feat(database): 初始化数据库结构及添加默认评价方案
- 创建候选人主表 candidates，包含基本信息和索引 - 创建简历内容表 resumes，支持附件和版本控制 - 创建职位信息表 jobs，包含职位详情及状态索引 - 创建评价方案表 evaluation_schemas，支持多维度配置及权重 - 创建评价记录表 evaluations，关联候选人、方案及职位，支持多维评分及推荐 - 创建通知记录表 notifications，涵盖多渠道通知及状态管理 - 插入通用和Java后端岗位的默认评价方案，支持重复时更新 - 添加详细的数据库配置指南和常用查询示例文档README.md
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migrations/001_init_schema.sql
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migrations/001_init_schema.sql
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-- 简历智能体系统 - 数据库初始化脚本
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-- 支持: MySQL 8.0+ / SQLite 3 / PostgreSQL
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-- ============================================
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-- 1. 候选人主表
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-- ============================================
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CREATE TABLE IF NOT EXISTS candidates (
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id VARCHAR(64) PRIMARY KEY,
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source VARCHAR(32) NOT NULL, -- BOSS, LIEPIN, ZHILIAN, OTHER
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source_id VARCHAR(128) NOT NULL, -- 来源平台ID
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name VARCHAR(64) NOT NULL,
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phone VARCHAR(32),
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email VARCHAR(128),
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wechat VARCHAR(64),
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gender TINYINT DEFAULT 0, -- 0:未知, 1:男, 2:女
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age INT,
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location VARCHAR(128),
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current_company VARCHAR(256),
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current_position VARCHAR(128),
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work_years DECIMAL(4,1),
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education VARCHAR(64),
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school VARCHAR(256),
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salary_min INT, -- 期望薪资下限(K)
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salary_max INT, -- 期望薪资上限(K)
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status VARCHAR(32) DEFAULT 'NEW', -- NEW, ANALYZED, PUSHED, CONTACTED, INTERVIEWED, HIRED, REJECTED
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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UNIQUE KEY uk_source_source_id (source, source_id),
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INDEX idx_phone (phone),
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INDEX idx_email (email),
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INDEX idx_name (name),
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INDEX idx_status (status),
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INDEX idx_created_at (created_at)
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);
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-- ============================================
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-- 2. 简历内容表
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-- ============================================
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CREATE TABLE IF NOT EXISTS resumes (
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id VARCHAR(64) PRIMARY KEY,
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candidate_id VARCHAR(64) NOT NULL,
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raw_content TEXT, -- 原始简历文本
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parsed_content JSON, -- 结构化解析内容
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attachment_url VARCHAR(512), -- 附件URL
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attachment_type VARCHAR(32), -- pdf, doc, docx
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version INT DEFAULT 1, -- 版本号
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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FOREIGN KEY (candidate_id) REFERENCES candidates(id) ON DELETE CASCADE,
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INDEX idx_candidate_id (candidate_id)
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);
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-- ============================================
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-- 3. 职位信息表
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-- ============================================
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CREATE TABLE IF NOT EXISTS jobs (
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id VARCHAR(64) PRIMARY KEY,
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source VARCHAR(32) NOT NULL, -- BOSS, LIEPIN, etc.
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source_id VARCHAR(128) NOT NULL,
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title VARCHAR(256) NOT NULL,
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department VARCHAR(128),
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location VARCHAR(128),
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salary_min INT,
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salary_max INT,
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requirements TEXT, -- 职位要求JSON
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description TEXT, -- 职位描述
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status VARCHAR(32) DEFAULT 'ACTIVE', -- ACTIVE, PAUSED, CLOSED, ARCHIVED
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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UNIQUE KEY uk_source_source_id (source, source_id),
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INDEX idx_status (status)
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);
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-- ============================================
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-- 4. 评价方案表
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-- ============================================
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CREATE TABLE IF NOT EXISTS evaluation_schemas (
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id VARCHAR(64) PRIMARY KEY,
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name VARCHAR(128) NOT NULL,
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description TEXT,
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dimensions JSON NOT NULL, -- 评价维度配置
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weights JSON NOT NULL, -- 维度权重
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prompt_template TEXT, -- AI提示词模板
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is_default BOOLEAN DEFAULT FALSE,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
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INDEX idx_is_default (is_default)
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);
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-- ============================================
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-- 5. 评价记录表
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-- ============================================
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CREATE TABLE IF NOT EXISTS evaluations (
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id VARCHAR(64) PRIMARY KEY,
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candidate_id VARCHAR(64) NOT NULL,
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schema_id VARCHAR(64) NOT NULL,
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job_id VARCHAR(64),
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overall_score DECIMAL(4,1), -- 综合评分 0-100
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dimension_scores JSON, -- 各维度评分详情
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tags JSON, -- AI标签
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summary TEXT, -- 评价摘要
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strengths JSON, -- 优势列表
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weaknesses JSON, -- 不足列表
