first commit

2026-06-09 14:50:53 +08:00
commit 6aebc60bfd
55 changed files with 3126 additions and 0 deletions
--- a/src/302ai/test.js
+++ b/src/302ai/test.js
@@ -0,0 +1,9 @@
+import { get302AiReply } from './index.js'
+
+// 测试 302 ai api
+async function testMessage() {
+  const message = await get302AiReply('hello')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/302ai/index.js
+++ b/src/302ai/index.js
@@ -0,0 +1,41 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+
+dotenv.config()
+const env = dotenv.config().parsed
+const key = env._302AI_API_KEY
+const model = env._302AI_MODEL ? env._302AI_MODEL : 'gpt-4o-mini'
+
+function setConfig(prompt) {
+  return {
+    method: 'post',
+    url: 'https://api.302.ai/v1/chat/completions',
+    headers: {
+      Accept: 'application/json',
+      Authorization: `Bearer ${key}`,
+      'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+      'Content-Type': 'application/json',
+    },
+    data: JSON.stringify({
+      model: model,
+      messages: [
+        {
+          role: 'user',
+          content: prompt,
+        },
+      ],
+    }),
+  }
+}
+
+export async function get302AiReply(prompt) {
+  try {
+    const config = setConfig(prompt)
+    const response = await axios(config)
+    const { choices } = response.data
+    return choices[0].message.content
+  } catch (error) {
+    console.error(error.code)
+    console.error(error.message)
+  }
+}
--- a/src/adapters/lark.js
+++ b/src/adapters/lark.js
@@ -0,0 +1,79 @@
+import { getLarkRuntimeConfig } from '../config/env.js'
+import { runCommand, streamCommand } from '../utils/process.js'
+
+function getLarkBin() {
+  return getLarkRuntimeConfig().bin
+}
+
+export async function larkLogin(options = {}) {
+  const args = ['auth', 'login']
+
+  if (options.deviceCode) {
+    args.push('--device-code', options.deviceCode)
+  } else if (options.scope) {
+    args.push('--scope', options.scope)
+  } else {
+    args.push('--domain', options.domain || 'im')
+  }
+
+  if (options.noWait || options.wait === false) {
+    args.push('--no-wait', '--json')
+  }
+
+  return streamCommand(getLarkBin(), args)
+}
+
+export async function larkStatus() {
+  return streamCommand(getLarkBin(), ['auth', 'status'])
+}
+
+export async function larkSendText(options = {}) {
+  const identity = options.as || getLarkRuntimeConfig().defaultIdentity
+  const args = ['im', '+messages-send', '--as', identity, '--text', options.text || '']
+
+  if (options.chatId) {
+    args.push('--chat-id', options.chatId)
+  } else if (options.userId) {
+    args.push('--user-id', options.userId)
+  } else {
+    throw new Error('larkSendText requires chatId or userId')
+  }
+
+  return streamCommand(getLarkBin(), args)
+}
+
+export async function larkListMessages(options = {}) {
+  const identity = options.as || getLarkRuntimeConfig().defaultIdentity
+  const args = ['im', '+chat-messages-list', '--as', identity, '--format', options.format || 'pretty']
+
+  if (options.chatId) {
+    args.push('--chat-id', options.chatId)
+  } else if (options.userId) {
+    args.push('--user-id', options.userId)
+  } else {
+    throw new Error('larkListMessages requires chatId or userId')
+  }
+
+  if (options.start) args.push('--start', options.start)
+  if (options.end) args.push('--end', options.end)
+  if (options.pageSize) args.push('--page-size', String(options.pageSize))
+
+  return streamCommand(getLarkBin(), args)
+}
+
+export async function larkSearchMessages(options = {}) {
