Add function to identify official OpenAI API and update reasoning handling in LLM kwargs

Introduce a new helper function to check if the LLM base URI targets the official OpenAI API. Modify the reasoning handling in the build_llm_kwargs function to differentiate between official OpenAI and other OpenAI-compatible providers, ensuring correct structuring of reasoning data in the kwargs. Enhance tests to validate these changes.

Author: stormaref

src/sub_agent_mcp/agent/builder.py

@@ -17,6 +17,11 @@
 DEFAULT_RECURSION_LIMIT = int(os.getenv("AGENT_RECURSION_LIMIT", "25"))
 
 
+def _is_official_openai_api(base_uri: str) -> bool:
+    """Return True when the LLM base URL targets the official OpenAI API."""
+    return "api.openai.com" in base_uri.lower()
+
+
 def build_llm_kwargs(agent: AgentConfig) -> dict[str, Any]:
     """Map agent LLM config to ChatOpenAI constructor kwargs."""
     llm = agent.llm
@@ -34,14 +39,17 @@ def build_llm_kwargs(agent: AgentConfig) -> dict[str, Any]:
     reasoning: dict[str, str] = {}
     if llm.reasoning_effort is not None:
         reasoning["effort"] = llm.reasoning_effort
-        kwargs["reasoning_effort"] = llm.reasoning_effort
     if llm.reasoning_summary is not None:
         reasoning["summary"] = llm.reasoning_summary
 
     if reasoning:
-        kwargs["reasoning"] = reasoning
-        # OpenRouter and other OpenAI-compatible providers expect reasoning here.
-        kwargs["extra_body"] = {"reasoning": reasoning}
+        if _is_official_openai_api(str(llm.base_uri)):
+            # Official OpenAI uses the Responses API reasoning object.
+            kwargs["reasoning"] = reasoning
+        else:
+            # OpenRouter and other OpenAI-compatible providers use Chat Completions
+            # with provider-specific fields nested under extra_body.
+            kwargs["extra_body"] = {"reasoning": reasoning}
 
     return kwargs
 

tests/test_builder.py

@@ -37,11 +37,32 @@ def test_build_llm_kwargs_minimal() -> None:
 def test_build_llm_kwargs_includes_reasoning_effort() -> None:
     kwargs = build_llm_kwargs(_agent(reasoning_effort="high"))
 
-    assert kwargs["reasoning_effort"] == "high"
-    assert kwargs["reasoning"] == {"effort": "high"}
+    assert "reasoning_effort" not in kwargs
+    assert "reasoning" not in kwargs
     assert kwargs["extra_body"] == {"reasoning": {"effort": "high"}}
 
 
+def test_build_llm_kwargs_openai_uses_reasoning_object() -> None:
+    agent = AgentConfig(
+        id="researcher",
+        title="Research Agent",
+        description="Test agent",
+        llm=LLMConfig(
+            base_uri="https://api.openai.com/v1",
+            api_key=SecretStr("test-key"),
+            model_id="gpt-5-nano",
+            reasoning_effort="medium",
+        ),
+        system_prompt="You are helpful.",
+    )
+
+    kwargs = build_llm_kwargs(agent)
+
+    assert kwargs["reasoning"] == {"effort": "medium"}
+    assert "extra_body" not in kwargs
+    assert "reasoning_effort" not in kwargs
+
+
 def test_build_llm_kwargs_includes_reasoning_summary() -> None:
     kwargs = build_llm_kwargs(
         _agent(