"""Phase W - the lightweight, from-scratch classifier we own.

A transparent weighted-lexical scorer: it runs the rule sets in rules.py over a
normalized copy of the text and returns a per-category score in [0, 1] (the max
weight of any matching signal for that category). It is intentionally simple and
dependency-free; the `score()` method is the seam a trained model can later
replace without touching any caller.
"""
from server.safety import rules
from server.safety.config import CATEGORIES


class LexicalClassifier:
    """Rule-driven scorer. Swap-compatible with a future learned model."""

    def score(self, text: str) -> dict:
        scores = {c: 0.0 for c in CATEGORIES}
        norm = rules.normalize(text)
        if not norm:
            return scores

        for rx, weight, cat in rules.RULES:
            if weight > scores[cat] and rx.search(norm):
                scores[cat] = weight

        for cat, a_rx, b_rx, weight in rules.COOCCURRENCE:
            if weight > scores[cat] and a_rx.search(norm) and b_rx.search(norm):
                scores[cat] = weight

        return scores


default_classifier = LexicalClassifier()