memind/chat-intent-router.test.mjs

import assert from 'node:assert/strict';
import test from 'node:test';
import {
  applyAgentOrchestrationToUserMessage,
  buildRouterContext,
  buildAgentOrchestrationAgentText,
  CHAT_INTENT_ROUTE,
  classifyWithRules,
  createChatIntentRouter,
  createManagedChatIntentRouter,
} from './chat-intent-router.mjs';

test('classifyWithRules routes greetings to direct chat', () => {
  const result = classifyWithRules({
    text: '你好',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '你好' }],
      metadata: { displayText: '你好' },
    },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.equal(result.source, 'rule');
});

test('classifyWithRules routes page generation to agent orchestration', () => {
  const result = classifyWithRules({
    text: '帮我做一个秋夜诗的 H5 页面',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '帮我做一个秋夜诗的 H5 页面' }],
      metadata: { displayText: '帮我做一个秋夜诗的 H5 页面' },
    },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.suggestedSkill, 'static-page-publish');
});

test('classifyWithRules routes themed article requests to agent orchestration', () => {
  const result = classifyWithRules({
    text: '帮我写个主题文章',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '帮我写个主题文章' }],
      metadata: { displayText: '帮我写个主题文章' },
    },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.suggestedSkill, 'static-page-publish');
});

test('classifyWithRules honors forceDeepReasoning bypass', () => {
  const result = classifyWithRules({
    text: '你好',
    forceDeepReasoning: true,
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '你好' }],
    },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.match(result.reason, /深度推理/);
});

test('classifyWithRules skips session continuation when llm router is enabled', () => {
  const continued = classifyWithRules({
    text: '我想去日本玩',
    sessionId: '20260704_10',
    sessionMessageCount: 2,
    llmRouterEnabled: true,
  });
  assert.equal(continued, null);
});

test('classifyWithRules keeps empty pre-created sessions eligible for llm routing', () => {
  const continued = classifyWithRules({
    text: '继续聊聊',
    sessionId: '20260704_2',
    sessionMessageCount: 2,
  });
  assert.equal(continued.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(continued.reason, '延续已有 Agent 会话');

  const fresh = classifyWithRules({
    text: '我是 John，你对我的记忆知道多少？',
    sessionId: '20260704_3',
    sessionMessageCount: 0,
  });
  assert.equal(fresh.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.match(fresh.reason, /记忆/);
});

test('classifyWithRules routes memory recall to direct chat even in agent session', () => {
  const result = classifyWithRules({
    text: '你记得我说想去哪儿吗',
    sessionId: '20260704_9',
    sessionMessageCount: 4,
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '你记得我说想去哪儿吗' }],
      metadata: { displayText: '你记得我说想去哪儿吗' },
    },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.match(result.reason, /记忆/);
});

test('classifyWithRules bypasses llm router when user selected summarize skill', async () => {
  const llmCalls = [];
  const router = createChatIntentRouter({
    enabled: true,
    llmProviderService: {
      async createChatCompletion() {
        llmCalls.push(1);
        return { ok: true, reply: '{"route":"direct_chat","confidence":0.9,"reason":"x"}' };
      },
    },
    memoryV2: {
      async resolve() {
        assert.fail('memory resolve should not run for explicit skill selection');
      },
    },
  });

  const prompt = '请总结以下内容，提炼核心结论、重点信息和可执行建议（条理清晰、中文输出）：';
  const result = await router.classify({
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: `${prompt}这是待总结的正文` }],
      metadata: {
        displayText: `${prompt}这是待总结的正文`,
        memindRun: { selectedChatSkill: 'summarize' },
      },
    },
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.source, 'rule');
  assert.equal(result.reason, '用户已选择 skill');
  assert.equal(llmCalls.length, 0);
});

test('classifyWithRules bypasses llm router for explicit web skill prompt', async () => {
  const llmCalls = [];
  const router = createChatIntentRouter({
    enabled: true,
    llmProviderService: {
      async createChatCompletion() {
        llmCalls.push(1);
        return { ok: true, reply: '{"route":"direct_chat","confidence":0.9,"reason":"x"}' };
      },
    },
  });

  const result = await router.classify({
    userMessage: {
      role: 'user',
      content: [{
        type: 'text',
        text: '请使用 web 技能：帮我搜索并查阅相关资料（优先官方文档），并给出中文摘要与来源链接。我的问题是：今天 AI 新闻',
      }],
      metadata: { displayText: '今天 AI 新闻' },
    },
    grantedSkills: ['web'],
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.suggestedSkill, 'web');
  assert.equal(llmCalls.length, 0);
});

test('createChatIntentRouter classifies continued sessions through llm when enabled', async () => {
  const llmCalls = [];
  const router = createChatIntentRouter({
    enabled: true,
    modelProviderKeyId: 'key-router',
    model: 'deepseek-chat',
    llmProviderService: {
      async createChatCompletion(payload) {
        llmCalls.push(payload);
        return {
          ok: true,
          reply: JSON.stringify({
            route: 'agent_orchestration',
            confidence: 0.88,
            reason: '用户要规划日本旅行，需要搜索和生成内容',
            suggested_skill: 'static-page-publish',
            agent_brief: '整理日本旅行攻略',
          }),
        };
      },
    },
    memoryV2: {
      async resolve() {
        return { source: 'legacy-conversation-memory', memories: [{ label: 'goal', text: '用户想去日本旅游' }] };
      },
    },
  });

