def stereotypes(
        self,
        prompt: str,
        response: str,
        criteria: Optional[str] = None,
        min_score_val: Optional[int] = 0,
        max_score_val: Optional[int] = 3,
        temperature: Optional[float] = 0.0,
    ) -> float:
        """
        Uses chat completion model. A function that completes a template to
        check adding assumed stereotypes in the response when not present in the
        prompt.

        Example:
            ```python
            feedback = Feedback(provider.stereotypes).on_input_output()
            ```

        Args:
            prompt (str): A text prompt to an agent.
            response (str): The agent's response to the prompt.
            min_score_val (int): The minimum score value used by the LLM before normalization. Defaults to 0.
            max_score_val (int): The maximum score value used by the LLM before normalization. Defaults to 3.

        Returns:
            A value between 0.0 (no stereotypes assumed) and 1.0 (stereotypes assumed).
        """

        output_space = self._determine_output_space(
            min_score_val, max_score_val
        )

        system_prompt = feedback_v2.Stereotypes.generate_system_prompt(
            min_score=min_score_val,
            max_score=max_score_val,
            criteria=criteria,
            output_space=output_space,
        )
        user_prompt = str.format(
            feedback_prompts.STEREOTYPES_USER_PROMPT,
            prompt=prompt,
            response=response,
        )
        return self.generate_score(
            system_prompt,
            user_prompt,
            min_score_val=min_score_val,
            max_score_val=max_score_val,
            temperature=temperature,
        )

        Uses chat completion model. A function that completes a template to
        check adding assumed stereotypes in the response when not present in the
        prompt.

        Example:
            ```python
            feedback = Feedback(provider.stereotypes).on_input_output()
            ```

        Args:
            prompt (str): A text prompt to an agent.
            response (str): The agent's response to the prompt.
            min_score_val (int): The minimum score value used by the LLM before normalization. Defaults to 0.
            max_score_val (int): The maximum score value used by the LLM before normalization. Defaults to 3.

        Returns:
            A value between 0.0 (no stereotypes assumed) and 1.0 (stereotypes assumed).
        
src/feedback/trulens/feedback/llm_provider.py