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>
99 lines
4.6 KiB
Python
99 lines
4.6 KiB
Python
"""Turn and card builders for the Builder conversation."""
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from __future__ import annotations
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from typing import Any
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from ..fsm import anchor_field_specs, assistant_turn, component
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from ..models import ComposerMode
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from .constants import SECTION_HEADINGS, SECTION_PRIORITY, u
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from .state import _completed_sections, _set_stream_phases, ensure_builder_state
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def recommended_section(profile: dict[str, Any], resume_content: dict[str, Any] | None = None) -> str:
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priorities = SECTION_PRIORITY.get(str(profile.get("job_type") or "campus"), SECTION_PRIORITY["campus"])
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completed = _completed_sections(resume_content or {})
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return next((section for section in priorities if section not in completed), priorities[0])
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def welcome_turn(
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profile: dict[str, Any],
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resume_id: str | None,
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*,
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imported: bool = False,
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resume_content: dict[str, Any] | None = None,
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) -> tuple[dict[str, Any], dict[str, Any]]:
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state = ensure_builder_state(profile)
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state["imported"] = imported
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if imported:
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turn = assistant_turn("简历已经导入。你想先修改哪一段经历，还是补充一段新的内容？", [], mode=ComposerMode.CHAT)
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_set_stream_phases(profile, "suggesting_next")
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return profile, turn
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turn = _next_step_turn(recommended_section(profile, resume_content))
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_set_stream_phases(profile, "suggesting_next")
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return profile, turn
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def _next_step_turn(section: str, *, prefix: str = "") -> dict[str, Any]:
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lead = f"{prefix} " if prefix else ""
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return assistant_turn(
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f"{lead}接下来建议补充{SECTION_HEADINGS[section]}。你想继续这类经历，还是改选其他经历类型？",
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[_section_choice_card(section)],
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mode=ComposerMode.CHAT,
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)
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def _section_choice_card(recommended: str) -> dict[str, Any]:
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return component(
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"ChoiceChips",
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module="builder_next_section",
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title=u("选择下一步"),
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description=f"{u('建议先补充')}{SECTION_HEADINGS[recommended]}{u('，也可以换一种经历、推荐岗位技能，或直接完成。')}",
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options=[
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*({"value": kind, "label": heading} for kind, heading in SECTION_HEADINGS.items()),
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{"value": "builder_recommend_skills", "label": u("推荐岗位技能")},
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{"value": "builder_finish", "label": u("完成并生成个人总结")},
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],
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value=recommended,
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)
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def _entry_choice_card(matches: list[tuple[dict[str, Any], dict[str, Any]]]) -> dict[str, Any]:
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options = [{"value": str(entry.get("id") or ""), "label": _entry_label(entry, str(section.get("kind") or ""))} for section, entry in matches]
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return component("ChoiceChips", module="builder_entry_select", title="选择要修改的经历", options=options)
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def _record_card(section: str, *, title: str, value: dict[str, Any] | None = None, entry_id: Any = None, skippable: bool = False) -> dict[str, Any]:
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props: dict[str, Any] = {
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"module": "builder_identity",
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"record_type": section,
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"title": title,
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"fields": anchor_field_specs(section),
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"show_description": False,
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"require_description": False,
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"skippable": skippable,
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"skip_label": "稍后补充",
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}
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if value:
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props["value"] = value
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if entry_id:
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props["entry_id"] = entry_id
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return component("RecordFields", **props)
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def _fact_prompt(section: str) -> str:
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prompts = {
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"education": "请补充这段教育经历的真实信息，例如课程项目、竞赛、实践或学习成果；没有也可以直接说没有。",
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"campus_experience": "请补充你实际承担的职责，或规模和结果中的一两项；没有也可以直接说没有。",
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"project_experience": "请补充个人动作、方法或工具，以及交付物、规模或量化结果中的一两项；没有也可以直接说没有。",
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"work_experience": "请补充个人动作、方法或工具，以及交付物、规模或量化结果中的一两项；没有也可以直接说没有。",
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"internship_experience": "请补充个人动作、方法或工具，以及交付物、规模或量化结果中的一两项；没有也可以直接说没有。",
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}
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return prompts[section]
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def _entry_label(entry: dict[str, Any], kind: str) -> str:
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identity = next((str(entry.get(key) or "").strip() for key in ("school", "company", "project_name", "organization") if str(entry.get(key) or "").strip()), SECTION_HEADINGS.get(kind, "经历"))
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role = next((str(entry.get(key) or "").strip() for key in ("major", "position", "project_role", "role") if str(entry.get(key) or "").strip()), "")
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return f"{identity} · {role}" if role else identity
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