[Py] Default to unnamed (#1024)

Also use cached client for defaults in testing to avoid creating new
threads

python/langsmith/_expect.py

@@ -59,6 +59,7 @@ def test_output_semantically_close():
 
 from langsmith import client as ls_client
 from langsmith import run_helpers as rh
+from langsmith import run_trees as rt
 from langsmith import utils as ls_utils
 
 if TYPE_CHECKING:
@@ -103,7 +104,7 @@ def __init__(
     def _submit_feedback(self, score: int, message: Optional[str] = None) -> None:
         if not ls_utils.test_tracking_is_disabled():
             if not self._client:
-                self._client = ls_client.Client()
+                self._client = rt.get_cached_client()
             self._executor.submit(
                 self._client.create_feedback,
                 run_id=self._run_id,
@@ -431,7 +432,7 @@ def _submit_feedback(self, key: str, results: dict):
         run_id = current_run.trace_id if current_run else None
         if not ls_utils.test_tracking_is_disabled():
             if not self._client:
-                self._client = ls_client.Client()
+                self._client = rt.get_cached_client()
             self.executor.submit(
                 self._client.create_feedback, run_id=run_id, key=key, **results
             )

python/langsmith/_internal/_embedding_distance.py

@@ -63,7 +63,7 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray:
 def _get_openai_encoder() -> Callable[[Sequence[str]], Sequence[Sequence[float]]]:
     """Get the OpenAI GPT-3 encoder."""
     try:
-        from openai import Client
+        from openai import Client as OpenAIClient
     except ImportError:
         raise ImportError(
             "THe default encoder for the EmbeddingDistance class uses the OpenAI API. "
@@ -72,7 +72,7 @@ def _get_openai_encoder() -> Callable[[Sequence[str]], Sequence[Sequence[float]]
         )
 
     def encode_text(texts: Sequence[str]) -> Sequence[Sequence[float]]:
-        client = Client()
+        client = OpenAIClient()
         response = client.embeddings.create(
             input=list(texts), model="text-embedding-3-small"
         )

python/langsmith/_testing.py

@@ -18,6 +18,7 @@
 from langsmith import client as ls_client
 from langsmith import env as ls_env
 from langsmith import run_helpers as rh
+from langsmith import run_trees as rt
 from langsmith import schemas as ls_schemas
 from langsmith import utils as ls_utils
 
@@ -387,7 +388,7 @@ def __init__(
         experiment: ls_schemas.TracerSession,
         dataset: ls_schemas.Dataset,
     ):
-        self.client = client or ls_client.Client()
+        self.client = client or rt.get_cached_client()
         self._experiment = experiment
         self._dataset = dataset
         self._version: Optional[datetime.datetime] = None
@@ -413,7 +414,7 @@ def from_test(
         func: Callable,
         test_suite_name: Optional[str] = None,
     ) -> _LangSmithTestSuite:
-        client = client or ls_client.Client()
+        client = client or rt.get_cached_client()
         test_suite_name = test_suite_name or _get_test_suite_name(func)
         with cls._lock:
             if not cls._instances:
@@ -526,7 +527,7 @@ def _get_test_repr(func: Callable, sig: inspect.Signature) -> str:
 def _ensure_example(
     func: Callable, *args: Any, langtest_extra: _UTExtra, **kwargs: Any
 ) -> Tuple[_LangSmithTestSuite, uuid.UUID]:
-    client = langtest_extra["client"] or ls_client.Client()
+    client = langtest_extra["client"] or rt.get_cached_client()
     output_keys = langtest_extra["output_keys"]
     signature = inspect.signature(func)
     inputs: dict = rh._get_inputs_safe(signature, *args, **kwargs)

python/langsmith/beta/_evals.py

@@ -9,6 +9,7 @@
 import uuid
 from typing import DefaultDict, List, Optional, Sequence, Tuple, TypeVar
 
+import langsmith.run_trees as rt
 import langsmith.schemas as ls_schemas
 from langsmith import evaluation as ls_eval
 from langsmith._internal._beta_decorator import warn_beta
@@ -121,7 +122,7 @@ def convert_runs_to_test(
     """
     if not runs:
         raise ValueError(f"""Expected a non-empty sequence of runs. Received: {runs}""")
-    client = client or Client()
+    client = client or rt.get_cached_client()
     ds = client.create_dataset(dataset_name=dataset_name)
     outputs = [r.outputs for r in runs] if include_outputs else None
     client.create_examples(
@@ -229,7 +230,7 @@ def compute_test_metrics(
             raise NotImplementedError(
                 f"Evaluation not yet implemented for evaluator of type {type(func)}"
             )
-    client = client or Client()
+    client = client or rt.get_cached_client()
     traces = _load_nested_traces(project_name, client)
     with ContextThreadPoolExecutor(max_workers=max_concurrency) as executor:
         results = executor.map(

python/langsmith/evaluation/_arunner.py

@@ -26,6 +26,7 @@
 import langsmith
 from langsmith import run_helpers as rh
 from langsmith import run_trees, schemas
+from langsmith import run_trees as rt
 from langsmith import utils as ls_utils
 from langsmith._internal import _aiter as aitertools
 from langsmith.evaluation._runner import (
@@ -324,7 +325,7 @@ async def aevaluate_existing(
 
