Files
AIclinicalresearch/backend/scripts/create-tool-c-ai-history-table.mjs
HaHafeng decff0bb1f docs(deploy): Complete full system deployment to Aliyun SAE
Summary:
- Successfully deployed complete system to Aliyun SAE (2025-12-25)
- All services running: Python microservice + Node.js backend + Frontend Nginx + CLB
- Public access available at http://8.140.53.236/

Major Achievements:
1. Python microservice deployed (v1.0, internal IP: 172.17.173.66:8000)
2. Node.js backend deployed (v1.3, internal IP: 172.17.173.73:3001)
   - Fixed 4 critical issues: bash path, config directory, pino-pretty, ES Module
3. Frontend Nginx deployed (v1.0, internal IP: 172.17.173.72:80)
4. CLB load balancer configured (public IP: 8.140.53.236)

New Documentation (9 docs):
- 11-Node.js backend SAE deployment config checklist (21 env vars)
- 12-Node.js backend SAE deployment operation manual
- 13-Node.js backend image fix record (config directory)
- 14-Node.js backend pino-pretty fix
- 15-Node.js backend deployment success summary
- 16-Frontend Nginx deployment success summary
- 17-Complete deployment practical manual 2025 edition (1800 lines)
- 18-Deployment documentation usage guide
- 19-Daily update quick operation manual (670 lines)

Key Fixes:
- Environment variable name correction: EXTRACTION_SERVICE_URL (not PYTHON_SERVICE_URL)
- Dockerfile fix: added COPY config ./config
- Logger configuration: conditional pino-pretty for dev only
- Health check fix: ES Module compatibility (require -> import)

Updated Files:
- System status document updated with full deployment info
- Deployment progress overview updated with latest IPs
- All 3 Docker services' Dockerfiles and configs refined

Verification:
- All health checks passed
- Tool C 7 features working correctly
- Literature screening module functional
- Response time < 1 second

BREAKING CHANGE: Node.js backend internal IP changed from 172.17.173.71 to 172.17.173.73

Closes #deployment-milestone
2025-12-25 21:24:37 +08:00

181 lines
4.8 KiB
JavaScript
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/**
* 创建 Tool C AI对话历史表
*
* 执行方式node scripts/create-tool-c-ai-history-table.mjs
*/
import { PrismaClient } from '@prisma/client';
const prisma = new PrismaClient();
async function createAiHistoryTable() {
console.log('========================================');
console.log('开始创建 Tool C AI对话历史表');
console.log('========================================\n');
try {
// 1. 检查表是否已存在
console.log('[1/4] 检查表是否已存在...');
const checkResult = await prisma.$queryRawUnsafe(`
SELECT EXISTS (
SELECT FROM information_schema.tables
WHERE table_schema = 'dc_schema'
AND table_name = 'dc_tool_c_ai_history'
) as exists
`);
const tableExists = checkResult[0].exists;
if (tableExists) {
console.log('✅ 表已存在: dc_schema.dc_tool_c_ai_history');
console.log('\n如需重新创建请手动执行: DROP TABLE dc_schema.dc_tool_c_ai_history CASCADE;\n');
return;
}
console.log('✅ 表不存在,准备创建\n');
// 2. 创建表
console.log('[2/4] 创建表 dc_tool_c_ai_history...');
await prisma.$executeRawUnsafe(`
CREATE TABLE dc_schema.dc_tool_c_ai_history (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
session_id VARCHAR(255) NOT NULL,
user_id VARCHAR(255) NOT NULL,
role VARCHAR(50) NOT NULL,
content TEXT NOT NULL,
-- Tool C特有字段
generated_code TEXT,
code_explanation TEXT,
execute_status VARCHAR(50),
execute_result JSONB,
execute_error TEXT,
retry_count INTEGER DEFAULT 0,
-- LLM相关
model VARCHAR(100),
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
)
`);
console.log('✅ 表创建成功\n');
// 3. 创建索引
console.log('[3/4] 创建索引...');
await prisma.$executeRawUnsafe(`
CREATE INDEX idx_dc_tool_c_ai_history_session_id
ON dc_schema.dc_tool_c_ai_history(session_id)
`);
await prisma.$executeRawUnsafe(`
CREATE INDEX idx_dc_tool_c_ai_history_user_id
ON dc_schema.dc_tool_c_ai_history(user_id)
`);
await prisma.$executeRawUnsafe(`
CREATE INDEX idx_dc_tool_c_ai_history_created_at
ON dc_schema.dc_tool_c_ai_history(created_at)
`);
console.log('✅ 索引创建成功\n');
// 4. 添加注释
console.log('[4/4] 添加表注释...');
await prisma.$executeRawUnsafe(`
COMMENT ON TABLE dc_schema.dc_tool_c_ai_history
IS 'Tool C (科研数据编辑器) AI对话历史表'
`);
await prisma.$executeRawUnsafe(`
COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.session_id
IS '关联Tool C Session ID'
`);
await prisma.$executeRawUnsafe(`
COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.generated_code
IS 'AI生成的Pandas代码'
`);
await prisma.$executeRawUnsafe(`
COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.execute_status
IS '执行状态: pending/success/failed'
`);
await prisma.$executeRawUnsafe(`
COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.retry_count
IS '自我修正重试次数'
`);
console.log('✅ 注释添加成功\n');
// 5. 验证表创建
console.log('========================================');
console.log('验证表结构');
console.log('========================================\n');
const columns = await prisma.$queryRawUnsafe(`
SELECT column_name, data_type, is_nullable
FROM information_schema.columns
WHERE table_schema = 'dc_schema'
AND table_name = 'dc_tool_c_ai_history'
ORDER BY ordinal_position
`);
console.log('表结构:');
console.table(columns);
const indexes = await prisma.$queryRawUnsafe(`
SELECT indexname, indexdef
FROM pg_indexes
WHERE schemaname = 'dc_schema'
AND tablename = 'dc_tool_c_ai_history'
`);
console.log('\n索引:');
console.table(indexes);
console.log('\n========================================');
console.log('🎉 Tool C AI对话历史表创建成功');
console.log('========================================\n');
console.log('表名: dc_schema.dc_tool_c_ai_history');
console.log(`列数: ${columns.length}`);
console.log(`索引数: ${indexes.length}\n`);
} catch (error) {
console.error('\n❌ 创建表失败:', error.message);
console.error('\n详细错误:');
console.error(error);
process.exit(1);
} finally {
await prisma.$disconnect();
}
}
// 执行
createAiHistoryTable()
.then(() => {
console.log('脚本执行完成');
process.exit(0);
})
.catch((error) => {
console.error('脚本执行失败:', error);
process.exit(1);
});