Init

docs/docs/guides/evaluation/guardrails_and_monitors.md

@@ -33,7 +33,7 @@ Guardrails are a way to prevent the LLM from generating harmful or inappropriate
 
 ```python
 res, call = op.call(user_input)
-scorer_res = await call.apply_scorer(guardrail)
+scorer_res = call.apply_scorer(guardrail)
 if scorer_res.score < 0.5:
     # Do something 
 else:

tests/trace/test_call_apply_scorer.py

@@ -1,4 +1,8 @@
-def test_scorer_op_no_context():
+
+
+def test_scorer_op_no_context(client):
+
+
     raise NotImplementedError()
 
 

weave/trace/weave_client.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import asyncio
 import dataclasses
 import datetime
 import inspect
@@ -462,7 +463,7 @@ def set_display_name(self, name: str | None) -> None:
     def remove_display_name(self) -> None:
         self.set_display_name(None)
 
-    async def apply_scorer(
+    async def _apply_scorer_async(
         self, scorer_op: Op | Scorer, additional_context: dict | None = None
     ) -> ApplyScorerResult:
         """
@@ -515,6 +516,11 @@ async def apply_scorer(
             score_call=score_call,
         )
 
+    def apply_scorer(
+        self, scorer_op: Op | Scorer, additional_context: dict | None = None
+    ) -> ApplyScorerResult:
+        return asyncio.run(self._apply_scorer_async(scorer_op, additional_context))
+
 
 def make_client_call(
     entity: str, project: str, server_call: CallSchema, server: TraceServerInterface