 
     """  # noqa: E501
-    client = client or langsmith.Client()
+    client = client or run_trees.get_cached_client()
     project = (
         experiment
         if isinstance(experiment, schemas.TracerSession)
@@ -366,7 +367,7 @@ async def _aevaluate(
     is_async_target = asyncio.iscoroutinefunction(target) or (
         hasattr(target, "__aiter__") and asyncio.iscoroutine(target.__aiter__())
     )
-    client = client or langsmith.Client()
+    client = client or rt.get_cached_client()
     runs = None if is_async_target else cast(Iterable[schemas.Run], target)
     experiment_, runs = await aitertools.aio_to_thread(
         _resolve_experiment,

python/langsmith/evaluation/_runner.py

@@ -36,7 +36,8 @@
 import langsmith
 from langsmith import env as ls_env
 from langsmith import run_helpers as rh
-from langsmith import run_trees, schemas
+from langsmith import run_trees as rt
+from langsmith import schemas
 from langsmith import utils as ls_utils
 from langsmith.evaluation.evaluator import (
     ComparisonEvaluationResult,
@@ -346,7 +347,7 @@ def evaluate_existing(
         ... )  # doctest: +ELLIPSIS
         View the evaluation results for experiment:...
     """  # noqa: E501
-    client = client or langsmith.Client()
+    client = client or rt.get_cached_client()
     project = (
         experiment
         if isinstance(experiment, schemas.TracerSession)
@@ -660,7 +661,7 @@ def evaluate_comparative(
         )
     if max_concurrency < 0:
         raise ValueError("max_concurrency must be a positive integer.")
-    client = client or langsmith.Client()
+    client = client or rt.get_cached_client()
 
     # TODO: Add information about comparison experiments
     projects = [_load_experiment(experiment, client) for experiment in experiments]
@@ -859,7 +860,7 @@ def _evaluate(
     experiment: Optional[Union[schemas.TracerSession, str, uuid.UUID]] = None,
 ) -> ExperimentResults:
     # Initialize the experiment manager.
-    client = client or langsmith.Client()
+    client = client or rt.get_cached_client()
     runs = None if _is_callable(target) else cast(Iterable[schemas.Run], target)
     experiment_, runs = _resolve_experiment(
         experiment,
@@ -982,7 +983,7 @@ def __init__(
         client: Optional[langsmith.Client] = None,
         description: Optional[str] = None,
     ):
-        self.client = client or langsmith.Client()
+        self.client = client or rt.get_cached_client()
         self._experiment: Optional[schemas.TracerSession] = None
         if experiment is None:
             self._experiment_name = _get_random_name()
@@ -1556,7 +1557,7 @@ def _forward(
 ) -> _ForwardResults:
     run: Optional[schemas.RunBase] = None
 
-    def _get_run(r: run_trees.RunTree) -> None:
+    def _get_run(r: rt.RunTree) -> None:
         nonlocal run
         run = r
 

python/langsmith/run_trees.py

@@ -31,7 +31,8 @@
 _LOCK = threading.Lock()
 
 
-def _get_client() -> Client:
+# Note, this is called directly by langchain. Do not remove.
+def get_cached_client() -> Client:
     global _CLIENT
     if _CLIENT is None:
         with _LOCK:
@@ -78,11 +79,13 @@ class Config:
     @root_validator(pre=True)
     def infer_defaults(cls, values: dict) -> dict:
         """Assign name to the run."""
-        if values.get("name") is None and "serialized" in values:
+        if values.get("name") is None and values.get("serialized") is not None:
             if "name" in values["serialized"]:
                 values["name"] = values["serialized"]["name"]
             elif "id" in values["serialized"]:
                 values["name"] = values["serialized"]["id"][-1]
+        if values.get("name") is None:
+            values["name"] = "Unnamed"
         if "client" in values:  # Handle user-constructed clients
             values["_client"] = values["client"]
         if values.get("parent_run") is not None:
@@ -126,7 +129,7 @@ def client(self) -> Client:
         # Lazily load the client
         # If you never use this for API calls, it will never be loaded
         if not self._client:
-            self._client = _get_client()
+            self._client = get_cached_client()
         return self._client
 
     def add_tags(self, tags: Union[Sequence[str], str]) -> None:

python/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langsmith"
-version = "0.1.124"
+version = "0.1.125"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 authors = ["LangChain <support@langchain.dev>"]
 license = "MIT"