354 lines
12 KiB
JavaScript
354 lines
12 KiB
JavaScript
/**
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* SoftRuleEngine - 软规则质控引擎 (LLM 推理)
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*
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* 功能：
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* - 调用 LLM 进行复杂的医学逻辑判断
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* - 支持入排标准、AE 事件检测、方案偏离等场景
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* - 返回带证据链的结构化结果
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*
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* 设计原则：
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* - 智能推理：利用 LLM 处理模糊规则和复杂逻辑
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* - 证据链：每个判断都附带推理过程和证据
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* - 三态输出：PASS / FAIL / UNCERTAIN（需人工确认）
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*/
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import { PrismaClient } from '@prisma/client';
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import { LLMFactory } from '../../../common/llm/adapters/LLMFactory.js';
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import { logger } from '../../../common/logging/index.js';
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import { buildClinicalSlice } from '../services/PromptBuilder.js';
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const prisma = new PrismaClient();
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// ============================================================
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// SoftRuleEngine 实现
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// ============================================================
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export class SoftRuleEngine {
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constructor(projectId, config) {
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this.projectId = projectId;
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this.model = config?.model || 'deepseek-v3';
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this.timeoutMs = config?.timeoutMs || 30000;
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}
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/**
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* 执行软规则检查
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*
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* @param recordId 记录ID
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* @param data 记录数据
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* @param checks 要执行的检查列表
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* @returns 检查结果
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*/
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async execute(recordId, data, checks) {
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const startTime = Date.now();
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const results = [];
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const failedChecks = [];
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const uncertainChecks = [];
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logger.info('[SoftRuleEngine] Starting execution', {
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projectId: this.projectId,
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recordId,
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checkCount: checks.length,
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model: this.model,
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});
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// 逐个执行检查（可以改为并发，但需注意 Token 限制）
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for (const check of checks) {
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try {
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const result = await this.executeCheck(recordId, data, check);
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results.push(result);
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if (result.status === 'FAIL') {
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failedChecks.push(result);
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}
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else if (result.status === 'UNCERTAIN') {
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uncertainChecks.push(result);
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}
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}
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catch (error) {
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logger.error('[SoftRuleEngine] Check execution failed', {
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checkId: check.id,
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error: error.message,
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});
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// 发生错误时标记为 UNCERTAIN
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const errorResult = {
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checkId: check.id,
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checkName: check.name,
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status: 'UNCERTAIN',
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reason: `执行出错: ${error.message}`,
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evidence: {},
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confidence: 0,
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severity: check.severity,
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category: check.category,
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};
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results.push(errorResult);
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uncertainChecks.push(errorResult);
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}
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}
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// 计算整体状态
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let overallStatus = 'PASS';
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if (failedChecks.length > 0) {
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overallStatus = 'FAIL';
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}
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else if (uncertainChecks.length > 0) {
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overallStatus = 'UNCERTAIN';
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}
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const duration = Date.now() - startTime;
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logger.info('[SoftRuleEngine] Execution completed', {
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recordId,
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overallStatus,
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totalChecks: checks.length,
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failed: failedChecks.length,
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uncertain: uncertainChecks.length,
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duration: `${duration}ms`,
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});
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return {
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recordId,
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projectId: this.projectId,
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timestamp: new Date().toISOString(),
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overallStatus,
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summary: {
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totalChecks: checks.length,
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passed: results.filter(r => r.status === 'PASS').length,
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failed: failedChecks.length,
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uncertain: uncertainChecks.length,
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},
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results,
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failedChecks,
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uncertainChecks,
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};
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}
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/**
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* 执行单个检查
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*/
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async executeCheck(recordId, data, check) {
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const startTime = Date.now();
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// 1. 构建 Prompt
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const prompt = this.buildCheckPrompt(recordId, data, check);
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// 2. 调用 LLM
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const llmAdapter = LLMFactory.getAdapter(this.model);
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const response = await llmAdapter.chat([
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{
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role: 'system',
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content: this.getSystemPrompt(),
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},
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{
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role: 'user',
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content: prompt,
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},
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]);
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const rawResponse = response.content;
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// 3. 解析响应
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const parsed = this.parseResponse(rawResponse, check);
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const duration = Date.now() - startTime;
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logger.debug('[SoftRuleEngine] Check executed', {
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checkId: check.id,
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status: parsed.status,
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confidence: parsed.confidence,
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duration: `${duration}ms`,
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});
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return {
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checkId: check.id,
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checkName: check.name,
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status: parsed.status,
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reason: parsed.reason,
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evidence: parsed.evidence,
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confidence: parsed.confidence,
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severity: check.severity,
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category: check.category,
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rawResponse,
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};
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}
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/**
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* 构建检查 Prompt
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*/
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buildCheckPrompt(recordId, data, check) {
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// 使用 PromptBuilder 生成临床数据切片
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const clinicalSlice = buildClinicalSlice({
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task: check.name,
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criteria: [check.description || check.name],
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patientData: data,
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tags: check.requiredTags,
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instruction: '请根据以下数据进行判断。',
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});
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// 替换 Prompt 模板中的变量
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let userPrompt = check.promptTemplate;
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// 替换 {{variable}} 格式的占位符
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userPrompt = userPrompt.replace(/\{\{(\w+)\}\}/g, (_, key) => {
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return data[key] !== undefined ? String(data[key]) : `[${key}未提供]`;
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});
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// 替换 {{#tag}} 格式的数据标签
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userPrompt = userPrompt.replace(/\{\{#(\w+)\}\}/g, (_, tag) => {
