fix(router): route aspeech through async_function_with_fallbacks

Router.aspeech selected a deployment and awaited litellm.aspeech
directly, so TTS requests got no retry on failure and no failover to
backup deployments; the except block only fired an exception alert and
re-raised. Every other router endpoint (acompletion, aembedding,
atranscription, arerank) already delegates to
async_function_with_fallbacks

Mirror the atranscription pattern: move deployment selection and the
litellm.aspeech call into a private _aspeech method, then have the
public aspeech set kwargs["original_function"] = self._aspeech and
await self.async_function_with_fallbacks(**kwargs). _aspeech also picks
up the shared _get_async_openai_model_client helper and the same
total/success/fail call accounting the sibling endpoints use

Fixes #27778.

litellm/router.py

@@ -4042,47 +4042,13 @@ class Router:
         ```
         """
         try:
+            kwargs["model"] = model
             kwargs["input"] = input
             kwargs["voice"] = voice
-
-            deployment = await self.async_get_available_deployment(
-                model=model,
-                messages=[{"role": "user", "content": "prompt"}],
-                specific_deployment=kwargs.pop("specific_deployment", None),
-                request_kwargs=kwargs,
-            )
+            kwargs["original_function"] = self._aspeech
             self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs)
-            data = deployment["litellm_params"].copy()
-            data["model"]
-            for k, v in self.default_litellm_params.items():
-                if (
-                    k not in kwargs
-                ):  # prioritize model-specific params > default router params
-                    kwargs[k] = v
-                elif k == "metadata":
-                    kwargs[k].update(v)
+            response = await self.async_function_with_fallbacks(**kwargs)
 
-            potential_model_client = self._get_client(
-                deployment=deployment, kwargs=kwargs, client_type="async"
-            )
-            # check if provided keys == client keys #
-            dynamic_api_key = kwargs.get("api_key", None)
-            if (
-                dynamic_api_key is not None
-                and potential_model_client is not None
-                and dynamic_api_key != potential_model_client.api_key
-            ):
-                model_client = None
-            else:
-                model_client = potential_model_client
-
-            response = await litellm.aspeech(
-                **{
-                    **data,
-                    "client": model_client,
-                    **kwargs,
-                }
-            )
             return response
         except Exception as e:
             asyncio.create_task(
@@ -4095,6 +4061,56 @@ class Router:
             )
             raise e
 
+    async def _aspeech(self, model: str, input: str, voice: str, **kwargs):
+        model_name = model
+        try:
+            verbose_router_logger.debug(
+                f"Inside _aspeech()- model: {model}; kwargs: {kwargs}"
+            )
+            deployment = await self.async_get_available_deployment(
+                model=model,
+                messages=[{"role": "user", "content": "prompt"}],
+                specific_deployment=kwargs.pop("specific_deployment", None),
+                request_kwargs=kwargs,
+            )
+            data = deployment["litellm_params"].copy()
+            for k, v in self.default_litellm_params.items():
+                if (
+                    k not in kwargs
+                ):  # prioritize model-specific params > default router params
+                    kwargs[k] = v
+                elif k == "metadata":
+                    kwargs[k].update(v)
+
+            model_client = self._get_async_openai_model_client(
+                deployment=deployment,
+                kwargs=kwargs,
+            )
+
+            self.total_calls[model_name] += 1
+            response = await litellm.aspeech(
+                **{
+                    **data,
+                    "input": input,
+                    "voice": voice,
+                    "client": model_client,
+                    **kwargs,
+                }
+            )
+
+            self.success_calls[model_name] += 1
+            verbose_router_logger.info(
+                f"litellm.aspeech(model={model_name})\033[32m 200 OK\033[0m"
+            )
+            return response
+        except Exception as e:
+            verbose_router_logger.info(
+                f"litellm.aspeech(model={model_name})\033[31m Exception {str(e)}\033[0m"
+            )
+            if model_name is not None:
+                self.fail_calls[model_name] += 1
+            raise e
+
     async def arerank(self, model: str, **kwargs):
         try:
             kwargs["model"] = model

tests/router_unit_tests/test_router_endpoints.py

@@ -198,6 +198,70 @@ async def test_audio_speech_router(mode):
     assert test_logger.standard_logging_object["model_group"] == "tts"
 
 
+@pytest.mark.asyncio
+async def test_aspeech_fallbacks_on_deployment_failure():
+    router = Router(
+        model_list=[
+            {
+                "model_name": "tts-main",
+                "litellm_params": {"model": "openai/tts-1", "api_key": "fake-key"},
+            },
+            {
+                "model_name": "tts-backup",
+                "litellm_params": {"model": "openai/tts-1-hd", "api_key": "fake-key"},
+            },
+        ],
+        fallbacks=[{"tts-main": ["tts-backup"]}],
+        num_retries=0,
+    )
+
+    called_models = []
+
+    async def mock_aspeech(*args, **kwargs):
+        called_models.append(kwargs["model"])
+        if kwargs["model"] == "openai/tts-1":
+            raise litellm.InternalServerError(
+                message="deployment down",
+                llm_provider="openai",
+                model="tts-1",
+            )
+        return MagicMock()
+
+    with patch("litellm.aspeech", side_effect=mock_aspeech):
+        response = await router.aspeech(
+            model="tts-main",
+            input="the quick brown fox jumped over the lazy dogs",
+            voice="alloy",
+        )
+
+    assert response is not None
+    assert called_models == ["openai/tts-1", "openai/tts-1-hd"]
+
+
+@pytest.mark.asyncio
+async def test_aspeech_success_returns_response():
+    router = Router(
+        model_list=[
+            {
+                "model_name": "tts",
+                "litellm_params": {"model": "openai/tts-1", "api_key": "fake-key"},
+            },
+        ]
+    )
+
+    mock_response = MagicMock()
+    with patch("litellm.aspeech", return_value=mock_response) as mock_aspeech:
+        response = await router.aspeech(
+            model="tts",
+            input="the quick brown fox jumped over the lazy dogs",
+            voice="alloy",
+        )
+
+    assert response is mock_response
+    mock_aspeech.assert_called_once()
+    assert mock_aspeech.call_args.kwargs["model"] == "openai/tts-1"
+
+
 @pytest.mark.asyncio()
 async def test_rerank_endpoint(model_list):
     from litellm.types.utils import RerankResponse