+  const args = ['im', '+messages-search', '--as', 'user', '--format', options.format || 'pretty']
+  if (options.query) args.push('--query', options.query)
+  if (options.chatId) args.push('--chat-id', options.chatId)
+  if (options.chatType) args.push('--chat-type', options.chatType)
+  if (options.start) args.push('--start', options.start)
+  if (options.end) args.push('--end', options.end)
+  if (options.pageAll) args.push('--page-all')
+  if (options.pageLimit) args.push('--page-limit', String(options.pageLimit))
+
+  return streamCommand(getLarkBin(), args)
+}
+
+export async function larkCheckImAuth() {
+  return runCommand(getLarkBin(), ['auth', 'check', '--domain', 'im'], { echo: true })
+}
--- a/src/adapters/opencli.js
+++ b/src/adapters/opencli.js
@@ -0,0 +1,27 @@
+import { getOpenCliRuntimeConfig } from '../config/env.js'
+import { splitCommand, streamCommand } from '../utils/process.js'
+
+export function resolveOpenCliCommand() {
+  const config = getOpenCliRuntimeConfig()
+  const configured = splitCommand(config.bin)
+  if (configured.length) {
+    return {
+      command: configured[0],
+      args: configured.slice(1),
+    }
+  }
+
+  return {
+    command: 'npx',
+    args: ['--yes', config.npmPackage],
+  }
+}
+
+export async function runOpenCli(args = []) {
+  const base = resolveOpenCliCommand()
+  return streamCommand(base.command, [...base.args, ...args])
+}
+
+export async function runWxCli(args = []) {
+  return runOpenCli(['wx-cli', ...args])
+}
--- a/src/adapters/pi.js
+++ b/src/adapters/pi.js
@@ -0,0 +1,39 @@
+import { getPiRuntimeConfig } from '../config/env.js'
+import { splitCommand, runCommand, streamCommand } from '../utils/process.js'
+
+export function resolvePiCommand() {
+  const config = getPiRuntimeConfig()
+  const configured = splitCommand(config.bin)
+  if (configured.length) {
+    return {
+      command: configured[0],
+      args: configured.slice(1),
+    }
+  }
+
+  return {
+    command: 'npx',
+    args: ['--yes', config.npmPackage],
+  }
+}
+
+export async function runPi(args = []) {
+  const base = resolvePiCommand()
+  return streamCommand(base.command, [...base.args, ...args])
+}
+
+export async function askPi(prompt, options = {}) {
+  const base = resolvePiCommand()
+  const config = getPiRuntimeConfig()
+  const agentArgs = splitCommand(options.agentArgs || config.agentArgs)
+  const result = await runCommand(base.command, [...base.args, ...agentArgs, prompt], {
+    cwd: options.cwd || process.cwd(),
+  })
+
+  if (result.code !== 0) {
+    const detail = result.stderr || result.stdout || `exit code ${result.code}`
+    throw new Error(`pi failed: ${detail}`)
+  }
+
+  return (result.stdout || result.stderr || '').trim()
+}
--- a/src/analysis/test.js
+++ b/src/analysis/test.js
@@ -0,0 +1,56 @@
+import assert from 'assert'
+import fs from 'fs'
+import os from 'os'
+import path from 'path'
+import { analyzeWechatMessages, buildWechatStats } from './wechatAnalyzer.js'
+
+const records = [
+  {
+    timestamp: '2026-05-12T08:00:00.000Z',
+    roomName: '研发群',
+    talkerName: 'Alice',
+    talkerAlias: 'Alice',
+    receiverName: '',
+    text: '今天排查登录问题',
+    typeName: 'Text',
+  },
+  {
+    timestamp: '2026-05-12T09:00:00.000Z',
+    roomName: '研发群',
+    talkerName: 'Bob',
+    talkerAlias: 'Bob',
+    receiverName: '',
+    text: '我来补日志',
+    typeName: 'Text',
+  },
+  {
+    timestamp: '2026-05-12T10:00:00.000Z',
+    roomName: '',
