Add reasoning summaries support

llm_openai.py

@@ -82,6 +82,12 @@ class ReasoningEffortEnum(str, Enum):
     high = "high"
 
 
+class ReasoningSummaryEnum(str, Enum):
+    auto = "auto"
+    concise = "concise"
+    detailed = "detailed"
+
+
 class BaseOptions(Options):
     max_output_tokens: Optional[int] = Field(
         description=(
@@ -149,6 +155,14 @@ class ReasoningOptions(Options):
         ),
         default=None,
     )
+    reasoning_summary: Optional[ReasoningSummaryEnum] = Field(
+        description=(
+            "A summary of the reasoning performed by the model. This can be useful for "
+            "debugging and understanding the model's reasoning process. One of 'auto', "
+            "'concise', or 'detailed'."
+        ),
+        default=None,
+    )
 
 
 class _SharedResponses:
@@ -286,6 +300,17 @@ def _build_kwargs(self, prompt, conversation):
             if value is not None:
                 kwargs[option] = value
 
+        # Build reasoning options if either effort or summary is specified
+        reasoning_effort = getattr(prompt.options, "reasoning_effort", None)
+        reasoning_summary = getattr(prompt.options, "reasoning_summary", None)
+        if reasoning_effort is not None or reasoning_summary is not None:
+            reasoning = {}
+            if reasoning_effort is not None:
+                reasoning["effort"] = reasoning_effort.value
+            if reasoning_summary is not None:
+                reasoning["summary"] = reasoning_summary.value
+            kwargs["reasoning"] = reasoning
+
         if prompt.tools:
             tool_defs = []
             for tool in prompt.tools:

tests/test_openai.py

@@ -76,3 +76,49 @@ def simple_tool(number):
     )
     output = chain_response.text()
     assert output == snapshot
+
+
+def test_reasoning_options_in_kwargs():
+    """Test that reasoning options are correctly passed to the API."""
+    model = llm.get_model("openai/gpt-5-mini")
+    prompt = llm.Prompt(
+        model=model,
+        prompt="What is 2+2?",
+        options=model.Options(reasoning_effort="high", reasoning_summary="auto")
+    )
+    kwargs = model._build_kwargs(prompt, conversation=None)
+
+    # Verify reasoning parameter is set correctly
+    assert "reasoning" in kwargs
+    assert kwargs["reasoning"]["effort"] == "high"
+    assert kwargs["reasoning"]["summary"] == "auto"
+
+
+def test_reasoning_effort_only_in_kwargs():
+    """Test that reasoning_effort works without reasoning_summary."""
+    model = llm.get_model("openai/gpt-5-mini")
+    prompt = llm.Prompt(
+        model=model,
+        prompt="What is 2+2?",
+        options=model.Options(reasoning_effort="medium")
+    )
+    kwargs = model._build_kwargs(prompt, conversation=None)
+
+    assert "reasoning" in kwargs
+    assert kwargs["reasoning"]["effort"] == "medium"
+    assert "summary" not in kwargs["reasoning"]
+
+
+def test_reasoning_summary_only_in_kwargs():
+    """Test that reasoning_summary works without reasoning_effort."""
+    model = llm.get_model("openai/gpt-5-mini")
+    prompt = llm.Prompt(
+        model=model,
+        prompt="What is 2+2?",
+        options=model.Options(reasoning_summary="detailed")
+    )
+    kwargs = model._build_kwargs(prompt, conversation=None)
+
+    assert "reasoning" in kwargs
+    assert kwargs["reasoning"]["summary"] == "detailed"
+    assert "effort" not in kwargs["reasoning"]