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>
Resume Agent backend
FastAPI service for the conversational resume builder: sessions, turns, resumes, imports, and light-optimization state, persisted in SQLite (pilot) or PostgreSQL (production).
Run locally
Python 3.11 or newer is required.
python -m pip install -r requirements.txt
cp .env.example .env
# Leave OPENAI_API_KEY empty for offline rules, or fill in the live LLM gateway values.
python -m uvicorn app.asgi:application --reload --port 8000
app.asgi:application wraps app.main:app and hides /docs, /redoc, and /openapi.json
by default; set RESUME_AGENT_API_DOCS=1 to expose them (development only).
The runtime expects DATABASE_URL (PostgreSQL) and uses the resume_agent schema by
default; override with RESUME_AGENT_DATABASE_SCHEMA. Run alembic upgrade head to create
the tables, and python scripts/migrate_sqlite_to_postgres.py to move existing SQLite data.
SQLite is used only when database_path is passed explicitly (tests, local pilot).
CORS defaults to http://localhost:5173; set a comma-separated RESUME_AGENT_CORS_ORIGINS.
The health check at GET /health is always open.
Tests
python -m pytest tests -q
Postgres-backed tests require RESUME_AGENT_TEST_DATABASE_URL; the rest run on SQLite
temporary files. Tests force the rule-based LLM provider, so no API key is needed.