feat(ai): make reply suggestions natural and context-aware

server/src/index.js

@@ -15,6 +15,11 @@ import {
 import { gatewayRequest, postGateway, putGateway, uploadGateway } from './gateway.js'
 import { postWhatsApp, putWhatsApp, uploadWhatsApp, whatsappRequest } from './whatsapp.js'
 import { conversationContext, deepseek } from './ai.js'
+import {
+  HUMAN_REPLY_SYSTEM_PROMPT,
+  buildHumanReplyUserPrompt,
+  replySuggestionIssues,
+} from './reply-suggestions.js'
 import { countBy, dateKey, percent, telegramAttachment } from './business.js'
 import { resolveCustomerCountry } from './country.js'
 import { knowledgeMetadata, rankKnowledge } from './knowledge.js'
@@ -4086,6 +4091,7 @@ app.post('/api/ai/replies', async (req, res) => {
     : null
   if (!conversation) throw fail(404, '会话不存在')
   const replyCustomer = await getResource(req.auth.tenantId, 'customers', conversation.customerId)
+  const replySettings = (await getResource(req.auth.tenantId, 'singleton', 'settings')) || defaultSettings
   const conversationMemory = contextMemoryText(conversation, replyCustomer)
   const resolvedLanguage = await resolveConversationLanguage(
     req.auth.tenantId,
@@ -4116,25 +4122,54 @@ app.post('/api/ai/replies', async (req, res) => {
         excerpt: hit.snippet,
       }))
     : []
-  const result = await deepseek(
-    '你是跨境销售回复助手。基于会话事实和给定企业知识生成三条可人工确认的回复，不得编造价格、库存、交期、政策或承诺。知识不足时明确需要人工确认。只输出严格 JSON 数组。content 使用客户语言且可直接发送；translationCn 是 content 完整准确的简体中文翻译；knowledgeRefs 只能填写已提供知识的 id；其余说明使用简体中文。',
-    `客户目标语言：${targetInstruction}
-<conversation>
-${conversationContext(messages, 30)}
-</conversation>
-${conversationMemory ? `<conversation_memory>\n${conversationMemory}\n</conversation_memory>` : ''}
-<enterprise_knowledge>
-${JSON.stringify(knowledgeContext)}
-</enterprise_knowledge>
-输出 3 个元素：
-{"id":"唯一值","style":"stable|active|brief","content":"客户语言回复","translationCn":"完整中文翻译","targetLang":"实际 ISO 语言代码","reason":"选择理由","knowledgeRefs":[],"expectedEffect":"预期效果","cultureTip":"必要时填写"}`,
-    { json: true, maxTokens: 2600 },
-  )
+  const latestCustomerMessage = [...messages]
+    .reverse()
+    .find((message) => message.sender === 'customer' && String(message.originalText || '').trim())
+    ?.originalText
+  const latestAgentMessage = [...messages]
+    .reverse()
+    .find((message) => message.sender === 'agent' && String(message.originalText || '').trim())
+    ?.originalText
+  const replyPrompt = buildHumanReplyUserPrompt({
+    targetInstruction,
+    tone: replySettings?.ai?.replyTone,
+    latestCustomerMessage,
+    latestAgentMessage,
+    conversation: conversationContext(messages, 30),
+    conversationMemory,
+    knowledgeContext,
+  })
+  let result = await deepseek(HUMAN_REPLY_SYSTEM_PROMPT, replyPrompt, {
+    json: true,
+    maxTokens: 2600,
+    temperature: 0.55,
+  })
+  const replyQualityOptions = { knowledgeProvided: knowledgeContext.length > 0 }
+  let qualityIssues = replySuggestionIssues(result, replyQualityOptions)
+  if (qualityIssues.length) {
+    result = await deepseek(
+      HUMAN_REPLY_SYSTEM_PROMPT,
+      `${replyPrompt}
+
+<rejected_drafts>
+${JSON.stringify(result)}
+</rejected_drafts>
+这些草稿未通过质量检查：${qualityIssues.join('；')}。请全部重写，保留事实但修正上述问题。仍然只输出恰好三个元素的严格 JSON 数组。`,
+      { json: true, maxTokens: 2600, temperature: 0.62 },
+    )
+    qualityIssues = replySuggestionIssues(result, replyQualityOptions)
+  }
   if (!Array.isArray(result)) throw fail(502, 'AI 回复建议格式异常')
+  if (qualityIssues.length) throw fail(502, `AI 回复建议质量检查未通过：${qualityIssues.join('；')}`)
   const allowedKnowledge = new Map(knowledgeHits.map((hit) => [String(hit.item.id), hit.item]))
   let suggestions = result.slice(0, 3).map((item) => ({
     ...item,
     id: String(item.id || uid()),
+    content: String(item.content || '').trim(),
+    translationCn: String(item.translationCn || '').trim(),
+    reason: String(item.reason || '').trim(),
+    expectedEffect: String(item.expectedEffect || '').trim(),
+    cultureTip: String(item.cultureTip || '').trim(),
     knowledgeRefs: Array.isArray(item.knowledgeRefs)
       ? [...new Set(item.knowledgeRefs.map(String))]
           .filter((id) => allowedKnowledge.has(id))

