Evaluate on Version

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

@@ -968,20 +968,24 @@ def _run_llm_or_chain(
     return result
 
 
-## Public API
-
-
 def _prepare_eval_run(
     client: Client,
     dataset_name: str,
     llm_or_chain_factory: MODEL_OR_CHAIN_FACTORY,
     project_name: str,
     project_metadata: Optional[Dict[str, Any]] = None,
     tags: Optional[List[str]] = None,
+    dataset_version: Optional[Union[str, datetime]] = None,
 ) -> Tuple[MCF, TracerSession, Dataset, List[Example]]:
     wrapped_model = _wrap_in_chain_factory(llm_or_chain_factory, dataset_name)
     dataset = client.read_dataset(dataset_name=dataset_name)
-    examples = list(client.list_examples(dataset_id=dataset.id))
+    as_of = dataset_version if isinstance(dataset_version, datetime) else None
+    if isinstance(dataset_version, str):
+        raise NotImplementedError(
+            "Selecting dataset_version by tag is not yet supported."
+            " Please use a datetime object."
+        )
+    examples = list(client.list_examples(dataset_id=dataset.id, as_of=as_of))
     if not examples:
         raise ValueError(f"Dataset {dataset_name} has no example rows.")
     modified_at = [ex.modified_at for ex in examples if ex.modified_at]
@@ -1173,6 +1177,7 @@ def prepare(
         concurrency_level: int = 5,
         project_metadata: Optional[Dict[str, Any]] = None,
         revision_id: Optional[str] = None,
+        dataset_version: Optional[Union[datetime, str]] = None,
     ) -> _DatasetRunContainer:
         project_name = project_name or name_generation.random_name()
         if revision_id:
@@ -1186,6 +1191,7 @@ def prepare(
             project_name,
             project_metadata=project_metadata,
             tags=tags,
+            dataset_version=dataset_version,
         )
         tags = tags or []
         for k, v in (project.metadata.get("git") or {}).items():
@@ -1269,18 +1275,20 @@ def _display_aggregate_results(aggregate_results: pd.DataFrame) -> None:
     "langchain.schema.runnable.base.RunnableLambda.html)"
 )
 
+## Public API
+
 
 async def arun_on_dataset(
     client: Optional[Client],
     dataset_name: str,
     llm_or_chain_factory: MODEL_OR_CHAIN_FACTORY,
     *,
     evaluation: Optional[smith_eval.RunEvalConfig] = None,
+    dataset_version: Optional[Union[datetime, str]] = None,
     concurrency_level: int = 5,
     project_name: Optional[str] = None,
     project_metadata: Optional[Dict[str, Any]] = None,
     verbose: bool = False,
-    tags: Optional[List[str]] = None,
     revision_id: Optional[str] = None,
     **kwargs: Any,
 ) -> Dict[str, Any]:
@@ -1289,6 +1297,13 @@ async def arun_on_dataset(
         warn_deprecated("0.0.305", message=_INPUT_MAPPER_DEP_WARNING, pending=True)
     if revision_id is None:
         revision_id = get_langchain_env_var_metadata().get("revision_id")
+    tags = kwargs.pop("tags", None)
+    if tags:
+        warn_deprecated(
+            "0.1.9",
+            message="The tags argument is deprecated and will be"
+            " removed in a future release. Please specify project_metadata instead.",
+        )
 
     if kwargs:
         warn_deprecated(
@@ -1310,6 +1325,7 @@ async def arun_on_dataset(
         concurrency_level,
         project_metadata=project_metadata,
         revision_id=revision_id,
+        dataset_version=dataset_version,
     )
     batch_results = await runnable_utils.gather_with_concurrency(
         container.configs[0].get("max_concurrency"),
@@ -1332,17 +1348,24 @@ def run_on_dataset(
     llm_or_chain_factory: MODEL_OR_CHAIN_FACTORY,
     *,
     evaluation: Optional[smith_eval.RunEvalConfig] = None,
+    dataset_version: Optional[Union[datetime, str]] = None,
     concurrency_level: int = 5,
     project_name: Optional[str] = None,
     project_metadata: Optional[Dict[str, Any]] = None,
     verbose: bool = False,
-    tags: Optional[List[str]] = None,
     revision_id: Optional[str] = None,
     **kwargs: Any,
 ) -> Dict[str, Any]:
     input_mapper = kwargs.pop("input_mapper", None)
     if input_mapper:
         warn_deprecated("0.0.305", message=_INPUT_MAPPER_DEP_WARNING, pending=True)
+    tags = kwargs.pop("tags", None)
+    if tags:
+        warn_deprecated(
+            "0.1.9",
+            message="The tags argument is deprecated and will be"
+            " removed in a future release. Please specify project_metadata instead.",
+        )
     if revision_id is None:
         revision_id = get_langchain_env_var_metadata().get("revision_id")
 
@@ -1366,6 +1389,7 @@ def run_on_dataset(
         concurrency_level,
         project_metadata=project_metadata,
         revision_id=revision_id,
+        dataset_version=dataset_version,
     )
     if concurrency_level == 0:
         batch_results = [
@@ -1458,8 +1482,8 @@ def construct_chain():
     client = Client()
     run_on_dataset(
         client,
-        "<my_dataset_name>",
-        construct_chain,
+        dataset_name="<my_dataset_name>",
+        llm_or_chain_factory=construct_chain,
         evaluation=evaluation_config,
     )
 
@@ -1496,8 +1520,8 @@ def _evaluate_strings(self, prediction, reference=None, input=None, **kwargs) ->
 
     run_on_dataset(
         client,
-        "<my_dataset_name>",
-        construct_chain,
+        dataset_name="<my_dataset_name>",
+        llm_or_chain_factory=construct_chain,
         evaluation=evaluation_config,
     )
 """  # noqa: E501