import textwrap

# local_grader: anything callable that takes a prompt and returns text.
# we're running a distilled 1B model on the same box as the pipeline -
# it doesn't need to be smart, it needs to be fast and not fall over

GRADER_PROMPT = textwrap.dedent("""\
    A downstream agent is about to receive this account history payload:
    {payload}

    It was requested for account_id: {account_id}

    Answer strictly as JSON: {{"is_plausible": bool, "reason": str, "confidence": float}}
    Flag it as implausible if the account_id doesn't match, if billing_records
    is empty for a subscription marked active, or if the payload looks like
    a default/fallback value rather than a real lookup result.
""")


def grade_handoff(request_account_id: str, payload: AccountHistoryPayload, local_grader) -> HandoffVerdict:
    prompt = GRADER_PROMPT.format(payload=payload.model_dump_json(), account_id=request_account_id)
    raw_response = local_grader(prompt)

    try:
        verdict = HandoffVerdict.model_validate_json(raw_response)
    except ValueError:
        # the grader itself can return garbage - if we can't parse its verdict,
        # don't just shrug and let the handoff through, that defeats the point
        logger.error("Grader returned unparseable output, blocking handoff: %r", raw_response[:200])
        return HandoffVerdict(is_plausible=False, reason="grader output unparseable", confidence=0.0)

    if not verdict.is_plausible or verdict.confidence < CONFIDENCE_FLOOR:
        logger.warning(
            "Handoff rejected for account_id=%s: %s (confidence=%.2f)\npayload=%s",
            request_account_id, verdict.reason, verdict.confidence, payload.model_dump_json(),
        )
    return verdict