from app.llm.prompts import CLASSIFIER_PROMPT
from app.llm.schemas import Classification


def _confidence(value: object) -> float:
    named_levels = {"high": 0.9, "medium": 0.6, "low": 0.3}
    if isinstance(value, str) and value.lower() in named_levels:
        return named_levels[value.lower()]
    try:
        return min(1.0, max(0.0, float(value)))
    except (TypeError, ValueError):
        return 0.0


def _flag(value: object) -> bool:
    if isinstance(value, str):
        return value.strip().lower() in {"true", "yes", "1"}
    return bool(value)


class MessageClassifier:
    def __init__(self, llm):
        self.llm = llm

    async def classify(self, text: str) -> Classification:
        data = await self.llm.json(
            [{"role": "user", "content": f"{CLASSIFIER_PROMPT}\nMessage:\n{text}"}]
        )
        return Classification(
            is_question=_flag(data.get("is_question")),
            project_related=_flag(data.get("project_related")),
            asks_new_decision=_flag(data.get("asks_new_decision")),
            rhetorical=_flag(data.get("rhetorical")),
            blocker=_flag(data.get("blocker")),
            confidence=_confidence(data.get("confidence", 0)),
        )