silly mypy fun

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

@@ -9,6 +9,7 @@ from enum import Enum
 from typing import (
     TYPE_CHECKING,
     Any,
+    Awaitable,
     Callable,
     Dict,
     List,
@@ -19,11 +20,18 @@ from typing import (
     cast,
 )
 
-from langsmith import Client, RunEvaluator
+from langsmith.client import Client
+from langsmith.evaluation import RunEvaluator
+from langsmith.run_helpers import is_traceable_function
+from langsmith.run_trees import RunTree
 from langsmith.schemas import Dataset, DataType, Example
 
 from langchain._api import warn_deprecated
-from langchain.callbacks.manager import Callbacks
+from langchain.callbacks.manager import (
+    AsyncCallbackManager,
+    CallbackManager,
+    Callbacks,
+)
 from langchain.callbacks.tracers.evaluation import (
     EvaluatorCallbackHandler,
     wait_for_all_evaluators,
@@ -41,7 +49,7 @@ from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import BaseMessage, messages_from_dict
 from langchain.schema.runnable import Runnable, RunnableConfig, RunnableLambda
 from langchain.schema.runnable import config as runnable_config
-from langchain.schema.runnable import utils as runnable_utils
+from langchain.schema.runnable.utils import Input, Output, gather_with_concurrency
 from langchain.smith import evaluation as smith_eval
 from langchain.smith.evaluation import config as smith_eval_config
 from langchain.smith.evaluation import name_generation, progress
@@ -49,6 +57,7 @@ from langchain.smith.evaluation import name_generation, progress
 if TYPE_CHECKING:
     import pandas as pd
 
+
 logger = logging.getLogger(__name__)
 
 MODEL_OR_CHAIN_FACTORY = Union[
@@ -68,6 +77,96 @@ class InputFormatError(Exception):
 ## Shared Utilities
 
 
+class RunnableTraceable(RunnableLambda):
+    """RunnableTraceable converts a @traceable decorated function
+
+    to a Runnable in a way that hands off the LangSmith tracing context.
+    """
+
+    def __init__(
+        self,
+        func: Callable,
+        afunc: Optional[Callable[..., Awaitable[Output]]] = None,
+    ) -> None:
+        wrapped: Optional[Callable[[Input], Output]] = None
+        awrapped = self._wrap_async(afunc)
+        if inspect.iscoroutinefunction(func):
+            if awrapped is not None:
+                raise TypeError(
+                    "Func was provided as a coroutine function, but afunc was "
+                    "also provided. If providing both, func should be a regular "
+                    "function to avoid ambiguity."
+                )
+            wrapped = cast(Callable[[Input], Output], self._wrap_async(func))
+        elif is_traceable_function(func):
+            wrapped = cast(Callable[[Input], Output], self._wrap_sync(func))
+        if wrapped is None:
+            raise ValueError(
+                f"{self.__class__.__name__} expects a function wrapped by the LangSmith"
+                f" @traceable decorator. Got {func}"
+            )
+
+        super().__init__(wrapped, awrapped)
+
+    @staticmethod
+    def _configure_run_tree(callback_manager: Any) -> Optional[RunTree]:
+        run_tree: Optional[RunTree] = None
+        if isinstance(callback_manager, (CallbackManager, AsyncCallbackManager)):
+            lc_tracers = [
+                handler
+                for handler in callback_manager.handlers
+                if isinstance(handler, LangChainTracer)
+            ]
+            if lc_tracers:
+                lc_tracer = lc_tracers[0]
+                run_tree = RunTree(
+                    id=callback_manager.parent_run_id,
+                    session_name=lc_tracer.project_name,
+                    name="Wrapping",
+                    run_type="chain",
+                    inputs={},
+                    tags=callback_manager.tags,
+                    extra={"metadata": callback_manager.metadata},
+                )
+        return run_tree
+
+    @staticmethod
+    def _wrap_sync(
+        func: Callable[..., Output]
+    ) -> Callable[[Input, RunnableConfig], Output]:
+        """Wrap a synchronous function to make it asynchronous."""
+
+        def wrap_traceable(inputs: dict, config: RunnableConfig) -> Any:
+            run_tree = RunnableTraceable._configure_run_tree(config.get("callbacks"))
+            return func(**inputs, langsmith_extra={"run_tree": run_tree})
+
+        return cast(Callable[[Input, RunnableConfig], Output], wrap_traceable)
+
+    @staticmethod
+    def _wrap_async(
+        afunc: Optional[Callable[..., Awaitable[Output]]]
+    ) -> Optional[Callable[[Input, RunnableConfig], Awaitable[Output]]]:
+        """Wrap an async function to make it synchronous."""
+
+        if afunc is None:
+            return None
+
+        if not is_traceable_function(afunc):
+            raise ValueError(
+                "RunnableTraceable expects a function wrapped by the LangSmith"
+                f" @traceable decorator. Got {afunc}"
+            )
+        afunc_ = cast(Callable[..., Awaitable[Output]], afunc)
+
+        async def awrap_traceable(inputs: dict, config: RunnableConfig) -> Any:
+            run_tree = RunnableTraceable._configure_run_tree(config.get("callbacks"))
+            return await afunc_(**inputs, langsmith_extra={"run_tree": run_tree})
+
+        return cast(
+            Callable[[Input, RunnableConfig], Awaitable[Output]], awrap_traceable
+        )
+
+
 class TestResult(dict):
     """A dictionary of the results of a single test run."""
 