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// 根据标签筛选相关字段
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return JSON.stringify(data, null, 2);
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});
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return `${clinicalSlice}\n\n---\n\n## 检查任务\n\n${userPrompt}`;
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}
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/**
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* 获取系统 Prompt
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*/
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getSystemPrompt() {
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return `你是一个专业的临床研究数据监查员 (CRA)，负责核查受试者数据的质量和合规性。
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## 你的职责
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1. 仔细分析提供的临床数据
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2. 根据检查任务进行判断
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3. 给出清晰的判断结果和理由
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## 输出格式要求
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请严格按照以下 JSON 格式输出：
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\`\`\`json
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{
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"status": "PASS" | "FAIL" | "UNCERTAIN",
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"reason": "判断理由的详细说明",
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"evidence": {
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"key_field_1": "相关数据值",
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"key_field_2": "相关数据值"
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},
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"confidence": 0.95
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}
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\`\`\`
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## 状态说明
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- **PASS**: 检查通过，数据符合要求
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- **FAIL**: 检查失败，发现问题
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- **UNCERTAIN**: 数据不足或存在歧义，需要人工确认
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## 置信度说明
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- 0.9-1.0: 非常确定
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- 0.7-0.9: 比较确定
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- 0.5-0.7: 有一定把握
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- <0.5: 不太确定，建议人工复核
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请只输出 JSON，不要有其他内容。`;
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}
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/**
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* 解析 LLM 响应
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*/
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parseResponse(rawResponse, check) {
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try {
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// 尝试提取 JSON
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const jsonMatch = rawResponse.match(/```json\s*([\s\S]*?)\s*```/);
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const jsonStr = jsonMatch ? jsonMatch[1] : rawResponse;
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const parsed = JSON.parse(jsonStr.trim());
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// 验证状态值
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const validStatuses = ['PASS', 'FAIL', 'UNCERTAIN'];
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const status = validStatuses.includes(parsed.status?.toUpperCase())
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? parsed.status.toUpperCase()
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: 'UNCERTAIN';
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return {
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status: status,
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reason: parsed.reason || '未提供理由',
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evidence: parsed.evidence || {},
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confidence: typeof parsed.confidence === 'number'
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? Math.min(1, Math.max(0, parsed.confidence))
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: 0.5,
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};
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}
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catch (error) {
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logger.warn('[SoftRuleEngine] Failed to parse LLM response', {
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checkId: check.id,
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rawResponse: rawResponse.substring(0, 500),
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});
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// 解析失败时尝试简单匹配
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const lowerResponse = rawResponse.toLowerCase();
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if (lowerResponse.includes('pass') || lowerResponse.includes('通过')) {
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return {
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status: 'PASS',
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reason: rawResponse,
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evidence: {},
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confidence: 0.6,
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};
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}
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else if (lowerResponse.includes('fail') || lowerResponse.includes('失败') || lowerResponse.includes('不符合')) {
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return {
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status: 'FAIL',
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reason: rawResponse,
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evidence: {},
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confidence: 0.6,
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};
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}
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return {
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status: 'UNCERTAIN',
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reason: `无法解析响应: ${rawResponse.substring(0, 200)}`,
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evidence: {},
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confidence: 0.3,
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};
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}
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}
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/**
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* 批量执行检查
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*
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* @param records 记录列表
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* @param checks 检查列表
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* @returns 所有记录的检查结果
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*/
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async executeBatch(records, checks) {
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const results = [];
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for (const record of records) {
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const result = await this.execute(record.recordId, record.data, checks);
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results.push(result);
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}
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return results;
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}
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}
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// ============================================================
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// 工厂函数
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// ============================================================
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/**
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* 创建 SoftRuleEngine 实例
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*
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* @param projectId 项目ID
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* @param config 可选配置
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* @returns SoftRuleEngine 实例
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*/
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export function createSoftRuleEngine(projectId, config) {
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return new SoftRuleEngine(projectId, config);
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}
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// ============================================================
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// 预置检查模板
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// ============================================================
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/**
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* 入排标准检查模板
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*/
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export const INCLUSION_EXCLUSION_CHECKS = [
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{
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id: 'IE-001',
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name: '年龄入组标准',
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description: '检查受试者年龄是否符合入组标准',
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promptTemplate: '请根据受试者数据，判断其年龄是否在研究方案规定的入组范围内。如果年龄字段缺失，请标记为 UNCERTAIN。',
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requiredTags: ['#demographics'],
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category: 'inclusion',
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severity: 'critical',
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},
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{
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id: 'IE-002',
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name: '确诊时间入组标准',
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description: '检查受试者确诊时间是否符合入组标准（通常要求确诊在一定时间内）',
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promptTemplate: '请根据受试者的确诊日期和入组日期，判断确诊时间是否符合研究方案要求。',
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requiredTags: ['#demographics', '#medical_history'],
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category: 'inclusion',
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severity: 'critical',
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},
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];
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/**
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* AE 事件检测模板
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*/
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export const AE_DETECTION_CHECKS = [
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{
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id: 'AE-001',
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name: 'Lab 异常与 AE 一致性',
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description: '检查实验室检查异常值是否已在 AE 表中报告',
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promptTemplate: '请对比实验室检查数据和不良事件记录，判断是否存在未报告的实验室异常（Grade 3 及以上）。',
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requiredTags: ['#lab', '#ae'],
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category: 'ae_detection',
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severity: 'critical',
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},
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];
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/**
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* 方案偏离检测模板
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*/
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export const PROTOCOL_DEVIATION_CHECKS = [
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{
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id: 'PD-001',
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name: '访视超窗检测',
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description: '检查访视是否在方案规定的时间窗口内',
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promptTemplate: '请根据访视日期数据，判断各访视之间的时间间隔是否符合方案规定的访视窗口。',
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requiredTags: ['#visits'],
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category: 'protocol_deviation',
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severity: 'warning',
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},
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];
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