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recommendation VARCHAR(32), -- strong_recommend, recommend, consider, not_recommend
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raw_response TEXT, -- LLM原始响应
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (candidate_id) REFERENCES candidates(id) ON DELETE CASCADE,
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FOREIGN KEY (schema_id) REFERENCES evaluation_schemas(id),
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FOREIGN KEY (job_id) REFERENCES jobs(id) ON DELETE SET NULL,
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INDEX idx_candidate_id (candidate_id),
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INDEX idx_schema_id (schema_id),
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INDEX idx_overall_score (overall_score),
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INDEX idx_created_at (created_at)
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);
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-- ============================================
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-- 6. 通知记录表
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-- ============================================
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CREATE TABLE IF NOT EXISTS notifications (
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id VARCHAR(64) PRIMARY KEY,
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candidate_id VARCHAR(64) NOT NULL,
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evaluation_id VARCHAR(64),
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channel VARCHAR(32) NOT NULL, -- WECHAT_WORK, DINGTALK, EMAIL, WEBHOOK
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content TEXT,
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status VARCHAR(32) DEFAULT 'PENDING', -- PENDING, SENT, FAILED
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error_message TEXT,
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sent_at TIMESTAMP,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (candidate_id) REFERENCES candidates(id) ON DELETE CASCADE,
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FOREIGN KEY (evaluation_id) REFERENCES evaluations(id) ON DELETE SET NULL,
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INDEX idx_candidate_id (candidate_id),
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INDEX idx_status (status),
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INDEX idx_created_at (created_at)
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);
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-- ============================================
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-- 7. 插入默认评价方案
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-- ============================================
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INSERT INTO evaluation_schemas (id, name, description, dimensions, weights, is_default) VALUES
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('general', '通用评价方案', '适用于各类岗位的通用评价方案',
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'[
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{"id": "professional", "name": "专业能力", "description": "岗位相关专业技能水平"},
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{"id": "experience", "name": "工作经验", "description": "相关工作经验丰富度"},
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{"id": "education", "name": "教育背景", "description": "学历和专业匹配度"},
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{"id": "potential", "name": "发展潜力", "description": "未来成长空间"},
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{"id": "culture_fit", "name": "文化匹配", "description": "与企业文化的匹配度"}
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]',
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'{"professional": 0.30, "experience": 0.25, "education": 0.15, "potential": 0.15, "culture_fit": 0.15}',
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TRUE)
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ON DUPLICATE KEY UPDATE
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name = VALUES(name),
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description = VALUES(description),
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dimensions = VALUES(dimensions),
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weights = VALUES(weights);
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INSERT INTO evaluation_schemas (id, name, description, dimensions, weights) VALUES
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('java_backend', 'Java后端工程师评价方案', '针对Java后端开发岗位的综合评价方案',
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'[
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{"id": "tech_capability", "name": "技术能力", "description": "Java技术栈掌握程度", "criteria": ["Java基础扎实程度", "Spring生态熟悉度", "数据库设计与优化", "分布式系统经验"]},
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{"id": "project_exp", "name": "项目经验", "description": "项目经历的丰富度和质量", "criteria": ["项目复杂度", "承担角色重要性", "技术挑战解决能力"]},
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{"id": "learning_ability", "name": "学习能力", "description": "学习新技术和适应新环境的能力", "criteria": ["技术广度", "新技术掌握速度", "自我驱动学习"]},
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{"id": "communication", "name": "沟通协作", "description": "团队协作和沟通能力", "criteria": ["跨团队协作经验", "技术文档能力", "问题表达能力"]},
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{"id": "stability", "name": "稳定性", "description": "职业稳定性和忠诚度", "criteria": ["平均在职时长", "跳槽频率", "职业发展规划清晰度"]}
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]',
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'{"tech_capability": 0.35, "project_exp": 0.25, "learning_ability": 0.15, "communication": 0.15, "stability": 0.10}')
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ON DUPLICATE KEY UPDATE
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name = VALUES(name),
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description = VALUES(description),
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dimensions = VALUES(dimensions),
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weights = VALUES(weights);
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184
migrations/README.md
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migrations/README.md
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# 数据库配置指南
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## 1. 数据库设计文档
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### 核心表结构
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| 表名 | 说明 | 主要字段 |
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|------|------|----------|
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| `candidates` | 候选人主表 | 基本信息、职业信息、联系方式、状态 |
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| `resumes` | 简历内容表 | 原始内容、解析内容、附件、版本 |
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| `jobs` | 职位信息表 | 职位名称、部门、薪资、要求 |
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| `evaluation_schemas` | 评价方案表 | 维度配置、权重、提示词模板 |
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| `evaluations` | 评价记录表 | 评分结果、AI分析、推荐意见 |
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| `notifications` | 通知记录表 | 通知渠道、状态、发送时间 |
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### ER 关系图
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```
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┌─────────────┐ ┌─────────────┐ ┌─────────────┐
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│ candidates │────<│ resumes │ │ jobs │
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│ (候选人) │ │ (简历) │ │ (职位) │
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└──────┬──────┘ └─────────────┘ └──────┬──────┘
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│ │
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│ ┌─────────────┐ │
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└────────>│ evaluations │<─────────────┘
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│ (评价记录) │
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└──────┬──────┘
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│
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┌──────┴──────┐
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│ notifications│
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│ (通知记录) │