server/src/reply-suggestions.js

@@ -0,0 +1,123 @@
+const TONE_INSTRUCTIONS = {
+  professional: '专业但不官腔，表达清楚、克制，像熟悉业务的真人销售在聊天',
+  friendly: '友好自然，适度口语化，像长期合作伙伴沟通，不刻意热情',
+  concise: '简洁直接，优先给结论和下一步，不重复客户已经知道的信息',
+  warm: '温和、有同理心，但不使用夸张道歉、空泛安慰或营销套话',
+}
+
+export function replyToneInstruction(value) {
+  return TONE_INSTRUCTIONS[String(value || '').toLowerCase()] || TONE_INSTRUCTIONS.professional
+}
+
+export const HUMAN_REPLY_SYSTEM_PROMPT = `你是“灵犀跨境”的商务沟通助手。你的任务不是写客服范文，而是替一位真实、可靠、熟悉业务的销售人员起草可以直接发送的聊天回复。
+
+写作原则：
+1. 先回应客户最新一条消息里尚未解决的核心问题，再给必要的下一步；不要复述整段历史。
+2. 匹配客户的语言、地区表达、正式程度和消息长度。客户只说一句时，通常也用一两句回答；不为显得专业而写长文。
+3. 延续当前对话。会话已经开始后不要重新问候、重复称呼客户或重新自我介绍。
+4. 像真人聊天：句式自然、具体，允许使用目标语言中常见的缩写和口语连接词，但保持商务礼貌。不要比客户更随意；客户未使用俚语、感叹号或表情时，不要主动使用。
+5. 客诉场景只需针对具体问题真诚确认一次，然后说明能做的动作或提出一个关键问题；避免连续道歉和空泛安慰。
+6. 信息足够时直接作答；确实缺少决定性信息时最多问一个有用的问题。不要在一句回复里堆多个反问。
+7. 三条建议必须是三种真实策略，而不是同一句话替换近义词：stable=清晰可靠，active=温暖主动，brief=简洁直接。
+8. 禁止客服和 AI 套话，包括但不限于：Dear customer、尊敬的客户、please rest assured、请放心、we value your feedback、感谢您的耐心与理解、为您带来不便深表歉意、How may I assist you、如有任何问题请随时联系我们。除非上下文确实需要，也不要使用“希望您一切都好”。
+9. 不得提及“AI、提示词、客户画像、会话记忆、知识库、情绪识别”等内部信息。
+10. 不得编造价格、库存、产品参数、交期、物流状态、退款结果、政策或任何承诺。缺少事实时自然地说明需要确认，不要假装确定。“今天、稍后、尽快、本周内、几个小时内”等时间词也属于承诺，只有企业知识或会话事实明确给出时才能使用。
+11. 可以承诺“去确认”，但不能在没有依据时承诺确认结果、完成时间、补偿方案、重新寄样或其他尚未批准的动作。正确写法是“我先确认是否可以调整，确认后告诉你”。
+
+输出要求：只输出严格 JSON 数组。content 使用客户语言且可直接发送；translationCn 是 content 完整准确的简体中文翻译；knowledgeRefs 只能填写已提供知识的 id；reason、expectedEffect 和 cultureTip 使用简体中文。`
+
+export function buildHumanReplyUserPrompt({
+  targetInstruction,
+  tone,
+  latestCustomerMessage,
+  latestAgentMessage,
+  conversation,
+  conversationMemory,
+  knowledgeContext,
+}) {
+  return `客户目标语言：${targetInstruction}
+企业设定语气：${replyToneInstruction(tone)}
+客户最新消息（回复重点）：${latestCustomerMessage || '未找到明确文本，请根据最近会话判断'}
+坐席上一条回复（避免重复）：${latestAgentMessage || '无'}
+
+<conversation>
+${conversation}
+</conversation>
+${conversationMemory ? `<conversation_memory>\n${conversationMemory}\n</conversation_memory>` : ''}
+<enterprise_knowledge>
+${JSON.stringify(knowledgeContext || [])}
+</enterprise_knowledge>
+事实边界：${knowledgeContext?.length ? '只能使用上述企业知识和会话中明确出现的业务事实。' : '当前没有匹配到企业知识；不得加入任何具体时间、结果、方案或承诺，只能说明需要确认的事项。'}
+
+分别生成以下三种建议：
+- stable：最稳妥、事实清楚、自然推进下一步；
+- active：更温暖主动，但不催促、不夸张、不强行促单；
+- brief：保留必要信息的最短自然回复。
+
