Merge pull request #750 from stanfordnlp/custom-rationale-typed-cot

Add Custom Rationale Type option in TypedChainOfThought Module

Author: krypticmouse

dspy/functional/functional.py

@@ -67,17 +67,21 @@ def __init__(self):
                 self.__dict__[name] = attr.copy()
 
 
-def TypedChainOfThought(signature, instructions=None, *, max_retries=3) -> dspy.Module:  # noqa: N802
+def TypedChainOfThought(signature, instructions=None, reasoning=None, *, max_retries=3) -> dspy.Module:  # noqa: N802
     """Just like TypedPredictor, but adds a ChainOfThought OutputField."""
     signature = ensure_signature(signature, instructions)
     output_keys = ", ".join(signature.output_fields.keys())
+
+    DEFAULT_RATIONALE = dspy.OutputField(
+        prefix="Reasoning: Let's think step by step in order to",
+        desc="${produce the " + output_keys + "}. We ...",
+    )
+    reasoning = reasoning or DEFAULT_RATIONALE
+
     return TypedPredictor(
         signature.prepend(
             "reasoning",
-            dspy.OutputField(
-                prefix="Reasoning: Let's think step by step in order to",
-                desc="${produce the " + output_keys + "}. We ...",
-            ),
+            reasoning,
         ),
         max_retries=max_retries,
     )

tests/functional/test_functional.py

@@ -619,6 +619,48 @@ class ScoredSignature(dspy.Signature):
         Proposed Signature: Output""")
 
 
+def test_custom_reasoning_field():
+    class Question(pydantic.BaseModel):
+        value: str
+
+    class QuestionSignature(dspy.Signature):
+        topic: str = dspy.InputField()
+        question: Question = dspy.OutputField()
+
+    reasoning = dspy.OutputField(
+        prefix="Custom Reasoning: Let's break this down. To generate a question about",
+        desc="${topic}, we should ...",
+    )
+
+    program = TypedChainOfThought(QuestionSignature, reasoning=reasoning)
+
+    expected = "What is the speed of light?"
+    lm = DummyLM(["Thoughts", f'{{"value": "{expected}"}}'])
+    dspy.settings.configure(lm=lm)
+
+    output = program(topic="Physics")
+
+    assert isinstance(output.question, Question)
+    assert output.question.value == expected
+
+    assert lm.get_convo(-1) == textwrap.dedent("""\
+        Given the fields `topic`, produce the fields `question`.
+
+        ---
+
+        Follow the following format.
+
+        Topic: ${topic}
+        Custom Reasoning: Let's break this down. To generate a question about ${topic}, we should ...
+        Question: ${question}. Respond with a single JSON object. JSON Schema: {"properties": {"value": {"title": "Value", "type": "string"}}, "required": ["value"], "title": "Question", "type": "object"}
+
+        ---
+
+        Topic: Physics
+        Custom Reasoning: Let's break this down. To generate a question about Thoughts
+        Question: {"value": "What is the speed of light?"}""")
+
+
 def test_generic_signature():
     T = TypeVar("T")