generated from kgod/ai-review-template
59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
"""Candidate-only skill recommendations for the resume preview editor."""
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from __future__ import annotations
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from typing import Any
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from .skill_classifier import classify_skills
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from .skill_suggester import SkillSuggester
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def recommend_skill_candidates(
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profile: dict[str, Any],
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existing_skills: list[str],
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question: str,
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suggester: SkillSuggester,
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) -> list[dict[str, Any]]:
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"""Return suggestions only; callers must never write them into the resume automatically."""
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working_profile = dict(profile)
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tags = dict(working_profile.get("tags") or {})
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tags["skills"] = existing_skills
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working_profile["tags"] = tags
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suggestions = suggester.suggest(working_profile)
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source_text = _profile_text(working_profile).casefold()
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target = str(working_profile.get("target_position") or "目标岗位").strip()
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candidates: list[dict[str, Any]] = []
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for skill in suggestions:
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clean = str(skill).strip()
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if not clean:
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continue
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group = classify_skills([clean])
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category = str(group[0]["category"]) if group else "其他技能"
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supported = clean.casefold() in source_text
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reason = (
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"已在你填写的经历中出现，可作为已掌握技能确认。"
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if supported
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else f"与{target}及你的提问“{question.strip()}”相关，作为待学习或待确认技能建议。"
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)
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candidates.append({
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"skill": clean,
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"category": category,
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"reason": reason[:160],
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"evidence_supported": supported,
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})
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return candidates[:12]
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def _profile_text(profile: dict[str, Any]) -> str:
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values: list[str] = []
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entries: list[Any] = [profile.get("anchor")]
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entries.extend(profile.get("experiences") or [])
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for records in (profile.get("records") or {}).values():
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entries.extend(records or [])
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for entry in entries:
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if not isinstance(entry, dict):
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continue
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values.append(str(entry.get("description") or ""))
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values.extend(str(item) for item in entry.get("highlights") or [] if item)
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return "\n".join(values)
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