Sprint 1-3 Completed (Backend + Frontend): Backend (Sprint 1-2): - Implement 5-layer Agent framework (Query->Planner->Executor->Tools->Reflection) - Create agent_schema with 6 tables (agent_definitions, stages, prompts, sessions, traces, reflexion_rules) - Create protocol_schema with 2 tables (protocol_contexts, protocol_generations) - Implement Protocol Agent core services (Orchestrator, ContextService, PromptBuilder) - Integrate LLM service adapter (DeepSeek/Qwen/GPT-5/Claude) - 6 API endpoints with full authentication - 10/10 API tests passed Frontend (Sprint 3): - Add Protocol Agent entry in AgentHub (indigo theme card) - Implement ProtocolAgentPage with 3-column layout - Collapsible sidebar (Gemini style, 48px <-> 280px) - StatePanel with 5 stage cards (scientific_question, pico, study_design, sample_size, endpoints) - ChatArea with sync button and action cards integration - 100% prototype design restoration (608 lines CSS) - Detailed endpoints structure: baseline, exposure, outcomes, confounders Features: - 5-stage dialogue flow for research protocol design - Conversation-driven interaction with sync-to-protocol button - Real-time context state management - One-click protocol generation button (UI ready, backend pending) Database: - agent_schema: 6 tables for reusable Agent framework - protocol_schema: 2 tables for Protocol Agent - Seed data: 1 agent + 5 stages + 9 prompts + 4 reflexion rules Code Stats: - Backend: 13 files, 4338 lines - Frontend: 14 files, 2071 lines - Total: 27 files, 6409 lines Status: MVP core functionality completed, pending frontend-backend integration testing Next: Sprint 4 - One-click protocol generation + Word export
71 lines
1.5 KiB
TypeScript
71 lines
1.5 KiB
TypeScript
import { PrismaClient } from '@prisma/client';
|
|
|
|
const prisma = new PrismaClient();
|
|
|
|
async function main() {
|
|
// 查询所有 schema
|
|
const schemas = await prisma.$queryRaw`
|
|
SELECT schema_name
|
|
FROM information_schema.schemata
|
|
WHERE schema_name NOT IN ('pg_catalog', 'information_schema', 'pg_toast')
|
|
ORDER BY schema_name;
|
|
`;
|
|
console.log('\n=== 数据库中的 Schemas ===');
|
|
console.log(schemas);
|
|
|
|
// 查询每个 schema 下的表
|
|
const tables = await prisma.$queryRaw`
|
|
SELECT table_schema, table_name
|
|
FROM information_schema.tables
|
|
WHERE table_schema NOT IN ('pg_catalog', 'information_schema', 'pg_toast')
|
|
AND table_type = 'BASE TABLE'
|
|
ORDER BY table_schema, table_name;
|
|
`;
|
|
console.log('\n=== 数据库中的所有表 ===');
|
|
console.log(tables);
|
|
|
|
// 检查 platform_schema.users 的数据量
|
|
try {
|
|
const userCount = await prisma.$queryRaw`SELECT COUNT(*) as count FROM platform_schema.users;`;
|
|
console.log('\n=== platform_schema.users 数据量 ===');
|
|
console.log(userCount);
|
|
} catch (e) {
|
|
console.log('\n=== platform_schema.users 不存在或出错 ===');
|
|
}
|
|
|
|
// 检查 public.users 的数据量
|
|
try {
|
|
const publicUserCount = await prisma.$queryRaw`SELECT COUNT(*) as count FROM public.users;`;
|
|
console.log('\n=== public.users 数据量 ===');
|
|
console.log(publicUserCount);
|
|
} catch (e) {
|
|
console.log('\n=== public.users 不存在或出错 ===');
|
|
}
|
|
}
|
|
|
|
main()
|
|
.catch(console.error)
|
|
.finally(() => prisma.$disconnect());
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|