"""
Heuristic adapter router.

Priority: explicit `mode` override → keyword match → default "support".
Swap in model self-classification by uncommenting _model_classify below.
"""
from typing import Literal

AdapterName = Literal["support", "analytics", "form"]

_KEYWORDS: dict[str, list[str]] = {
    "support": [
        "error", "help", "issue", "problem", "broken", "fix",
        "support", "bug", "crash", "fail", "wrong", "not working",
    ],
    "analytics": [
        "chart", "graph", "data", "analytics", "trend", "report",
        "metric", "dashboard", "stat", "plot", "visuali", "insight",
    ],
    "form": [
        "form", "fill", "submit", "input", "register", "sign up",
        "signup", "onboard", "enter your", "complete", "provide",
    ],
}

_VALID: set[str] = set(_KEYWORDS.keys())


def route(messages: list[dict], explicit_mode: str | None = None) -> AdapterName:
    if explicit_mode and explicit_mode in _VALID:
        return explicit_mode  # type: ignore[return-value]

    text = _last_user_content(messages).lower()
    if not text:
        return "support"

    scores: dict[str, int] = {k: 0 for k in _KEYWORDS}
    for name, kws in _KEYWORDS.items():
        for kw in kws:
            if kw in text:
                scores[name] += 1

    best = max(scores, key=lambda k: scores[k])
    return best if scores[best] > 0 else "support"  # type: ignore[return-value]

    # Uncomment to replace keyword match with model self-classification:
    # return _model_classify(messages)


def _last_user_content(messages: list[dict]) -> str:
    for msg in reversed(messages):
        if msg.get("role") == "user":
            return str(msg.get("content", ""))
    return ""


# def _model_classify(messages):
#     """Classify using a lightweight model (e.g. a 0-shot instruct call)."""
#     raise NotImplementedError