Use call directly for chain (#8655)

for run_on_dataset since the `run()` method requires a single output

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

@@ -604,11 +604,8 @@ async def _arun_chain(
             inputs_, callbacks=callbacks, tags=tags
         )
     else:
-        if len(inputs) == 1:
-            inputs_ = next(iter(inputs.values()))
-            output = await chain.arun(inputs_, callbacks=callbacks, tags=tags)
-        else:
-            output = await chain.acall(inputs, callbacks=callbacks, tags=tags)
+        inputs_ = next(iter(inputs.values())) if len(inputs) == 1 else inputs
+        output = await chain.acall(inputs_, callbacks=callbacks, tags=tags)
     return output
 
 
@@ -926,11 +923,8 @@ def _run_chain(
         inputs_ = input_mapper(inputs)
         output: Union[dict, str] = chain(inputs_, callbacks=callbacks, tags=tags)
     else:
-        if len(inputs) == 1:
-            inputs_ = next(iter(inputs.values()))
-            output = chain.run(inputs_, callbacks=callbacks, tags=tags)
-        else:
-            output = chain(inputs, callbacks=callbacks, tags=tags)
+        inputs_ = next(iter(inputs.values())) if len(inputs) == 1 else inputs
+        output = chain(inputs_, callbacks=callbacks, tags=tags)
     return output