+    talkerName: 'Carol',
+    talkerAlias: 'Carol',
+    receiverName: 'me',
+    text: '周会改到下午',
+    typeName: 'Text',
+  },
+]
+
+const stats = buildWechatStats(records)
+assert.equal(stats.totalMessages, 3)
+assert.equal(stats.textMessages, 3)
+assert.equal(stats.topSpeakers[0].name, 'Alice')
+
+const tmpDir = fs.mkdtempSync(path.join(os.tmpdir(), 'wechat-bot-analysis-'))
+fs.mkdirSync(tmpDir, { recursive: true })
+fs.writeFileSync(path.join(tmpDir, 'messages.jsonl'), records.map((record) => JSON.stringify(record)).join('\n'), 'utf8')
+
+const result = await analyzeWechatMessages({
+  dataDir: tmpDir,
+  room: '研发群',
+  statsOnly: true,
+})
+
+assert.equal(result.target, '群聊「研发群」')
+assert.equal(result.stats.totalMessages, 2)
+assert.equal(result.analysis, '')
+
+console.log('analysis tests passed')
--- a/src/analysis/wechatAnalyzer.js
+++ b/src/analysis/wechatAnalyzer.js
@@ -0,0 +1,95 @@
+import { getServe } from '../wechaty/serve.js'
+import { filterWechatMessages, loadWechatMessages } from '../platforms/wechat/messageStore.js'
+
+function increment(map, key, step = 1) {
+  if (!key) return
+  map.set(key, (map.get(key) || 0) + step)
+}
+
+function topEntries(map, limit = 10) {
+  return [...map.entries()]
+    .sort((a, b) => b[1] - a[1])
+    .slice(0, limit)
+    .map(([name, count]) => ({ name, count }))
+}
+
+export function buildWechatStats(records) {
+  const speakers = new Map()
+  const rooms = new Map()
+  const hourly = new Map()
+  let textMessages = 0
+  let totalTextLength = 0
+
+  for (const record of records) {
+    increment(speakers, record.talkerAlias || record.talkerName || 'unknown')
+    increment(rooms, record.roomName || 'private')
+    if (record.timestamp) {
+      increment(hourly, new Date(record.timestamp).getHours().toString().padStart(2, '0'))
+    }
+    if (record.text) {
+      textMessages += 1
+      totalTextLength += record.text.length
+    }
+  }
+
+  return {
+    totalMessages: records.length,
+    textMessages,
+    averageTextLength: textMessages ? Number((totalTextLength / textMessages).toFixed(1)) : 0,
+    topSpeakers: topEntries(speakers),
+    topRooms: topEntries(rooms),
+    hourly: topEntries(hourly, 24).sort((a, b) => a.name.localeCompare(b.name)),
+  }
+}
+
+export function buildWechatAnalysisPrompt({ records, stats, target }) {
+  const recentMessages = records
+    .slice(-120)
+    .map((record) => {
+      const speaker = record.talkerAlias || record.talkerName || 'unknown'
+      return `[${record.timestamp}] ${speaker}: ${record.text || `[${record.typeName}]`}`
+    })
+    .join('\n')
+
+  return [
+    '你是一个严谨的中文聊天数据分析助手。',
+    '请基于用户显式提供的本地微信聊天记录做分析，不要编造记录之外的事实。',
+    '输出结构：1. 关键统计；2. 主要话题；3. 互动模式；4. 风险或误读提醒；5. 可执行建议。',
+    `分析对象：${target}`,
+    `基础统计：${JSON.stringify(stats, null, 2)}`,
+    '最近消息样本：',
+    recentMessages || '无文本消息样本。',
+  ].join('\n\n')
+}
+
+export async function analyzeWechatMessages(options = {}) {
+  const allRecords = loadWechatMessages({
+    dataDir: options.dataDir,
+    limit: options.limit || 5000,
+  })
+
+  const records = filterWechatMessages(allRecords, {
+    room: options.room,
+    friend: options.friend,
+    query: options.query,
+    start: options.start,
+    end: options.end,
+  })
+
+  const stats = buildWechatStats(records)
+  const target = options.room ? `群聊「${options.room}」` : options.friend ? `好友「${options.friend}」` : '全部本地记录'
+
+  if (options.statsOnly || !records.length) {
+    return {
+      target,
