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>

backend/app/target_position_suggester.py

@@ -0,0 +1,81 @@
+"""Grounded target-position recommendations for users who are still exploring."""
+
+from __future__ import annotations
+
+from typing import Any, Protocol
+
+from pydantic import Field
+
+from .llm_services import OpenAICompatibleStructuredClient, StrictSchema
+from .settings import Settings
+
+
+class PositionSuggestion(StrictSchema):
+    title: str = Field(min_length=1, max_length=32)
+    reason: str = Field(min_length=1, max_length=100)
+
+
+class TargetPositionSuggestionOutput(StrictSchema):
+    positions: list[PositionSuggestion] = Field(min_length=3, max_length=5)
+
+
+class TargetPositionSuggester(Protocol):
+    def suggest(self, *, major: str, job_type: str | None, interests: str | None) -> list[dict[str, str]]: ...
+
+
+class RuleBasedTargetPositionSuggester:
+    def suggest(self, *, major: str, job_type: str | None, interests: str | None) -> list[dict[str, str]]:
+        text = f"{major} {interests or ''}".casefold()
+        if any(token in text for token in ("计算机", "软件", "网络", "data", "人工智能", "ai")):
+            titles = ["后端工程师", "前端工程师", "测试开发工程师", "数据分析师", "产品经理"]
+        elif any(token in text for token in ("设计", "视觉", "艺术", "media")):
+            titles = ["UI/UX 设计师", "视觉设计师", "产品经理", "新媒体运营", "品牌营销专员"]
+        elif any(token in text for token in ("财务", "会计", "金融", "经济")):
+            titles = ["财务分析师", "审计助理", "数据分析师", "商业分析师", "产品运营"]
+        else:
+            titles = ["产品运营", "项目助理", "数据分析师", "市场专员", "客户成功专员"]
+        suffix = "实习岗位" if job_type == "internship" else "校招/社招岗位"
+        return [
+            {"title": title, "reason": f"结合{major}及已填写方向的{suffix}建议"}
+            for title in titles
+        ]
+
+
+class OpenAITargetPositionSuggester:
+    def __init__(self, completion: OpenAICompatibleStructuredClient) -> None:
+        self.completion = completion
+
+    def suggest(self, *, major: str, job_type: str | None, interests: str | None) -> list[dict[str, str]]:
+        output = self.completion.complete(
+            schema=TargetPositionSuggestionOutput,
+            schema_name="target_position_suggestions",
+            system_prompt=(
+                "Recommend 3 to 5 realistic Chinese job titles from the user's major and optional interests. "
+                "These are exploratory suggestions, not facts about the user. "
+                "When interests explicitly name a role or domain, put that exact role/domain first and prioritize its direct adjacent roles; "
+                "do not replace an explicit technical interest such as 后端开发 with unrelated general roles. "
+                "Do not claim skills, experience, qualifications, or hiring outcomes."
+            ),
+            payload={"major": major, "job_type": job_type, "interests": interests},
+        )
+        return [item.model_dump() for item in output.positions]
+
+
+class FallbackTargetPositionSuggester:
+    def __init__(self, primary: TargetPositionSuggester, fallback: TargetPositionSuggester) -> None:
+        self.primary = primary
+        self.fallback = fallback
+
+    def suggest(self, *, major: str, job_type: str | None, interests: str | None) -> list[dict[str, str]]:
+        try:
+            return self.primary.suggest(major=major, job_type=job_type, interests=interests)
+        except Exception:
+            return self.fallback.suggest(major=major, job_type=job_type, interests=interests)
+
+
+def build_target_position_suggester(settings: Settings, client: Any | None = None) -> TargetPositionSuggester:
+    rules = RuleBasedTargetPositionSuggester()
+    if not settings.use_openai:
+        return rules
+    primary = OpenAITargetPositionSuggester(OpenAICompatibleStructuredClient(settings, client))
+    return FallbackTargetPositionSuggester(primary, rules) if settings.fallback_to_rules else primary