def context_relevance(self, prompt: str, context: str) -> float:
        """
        Uses HuggingFace's truera/context_relevance model, a
        model that uses computes the relevance of a given context to the prompt.
        The model can be found at https://huggingface.co/truera/context_relevance.

        Example:
            ```python
            from trulens.core import Feedback
            from trulens.providers.huggingface import Huggingface
            huggingface_provider = Huggingface()

            feedback = (
                Feedback(huggingface_provider.context_relevance)
                .on_input()
                .on(context)
                .aggregate(np.mean)
                )
            ```

        Args:
            prompt (str): The given prompt.
            context (str): Comparative contextual information.

        Returns:
            float: A value between 0 and 1. 0 being irrelevant and 1 being a relevant context for addressing the prompt.
        """

        if prompt[len(prompt) - 1] != ".":
            prompt += "."
        ctx_relevance_string = prompt + "<eos>" + context
        return self._context_relevance_endpoint(ctx_relevance_string)

        Uses HuggingFace's truera/context_relevance model, a
        model that uses computes the relevance of a given context to the prompt.
        The model can be found at https://huggingface.co/truera/context_relevance.

        Example:
            ```python
            from trulens.core import Feedback
            from trulens.providers.huggingface import Huggingface
            huggingface_provider = Huggingface()

            feedback = (
                Feedback(huggingface_provider.context_relevance)
                .on_input()
                .on(context)
                .aggregate(np.mean)
                )
            ```

        Args:
            prompt (str): The given prompt.
            context (str): Comparative contextual information.

        Returns:
            float: A value between 0 and 1. 0 being irrelevant and 1 being a relevant context for addressing the prompt.
        
src/providers/huggingface/trulens/providers/huggingface/provider.py