+      stats,
+      analysis: records.length ? '' : '没有匹配到可分析的本地微信消息。',
+    }
+  }
+
+  const getReply = getServe(options.serviceType || 'ChatGPT')
+  const prompt = buildWechatAnalysisPrompt({ records, stats, target })
+  const analysis = await getReply(prompt)
+
+  return { target, stats, analysis }
+}
--- a/src/chatgpt/index.js
+++ b/src/chatgpt/index.js
@@ -0,0 +1,35 @@
+import { ChatGPTAPI } from 'chatgpt'
+import dotenv from 'dotenv'
+
+const env = dotenv.config().parsed // 环境参数
+
+// 定义ChatGPT的配置
+const config = {
+  markdown: true, // 返回的内容是否需要markdown格式
+  AutoReply: true, // 是否自动回复
+  clearanceToken: env.CHATGPT_CLEARANCE, // ChatGPT的clearance，从cookie取值
+  sessionToken: env.CHATGPT_SESSION_TOKEN, // ChatGPT的sessionToken, 从cookie取值
+  userAgent: env.CHATGPT_USER_AGENT, // ChatGPT的user-agent，从浏览器取值,或者替换为与你的真实浏览器的User-Agent相匹配的值
+  accessToken: env.CHATGPT_ACCESS_TOKEN, // 在用户授权情况下，访问https://chat.openai.com/api/auth/session，获取accesstoken
+}
+const api = new ChatGPTAPI(config)
+
+// 获取 chatGPT 的回复
+export async function getChatGPTReply(content) {
+  await api.ensureAuth()
+  console.log('🚀🚀🚀 / content', content)
+  // 调用ChatGPT的接口
+  const reply = await api.sendMessage(content, {
+    //  "ChatGPT 请求超时！最好开下全局代理。"
+    timeoutMs: 2 * 60 * 1000,
+  })
+  console.log('🚀🚀🚀 / reply', reply)
+  return reply
+
+  // // 如果你想要连续语境对话，可以使用下面的代码
+  // const conversation = api.getConversation();
+  // return await conversation.sendMessage(content, {
+  //   //  "ChatGPT 请求超时！最好开下全局代理。"
+  //   timeoutMs: 2 * 60 * 1000,
+  // });
+}
--- a/src/claude/index.js
+++ b/src/claude/index.js
@@ -0,0 +1,72 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+
+dotenv.config()
+const env = dotenv.config().parsed
+
+/**
+ * 用于规整env文件中配置的url到标准格式
+ */
+function normalizeClaudeBaseUrl(url) {
+  if (!url) {
+    return 'https://api.anthropic.com/v1/messages'
+  }
+  
+  let normalizedUrl = url.replace(/\/$/, '')
+  
+  if (normalizedUrl.includes('/v1/messages')) {
+    return normalizedUrl
+  }
+  
+  if (normalizedUrl.includes('/v1') && !normalizedUrl.includes('/messages')) {
+    return `${normalizedUrl}/messages`
+  }
+  
+  if (normalizedUrl.includes('/messages') && !normalizedUrl.includes('/v1')) {
+    return normalizedUrl.replace('/messages', '/v1/messages')
+  }
+  
+  return `${normalizedUrl}/v1/messages`
+}
+
+const key = env.CLAUDE_API_KEY || ''
+const model = env.CLAUDE_MODEL ? env.CLAUDE_MODEL : 'claude-3-5-sonnet-latest'
+const baseUrl = normalizeClaudeBaseUrl(env.CLAUDE_BASE_URL)  
+const system = env.CLAUDE_SYSTEM || ''
+const apiVersion = env.CLAUDE_API_VERSION || '2023-06-01'
+
+function claudeConfig(prompt) {
+  const body = {
+    model: model,
+    temperature: 0.4,
+    max_tokens: 1024,
+    messages: [
+      {
+        role: 'user',
+        content: prompt,
+      },
+    ],
+  }
+  if (system !== '') {
+    body.system = system
+  }
+  return {
+    method: 'post',
+    url: baseUrl,
+    headers: {
+      'x-api-key': key,
+      'anthropic-version': apiVersion,
+      'Content-Type': 'application/json',
+    },
+    data: body,
+  }
+}
+export async function getClaudeReply(prompt) {
+  try {
+    const claude = claudeConfig(prompt)
+    const reply = await axios(claude)
+    return reply.data.content[0].text || ''
+  } catch (error) {
+    console.error(error)
+  }
+}
--- a/src/config/env.js
+++ b/src/config/env.js
@@ -0,0 +1,50 @@
+import dotenv from 'dotenv'
+
+const dotenvResult = dotenv.config()
+
+export const env = {
