Update BootstrapFewShot.md

docs/api/optimizers/BootstrapFewShot.md

@@ -10,7 +10,7 @@ The constructor initializes the `BootstrapFewShot` class and sets up parameters
 
 ```python
 class BootstrapFewShot(Teleprompter):
- def __init__(self, metric=None, teacher_settings={}, max_bootstrapped_demos=4, max_labeled_demos=16, max_rounds=1):
+ def __init__(self, metric=None, metric_threshold=None, teacher_settings={}, max_bootstrapped_demos=4, max_labeled_demos=16, max_rounds=1, max_errors=5):
  self.metric = metric
  self.teacher_settings = teacher_settings
 
@@ -21,10 +21,12 @@ class BootstrapFewShot(Teleprompter):
 
 **Parameters:**
 - `metric` (_callable_, _optional_): Metric function to evaluate examples during bootstrapping. Defaults to `None`.
+- `metric_threshold` (_float_, _optional_): Score threshold for metric to determine successful example. Defaults to `None`.
 - `teacher_settings` (_dict_, _optional_): Settings for teacher predictor. Defaults to empty dictionary.
 - `max_bootstrapped_demos` (_int_, _optional_): Maximum number of bootstrapped demonstrations per predictor. Defaults to 4.
 - `max_labeled_demos` (_int_, _optional_): Maximum number of labeled demonstrations per predictor. Defaults to 16.
 - `max_rounds` (_int_, _optional_): Maximum number of bootstrapping rounds. Defaults to 1.
+- `max_errors` (_int_): Maximum errors permitted during evaluation. Halts run with the latest error message. Defaults to 5. Configure to 1 if no evaluation run error is desired.
 
 ### Method