ontolearn.verbalizer
====================

.. py:module:: ontolearn.verbalizer


Classes
-------

.. autoapisummary::

   ontolearn.verbalizer.LLMVerbalizer


Functions
---------

.. autoapisummary::

   ontolearn.verbalizer.verbalize_learner_prediction


Module Contents
---------------

.. py:class:: LLMVerbalizer(model: str = 'mixtral:8x7b', url: str = 'http://tentris-ml.cs.upb.de:8000/api/generate', api_key: Optional[str] = None)

   .. py:attribute:: model
      :value: 'mixtral:8x7b'



   .. py:attribute:: url
      :value: 'http://tentris-ml.cs.upb.de:8000/api/generate'



   .. py:attribute:: api_key
      :value: None



   .. py:method:: __call__(text: str)

      :param text: String representation of an OWL Class Expression



.. py:function:: verbalize_learner_prediction(prediction: Union[str, object] = None, num_predictions: int = 3) -> None

   Generate and print multiple verbalized versions of a learner's prediction using an LLM verbalizer.

   This function takes a prediction (either a string or object), uses an LLMVerbalizer to generate
   three verbalized responses, and prints them. This is useful for inspecting how the model might
   rephrase or interpret a given prediction.

   :param prediction: The learner's prediction to verbalize. Must not be None.
   :type prediction: Union[str, object]
   :param num_predictions: Number of prediction ouputs from the verbalizer with default value of 3
   :type num_predictions: int

   :raises AssertionError: If the prediction is None.