From 00a20591746b1d40f9c0ec5407ea06efb5a31234 Mon Sep 17 00:00:00 2001 From: mateo Date: Thu, 13 Aug 2026 19:51:34 +0000 Subject: [PATCH] fix(router): resolve realtime session model to routed deployment Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/router.py | 22 +++++++++ tests/test_litellm/test_router.py | 76 +++++++++++++++++++++++++++++++ 2 files changed, 98 insertions(+) diff --git a/litellm/router.py b/litellm/router.py index fb2af41dcf2..95509bcdbba 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -29,6 +29,7 @@ import anyio import httpx import openai from openai import AsyncOpenAI +from pydantic import TypeAdapter, ValidationError from typing_extensions import overload import litellm @@ -342,6 +343,26 @@ def _stream_chunks_have_generated_content(chunks: Sequence[ModelResponseStream]) return False +_NO_SESSION_KWARGS: Final[Mapping[str, Mapping[str, object]]] = MappingProxyType({}) +_SESSION_ADAPTER: Final = TypeAdapter(Mapping[str, object]) + + +def _with_router_resolved_session_model(session: object, model_name: str) -> Mapping[str, Mapping[str, object]]: + """ + Realtime client-secret requests carry the model inside ``session`` as well, and the caller's copy of it still + holds the pre-routing model group name, so it has to follow the deployment the router just picked. + + Returns kwargs to merge into the downstream call, empty when there is no session model to resolve. + """ + try: + typed_session: Final = _SESSION_ADAPTER.validate_python(session) + except ValidationError: + return _NO_SESSION_KWARGS + if "model" not in typed_session: + return _NO_SESSION_KWARGS + return MappingProxyType({"session": {**typed_session, "model": model_name}}) + + class RoutingArgs(enum.Enum): ttl = 60 # 1min (RPM/TPM expire key) @@ -4685,6 +4706,7 @@ class Router: "caching": self.cache_responses, **kwargs, "model": model_name, + **_with_router_resolved_session_model(kwargs.get("session"), model_name), } # Only set custom_llm_provider if it's not None if custom_llm_provider is not None: diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index bdbf33fb0e1..fbefcc59477 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -1298,6 +1298,82 @@ async def test_ageneric_api_call_deployment_model_overrides_alias(): ), f"Expected deployment model 'vertex_ai/gemini-2.5-flash', got '{captured['model']}'" +@pytest.mark.asyncio +async def test_ageneric_api_call_resolves_realtime_session_model(): + """ + Regression for #36742: realtime client secret requests carry the model inside `session` too, and the proxy + fills it with the pre-routing model group name. The underlying litellm function reads session.model first, + so it must see the resolved deployment, while a caller's nested transcription model stays untouched. + """ + captured: dict = {} + + async def capture_kwargs(**kwargs): + captured.update(kwargs) + return {"result": "ok"} + + router = litellm.Router( + model_list=[ + { + "model_name": "my-realtime-group", + "litellm_params": { + "model": "openai/gpt-realtime-2.1-mini", + "api_key": "fake-key", + }, + "model_info": {"mode": "realtime"}, + } + ] + ) + + await router._ageneric_api_call_with_fallbacks( + model="my-realtime-group", + original_function=capture_kwargs, + session={ + "type": "realtime", + "model": "my-realtime-group", + "audio": {"input": {"transcription": {"model": "gpt-4o-transcribe"}}}, + }, + ) + + assert captured["model"] == "openai/gpt-realtime-2.1-mini" + assert captured["session"]["model"] == "openai/gpt-realtime-2.1-mini" + assert captured["session"]["audio"]["input"]["transcription"]["model"] == "gpt-4o-transcribe" + + +@pytest.mark.asyncio +async def test_ageneric_api_call_does_not_add_session_model(): + """ + A session that never carried a model must not gain one from routing: the underlying function then falls back + to the resolved `model` kwarg itself, and the outgoing session body keeps the caller's shape. + """ + captured: dict = {} + + async def capture_kwargs(**kwargs): + captured.update(kwargs) + return {"result": "ok"} + + router = litellm.Router( + model_list=[ + { + "model_name": "my-realtime-group", + "litellm_params": { + "model": "openai/gpt-realtime-2.1-mini", + "api_key": "fake-key", + }, + "model_info": {"mode": "realtime"}, + } + ] + ) + + await router._ageneric_api_call_with_fallbacks( + model="my-realtime-group", + original_function=capture_kwargs, + session={"type": "realtime"}, + ) + + assert captured["model"] == "openai/gpt-realtime-2.1-mini" + assert captured["session"] == {"type": "realtime"} + + def test_router_get_model_access_groups_team_only_models(): """ Test that Router.get_model_access_groups returns the correct response for team-only models