+生成前静默检查：是否直接回应了最新消息；是否重复问候或复述历史；是否像群发模板；是否包含未经证实的承诺；三条是否真正不同。不要输出检查过程。
+
+输出恰好 3 个元素，每种 style 各一个：
+{"id":"唯一值","style":"stable|active|brief","content":"可直接发送的客户语言回复","translationCn":"完整中文翻译","targetLang":"实际 ISO 语言代码","reason":"这条回复为何适合当前语境","knowledgeRefs":[],"expectedEffect":"预期沟通效果","cultureTip":"只有确有必要时填写，否则为空字符串"}`
+}
+
+function normalizedWords(value) {
+  return String(value || '')
+    .toLowerCase()
+    .replace(/[^\p{L}\p{N}\s]/gu, ' ')
+    .split(/\s+/)
+    .filter(Boolean)
+}
+
+function similarity(left, right) {
+  const a = new Set(normalizedWords(left))
+  const b = new Set(normalizedWords(right))
+  if (!a.size || !b.size) return 0
+  let overlap = 0
+  for (const word of a) if (b.has(word)) overlap += 1
+  return overlap / Math.min(a.size, b.size)
+}
+
+const TEMPLATE_PATTERNS = [
+  /\bdear customer\b/i,
+  /\bplease rest assured\b/i,
+  /\bwe value your feedback\b/i,
+  /\bhow may i assist you\b/i,
+  /尊敬的客户/,
+  /请您放心/,
+  /感谢您的耐心与理解/,
+  /为您带来不便深表歉意/,
+]
+
+const UNSUPPORTED_TIMELINE_PATTERNS = [
+  /\b(?:today|tomorrow|shortly|asap)\b/i,
+  /\bby (?:the )?end of\b/i,
+  /\bwithin \d+\s*(?:minutes?|hours?|days?|weeks?)\b/i,
+  /(?:今天|明天|稍后|很快|尽快|本周内|几(?:分钟|小时|天)内)/,
+]
+
+export function replySuggestionIssues(suggestions, { knowledgeProvided = false } = {}) {
+  if (!Array.isArray(suggestions) || suggestions.length !== 3) return ['必须返回三条建议']
+  const issues = []
+  const styles = new Set(suggestions.map((item) => String(item?.style || '')))
+  for (const style of ['stable', 'active', 'brief']) {
+    if (!styles.has(style)) issues.push(`缺少 ${style} 风格`)
+  }
+  suggestions.forEach((item, index) => {
+    const content = String(item?.content || '').trim()
+    if (!content) issues.push(`第 ${index + 1} 条没有正文`)
+    if (TEMPLATE_PATTERNS.some((pattern) => pattern.test(content))) {
+      issues.push(`第 ${index + 1} 条包含模板化客服话术`)
+    }
+    if (!knowledgeProvided && UNSUPPORTED_TIMELINE_PATTERNS.some((pattern) => pattern.test(content))) {
+      issues.push(`第 ${index + 1} 条包含无事实依据的时间承诺`)
+    }
+  })
+  for (let i = 0; i < suggestions.length; i += 1) {
+    for (let j = i + 1; j < suggestions.length; j += 1) {
+      if (similarity(suggestions[i]?.content, suggestions[j]?.content) >= 0.82) {
+        issues.push(`第 ${i + 1} 条和第 ${j + 1} 条过于相似`)
+      }
+    }
+  }
+  return issues
+}