+  ...(dotenvResult.parsed || {}),
+  ...process.env,
+}
+
+export function readCsvEnv(key) {
+  return (env[key] || '')
+    .split(',')
+    .map((item) => item.trim())
+    .filter(Boolean)
+}
+
+export function getWechatRuntimeConfig() {
+  return {
+    botName: env.BOT_NAME || '',
+    autoReplyPrefix: env.AUTO_REPLY_PREFIX || '',
+    aliasWhiteList: readCsvEnv('ALIAS_WHITELIST'),
+    roomWhiteList: readCsvEnv('ROOM_WHITELIST'),
+    dataDir: env.WECHAT_DATA_DIR || '.data/wechat',
+    storeMessages: env.WECHAT_STORE_MESSAGES !== 'false',
+    commandPrefix: env.BOT_COMMAND_PREFIX || '/',
+    enableRemoteOpenCli: env.ENABLE_REMOTE_OPENCLI === 'true',
+  }
+}
+
+export function getLarkRuntimeConfig() {
+  return {
+    bin: env.LARK_CLI_BIN || 'lark-cli',
+    defaultIdentity: env.LARK_DEFAULT_IDENTITY || 'user',
+  }
+}
+
+export function getOpenCliRuntimeConfig() {
+  return {
+    bin: env.OPENCLI_BIN || '',
+    npmPackage: env.OPENCLI_NPM_PACKAGE || '@jackwener/opencli',
+  }
+}
+
+export function getPiRuntimeConfig() {
+  return {
+    bin: env.PI_BIN || '',
+    npmPackage: env.PI_NPM_PACKAGE || '@earendil-works/pi-coding-agent',
+    agentArgs: env.PI_AGENT_ARGS || '--print --no-session',
+  }
+}
--- a/src/deepseek-free/test.js
+++ b/src/deepseek-free/test.js
@@ -0,0 +1,9 @@
+import { getDeepSeekFreeReply } from './index.js'
+
+// 测试 open ai api
+async function testMessage() {
+  const message = await getDeepSeekFreeReply('hello')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/deepseek-free/index.js
+++ b/src/deepseek-free/index.js
@@ -0,0 +1,49 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+// 加载环境变量
+dotenv.config()
+const env = dotenv.config().parsed // 环境参数
+const token = env.DEEPSEEK_FREE_TOKEN
+const model = env.DEEPSEEK_FREE_MODEL
+const url = env.DEEPSEEK_FREE_URL
+const syscontent = env.DEEPSEEK_FREE_SYSTEM_MESSAGE
+
+function setConfig(prompt) {
+  return {
+    method: 'post',
+    maxBodyLength: Infinity,
+    // url: 'https://api.deepseek.com/chat/completions',
+    url: url,
+    headers: {
+      'Content-Type': 'application/json',
+      Accept: 'application/json',
+      Authorization: `Bearer ${token}`,
+    },
+    data: JSON.stringify({
+      model: model,
+      messages: [
+        {
+          role: 'system',
+          content: syscontent,
+        },
+        {
+          role: 'user',
+          content: prompt,
+        },
+      ],
+      stream: false,
+    }),
+  }
+}
+
+export async function getDeepSeekFreeReply(prompt) {
+  try {
+    const config = setConfig(prompt)
+    const response = await axios(config)
+    const { choices } = response.data
+    return choices[0].message.content
+  } catch (error) {
+    console.error(error.code)
+    console.error(error.message)
+  }
+}
--- a/src/deepseek/test.js
+++ b/src/deepseek/test.js
@@ -0,0 +1,9 @@
+import { getDoubaoReply } from './index.js'
+
+// 测试 open ai api
+async function testMessage() {
+  const message = await getDoubaoReply('猪可以吃钛合金吗')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/deepseek/index.js
+++ b/src/deepseek/index.js
@@ -0,0 +1,36 @@
+import { remark } from 'remark'
+import stripMarkdown from 'strip-markdown'
+import OpenAI from 'openai'
+import dotenv from 'dotenv'
+const env = dotenv.config().parsed // 环境参数
+import fs from 'fs'
+import path from 'path'
+
+const __dirname = path.resolve()
+// 判断是否有 .env 文件, 没有则报错
+const envPath = path.join(__dirname, '.env')
+if (!fs.existsSync(envPath)) {