@@ -152,6 +251,8 @@ def _wrap_in_chain_factory(
         lcf = llm_or_chain_factory
         return lambda: lcf
     elif callable(llm_or_chain_factory):
+        if is_traceable_function(llm_or_chain_factory):
+            return lambda: RunnableTraceable(cast(Callable, llm_or_chain_factory))
         try:
             _model = llm_or_chain_factory()  # type: ignore[call-arg]
         except TypeError:
@@ -166,6 +267,8 @@ def _wrap_in_chain_factory(
             # It's not uncommon to do an LLM constructor instead of raw LLM,
             # so we'll unpack it for the user.
             return _model
+        elif is_traceable_function(_model):
+            return lambda: RunnableTraceable(constructor)
         elif not isinstance(_model, Runnable):
             # This is unlikely to happen - a constructor for a model function
             return lambda: RunnableLambda(constructor)
@@ -1021,7 +1124,7 @@ async def arun_on_dataset(
         project_metadata=project_metadata,
     )
 
-    batch_results = await runnable_utils.gather_with_concurrency(
+    batch_results = await gather_with_concurrency(
         configs[0].get("max_concurrency"),
         *map(
             functools.partial(

libs/langchain/poetry.lock

@@ -3729,7 +3729,6 @@ optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
-    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
 ]
 
 [[package]]
@@ -4098,13 +4097,13 @@ all = ["datasets (>=2.12.0,<3.0.0)", "evaluate (>=0.4.0,<0.5.0)", "faiss-cpu (>=
 
 [[package]]
 name = "langsmith"
-version = "0.0.44"
+version = "0.0.51"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langsmith-0.0.44-py3-none-any.whl", hash = "sha256:5e7e5b45360ce89a2d5d6066a3b9fdd31b1f874a0cf19b1666c9792fecef0a1b"},
-    {file = "langsmith-0.0.44.tar.gz", hash = "sha256:74a262ba23a958ca1a4863d5386c151be462e40ccfcb8b39d0a5d8c9eaa40164"},
+    {file = "langsmith-0.0.51-py3-none-any.whl", hash = "sha256:6d65d038f8410344fba13a67437d1d7644a728983ca22ccf2c40dc32b8ba0368"},
+    {file = "langsmith-0.0.51.tar.gz", hash = "sha256:b014e16d95c48797e6ed7a053c952bbd23d3034883df4bca13cc958334332a7f"},
 ]
 
 [package.dependencies]
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-    {file = "scikit_learn-1.3.1-cp312-cp312-win_amd64.whl", hash = "sha256:0e1aa8f206d0de814b81b41d60c1ce31f7f2c7354597af38fae46d9c47c45122"},
     {file = "scikit_learn-1.3.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:52b77cc08bd555969ec5150788ed50276f5ef83abb72e6f469c5b91a0009bbca"},
     {file = "scikit_learn-1.3.1-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:a683394bc3f80b7c312c27f9b14ebea7766b1f0a34faf1a2e9158d80e860ec26"},
     {file = "scikit_learn-1.3.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a15d964d9eb181c79c190d3dbc2fff7338786bf017e9039571418a1d53dab236"},
@@ -10973,4 +10947,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "a36eb1f9d28e59ddc0cc5f3eee584ee4e054c8a87bf7c3c9a258b4a319aa1744"
+content-hash = "7eb9b03db03e3388d86889b4303df5d82fc9858b8827190f25b15d9965be2d76"

libs/langchain/pyproject.toml

@@ -115,7 +115,7 @@ cassio = {version = "^0.1.0", optional = true}
 rdflib = {version = "^6.3.2", optional = true}
 sympy = {version = "^1.12", optional = true}
 rapidfuzz = {version = "^3.1.1", optional = true}
-langsmith = "~0.0.43"
+langsmith = "~0.0.51"
 rank-bm25 = {version = "^0.2.2", optional = true}
 amadeus = {version = ">=8.1.0", optional = true}
 geopandas = {version = "^0.13.1", optional = true}