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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+"""B-Step1c: intent router settings, shadow logger, and Builder flow mount (P0 observe-only)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import pytest
+
+from app.chat_intent_classifier import RuleBasedChatIntentClassifier
+from app.chat_intent_shadow import (
+    ChatIntentShadowLogger,
+    build_chat_intent_shadow,
+)
+from app.chat_intents import ChatTurnClassification
+from app.settings import Settings, load_settings
+from builder_flow_helpers import create_builder_session, send_message
+
+
+def test_intent_router_settings_defaults() -> None:
+    settings = Settings()
+    assert settings.intent_router_mode == "off"
+    assert settings.intent_model is None
+
+
+def test_intent_router_settings_from_env(monkeypatch: pytest.MonkeyPatch, tmp_path: Any) -> None:
+    monkeypatch.setenv("RESUME_AGENT_INTENT_ROUTER_MODE", "shadow")
+    monkeypatch.setenv("RESUME_AGENT_INTENT_MODEL", "kimi-k3")
+    settings = load_settings(tmp_path / "missing.env")
+    assert settings.intent_router_mode == "shadow"
+    assert settings.intent_model == "kimi-k3"
+    monkeypatch.setenv("RESUME_AGENT_INTENT_ROUTER_MODE", "bogus")
+    with pytest.raises(ValueError, match="INTENT_ROUTER_MODE"):
+        load_settings(tmp_path / "missing.env")
+
+
+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 _captured_events(monkeypatch: pytest.MonkeyPatch) -> list[tuple[str, dict[str, Any]]]:
+    events: list[tuple[str, dict[str, Any]]] = []
+    monkeypatch.setattr(
+        "app.chat_intent_shadow.log_ai_event",
+        lambda event, **fields: events.append((event, fields)),
+    )
+    return events
+
+
+def test_shadow_logs_llm_vs_rule_disagreement(monkeypatch: pytest.MonkeyPatch) -> None:
+    events = _captured_events(monkeypatch)
+    shadow = ChatIntentShadowLogger(
+        _StubClassifier(ChatTurnClassification(intent="ask_question", confidence=0.9)),
+        RuleBasedChatIntentClassifier(),
+    )
+    shadow.observe("没有", state_summary={})
+    assert events == [
+        (
+            "chat_intent_shadow",
+            {
+                "registry_version": "1",
+                "rule_intent": "no_info",
+                "llm_intent": "ask_question",
+                "llm_confidence": 0.9,
+                "disagreement": True,
+            },
+        )
+    ]
+
+
+def test_shadow_logs_agreement_and_survives_llm_failure(monkeypatch: pytest.MonkeyPatch) -> None:
+    events = _captured_events(monkeypatch)
+    agree = ChatIntentShadowLogger(
+        _StubClassifier(ChatTurnClassification(intent="no_info")),
+        RuleBasedChatIntentClassifier(),
+    )
+    agree.observe("没有", state_summary={})
+    assert events[0][1]["disagreement"] is False
+
+    failing = ChatIntentShadowLogger(
+        _StubClassifier(exc=RuntimeError("boom")),
+        RuleBasedChatIntentClassifier(),
+    )
+    failing.observe("没有", state_summary={})  # must not raise
+    assert events[1][0] == "chat_intent_shadow_error"
+
+
+def test_build_chat_intent_shadow_requires_shadow_mode_and_openai() -> None:
+    openai = {"llm_provider": "openai", "openai_api_key": "k"}
+    assert build_chat_intent_shadow(Settings(**openai, intent_router_mode="off")) is None
+    assert build_chat_intent_shadow(Settings(llm_provider="rule", intent_router_mode="shadow")) is None
+    shadow = build_chat_intent_shadow(Settings(**openai, intent_router_mode="shadow"))
+    assert isinstance(shadow, ChatIntentShadowLogger)
+    tuned = build_chat_intent_shadow(Settings(**openai, intent_router_mode="shadow", intent_model="kimi-k3"))
+    assert tuned is not None
+    assert tuned.primary._client.settings.openai_model == "kimi-k3"
+
+
+class _Spy:
+    def __init__(self, *, raises: bool = False) -> None:
+        self.raises = raises
+        self.calls: list[dict[str, Any]] = []
+
+    def observe(self, message: str, *, state_summary: dict[str, Any]) -> None:
+        if self.raises:
+            raise RuntimeError("spy boom")
+        self.calls.append({"message": message, "state_summary": state_summary})
+
+
+def test_process_message_notifies_mounted_shadow(client: Any, monkeypatch: pytest.MonkeyPatch) -> None:
+    agent = client.app.state.resume_agent
+    spy = _Spy()
+    monkeypatch.setattr(agent, "_chat_intent_shadow", spy, raising=False)
+    session_id, _ = create_builder_session(client)
+    send_message(client, session_id, "新增一段教育经历")
+    assert spy.calls[0]["message"] == "新增一段教育经历"
+    assert "confirmed_entries" in spy.calls[0]["state_summary"]
+
+
+def test_shadow_failure_never_breaks_routing(client: Any, monkeypatch: pytest.MonkeyPatch) -> None:
+    agent = client.app.state.resume_agent
+    monkeypatch.setattr(agent, "_chat_intent_shadow", _Spy(raises=True), raising=False)
+    session_id, _ = create_builder_session(client)
+    body = send_message(client, session_id, "新增一段教育经历")
+    assert body["turn"]["role"] == "assistant"