fix(LM): Change default temperature and max_tokens to be None (#8908)

* Set default parameters for reasoning model if not passed in.

* change warning level

* ruff

* remove default temperature and max_tokens

* Update tests to check that reasoning models with no params work

* Update dspy/clients/lm.py

Co-authored-by: Chen Qian <chen.qian@databricks.com>

---------

Co-authored-by: Chen Qian <chen.qian@databricks.com>

Author: isaacbmiller

dspy/clients/lm.py

@@ -31,8 +31,8 @@ def __init__(
         self,
         model: str,
         model_type: Literal["chat", "text", "responses"] = "chat",
-        temperature: float = 0.0,
-        max_tokens: int = 4000,
+        temperature: float | None = None,
+        max_tokens: int | None = None,
         cache: bool = True,
         callbacks: list[BaseCallback] | None = None,
         num_retries: int = 3,
@@ -88,9 +88,10 @@ def __init__(
         model_pattern = re.match(r"^(?:o[1345]|gpt-5)(?:-(?:mini|nano))?", model_family)
 
         if model_pattern:
-            if max_tokens < 16000 or temperature != 1.0:
+
+            if (temperature and temperature != 1.0) or (max_tokens and max_tokens < 16000):
                 raise ValueError(
-                    "OpenAI's reasoning models require passing temperature=1.0 and max_tokens >= 16000 to "
+                    "OpenAI's reasoning models require passing temperature=1.0 or None and max_tokens >= 16000 or None to "
                     "`dspy.LM(...)`, e.g., dspy.LM('openai/gpt-5', temperature=1.0, max_tokens=16000)"
                 )
             self.kwargs = dict(temperature=temperature, max_completion_tokens=max_tokens, **kwargs)

tests/clients/test_lm.py

@@ -318,7 +318,7 @@ def test_reasoning_model_requirements(model_name):
     # Should raise assertion error if temperature or max_tokens requirements not met
     with pytest.raises(
         ValueError,
-        match="reasoning models require passing temperature=1.0 and max_tokens >= 16000",
+        match="reasoning models require passing temperature=1.0 or None and max_tokens >= 16000 or None",
     ):
         dspy.LM(
             model=model_name,
@@ -334,6 +334,13 @@ def test_reasoning_model_requirements(model_name):
     )
     assert lm.kwargs["max_completion_tokens"] == 16_000
 
+    # Should pass with no parameters
+    lm = dspy.LM(
+        model=model_name,
+    )
+    assert lm.kwargs["temperature"] == None
+    assert lm.kwargs["max_completion_tokens"] == None
+
 
 def test_dump_state():
     lm = dspy.LM(