memind/conversation-memory.test.mjs

import assert from 'node:assert/strict';
import test from 'node:test';
import { createConversationMemoryService, extractConversationMessageText } from './conversation-memory.mjs';
import { encryptSecret } from './llm-providers.mjs';

function createPool({ provider = null } = {}) {
  const state = {
    messages: [],
    memories: [],
    analyzed: new Set(),
  };
  return {
    state,
    async query(sql, params = []) {
      if (sql.includes('INSERT INTO h5_conversation_messages')) {
        for (const row of params[0]) {
          const [
            id,
            userId,
            sessionId,
            messageKey,
            sequenceNo,
            role,
            text,
            rawJson,
            createdAt,
            updatedAt,
          ] = row;
          const existing = state.messages.find(
            (item) => item.agent_session_id === sessionId && item.message_key === messageKey,
          );
          const next = {
            id,
            user_id: userId,
            agent_session_id: sessionId,
            message_key: messageKey,
            sequence_no: sequenceNo,
            role,
            text,
            raw_json: rawJson,
            created_at: createdAt,
            updated_at: updatedAt,
            analyzed_at: existing?.analyzed_at ?? null,
          };
          if (existing) Object.assign(existing, next);
          else state.messages.push(next);
        }
        return [{ affectedRows: params[0].length }];
      }
      if (sql.includes('FROM h5_conversation_messages')) {
        const [userId, limit] = params;
        return [
          state.messages
            .filter((item) => item.user_id === userId && item.role === 'user' && item.analyzed_at == null)
            .slice(0, limit),
        ];
      }
      if (sql.includes('INSERT INTO h5_user_memory_items')) {
        for (const row of params[0]) {
          const [
            id,
            userId,
            label,
            memoryHash,
            memoryText,
            evidenceMessageId,
            sourceSessionId,
            confidence,
            rawJson,
            createdAt,
            updatedAt,
          ] = row;
          state.memories.push({
            id,
            user_id: userId,
            label,
            memory_hash: memoryHash,
            memory_text: memoryText,
            evidence_message_id: evidenceMessageId,
            source_session_id: sourceSessionId,
            confidence,
            raw_json: rawJson,
            created_at: createdAt,
            updated_at: updatedAt,
          });
        }
        return [{ affectedRows: params[0].length }];
      }
      if (sql.includes('UPDATE h5_conversation_messages SET analyzed_at')) {
        const [analyzedAt, ids] = params;
        for (const item of state.messages) {
          if (ids.includes(item.id)) item.analyzed_at = analyzedAt;
        }
        return [{ affectedRows: ids.length }];
      }
      if (sql.includes('FROM h5_user_memory_items')) {
        const [userId, limit] = params;
        return [
          state.memories
            .filter((item) => item.user_id === userId)
            .slice(0, limit)
            .map((item) => ({ ...item, status: 'active' })),
        ];
      }
      if (sql.includes('FROM h5_llm_provider_keys')) return [[provider].filter(Boolean)];
      throw new Error(`Unexpected SQL: ${sql}`);
    },
  };
}

test('extractConversationMessageText reads text content and display text', () => {
  assert.equal(
    extractConversationMessageText({ content: [{ type: 'text', text: ' hello ' }] }),
    'hello',
  );
  assert.equal(
    extractConversationMessageText({ content: [], metadata: { displayText: 'fallback' } }),
    'fallback',
  );
});

test('saveAndAnalyze stores messages and fallback memories', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '0';
  const pool = createPool();
  const service = createConversationMemoryService(pool, { now: () => 1000 });

  const result = await service.saveAndAnalyze('session-1', 'user-1', [
    {
      id: 'm1',
      role: 'user',
      content: [{ type: 'text', text: '我喜欢简洁直接的回答，也关注 AI 产品设计。' }],
      metadata: { userVisible: true },
    },
    {
      id: 'm2',
      role: 'assistant',
      content: [{ type: 'text', text: '好的。' }],
      metadata: { userVisible: true },
    },
  ]);

  assert.equal(result.saved, 2);
  assert.equal(result.analyzed, 1);
  assert.equal(result.memories, 1);
  assert.equal(pool.state.messages.length, 2);
  assert.equal(pool.state.memories[0].label, 'preference');
  assert.match(pool.state.memories[0].memory_text, /简洁直接/);
  assert.equal(pool.state.messages.find((item) => item.message_key === 'm1')?.analyzed_at, 1000);

  if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
});

test('saveAndAnalyze marks messages analyzed when llm extraction fails and no memory is stored', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '1';
  const pool = createPool();
  const service = createConversationMemoryService(pool, {
    now: () => 2000,
    llmProviderService: {
      async createChatCompletion() {
        throw new Error('upstream unavailable');
      },
    },
  });

