Override Keys Option (#13537)

Should be able to override the global key if you want to evaluate
different outputs in a single run

libs/langchain/langchain/smith/evaluation/config.py

@@ -54,6 +54,26 @@ class EvalConfig(BaseModel):
         return kwargs
 
 
+class SingleKeyEvalConfig(EvalConfig):
+    reference_key: Optional[str] = None
+    """The key in the dataset run to use as the reference string.
+    If not provided, we will attempt to infer automatically."""
+    prediction_key: Optional[str] = None
+    """The key from the traced run's outputs dictionary to use to
+    represent the prediction. If not provided, it will be inferred
+    automatically."""
+    input_key: Optional[str] = None
+    """The key from the traced run's inputs dictionary to use to represent the
+    input. If not provided, it will be inferred automatically."""
+
+    def get_kwargs(self) -> Dict[str, Any]:
+        kwargs = super().get_kwargs()
+        # Filer out the keys that are not needed for the evaluator.
+        for key in ["reference_key", "prediction_key", "input_key"]:
+            kwargs.pop(key, None)
+        return kwargs
+
+
 class RunEvalConfig(BaseModel):
     """Configuration for a run evaluation.
 
@@ -113,7 +133,7 @@ class RunEvalConfig(BaseModel):
     class Config:
         arbitrary_types_allowed = True
 
-    class Criteria(EvalConfig):
+    class Criteria(SingleKeyEvalConfig):
         """Configuration for a reference-free criteria evaluator.
 
         Parameters
@@ -134,7 +154,7 @@ class RunEvalConfig(BaseModel):
         ) -> None:
             super().__init__(criteria=criteria, **kwargs)
 
-    class LabeledCriteria(EvalConfig):
+    class LabeledCriteria(SingleKeyEvalConfig):
         """Configuration for a labeled (with references) criteria evaluator.
 
         Parameters
@@ -154,7 +174,7 @@ class RunEvalConfig(BaseModel):
         ) -> None:
             super().__init__(criteria=criteria, **kwargs)
 
-    class EmbeddingDistance(EvalConfig):
+    class EmbeddingDistance(SingleKeyEvalConfig):
         """Configuration for an embedding distance evaluator.
 
         Parameters
@@ -174,7 +194,7 @@ class RunEvalConfig(BaseModel):
         class Config:
             arbitrary_types_allowed = True
 
-    class StringDistance(EvalConfig):
+    class StringDistance(SingleKeyEvalConfig):
         """Configuration for a string distance evaluator.
 
         Parameters
@@ -196,7 +216,7 @@ class RunEvalConfig(BaseModel):
         """Whether to normalize the distance to between 0 and 1.
         Applies only to the Levenshtein and Damerau-Levenshtein distances."""
 
-    class QA(EvalConfig):
+    class QA(SingleKeyEvalConfig):
         """Configuration for a QA evaluator.
 
         Parameters
@@ -211,7 +231,7 @@ class RunEvalConfig(BaseModel):
         llm: Optional[BaseLanguageModel] = None
         prompt: Optional[BasePromptTemplate] = None
 
-    class ContextQA(EvalConfig):
+    class ContextQA(SingleKeyEvalConfig):
         """Configuration for a context-based QA evaluator.
 
         Parameters
@@ -227,7 +247,7 @@ class RunEvalConfig(BaseModel):
         llm: Optional[BaseLanguageModel] = None
         prompt: Optional[BasePromptTemplate] = None
 
-    class CoTQA(EvalConfig):
+    class CoTQA(SingleKeyEvalConfig):
         """Configuration for a context-based QA evaluator.
 
         Parameters
@@ -243,7 +263,7 @@ class RunEvalConfig(BaseModel):
         llm: Optional[BaseLanguageModel] = None
         prompt: Optional[BasePromptTemplate] = None
 
-    class JsonValidity(EvalConfig):
+    class JsonValidity(SingleKeyEvalConfig):
         """Configuration for a json validity evaluator.
 
         Parameters
@@ -261,7 +281,7 @@ class RunEvalConfig(BaseModel):
 
         evaluator_type: EvaluatorType = EvaluatorType.JSON_EQUALITY
 
-    class ExactMatch(EvalConfig):
+    class ExactMatch(SingleKeyEvalConfig):
         """Configuration for an exact match string evaluator.
 
         Parameters
@@ -279,7 +299,7 @@ class RunEvalConfig(BaseModel):
         ignore_punctuation: bool = False
         ignore_numbers: bool = False
 
-    class RegexMatch(EvalConfig):
+    class RegexMatch(SingleKeyEvalConfig):
         """Configuration for a regex match string evaluator.
 
         Parameters
@@ -291,7 +311,7 @@ class RunEvalConfig(BaseModel):
         evaluator_type: EvaluatorType = EvaluatorType.REGEX_MATCH
         flags: int = 0
 
-    class ScoreString(EvalConfig):
+    class ScoreString(SingleKeyEvalConfig):
         """Configuration for a score string evaluator.
         This is like the criteria evaluator but it is configured by
         default to return a score on the scale from 1-10.

libs/langchain/langchain/smith/evaluation/runner_utils.py

@@ -487,6 +487,11 @@ def _construct_run_evaluator(
         kwargs = {"llm": eval_llm, **eval_config.get_kwargs()}
         evaluator_ = load_evaluator(eval_config.evaluator_type, **kwargs)
         eval_type_tag = eval_config.evaluator_type.value
+        # Override keys if specified in the config
+        if isinstance(eval_config, smith_eval_config.SingleKeyEvalConfig):
+            input_key = eval_config.input_key or input_key
+            prediction_key = eval_config.prediction_key or prediction_key
+            reference_key = eval_config.reference_key or reference_key
 
     if isinstance(evaluator_, StringEvaluator):
         if evaluator_.requires_reference and reference_key is None: