Merge pull request #6 from guardrails-ai/fix_gpt4o_call

Fix typos and docstrings

validator/main.py

@@ -46,16 +46,16 @@ class RestrictToTopic(Validator):
             (one or many).
         invalid_topics (List[str], Optional, defaults to []): topics that the
             text cannot be about.
-        device (int, Optional, defaults to -1): Device ordinal for CPU/GPU
-            supports for Zero-Shot classifier. Setting this to -1 will leverage
+        device (Optional[Union[str, int]], Optional, defaults to -1): Device ordinal for
+            CPU/GPU supports for Zero-Shot classifier. Setting this to -1 will leverage
             CPU, a positive will run the Zero-Shot model on the associated CUDA
             device id.
         model (str, Optional, defaults to 'facebook/bart-large-mnli'): The
             Zero-Shot model that will be used to classify the topic. See a
             list of all models here:
             https://huggingface.co/models?pipeline_tag=zero-shot-classification
         llm_callable (Union[str, Callable, None], Optional, defaults to
-            'gpt-3.5-turbo'): Either the name of the OpenAI model, or a callable
+            'gpt-4o'): Either the name of the OpenAI model, or a callable
             that takes a prompt and returns a response.
         disable_classifier (bool, Optional, defaults to False): controls whether
             to use the Zero-Shot model. At least one of disable_classifier and
@@ -85,7 +85,7 @@ def __init__(
         disable_llm: Optional[bool] = False,
         on_fail: Optional[Callable[..., Any]] = None,
         zero_shot_threshold: Optional[float] = 0.5,
-        llm_theshold: Optional[int] = 3,
+        llm_threshold: Optional[int] = 3,
     ):
         super().__init__(
             valid_topics=valid_topics,
@@ -98,7 +98,7 @@ def __init__(
             llm_callable=llm_callable,
             on_fail=on_fail,
             zero_shot_threshold=zero_shot_threshold,
-            llm_theshold=llm_theshold,
+            llm_threshold=llm_threshold,
         )
         self._valid_topics = valid_topics
 
@@ -121,7 +121,7 @@ def __init__(
         if self._zero_shot_threshold < 0 or self._zero_shot_threshold > 1:
             raise ValueError("zero_shot_threshold must be a number between 0 and 1")
 
-        self._llm_threshold = llm_theshold
+        self._llm_threshold = llm_threshold
         if self._llm_threshold < 0 or self._llm_threshold > 5:
             raise ValueError("llm_threshold must be a number between 0 and 5")
         self.set_callable(llm_callable)
@@ -138,7 +138,6 @@ def __init__(
             # TODO api endpoint
             ...
 
-
     def get_topics_ensemble(self, text: str, candidate_topics: List[str]) -> List[str]:
         """Finds the topics in the input text based on if it is determined by the zero
         shot model or the llm.