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/tests/test_postgres_environment.py

@@ -0,0 +1,29 @@
+from __future__ import annotations
+
+import os
+
+from sqlalchemy import create_engine, text
+
+
+def test_langgraph_runtime_is_available() -> None:
+    from langgraph.graph import START, StateGraph
+
+    graph = StateGraph(dict)
+    graph.add_node("finish", lambda state: state)
+    graph.add_edge(START, "finish")
+
+    assert graph.compile().invoke({}) == {}
+
+
+def test_postgres_test_database_has_pgvector() -> None:
+    database_url = os.environ["RESUME_AGENT_TEST_DATABASE_URL"]
+    engine = create_engine(database_url)
+    try:
+        with engine.connect() as connection:
+            extension = connection.execute(
+                text("SELECT extname FROM pg_extension WHERE extname = 'vector'")
+            ).scalar_one_or_none()
+    finally:
+        engine.dispose()
+
+    assert extension == "vector"