How to evaluate LLM response that is structured as a pydantic object?

[CKAbundant]

I've structured my query_engine to output as a pydantic object:

class TechOffer(BaseModel):
    """Title of technical offer that is relevant to the query including reasons why technical offer is relevant to the query."""

    title: str = Field(
        description="Title of the technical offer that is relevant to the query."
    )
    reason: str = Field(
        description="Detailed step-by-step reasons why the technical offer are relevant to the query."
    )
    unique_value_proposition: str = Field(
        description="Unique benefits or advantages offered by the technical offer with reference to the query."
    )


class TechOfferTitles(BaseModel):
    """List of titles of technical offers that are relevant to the query."""

    title_list: List[TechOffer]

When I run eval_result = evaluator.evaluate_response(response=response), I got this error message:

AttributeError: 'TechOfferTitles' object has no attribute 'query_str'

How can I perform faithfulness evaluation when my LLM output is a pydantic object? Thanks!