"""Skill-suggestion cards and selection handling for the Builder."""

from __future__ import annotations

from copy import deepcopy
from typing import Any

from ..fsm import FSMError, Transition, component
from ..models import Stage
from ..resume_skill_advisor import recommend_skill_candidates
from ..skill_groups import update_skill_groups
from .constants import u
from .state import _set_stream_phases
from .turns import _next_step_turn, recommended_section


def _skill_choice_card(candidates: list[dict[str, Any]]) -> dict[str, Any]:
    return component(
        "ChoiceChips",
        module="builder_skill_select",
        title=u("确认岗位技能"),
        description=u("请选择你愿意确认加入简历的技能；未选择的候选不会写入。没有合适的也可以暂时跳过。"),
        multiple=True,
        skippable=True,
        skip_label=u("暂不添加"),
        options=[
            {
                "value": str(candidate["skill"]),
                "label": f'{candidate["skill"]}{u("（")}{candidate["category"]}{u("）")}',
            }
            for candidate in candidates
        ],
    )


def _builder_skill_candidates(
    profile: dict[str, Any],
    resume_content: dict[str, Any],
    skill_suggester: Any | None,
) -> list[dict[str, Any]]:
    if skill_suggester is None:
        return []
    existing = [
        str(skill).strip()
        for group in resume_content.get("skill_groups") or []
        if isinstance(group, dict)
        for skill in group.get("skills") or []
        if str(skill).strip()
    ]
    working_profile = deepcopy(profile)
    working_profile["tags"] = {**dict(working_profile.get("tags") or {}), "skills": existing}
    facts: list[dict[str, Any]] = []
    for section in resume_content.get("sections") or []:
        if not isinstance(section, dict):
            continue
        for entry in section.get("items") or []:
            if isinstance(entry, dict):
                facts.append(deepcopy(entry))
    working_profile["experiences"] = facts
    return recommend_skill_candidates(
        working_profile,
        existing,
        u("根据我选择的目标岗位推荐可确认技能"),
        skill_suggester,
    )


def _process_skill_selection(
    profile: dict[str, Any],
    state: dict[str, Any],
    action: str,
    payload: dict[str, Any],
    resume_content: dict[str, Any],
) -> Transition:
    if action == "skip":
        state["pending_skill_candidates"] = []
        _set_stream_phases(profile, "suggesting_next")
        return Transition(
            Stage.BUILDER_CONVERSATION,
            profile,
            _next_step_turn(recommended_section(profile, resume_content), prefix=u("好的，先不添加技能。")),
            lifecycle="dismissed",
        )
    if action != "select":
        raise FSMError("invalid_builder_skill_selection", "Confirm or skip the skill suggestions", status_code=422)
    selected = payload.get("values")
    if not isinstance(selected, list):
        selected = [payload.get("value")]
    allowed = {
        str(item.get("skill") or "").strip()
        for item in state.get("pending_skill_candidates") or []
        if isinstance(item, dict) and str(item.get("skill") or "").strip()
    }
    chosen = [str(value).strip() for value in selected if str(value or "").strip() in allowed]
    if not chosen:
        raise FSMError("invalid_builder_skill_selection", "Select at least one suggested skill or skip", status_code=422)
    existing = [
        str(skill).strip()
        for group in resume_content.get("skill_groups") or []
        if isinstance(group, dict)
        for skill in group.get("skills") or []
        if str(skill).strip()
    ]
    preferred = {
        str(item.get("skill") or "").strip(): str(item.get("category") or "").strip()
        for item in state.get("pending_skill_candidates") or []
        if isinstance(item, dict) and str(item.get("skill") or "").strip() and str(item.get("category") or "").strip()
    }
    content = update_skill_groups(resume_content, [*existing, *chosen], preferred_categories=preferred)
    state["pending_skill_candidates"] = []
    _set_stream_phases(profile, "saving", "suggesting_next")
    return Transition(
        Stage.BUILDER_CONVERSATION,
        profile,
        _next_step_turn(
            recommended_section(profile, content),
            prefix=u("已添加") + " " + u("、").join(chosen) + u("。"),
        ),
        lifecycle="confirmed",
        resume_content=content,
    )