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└─────────────┘
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```
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## 2. 数据库配置方法
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### 方法一：SQLite (开发测试)
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无需额外配置，默认使用 SQLite：
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```bash
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# 在项目根目录创建 .env 文件
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echo "DB_URL=sqlite:///./hr_agent.db" > .env
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```
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### 方法二：MySQL (生产环境)
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#### 2.1 创建数据库
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```sql
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CREATE DATABASE hr_agent CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
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CREATE USER 'hr_agent'@'%' IDENTIFIED BY 'your_password';
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GRANT ALL PRIVILEGES ON hr_agent.* TO 'hr_agent'@'%';
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FLUSH PRIVILEGES;
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```
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#### 2.2 配置连接
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```bash
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# .env 文件
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echo "DB_URL=mysql+pymysql://hr_agent:your_password@localhost:3306/hr_agent" > .env
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```
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#### 2.3 安装依赖
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```bash
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uv add pymysql cryptography
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```
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### 方法三：PostgreSQL
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#### 3.1 创建数据库
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```sql
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CREATE DATABASE hr_agent ENCODING 'UTF8';
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CREATE USER hr_agent WITH PASSWORD 'your_password';
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GRANT ALL PRIVILEGES ON DATABASE hr_agent TO hr_agent;
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```
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#### 3.2 配置连接
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```bash
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# .env 文件
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echo "DB_URL=postgresql+asyncpg://hr_agent:your_password@localhost:5432/hr_agent" > .env
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```
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#### 3.3 安装依赖
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```bash
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uv add asyncpg
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```
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## 3. 初始化数据库
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### 3.1 执行 SQL 脚本
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```bash
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# MySQL
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mysql -u hr_agent -p hr_agent < migrations/001_init_schema.sql
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# SQLite
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sqlite3 hr_agent.db < migrations/001_init_schema.sql
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# PostgreSQL
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psql -U hr_agent -d hr_agent -f migrations/001_init_schema.sql
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```
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### 3.2 验证初始化
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```sql
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-- 查看表结构
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SHOW TABLES;
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-- 查看默认评价方案
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SELECT * FROM evaluation_schemas;
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```
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## 4. 环境变量配置
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在项目根目录创建 `.env` 文件：
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```env
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# 数据库配置
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DB_URL=sqlite:///./hr_agent.db
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DB_ECHO=false
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# LLM 配置
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LLM_PROVIDER=mock
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LLM_API_KEY=
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LLM_MODEL=gpt-4
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# 爬虫配置
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CRAWLER_BOSS_WT_TOKEN=your_boss_token
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# 通知配置 (可选)
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NOTIFY_WECHAT_WORK_WEBHOOK=
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NOTIFY_DINGTALK_WEBHOOK=
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```
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## 5. 常用查询示例
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### 查询候选人列表
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```sql
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SELECT
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c.id,
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c.name,
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c.source,
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c.current_company,
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c.current_position,
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c.status,
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e.overall_score,
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e.recommendation
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FROM candidates c
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LEFT JOIN evaluations e ON c.id = e.candidate_id
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WHERE c.status = 'NEW'
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ORDER BY c.created_at DESC;
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```
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### 查询高分候选人
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```sql
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SELECT
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c.name,
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c.current_company,
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e.overall_score,
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e.summary
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FROM candidates c
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JOIN evaluations e ON c.id = e.candidate_id
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WHERE e.overall_score >= 80
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AND e.recommendation IN ('strong_recommend', 'recommend')
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ORDER BY e.overall_score DESC;
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```
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### 统计各渠道候选人数量
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```sql
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SELECT
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source,
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COUNT(*) as total,
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SUM(CASE WHEN status = 'ANALYZED' THEN 1 ELSE 0 END) as analyzed
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FROM candidates
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GROUP BY source;
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```
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Reference in New Issue
Block a user