generated from kgod/ai-review-template
hypandClaude
ae2d9b128d
自内部仓库剥离深度优化与 RAG 知识库后的交付版本： - Builder 对话式简历生成（FSM + 意图路由 LLM 兜底增强） - 条目级轻度优化：事实覆盖门禁 + STAR/bullet 修复链，功能/简介/成果与技术栈同级保护 - 简历导入：DOCX/PDF 解析、结构归一、手机号脱敏 - PostgreSQL 运行时 + Alembic 迁移链 Co-Authored-By: Claude <noreply@anthropic.com>
145 lines
4.1 KiB
Python
145 lines
4.1 KiB
Python
"""Position-anchored dimension weights for deterministic gap evaluation."""
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from __future__ import annotations
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_OPTIONAL_DIM_DEFAULTS = {
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"project_context": 1,
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"business_context": 1,
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"academic_result": 1,
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"project_or_activity": 1,
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"team_scope": 1,
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"organization_scope": 1,
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}
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_WEIGHT_TABLE: dict[str, dict[str, int]] = {
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"tech": {
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"personal_contribution": 3,
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"responsibility_scope": 2,
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"method_or_technology": 3,
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"business_action": 1,
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"outcome_or_delivery": 2,
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"quantified_outcome": 2,
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"coursework_or_practice": 2,
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"relevant_capability": 2,
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"work_or_solution": 3,
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"activity_execution": 1,
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"collaboration_scope": 1,
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**_OPTIONAL_DIM_DEFAULTS,
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},
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"data": {
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"personal_contribution": 2,
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"responsibility_scope": 2,
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"method_or_technology": 3,
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"business_action": 2,
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"outcome_or_delivery": 2,
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"quantified_outcome": 3,
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"coursework_or_practice": 2,
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"relevant_capability": 2,
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"work_or_solution": 2,
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"activity_execution": 1,
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"collaboration_scope": 1,
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**_OPTIONAL_DIM_DEFAULTS,
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},
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"product": {
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"personal_contribution": 3,
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"responsibility_scope": 2,
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"method_or_technology": 1,
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"business_action": 3,
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"outcome_or_delivery": 3,
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"quantified_outcome": 2,
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"coursework_or_practice": 1,
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"relevant_capability": 2,
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"work_or_solution": 2,
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"activity_execution": 2,
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"collaboration_scope": 3,
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**{**_OPTIONAL_DIM_DEFAULTS, "business_context": 2},
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},
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"design": {
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"personal_contribution": 3,
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"responsibility_scope": 2,
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"method_or_technology": 2,
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"business_action": 1,
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"outcome_or_delivery": 3,
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"quantified_outcome": 1,
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"coursework_or_practice": 2,
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"relevant_capability": 2,
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"work_or_solution": 2,
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"activity_execution": 1,
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"collaboration_scope": 2,
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**_OPTIONAL_DIM_DEFAULTS,
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},
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"business": {
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"personal_contribution": 2,
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"responsibility_scope": 3,
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"method_or_technology": 1,
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"business_action": 3,
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"outcome_or_delivery": 3,
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"quantified_outcome": 2,
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"coursework_or_practice": 1,
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"relevant_capability": 2,
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"work_or_solution": 1,
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"activity_execution": 2,
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"collaboration_scope": 3,
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**{**_OPTIONAL_DIM_DEFAULTS, "business_context": 2},
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},
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"default": {
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"personal_contribution": 2,
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"responsibility_scope": 2,
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"method_or_technology": 2,
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"business_action": 2,
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"outcome_or_delivery": 2,
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"quantified_outcome": 2,
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"coursework_or_practice": 1,
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"relevant_capability": 1,
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"work_or_solution": 2,
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"activity_execution": 1,
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"collaboration_scope": 1,
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**_OPTIONAL_DIM_DEFAULTS,
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},
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}
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_ALIASES: dict[str, str] = {
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"后端": "tech",
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"前端": "tech",
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"工程师": "tech",
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"开发": "tech",
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"算法": "tech",
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"测试": "tech",
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"运维": "tech",
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"数据": "data",
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"分析师": "data",
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"bi": "data",
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"产品": "product",
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"运营": "product",
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"增长": "product",
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"设计": "design",
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"ui": "design",
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"ux": "design",
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"视觉": "design",
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"市场": "business",
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"销售": "business",
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"财务": "business",
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"审计": "business",
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"人力": "business",
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"行政": "business",
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"客户成功": "business",
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"咨询": "business",
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}
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def position_family(target_position: str | None) -> str:
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"""Return the deterministic rubric family for a confirmed target position."""
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text = str(target_position or "").strip().casefold()
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if not text:
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return "default"
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for keyword, family in _ALIASES.items():
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if keyword in text:
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return family
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return "default"
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def dimension_weights(target_position: str | None) -> dict[str, int]:
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"""Return a copy so callers cannot mutate the module-level weight matrix."""
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return dict(_WEIGHT_TABLE[position_family(target_position)])
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