HaHafeng
707f783229
Finalize RVW tenant portal UX and reliability updates by aligning login/profile interactions, stabilizing SMS code sends in weak-network scenarios, and fixing multi-tenant assignment payload handling to prevent runtime errors. Refresh RVW status and deployment checklist docs with SAE routing, frontend image build, and post-release validation guidance. Made-with: Cursor
95 lines
3.3 KiB
TypeScript
95 lines
3.3 KiB
TypeScript
/**
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* RVW稿件审查模块 - 临床专业评估服务
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* @module rvw/services/clinicalService
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*
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* 使用 PromptService 获取 RVW_CLINICAL prompt
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* 返回纯 Markdown 报告（无分数）
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*/
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import { LLMFactory } from '../../../common/llm/adapters/LLMFactory.js';
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import { ModelType } from '../../../common/llm/adapters/types.js';
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import { logger } from '../../../common/logging/index.js';
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import { prisma } from '../../../config/database.js';
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import { getPromptService } from '../../../common/prompt/index.js';
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import { composeRvwSystemPrompt, sanitizeRvwBusinessPrompt } from './promptProtocols.js';
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export interface ClinicalReviewResult {
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report: string;
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summary: string;
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}
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/**
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* 临床专业评估
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* @param text 稿件文本
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* @param modelType 模型类型
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* @param userId 用户ID（用于灰度预览判断）
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* @returns 评估结果（Markdown 报告 + 摘要）
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*/
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export async function reviewClinical(
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text: string,
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modelType: ModelType = 'deepseek-v3',
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userId?: string,
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tenantExpertPrompt?: string | null
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): Promise<ClinicalReviewResult> {
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try {
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let businessPrompt = tenantExpertPrompt?.trim() || '';
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let isDraft = false;
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if (!businessPrompt) {
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const promptService = getPromptService(prisma);
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const result = await promptService.get('RVW_CLINICAL', {}, { userId });
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businessPrompt = result.content;
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isDraft = result.isDraft;
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}
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businessPrompt = sanitizeRvwBusinessPrompt('clinical', businessPrompt);
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if (isDraft) {
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logger.info('[RVW:Clinical] 使用 DRAFT 版本 Prompt（调试模式）', { userId });
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}
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const messages = [
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{ role: 'system' as const, content: composeRvwSystemPrompt('clinical', businessPrompt) },
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{
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role: 'user' as const,
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content: `请对以下医学稿件进行临床专业评估。\n\n稿件内容如下：\n${text}`,
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},
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];
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logger.info('[RVW:Clinical] 开始临床专业评估', { modelType });
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const llmAdapter = LLMFactory.getAdapter(modelType);
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const response = await llmAdapter.chat(messages, {
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temperature: 0.3,
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maxTokens: 8000,
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});
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const content = response.content ?? '';
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logger.info('[RVW:Clinical] 评估完成', {
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modelType,
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responseLength: content.length,
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});
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// 优先提取“总体评价”段落作为摘要，提取失败再兜底首段文本
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let summary = '临床专业评估已完成';
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const overallMatch = content.match(/(?:^|\n)\s*(?:#*\s*)?1[\.\、]\s*总体评价[\s\S]*?(?:\n(?:#*\s*)?2[\.\、]\s*详细问题清单与建议|$)/);
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if (overallMatch) {
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const extracted = overallMatch[0]
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.replace(/(?:^|\n)\s*(?:#*\s*)?1[\.\、]\s*总体评价\s*/m, '')
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.trim();
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if (extracted) {
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summary = extracted.substring(0, 200);
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}
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} else {
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const lines = content.split('\n').filter(l => l.trim() && !l.startsWith('#'));
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if (lines.length > 0) {
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summary = lines[0].trim().substring(0, 200);
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}
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}
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return { report: content, summary };
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} catch (error) {
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logger.error('[RVW:Clinical] 临床专业评估失败', {
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error: error instanceof Error ? error.message : 'Unknown error',
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stack: error instanceof Error ? error.stack : undefined,
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});
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throw new Error(`临床专业评估失败: ${error instanceof Error ? error.message : 'Unknown error'}`);
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}
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}
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