fix(llm): cap the subscription backend's responses too

strix/config/models.py

@@ -433,14 +433,15 @@ class StrixProvider(MultiProvider):
             # The ChatGPT subscription backend is always streamed; it has no
             # non-streaming mode to fall back to, so LLM_DISABLE_STREAMING
             # does not apply here.
-            return _CodexResponsesModel(
+            model: Model = _CodexResponsesModel(
                 slug,
                 codex.get_subscription_client(),
                 reasoning_effort=llm.reasoning_effort,
             )
-        model = super().get_model(model_name)
-        if llm.disable_streaming:
-            model = _NonStreamingModel(model)
+        else:
+            model = super().get_model(model_name)
+            if llm.disable_streaming:
+                model = _NonStreamingModel(model)
         return _TurnGuardModel(model, max_tool_calls_per_turn=llm.max_tool_calls_per_turn)
 
 

tests/test_disable_streaming.py

@@ -315,14 +315,16 @@ def test_get_model_keeps_streaming_by_default(
     assert model._inner is inner
 
 
-def test_get_model_does_not_wrap_subscription_model(
+def test_get_model_guards_subscription_model_but_keeps_it_streaming(
     monkeypatch: pytest.MonkeyPatch, _reset_settings: None
 ) -> None:
-    # Subscription (ChatGPT) models are always streamed and must not be wrapped.
+    # Subscription (ChatGPT) models are always streamed, so LLM_DISABLE_STREAMING
+    # must not apply — but a runaway response needs capping there too.
     monkeypatch.setattr(codex, "subscription_model", lambda *_: "gpt-5.5")
     monkeypatch.setattr(codex, "get_subscription_client", lambda: AsyncOpenAI(api_key="x"))
     monkeypatch.setenv("LLM_DISABLE_STREAMING", "true")
     load_settings()
 
     model = StrixProvider().get_model("gpt-5.5")
-    assert not isinstance(model, _NonStreamingModel)
+    assert isinstance(model, _TurnGuardModel)
+    assert not isinstance(model._inner, _NonStreamingModel)