makemd/server/src/services/PriorityTicketService.ts

import db from '../config/database';
import { logger } from '../utils/logger';
import { DecisionExplainabilityEngine } from '../core/ai/DecisionExplainabilityEngine';

export interface TicketSentiment {
  ticketId: string;
  sentimentScore: number; // 0 (negative) to 1 (positive)
  urgency: 'LOW' | 'MEDIUM' | 'HIGH' | 'CRITICAL';
  keywords: string[];
}

/**
 * [BIZ_OPS_135] 智能工单优先级调度建议 (Support Queue)
 * @description 核心逻辑：分析工单内容的情感极性与关键词，自动识别“紧急差评”或“退款威胁”，并建议优先处理。
 */
export class PriorityTicketService {
  private static readonly PRIORITY_AUDIT_TABLE = 'cf_ticket_priority_audit';

  /**
   * 初始化数据库表
   */
  static async initTable() {
    const hasTable = await db.schema.hasTable(this.PRIORITY_AUDIT_TABLE);
    if (!hasTable) {
      await db.schema.createTable(this.PRIORITY_AUDIT_TABLE, (table) => {
        table.increments('id').primary();
        table.string('tenant_id', 64).index();
        table.string('ticket_id', 64).index();
        table.string('priority_suggested', 16);
        table.text('reason');
        table.string('status', 32).defaultTo('PENDING_REVIEW');
        table.timestamp('created_at').defaultTo(db.fn.now());
      });
    }
  }

  /**
   * 优先调度工单 (BIZ_OPS_135)
   */
  static async prioritizeTickets(tenantId: string): Promise<any> {
    logger.info(`[TicketPriority] Analyzing tickets for Tenant: ${tenantId}`);

    try {
      // 1. 获取该租户下所有未解决的工单 (模拟查询)
      const tickets = await db('cf_support_tickets')
        .where({ tenant_id: tenantId, status: 'OPEN' })
        .limit(50);

      const prioritized = [];

      for (const ticket of tickets) {
        // 2. 情感与关键词分析 (模拟)
        const sentiment = await this.analyzeTicketSentiment(ticket.content);

        // 3. 优先级策略：情感极低 (< 0.2) 或 包含 "refund", "scam"
        let priority: 'LOW' | 'MEDIUM' | 'HIGH' | 'CRITICAL' = 'LOW';
        if (sentiment.sentimentScore < 0.2 || sentiment.keywords.some(k => ['refund', 'scam', 'bad', 'fraud'].includes(k.toLowerCase()))) {
          priority = 'CRITICAL';
        } else if (sentiment.sentimentScore < 0.5) {
          priority = 'HIGH';
        }

        if (priority === 'CRITICAL' || priority === 'HIGH') {
          const reason = `Ticket identified as ${priority} based on negative sentiment (${sentiment.sentimentScore.toFixed(2)}) ` +
            `and keywords: [${sentiment.keywords.join(', ')}].`;
          
          // 4. 生成优先处理建议 (Suggestion-First)
          const [suggestionId] = await db(this.PRIORITY_AUDIT_TABLE).insert({
            tenant_id: tenantId,
            ticket_id: ticket.id,
            priority_suggested: priority,
            reason: reason,
            status: 'PENDING_REVIEW',
            created_at: new Date()
          });

          // 5. [UX_XAI_01] 记录决策证据链
          await DecisionExplainabilityEngine.logDecision({
            tenantId,
            module: 'SUPPORT_TICKET',
            resourceId: String(suggestionId),
            decisionType: 'PRIORITY_SCHEDULING_SUGGESTION',
            causalChain: reason,
            factors: [
              { name: 'SentimentScore', value: sentiment.sentimentScore, weight: 0.6, impact: 'NEGATIVE' },
              { name: 'KeywordMatch', value: sentiment.keywords.length, weight: 0.4, impact: 'NEGATIVE' }
            ],
            traceId: 'ticket-priority-' + Date.now()
          });

          prioritized.push({ ticketId: ticket.id, priority, suggestionId });
        }
      }

      return { 
        success: true, 
        count: prioritized.length, 
        prioritized,
        status: 'PENDING_REVIEW' 
      };
    } catch (err: any) {
      logger.error(`[TicketPriority][WARN] Prioritization failed: ${err.message}`);
      return { success: false, error: err.message };
    }
  }

  private static async analyzeTicketSentiment(content: string): Promise<TicketSentiment> {
    // 实际业务中应调用 AIService 或专门的情感分析接口
    const score = Math.random(); // 模拟得分
    const keywords = ['refund', 'wait', 'shipping'].filter(() => Math.random() > 0.5);
    return {
      ticketId: 'mock',
      sentimentScore: score,
      urgency: 'MEDIUM',
      keywords
    };
  }
}