  const result = await router.classify({
    userId: 'user-john',
    sessionId: '20260704_10',
    sessionMessageCount: 2,
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '我想去日本玩' }],
      metadata: { displayText: '我想去日本玩' },
    },
  });

  assert.equal(llmCalls.length, 1);
  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.source, 'llm');
  assert.match(result.reason, /日本旅行/);
  assert.equal(result.memory?.itemsUsed ?? 0, 0);
});

test('createChatIntentRouter skips memory resolve for general conversational analysis', async () => {
  const llmCalls = [];
  const resolveCalls = [];
  const router = createChatIntentRouter({
    enabled: true,
    modelProviderKeyId: 'key-router',
    model: 'deepseek-chat',
    llmProviderService: {
      async createChatCompletion({ messages, providerKeyId, model, temperature }) {
        llmCalls.push({ messages, providerKeyId, model, temperature });
        return {
          ok: true,
          providerKeyId,
          model,
          reply: JSON.stringify({
            route: 'direct_chat',
            confidence: 0.91,
            reason: '用户在咨询概念，不需要执行工具',
            suggested_skill: null,
            agent_brief: '',
          }),
        };
      },
    },
    memoryV2: {
      async resolve(input) {
        resolveCalls.push(input);
        return {
          source: 'pgvector',
          memories: [{ label: 'preference', text: '用户偏好简洁回答，不喜欢冗长铺垫' }],
          activeGoals: ['完善春季促销活动页'],
        };
      },
    },
  });

  const result = await router.classify({
    userId: 'user-1',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: 'React 19 有哪些新特性？' }],
      metadata: { displayText: 'React 19 有哪些新特性？' },
    },
    grantedSkills: ['web'],
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.equal(result.source, 'llm');
  assert.equal(result.providerKeyId, 'key-router');
  assert.equal(result.model, 'deepseek-chat');
  assert.equal(result.memory?.itemsUsed ?? 0, 0);
  assert.equal(resolveCalls.length, 0);
  assert.equal(llmCalls.length, 1);
  assert.equal(llmCalls[0].providerKeyId, 'key-router');
  assert.equal(llmCalls[0].model, 'deepseek-chat');
  assert.equal(llmCalls[0].temperature, 0);
  assert.doesNotMatch(llmCalls[0].messages[1].content, /相关记忆/);
});

test('createChatIntentRouter resolves light memory for recall questions', async () => {
  const resolveCalls = [];
  const router = createChatIntentRouter({
    enabled: true,
    modelProviderKeyId: 'key-router',
    model: 'deepseek-chat',
    llmProviderService: {
      async createChatCompletion() {
        return {
          ok: true,
          reply: JSON.stringify({
            route: 'direct_chat',
            confidence: 0.95,
            reason: '用户在询问个人记忆',
            suggested_skill: null,
            agent_brief: '',
          }),
        };
      },
    },
    memoryV2: {
      async resolve(input) {
        resolveCalls.push(input);
        return {
          source: 'pgvector',
          memories: [{ label: 'goal', text: '用户想去日本旅游' }],
        };
      },
    },
  });

  const result = await router.classify({
    userId: 'user-john',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '你记得我说想去哪儿吗？' }],
      metadata: { displayText: '你记得我说想去哪儿吗？' },
    },
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.equal(resolveCalls.length, 1);
  assert.equal(resolveCalls[0].limit, 3);
  assert.equal(result.memory?.itemsUsed, 1);
});

test('buildRouterContext trims rich Memory V2 resolve payload for routing', () => {
  const context = buildRouterContext({
    source: 'letta',
    memories: [
      { label: 'preference', text: '用户偏好简洁回答，不喜欢冗长铺垫，尤其在工程排障时希望先给结论。' },
      { label: 'habit', text: '用户经常要求生成 H5 活动页并发布到 MindSpace。' },
    ],
    semanticMemories: ['上次正在修改活动页标题样式'],
    behaviorSummary: '用户倾向先本地验证，再决定是否发布生产。额外句子不应进入轻量摘要。',
    activeGoals: ['完善春季促销活动页'],
    profile: { ignored: true },
  });

  assert.equal(context.source, 'letta');
  assert.equal(context.itemsUsed, 5);
  assert.match(context.content, /相关记忆/);
  assert.match(context.content, /行为摘要/);
  assert.match(context.content, /进行中目标/);
  assert.doesNotMatch(context.content, /ignored/);
});

