feat: builder 简历生成 + 轻度优化 + 简历导入交付副本

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>
2026-08-05 11:08:30 +08:00
commit ae2d9b128d
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+"""LLM rescue for messages the keyword routing drops to the generic fallback (问题1b)."""
+
+from __future__ import annotations
+
+from types import SimpleNamespace
+from typing import Any
+
+import pytest
+
+from app.builder_conversation.rescue import llm_intent_rescue
+from app.chat_intents import ChatTurnClassification
+from app.settings import Settings
+from builder_flow_helpers import confirm_card, create_builder_session, finish_education, send_message, start_education
+from test_api import active_component
+
+RESUME = {
+    "sections": [
+        {
+            "kind": "project_experience",
+            "items": [{"id": "e1", "project_name": "AI Career Copilot", "description": "全栈求职助手平台。"}],
+        }
+    ]
+}
+
+
+class _StubClassifier:
+    def __init__(self, result: ChatTurnClassification | None = None, exc: Exception | None = None) -> None:
+        self.result = result
+        self.exc = exc
+
+    def classify(self, message: str, *, state_summary: dict[str, Any]) -> ChatTurnClassification:
+        if self.exc:
+            raise self.exc
+        assert self.result is not None
+        return self.result
+
+
+def _agent(classifier: Any) -> Any:
+    return SimpleNamespace(expander=SimpleNamespace(expand=lambda entry, *, context: {}), _chat_intent_classifier=classifier)
+
+
+def _components(transition: Any) -> list[dict[str, Any]]:
+    return [block["data"] for block in transition.turn["blocks"] if block.get("type") == "component"]
+
+
+def test_rescue_off_mode_returns_none(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(
+        "app.builder_conversation.rescue.load_settings",
+        lambda: Settings(llm_provider="rule", intent_router_mode="off"),
+    )
+    agent = SimpleNamespace()
+    assert llm_intent_rescue(agent, {"job_type": "campus"}, "帮我重新优化描述", RESUME) is None
+
+
+def test_rescue_revise_regenerates_candidate_card() -> None:
+    agent = _agent(_StubClassifier(ChatTurnClassification(
+        intent="revise_proposal", confidence=0.9,
+        target_entry_hint="AI Career Copilot", revision_instruction="重新优化",
+    )))
+    profile: dict[str, Any] = {"job_type": "campus"}
+    transition = llm_intent_rescue(agent, profile, "帮我重新优化AI Career Copilot描述内容", RESUME)
+
+    assert transition is not None
+    card = next(data for data in _components(transition) if data.get("component_name") == "ExperienceConfirmCard")
+    assert card["ai_proposal"]["optimized_description"] == "全栈求职助手平台。"
+    state = transition.profile["builder"]
+    assert state["editing_entry_id"] == "e1"
+    assert state["pending_entry"]["_proposal"]
+
+
+def test_rescue_edit_entry_begins_edit_flow() -> None:
+    agent = _agent(_StubClassifier(ChatTurnClassification(
+        intent="edit_entry", confidence=0.8, target_entry_hint="AI Career Copilot",
+    )))
+    transition = llm_intent_rescue(agent, {"job_type": "campus"}, "帮我改下AI Career Copilot这段", RESUME)
+
+    assert transition is not None
+    assert "我找到了这段" in transition.turn["content"]
+    assert transition.profile["builder"]["editing_entry_id"] == "e1"
+
+
+def test_rescue_edit_prefers_named_section_over_recent_entry() -> None:
+    """点名板块的修改必须落到该板块条目，而不是最近确认条目（教育→校园 错位根因）。"""
+    resume = {
+        "sections": [
+            {"kind": "campus_experience", "items": [{"id": "c1", "organization": "学生会", "description": "招新宣传。"}]},
+            {"kind": "education", "items": [{"id": "e9", "school": "Example University", "description": "主修课程。"}]},
+        ]
+    }
+    agent = _agent(_StubClassifier(ChatTurnClassification(
+        intent="edit_entry", confidence=0.9, target_section="education",
+    )))
+    profile: dict[str, Any] = {"job_type": "campus", "builder": {"last_confirmed_entry": {"entry_id": "c1"}}}
+    transition = llm_intent_rescue(agent, profile, "帮我重新优化教育经历", resume)
+
+    assert transition is not None
+    assert transition.profile["builder"]["editing_entry_id"] == "e9"
+
+