+  console.log('❌ 请先根据文档，创建并配置.env文件！')
+  process.exit(1)
+}
+
+let config = {
+  apiKey: env.DEEPSEEK_API_KEY,
+}
+if (env.DEEPSEEK_URL) {
+  config.baseURL = env.DEEPSEEK_URL
+}
+const openai = new OpenAI(config)
+const chosen_model = env.DEEPSEEK_MODEL
+export async function getDeepseekReply(prompt) {
+  console.log('🚀🚀🚀 / prompt', prompt)
+  const response = await openai.chat.completions.create({
+    messages: [
+      { role: 'system', content: env.DEEPSEEK_SYSTEM_MESSAGE },
+      { role: 'user', content: prompt },
+    ],
+    model: chosen_model,
+  })
+  console.log('🚀🚀🚀 / reply', response.choices[0].message.content)
+  return `${response.choices[0].message.content}`
+}
--- a/src/dify/test.js
+++ b/src/dify/test.js
@@ -0,0 +1,9 @@
+import { getDifyReply } from './index.js'
+
+// 测试 dify api
+async function testMessage() {
+  const message = await getDifyReply('hello')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/dify/index.js
+++ b/src/dify/index.js
@@ -0,0 +1,39 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+// 加载环境变量
+dotenv.config()
+const env = dotenv.config().parsed // 环境参数
+const token = env.DIFY_API_KEY
+const url = env.DIFY_URL
+const bot_name = env.BOT_NAME
+function setConfig(prompt) {
+  return {
+    method: 'post',
+    url: `${url}/chat-messages`,
+    headers: {
+      'Content-Type': 'application/json',
+      Accept: 'application/json',
+      Authorization: `Bearer ${token}`,
+    },
+    data: JSON.stringify({
+      inputs: {},
+      query: prompt,
+      response_mode: 'blocking',
+      user: bot_name,
+      files: [],
+    }),
+  }
+}
+
+export async function getDifyReply(prompt) {
+  try {
+    const config = setConfig(prompt)
+    console.log('🌸🌸🌸 / config: ', config)
+    const response = await axios(config)
+    console.log('🌸🌸🌸 / response: ', response)
+    return response.data.answer
+  } catch (error) {
+    console.error(error.code)
+    console.error(error.message)
+  }
+}
--- a/src/doubao/test.js
+++ b/src/doubao/test.js
@@ -0,0 +1,12 @@
+import { getDoubaoReply } from './index.js'
+
+// 测试 open ai api
+async function testMessage() {
+  let message
+  message = await getDoubaoReply('猪可以吃钛合金吗')
+  console.log('🌸🌸🌸 / message: ', message)
+  message = await getDoubaoReply('这是哪里？', 'https://ark-project.tos-cn-beijing.ivolces.com/images/view.jpeg')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/doubao/index.js
+++ b/src/doubao/index.js
@@ -0,0 +1,53 @@
+import { remark } from 'remark'
+import stripMarkdown from 'strip-markdown'
+import OpenAI from 'openai'
+import dotenv from 'dotenv'
+const env = dotenv.config().parsed // 环境参数
+import fs from 'fs'
+import path from 'path'
+
+const __dirname = path.resolve()
+// 判断是否有 .env 文件, 没有则报错
+const envPath = path.join(__dirname, '.env')
+if (!fs.existsSync(envPath)) {
+  console.log('❌ 请先根据文档，创建并配置.env文件！')
+  process.exit(1)
+}
+
+let config = {
+  apiKey: env.DOUBAO_API_KEY,
+  baseURL: env.DOUBAO_URL,
+}
+const openai = new OpenAI(config)
+const chosen_model = env.DOUBAO_MODEL
+export async function getDoubaoReply(prompt, img_url = '') {
+  const only_text = img_url == ''
+  console.log('🚀🚀🚀 / prompt', prompt)
+  let response
+  if (only_text) {
+    response = await openai.chat.completions.create({
+      messages: [{ role: 'user', content: [{ type: 'text', text: prompt }] }],
+      model: chosen_model,
+    })
+  } else {
+    response = await openai.chat.completions.create({
+      messages: [