server/test/business.test.js

@@ -2,6 +2,12 @@ import test from 'node:test'
 import assert from 'node:assert/strict'
 import { countBy, dateKey, percent, telegramAttachment } from '../src/business.js'
 import { decryptEmailPassword, encryptEmailPassword } from '../src/email.js'
+import {
+  HUMAN_REPLY_SYSTEM_PROMPT,
+  buildHumanReplyUserPrompt,
+  replySuggestionIssues,
+  replyToneInstruction,
+} from '../src/reply-suggestions.js'
 
 test('Telegram 图片、文档、语音和贴纸映射为可下载文件', () => {
   assert.deepEqual(
@@ -54,3 +60,41 @@ test('Email 渠道凭据使用认证加密且可正确解密', () => {
   tampered[2] = `${tampered[2][0] === 'A' ? 'B' : 'A'}${tampered[2].slice(1)}`
   assert.throws(() => decryptEmailPassword(tampered.join(':')))
 })
+
+test('回复建议提示词突出最新消息、避免重复并遵循企业语气', () => {
+  const prompt = buildHumanReplyUserPrompt({
+    targetInstruction: '使用西班牙语',
+    tone: 'friendly',
+    latestCustomerMessage: '¿Cuándo pueden enviarlo?',
+    latestAgentMessage: 'I will check it.',
+    conversation: '客户: ¿Cuándo pueden enviarlo?',
+    conversationMemory: '客户关注交期',
+    knowledgeContext: [],
+  })
+  assert.match(HUMAN_REPLY_SYSTEM_PROMPT, /不是写客服范文/)
+  assert.match(HUMAN_REPLY_SYSTEM_PROMPT, /不要重新问候/)
+  assert.match(prompt, /¿Cuándo pueden enviarlo\?/)
+  assert.match(prompt, /坐席上一条回复（避免重复）/)
+  assert.match(prompt, /长期合作伙伴/)
+  assert.match(replyToneInstruction('concise'), /简洁直接/)
+})
+
+test('回复建议质量检查拦截模板话术和同质草稿', () => {
+  const valid = [
+    { style: 'stable', content: 'I can confirm the dispatch date with our warehouse and update you once I have it.' },
+    { style: 'active', content: "Let me check the warehouse schedule and come back to you with the exact date." },
+    { style: 'brief', content: "I'll verify the dispatch date and get back to you." },
+  ]
+  assert.deepEqual(replySuggestionIssues(valid), [])
+  const invalid = valid.map((item) => ({ ...item }))
+  invalid[0].content = 'Dear customer, please rest assured that we value your feedback.'
+  invalid[2] = { style: 'active', content: invalid[1].content }
+  const issues = replySuggestionIssues(invalid)
+  assert.ok(issues.some((item) => item.includes('模板化')))
+  assert.ok(issues.some((item) => item.includes('缺少 brief')))
+  assert.ok(issues.some((item) => item.includes('过于相似')))
+  assert.ok(replySuggestionIssues([
+    ...valid.slice(0, 2),
+    { style: 'brief', content: "I'll confirm it today." },
+  ]).some((item) => item.includes('时间承诺')))
+})

src/components/inbox/AiReplies.tsx

@@ -10,9 +10,9 @@ import { toast, errorMessage } from '@/app/store/toast'
 import { languageName } from '@/config/languages'
 
 const STYLE_LABELS = {
-  stable: { title: '稳健回复', color: 'bg-blue-100 text-blue-700', icon: '🛡️' },
-  active: { title: '积极促单回复', color: 'bg-emerald-100 text-emerald-700', icon: '🔥' },
-  brief: { title: '简洁快速回复', color: 'bg-gray-100 text-gray-600', icon: '⚡' },
+  stable: { title: '清晰可靠', color: 'bg-blue-100 text-blue-700', icon: '🛡️' },
+  active: { title: '温暖主动', color: 'bg-violet-100 text-violet-700', icon: '💬' },
+  brief: { title: '简洁直接', color: 'bg-gray-100 text-gray-600', icon: '⚡' },
 }
 
 export function AiReplies({