test('createChatIntentRouter fails open when Memory V2 resolve fails', async () => {
  const router = createChatIntentRouter({
    enabled: true,
    llmProviderService: {
      async createChatCompletion({ messages }) {
        assert.match(messages[1].content, /\[Router Context\]\n无/);
        return {
          ok: true,
          reply: JSON.stringify({
            route: 'agent_orchestration',
            confidence: 0.82,
            reason: '需要工具执行',
            suggested_skill: 'web',
            agent_brief: '搜索并整理来源',
          }),
        };
      },
    },
    memoryV2: {
      async resolve() {
        throw new Error('memory down');
      },
    },
    logger: { warn() {} },
  });

  const result = await router.classify({
    userId: 'user-1',
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '你记得我之前说过什么吗？' }],
      metadata: { displayText: '你记得我之前说过什么吗？' },
    },
    grantedSkills: ['web'],
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.memory.degraded, true);
});

test('createManagedChatIntentRouter hot-loads admin config and stays closed by default', async () => {
  const states = [
    {
      fingerprint: 'off',
      overrides: {
        MEMIND_CHAT_LLM_ROUTER_ENABLED: '0',
      },
    },
    {
      fingerprint: 'on',
      overrides: {
        MEMIND_CHAT_LLM_ROUTER_ENABLED: '1',
        MEMIND_CHAT_ROUTER_MODEL_PROVIDER_KEY_ID: 'key-router',
        MEMIND_CHAT_ROUTER_MODEL: 'deepseek-chat',
      },
    },
  ];
  const llmCalls = [];
  const router = createManagedChatIntentRouter({
    configService: {
      async getRuntimeState() {
        return states[0];
      },
    },
    llmProviderService: {
      async createChatCompletion(input) {
        llmCalls.push(input);
        return {
          ok: true,
          providerKeyId: input.providerKeyId,
          model: input.model,
          reply: JSON.stringify({
            route: 'direct_chat',
            confidence: 0.9,
            reason: '纯文字问答',
            suggested_skill: null,
            agent_brief: '',
          }),
        };
      },
    },
  });

  assert.equal(await router.isEnabled(), false);
  states.shift();
  assert.equal(await router.isEnabled(), true);
  const result = await router.classify({
    userMessage: { role: 'user', content: [{ type: 'text', text: '你好' }] },
  });
  assert.equal(result.route, CHAT_INTENT_ROUTE.DIRECT_CHAT);
  assert.equal(llmCalls[0].providerKeyId, 'key-router');
});

test('createChatIntentRouter escalates low-confidence direct chat to agent', async () => {
  const router = createChatIntentRouter({
    enabled: true,
    minConfidence: 0.8,
    llmProviderService: {
      async createChatCompletion() {
        return {
          ok: true,
          reply: JSON.stringify({
            route: 'direct_chat',
            confidence: 0.42,
            reason: '可能是简单问答',
            suggested_skill: null,
            agent_brief: '',
          }),
        };
      },
    },
  });

  const result = await router.classify({
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '帮我整理一下这段材料' }],
      metadata: { displayText: '帮我整理一下这段材料' },
    },
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.source, 'threshold');
});

test('createChatIntentRouter falls back to agent when LLM fails', async () => {
  const router = createChatIntentRouter({
    enabled: true,
    llmProviderService: {
      async createChatCompletion() {
        return { ok: false, message: 'router model unavailable' };
      },
    },
  });

  const result = await router.classify({
    userMessage: {
      role: 'user',
      content: [{ type: 'text', text: '帮我查一下今天的 AI 新闻' }],
      metadata: { displayText: '帮我查一下今天的 AI 新闻' },
    },
    grantedSkills: ['web'],
  });

  assert.equal(result.route, CHAT_INTENT_ROUTE.AGENT);
  assert.equal(result.source, 'fallback');
});

test('applyAgentOrchestrationToUserMessage preserves displayText and adds task envelope', () => {
  const enriched = applyAgentOrchestrationToUserMessage(
    {
      role: 'user',
      content: [{ type: 'text', text: '帮我做一个页面' }],
      metadata: { displayText: '帮我做一个页面', userVisible: true },
    },
    {
      route: CHAT_INTENT_ROUTE.AGENT,
      confidence: 0.9,
      reason: '需要生成页面',
      suggestedSkill: 'static-page-publish',
      agentBrief: '生成 HTML 并发布',
      source: 'llm',
    },
    { grantedSkills: ['static-page-publish'] },
  );

  assert.equal(enriched.metadata.displayText, '帮我做一个页面');
  assert.match(enriched.content[0].text, /Memind 任务编排/);
  assert.match(enriched.content[0].text, /static-page-publish/);
  assert.match(enriched.content[0].text, /帮我做一个页面/);
});

test('buildAgentOrchestrationAgentText includes execution brief', () => {
  const text = buildAgentOrchestrationAgentText({
    displayText: '帮我搜索今天的新闻',
    classification: {
      reason: '需要实时搜索',
      suggestedSkill: 'web',
      agentBrief: '使用 web skill 搜索并整理来源',
    },
    skillPrompt: '请使用 web 技能：',
  });
  assert.match(text, /需要实时搜索/);
  assert.match(text, /帮我搜索今天的新闻/);
  assert.match(text, /请使用 web 技能/);
});