Files
AIclinicalresearch/backend/verify_job_common.ts
HaHafeng dfc0fe0b9a feat(pkb): Integrate pgvector and create Dify replacement plan
Summary:
- Migrate PostgreSQL to pgvector/pgvector:pg15 Docker image
- Successfully install and verify pgvector 0.8.1 extension
- Create comprehensive Dify-to-pgvector migration plan
- Update PKB module documentation with pgvector status
- Update system documentation with pgvector integration

Key changes:
- docker-compose.yml: Switch to pgvector/pgvector:pg15 image
- Add EkbDocument and EkbChunk data model design
- Design R-C-R-G hybrid retrieval architecture
- Add clinical data JSONB fields (pico, studyDesign, regimen, safety, criteria, endpoints)
- Create detailed 10-day implementation roadmap

Documentation updates:
- PKB module status: pgvector RAG infrastructure ready
- System status: pgvector 0.8.1 integrated
- New: Dify replacement development plan (01-Dify替换为pgvector开发计划.md)
- New: Enterprise medical knowledge base solution V2

Tested: PostgreSQL with pgvector verified, frontend and backend functionality confirmed
2026-01-20 00:00:58 +08:00

45 lines
927 B
TypeScript

import { PrismaClient } from '@prisma/client';
const prisma = new PrismaClient();
async function main() {
const result: any[] = await prisma.$queryRaw`
SELECT table_name
FROM information_schema.tables
WHERE table_schema = 'platform_schema' AND table_name = 'job_common'
`;
if (result.length > 0) {
console.log('✅ platform_schema.job_common 表已恢复!');
// 检查列结构
const cols: any[] = await prisma.$queryRaw`
SELECT column_name, data_type
FROM information_schema.columns
WHERE table_schema = 'platform_schema' AND table_name = 'job_common'
ORDER BY ordinal_position
`;
console.log('\n列结构:');
cols.forEach(c => console.log(` ${c.column_name}: ${c.data_type}`));
} else {
console.log('❌ platform_schema.job_common 表不存在');
}
}
main()
.catch(console.error)
.finally(() => prisma.$disconnect());