generated from kgod/ai-review-template
106 lines
3.8 KiB
Python
106 lines
3.8 KiB
Python
"""Injectable, grounded skill suggestions for the enrichment skills card."""
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from __future__ import annotations
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from typing import Any, Protocol
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from pydantic import Field
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from .enrichment_modules import skill_suggestions
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from .llm_services import OpenAICompatibleStructuredClient, StrictSchema
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from .settings import Settings
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class SkillSuggester(Protocol):
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"""Suggest skills from the user's target role and already-entered resume facts."""
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def suggest(self, profile: dict[str, Any]) -> list[str]: ...
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class RuleBasedSkillSuggester:
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def suggest(self, profile: dict[str, Any]) -> list[str]:
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return skill_suggestions(profile.get("target_position"), profile)
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class SkillSuggestionOutput(StrictSchema):
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skills: list[str] = Field(max_length=8)
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class OpenAISkillSuggester:
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def __init__(
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self, completion: OpenAICompatibleStructuredClient, fallback: SkillSuggester
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) -> None:
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self.completion = completion
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self.fallback = fallback
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def suggest(self, profile: dict[str, Any]) -> list[str]:
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fallback = self.fallback.suggest(profile)
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try:
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output = self.completion.complete(
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schema=SkillSuggestionOutput,
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schema_name="skill_suggestions",
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system_prompt=(
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"你是中文求职简历助手。根据目标岗位和用户已经填写的经历事实推荐技能标签。"
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"只输出适合技能卡的简短技能名称，不要写句子、等级、熟练度或虚构项目成果。"
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"可以补充目标岗位常见但用户尚未填写的技能，作为待学习/待确认建议；"
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"不要把公司、学校、课程或奖项名称当作技能。"
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),
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payload={
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"target_position": profile.get("target_position"),
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"facts": _skill_facts(profile),
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"existing_skills": (profile.get("tags") or {}).get("skills") or [],
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},
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)
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except Exception:
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return fallback
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return _merge_suggestions(output.skills, fallback, profile)
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def build_skill_suggester(
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settings: Settings, client: Any | None = None
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) -> SkillSuggester:
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rules = RuleBasedSkillSuggester()
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if not settings.use_openai:
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return rules
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return OpenAISkillSuggester(OpenAICompatibleStructuredClient(settings, client), rules)
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def _skill_facts(profile: dict[str, Any]) -> list[dict[str, Any]]:
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facts: list[dict[str, Any]] = []
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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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description = str(entry.get("description") or "").strip()
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highlights = [str(item).strip() for item in entry.get("highlights") or [] if str(item).strip()]
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if description or highlights:
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facts.append(
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{
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"record_type": entry.get("record_type"),
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"description": description or None,
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"highlights": highlights,
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}
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)
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return facts
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def _merge_suggestions(
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proposed: list[str], fallback: list[str], profile: dict[str, Any]
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) -> list[str]:
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existing = {
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str(skill).strip().casefold()
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for skill in ((profile.get("tags") or {}).get("skills") or [])
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if str(skill).strip()
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}
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result: list[str] = []
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seen: set[str] = set()
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for skill in [*proposed, *fallback]:
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normalized = str(skill).strip()
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key = normalized.casefold()
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if normalized and len(normalized) <= 32 and key not in existing and key not in seen:
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result.append(normalized)
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seen.add(key)
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return result[:8] |