command-R+
+    # For azure/command-r-plus we need to use openai.OpenAI because of how the Azure provider requires requests being sent
+    litellm.set_verbose = True
+    import logging
+    from litellm._logging import verbose_router_logger
+
+    verbose_router_logger.setLevel(logging.DEBUG)
+    try:
+        print("testing init 4 clients with diff timeouts")
+        model_list = [
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "azure/command-r-plus",
+                    "api_key": os.getenv("AZURE_COHERE_API_KEY"),
+                    "api_base": os.getenv("AZURE_COHERE_API_BASE"),
+                    "timeout": 0.01,
+                    "stream_timeout": 0.000_001,
+                    "max_retries": 7,
+                },
+            },
+        ]
+        router = Router(model_list=model_list, set_verbose=True)
+        for elem in router.model_list:
+            model_id = elem["model_info"]["id"]
+            async_client = router.cache.get_cache(f"{model_id}_async_client")
+            stream_async_client = router.cache.get_cache(
+                f"{model_id}_stream_async_client"
+            )
+            # Assert the Async Clients used are OpenAI clients and not Azure
+            # For using Azure/Command-R-Plus and Azure/Mistral the clients NEED to be OpenAI clients used
+            # this is weirdness introduced on Azure's side
+
+            assert "openai.AsyncOpenAI" in str(async_client)
+            assert "openai.AsyncOpenAI" in str(stream_async_client)
+        print("PASSED !")
+
+    except Exception as e:
+        traceback.print_exc()
+        pytest.fail(f"Error occurred: {e}")

litellm/utils.py

@@ -5563,6 +5563,19 @@ def get_formatted_prompt(
     return prompt
 
 
+def _is_non_openai_azure_model(model: str) -> bool:
+    try:
+        model_name = model.split("/", 1)[1]
+        if (
+            model_name in litellm.cohere_chat_models
+            or f"mistral/{model_name}" in litellm.mistral_chat_models
+        ):
+            return True
+    except:
+        return False
+    return False
+
+
 def get_llm_provider(
     model: str,
     custom_llm_provider: Optional[str] = None,
@@ -5576,13 +5589,8 @@ def get_llm_provider(
         # AZURE AI-Studio Logic - Azure AI Studio supports AZURE/Cohere
         # If User passes azure/command-r-plus -> we should send it to cohere_chat/command-r-plus
         if model.split("/", 1)[0] == "azure":
-            model_name = model.split("/", 1)[1]
-            if (
-                model_name in litellm.cohere_chat_models
-                or f"mistral/{model_name}" in litellm.mistral_chat_models
-            ):
+            if _is_non_openai_azure_model(model):
                 custom_llm_provider = "openai"
-                model = model_name
                 return model, custom_llm_provider, dynamic_api_key, api_base
 
         if custom_llm_provider: