generated from kgod/ai-review-template
122 lines
4.4 KiB
Python
122 lines
4.4 KiB
Python
"""Skill-suggestion cards and selection handling for the Builder."""
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from __future__ import annotations
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from copy import deepcopy
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from typing import Any
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from ..fsm import FSMError, Transition, component
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from ..models import Stage
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from ..resume_skill_advisor import recommend_skill_candidates
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from ..skill_groups import update_skill_groups
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from .constants import u
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from .state import _set_stream_phases
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from .turns import _next_step_turn, recommended_section
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def _skill_choice_card(candidates: list[dict[str, Any]]) -> dict[str, Any]:
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return component(
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"ChoiceChips",
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module="builder_skill_select",
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title=u("确认岗位技能"),
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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。"),
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multiple=True,
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skippable=True,
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skip_label=u("暂不添加"),
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options=[
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{
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"value": str(candidate["skill"]),
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"label": f'{candidate["skill"]}{u("（")}{candidate["category"]}{u("）")}',
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}
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for candidate in candidates
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],
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)
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def _builder_skill_candidates(
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profile: dict[str, Any],
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resume_content: dict[str, Any],
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skill_suggester: Any | None,
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) -> list[dict[str, Any]]:
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if skill_suggester is None:
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return []
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existing = [
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str(skill).strip()
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for group in resume_content.get("skill_groups") or []
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if isinstance(group, dict)
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for skill in group.get("skills") or []
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if str(skill).strip()
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]
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working_profile = deepcopy(profile)
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working_profile["tags"] = {**dict(working_profile.get("tags") or {}), "skills": existing}
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facts: list[dict[str, Any]] = []
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for section in resume_content.get("sections") or []:
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if not isinstance(section, dict):
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continue
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for entry in section.get("items") or []:
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if isinstance(entry, dict):
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facts.append(deepcopy(entry))
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working_profile["experiences"] = facts
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return recommend_skill_candidates(
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working_profile,
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existing,
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u("根据我选择的目标岗位推荐可确认技能"),
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skill_suggester,
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)
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def _process_skill_selection(
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profile: dict[str, Any],
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state: dict[str, Any],
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action: str,
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payload: dict[str, Any],
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resume_content: dict[str, Any],
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) -> Transition:
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if action == "skip":
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state["pending_skill_candidates"] = []
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_set_stream_phases(profile, "suggesting_next")
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return Transition(
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Stage.BUILDER_CONVERSATION,
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profile,
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_next_step_turn(recommended_section(profile, resume_content), prefix=u("好的，先不添加技能。")),
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lifecycle="dismissed",
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)
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if action != "select":
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raise FSMError("invalid_builder_skill_selection", "Confirm or skip the skill suggestions", status_code=422)
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selected = payload.get("values")
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if not isinstance(selected, list):
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selected = [payload.get("value")]
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allowed = {
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str(item.get("skill") or "").strip()
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for item in state.get("pending_skill_candidates") or []
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if isinstance(item, dict) and str(item.get("skill") or "").strip()
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}
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chosen = [str(value).strip() for value in selected if str(value or "").strip() in allowed]
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if not chosen:
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raise FSMError("invalid_builder_skill_selection", "Select at least one suggested skill or skip", status_code=422)
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existing = [
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str(skill).strip()
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for group in resume_content.get("skill_groups") or []
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if isinstance(group, dict)
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for skill in group.get("skills") or []
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if str(skill).strip()
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]
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preferred = {
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str(item.get("skill") or "").strip(): str(item.get("category") or "").strip()
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for item in state.get("pending_skill_candidates") or []
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if isinstance(item, dict) and str(item.get("skill") or "").strip() and str(item.get("category") or "").strip()
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}
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content = update_skill_groups(resume_content, [*existing, *chosen], preferred_categories=preferred)
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state["pending_skill_candidates"] = []
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_set_stream_phases(profile, "saving", "suggesting_next")
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return Transition(
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Stage.BUILDER_CONVERSATION,
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profile,
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_next_step_turn(
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recommended_section(profile, content),
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prefix=u("已添加") + " " + u("、").join(chosen) + u("。"),
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),
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lifecycle="confirmed",
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resume_content=content,
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)
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