  const result = await service.saveAndAnalyze('session-2', 'user-2', [
    {
      id: 'm3',
      role: 'user',
      content: [{ type: 'text', text: '今天下雨了。' }],
      metadata: { userVisible: true },
    },
  ]);

  assert.equal(result.saved, 1);
  assert.equal(result.memories, 0);
  assert.equal(pool.state.messages.find((item) => item.message_key === 'm3')?.analyzed_at, 2000);

  if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
});

test('saveAndAnalyze uses admin effective env for memory extraction model', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '1';
  const pool = createPool();
  const llmCalls = [];
  const service = createConversationMemoryService(pool, {
    now: () => 2600,
    getEffectiveEnv: async () => ({
      MEMIND_CHAT_ROUTER_MODEL_PROVIDER_KEY_ID: 'router-key',
      MEMIND_CHAT_ROUTER_MODEL: 'deepseek-chat',
    }),
    llmProviderService: {
      async createChatCompletion({ providerKeyId, model, messages }) {
        llmCalls.push({ providerKeyId, model, messages });
        return {
          ok: true,
          reply: JSON.stringify({
            memories: [{ label: 'fact', text: '用户叫 John', confidence: 0.9 }],
          }),
        };
      },
    },
  });

  await service.saveAndAnalyze('session-admin', 'user-admin', [
    {
      id: 'm-admin',
      role: 'user',
      content: [{ type: 'text', text: '我是 John。' }],
    },
  ]);

  assert.equal(llmCalls.length, 1);
  assert.equal(llmCalls[0].providerKeyId, 'router-key');
  assert.equal(llmCalls[0].model, 'deepseek-chat');

  if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
});

test('saveAndAnalyze extracts memories through llmProviderService', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '1';
  const pool = createPool();
  const service = createConversationMemoryService(pool, {
    now: () => 2500,
    llmProviderService: {
      async createChatCompletion({ messages }) {
        assert.match(String(messages?.[0]?.content ?? ''), /长期记忆/);
        return {
          ok: true,
          reply: JSON.stringify({
            memories: [{ label: 'goal', text: '用户计划去日本旅游', confidence: 0.82 }],
          }),
        };
      },
    },
  });

  const result = await service.saveAndAnalyze('session-llm', 'user-llm', [
    {
      id: 'm-japan',
      role: 'user',
      content: [{ type: 'text', text: '我打算带家人去日本玩 5 天。' }],
      metadata: { userVisible: true },
    },
  ]);

  assert.equal(result.memories, 1);
  assert.equal(pool.state.memories[0].label, 'goal');
  assert.match(pool.state.memories[0].memory_text, /日本/);

  if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
});

test('saveAndAnalyze throttles repeated llm extraction warnings', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '1';
  const warnings = [];
  const originalWarn = console.warn;
  console.warn = (...args) => warnings.push(args);
  let currentNow = 4000;
  try {
    const secret = encryptSecret('test-key', 'memory-test-key');
    const pool = createPool({
      provider: {
        api_url: 'https://llm.example.com/v1',
        default_model: 'memory-model',
        api_key_ciphertext: secret.ciphertext,
        api_key_iv: secret.iv,
        api_key_tag: secret.tag,
      },
    });
    const service = createConversationMemoryService(pool, {
      now: () => currentNow,
      encryptionKey: 'memory-test-key',
      llmWarningIntervalMs: 60000,
      fetch: async () => {
        throw new Error('upstream unavailable');
      },
    });

    await service.saveAndAnalyze('session-warn-1', 'user-warn', [
      {
        id: 'warn-1',
        role: 'user',
        content: [{ type: 'text', text: '今天下雨了。' }],
        metadata: { userVisible: true },
      },
    ]);
    currentNow += 1000;
    await service.saveAndAnalyze('session-warn-2', 'user-warn', [
      {
        id: 'warn-2',
        role: 'user',
        content: [{ type: 'text', text: '明天可能也下雨。' }],
        metadata: { userVisible: true },
      },
    ]);
  } finally {
    console.warn = originalWarn;
    if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
    else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
  }

  assert.equal(warnings.length, 1);
  assert.match(String(warnings[0][0]), /conversation-memory/);
});

test('saveAndAnalyze still marks messages analyzed when llm extraction is disabled and fallback stores nothing', async () => {
  const previous = process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = '0';
  const pool = createPool();
  const service = createConversationMemoryService(pool, { now: () => 3000 });

  const result = await service.saveAndAnalyze('session-3', 'user-3', [
    {
      id: 'm4',
      role: 'user',
      content: [{ type: 'text', text: '今天天气不错。' }],
      metadata: { userVisible: true },
    },
  ]);

  assert.equal(result.saved, 1);
  assert.equal(result.memories, 0);
  assert.equal(pool.state.messages.find((item) => item.message_key === 'm4')?.analyzed_at, 3000);

  if (previous == null) delete process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED;
  else process.env.USER_CONVERSATION_MEMORY_LLM_ENABLED = previous;
});