+def test_rescue_edit_derives_section_from_message_when_classifier_omits_it() -> None:
+    """分类器没给 target_section 时，消息里的板块名必须确定性生效（项目→教育 错位根因）。"""
+    resume = {
+        "sections": [
+            {"kind": "education", "items": [{"id": "e9", "school": "Example University", "description": "主修课程。"}]},
+            {"kind": "project_experience", "items": [{"id": "p1", "project_name": "AI Career Copilot", "description": "全栈平台。"}]},
+        ]
+    }
+    agent = _agent(_StubClassifier(ChatTurnClassification(intent="edit_entry", confidence=0.9)))
+    profile: dict[str, Any] = {"job_type": "campus", "builder": {"last_confirmed_entry": {"entry_id": "e9"}}}
+    transition = llm_intent_rescue(agent, profile, "帮我重新优化项目经历", resume)
+
+    assert transition is not None
+    assert transition.profile["builder"]["editing_entry_id"] == "p1"
+
+
+def test_rescue_edit_normalizes_chinese_section_label() -> None:
+    """分类器把 target_section 填成中文板块名时，先归一化到内部 kind 再定位。"""
+    resume = {
+        "sections": [
+            {"kind": "education", "items": [{"id": "e9", "school": "Example University", "description": "主修课程。"}]},
+            {"kind": "project_experience", "items": [{"id": "p1", "project_name": "AI Career Copilot", "description": "全栈平台。"}]},
+        ]
+    }
+    agent = _agent(_StubClassifier(ChatTurnClassification(
+        intent="edit_entry", confidence=0.9, target_section="项目经历",
+    )))
+    profile: dict[str, Any] = {"job_type": "campus", "builder": {"last_confirmed_entry": {"entry_id": "e9"}}}
+    transition = llm_intent_rescue(agent, profile, "帮我重新优化项目经历", resume)
+
+    assert transition is not None
+    assert transition.profile["builder"]["editing_entry_id"] == "p1"
+
+
+def test_rescue_new_entry_offers_section_card() -> None:
+    agent = _agent(_StubClassifier(ChatTurnClassification(
+        intent="new_entry", confidence=0.8, target_section="internship_experience",
+    )))
+    transition = llm_intent_rescue(agent, {"job_type": "campus"}, "我还想补一段实习", RESUME)
+
+    assert transition is not None
+    assert "实习经历" in transition.turn["content"]
+    assert any(data.get("component_name") == "RecordFields" for data in _components(transition))
+
+
+def test_rescue_declines_low_confidence_and_failures() -> None:
+    low = _agent(_StubClassifier(ChatTurnClassification(intent="edit_entry", confidence=0.4, target_entry_hint="AI Career Copilot")))
+    assert llm_intent_rescue(low, {"job_type": "campus"}, "改下AI Career Copilot", RESUME) is None
+    failing = _agent(_StubClassifier(exc=RuntimeError("boom")))
+    assert llm_intent_rescue(failing, {"job_type": "campus"}, "随便一句", RESUME) is None
+    unknown = _agent(_StubClassifier(ChatTurnClassification(intent="unclear", confidence=0.9)))
+    assert llm_intent_rescue(unknown, {"job_type": "campus"}, "嗯", RESUME) is None
+
+
+def test_bottom_fallback_unchanged_without_opt_in(client: Any) -> None:
+    session_id, body = create_builder_session(client)
+    card = start_education(client, session_id, body)
+    proposal = finish_education(client, session_id, card, "完成数据库课程项目。GPA: 4.3/5.0。")
+    confirm_card(client, session_id, proposal)
+    reply = send_message(client, session_id, "帮我重新优化Example University这段经历的描述")
+    assert reply["turn"]["content"].startswith("可以。")
+
+
+def test_bottom_fallback_rescued_by_llm_classifier(client: Any, monkeypatch: pytest.MonkeyPatch) -> None:
+    agent = client.app.state.resume_agent
+    stub = _StubClassifier(ChatTurnClassification(
+        intent="revise_proposal", confidence=0.92,
+        target_entry_hint="Example University", revision_instruction="重新优化描述",
+    ))
+    monkeypatch.setattr(agent, "_chat_intent_classifier", stub, raising=False)
+
+    session_id, body = create_builder_session(client)
+    card = start_education(client, session_id, body)
+    proposal = finish_education(client, session_id, card, "完成数据库课程项目。GPA: 4.3/5.0。")
+    confirm_card(client, session_id, proposal)
+    reply = send_message(client, session_id, "帮我重新优化Example University这段经历的描述")
+
+    assert active_component(reply)["data"]["component"] == "experience_confirm_card"
+    assert "重新" in reply["turn"]["content"]