automatically turn on reasoning for COT on reasoning model

Author: chenmoneygithub

dspy/adapters/base.py

@@ -73,13 +73,13 @@ def _call_preprocess(
 
                 return signature_for_native_function_calling
 
-        # Handle custom types that use native response
+        # Handle custom types that use native LM features, e.g., reasoning, citations, etc.
         for name, field in signature.output_fields.items():
             if (
                 isinstance(field.annotation, type)
                 and issubclass(field.annotation, Type)
                 and field.annotation in self.native_response_types
-                and field.annotation.is_natively_supported(lm, lm_kwargs)
+                and field.annotation.adapt_to_native_lm_feature(lm, lm_kwargs)
             ):
                 signature = signature.delete(name)
 
@@ -134,7 +134,7 @@ def _call_postprocess(
                     isinstance(field.annotation, type)
                     and issubclass(field.annotation, Type)
                     and field.annotation in self.native_response_types
-                    and field.annotation.is_natively_supported(lm, lm_kwargs)
+                    and field.annotation.adapt_to_native_lm_feature(lm, lm_kwargs)
                 ):
                     value[name] = field.annotation.parse_lm_response(output)
 

dspy/adapters/types/base_type.py

@@ -71,8 +71,8 @@ def serialize_model(self):
         return formatted
 
     @classmethod
-    def is_natively_supported(cls, lm, lm_kwargs) -> bool:
-        """Whether the custom type is natively supported by the LM."""
+    def adapt_to_native_lm_feature(cls, lm, lm_kwargs) -> bool:
+        """Check whether the custom type is natively supported by the LM and adapt to the native feature if possible."""
         return False
 
     @classmethod

dspy/adapters/types/citation.py

@@ -166,8 +166,7 @@ def __getitem__(self, index):
         return self.citations[index]
 
     @classmethod
-    def is_natively_supported(cls, lm, lm_kwargs) -> bool:
-        """Whether the Citations type is natively supported by the LM."""
+    def adapt_to_native_lm_feature(cls, lm, lm_kwargs) -> bool:
         return lm.model.startswith("anthropic/")
 
     @classmethod

dspy/adapters/types/reasoning.py

@@ -40,8 +40,7 @@ def validate_input(cls, data: Any):
         raise ValueError(f"Received invalid value for `dspy.Reasoning`: {data}")
 
     @classmethod
-    def is_natively_supported(cls, lm, lm_kwargs) -> bool:
-        """Whether the Reasoning type is natively supported by the LM."""
+    def adapt_to_native_lm_feature(cls, lm, lm_kwargs) -> bool:
         if not litellm.supports_reasoning(lm.model):
             return False
 
@@ -53,7 +52,11 @@ def is_natively_supported(cls, lm, lm_kwargs) -> bool:
         else:
             reasoning_effort = None
 
-        return reasoning_effort is not None
+        if reasoning_effort is None:
+            # Turn on the native reasoning
+            lm_kwargs["reasoning_effort"] = "low"
+
+        return True
 
     @classmethod
     def parse_lm_response(cls, response: str | dict[str, Any]) -> Optional["Reasoning"]:

tests/predict/test_chain_of_thought.py

@@ -31,7 +31,7 @@ async def test_async_chain_of_thought():
 def test_chain_of_thought_with_native_reasoning():
     """Test ChainOfThought with native reasoning support where LM returns reasoning natively."""
 
-    lm = dspy.LM(model="anthropic/claude-3-7-sonnet-20250219", reasoning_effort="low", cache=False)
+    lm = dspy.LM(model="anthropic/claude-3-7-sonnet-20250219", cache=False)
     dspy.settings.configure(lm=lm)
 
     with mock.patch("litellm.completion") as mock_completion:
@@ -53,6 +53,11 @@ def test_chain_of_thought_with_native_reasoning():
         assert isinstance(result.reasoning, dspy.Reasoning)
         assert result.reasoning.content == "Step-by-step thinking about the capital of France"
 
+        # Check that the reasoning_effort is automatically set to "low" when the LM supports native reasoning and not
+        # provided in the LM kwargs
+        args, kwargs = mock_completion.call_args
+        assert kwargs["reasoning_effort"] == "low"
+
 
 def test_chain_of_thought_with_manual_reasoning():
     """Test ChainOfThought with manual reasoning where LM doesn't support native reasoning."""