+        {
+          role: 'user',
+          content: [
+            {
+              type: 'image_url',
+              image_url: {
+                url: img_url,
+              },
+            },
+            { type: 'text', text: prompt },
+          ],
+        },
+      ],
+      model: chosen_model,
+    })
+  }
+  console.log('🚀🚀🚀 / reply', response.choices[0].message.content)
+  return `${response.choices[0].message.content}`
+}
--- a/src/index.js
+++ b/src/index.js
@@ -0,0 +1,259 @@
+import { Command } from 'commander'
+import inquirer from 'inquirer'
+import fs from 'fs'
+import path, { dirname } from 'path'
+import { fileURLToPath } from 'url'
+import { env, getWechatRuntimeConfig } from './config/env.js'
+import { analyzeWechatMessages } from './analysis/wechatAnalyzer.js'
+import { larkListMessages, larkLogin, larkSearchMessages, larkSendText, larkStatus } from './adapters/lark.js'
+import { runOpenCli, runWxCli } from './adapters/opencli.js'
+import { runPi } from './adapters/pi.js'
+
+const __filename = fileURLToPath(import.meta.url)
+const __dirname = dirname(__filename)
+const { version, name } = JSON.parse(fs.readFileSync(path.resolve(__dirname, '../package.json'), 'utf8'))
+
+export const serveList = [
+  { name: 'ChatGPT', value: 'ChatGPT' },
+  { name: 'doubao', value: 'doubao' },
+  { name: 'deepseek', value: 'deepseek' },
+  { name: 'Kimi', value: 'Kimi' },
+  { name: 'Xunfei', value: 'Xunfei' },
+  { name: 'deepseek-free', value: 'deepseek-free' },
+  { name: '302AI', value: '302AI' },
+  { name: 'dify', value: 'dify' },
+  { name: 'ollama', value: 'ollama' },
+  { name: 'tongyi', value: 'tongyi' },
+  { name: 'claude', value: 'claude' },
+  { name: 'pi', value: 'pi' },
+]
+
+function getMissingConfig(type) {
+  switch (type) {
+    case 'ChatGPT':
+      return env.OPENAI_API_KEY ? [] : ['OPENAI_API_KEY']
+    case 'doubao':
+      return env.DOUBAO_API_KEY ? [] : ['DOUBAO_API_KEY']
+    case 'deepseek':
+      return env.DEEPSEEK_API_KEY ? [] : ['DEEPSEEK_API_KEY']
+    case 'Kimi':
+      return env.KIMI_API_KEY ? [] : ['KIMI_API_KEY']
+    case 'Xunfei':
+      return env.XUNFEI_APP_ID && env.XUNFEI_API_KEY && env.XUNFEI_API_SECRET ? [] : ['XUNFEI_APP_ID', 'XUNFEI_API_KEY', 'XUNFEI_API_SECRET']
+    case 'deepseek-free':
+      return env.DEEPSEEK_FREE_URL && env.DEEPSEEK_FREE_TOKEN && env.DEEPSEEK_FREE_MODEL
+        ? []
+        : ['DEEPSEEK_FREE_URL', 'DEEPSEEK_FREE_TOKEN', 'DEEPSEEK_FREE_MODEL']
+    case '302AI':
+      return env._302AI_API_KEY ? [] : ['_302AI_API_KEY']
+    case 'dify':
+      return env.DIFY_API_KEY && env.DIFY_URL ? [] : ['DIFY_API_KEY', 'DIFY_URL']
+    case 'ollama':
+      return env.OLLAMA_URL && env.OLLAMA_MODEL ? [] : ['OLLAMA_URL', 'OLLAMA_MODEL']
+    case 'tongyi':
+      return env.TONGYI_URL && env.TONGYI_MODEL ? [] : ['TONGYI_URL', 'TONGYI_MODEL']
+    case 'claude':
+      return env.CLAUDE_API_KEY && env.CLAUDE_MODEL ? [] : ['CLAUDE_API_KEY', 'CLAUDE_MODEL']
+    case 'pi':
+      return []
+    default:
+      return ['SERVICE_TYPE']
+  }
+}
+
+async function startWechat(type) {
+  const serviceType = type || env.SERVICE_TYPE
+  if (!serveList.find((item) => item.value === serviceType)) {
+    console.log('服务类型错误，目前支持：' + serveList.map((item) => item.value).join(' | '))
+    return
+  }
+
+  const missing = getMissingConfig(serviceType)
+  if (missing.length) {
+    console.log(`请先配置 .env 文件中的 ${missing.join('，')}`)
+    return
+  }
+
+  console.log('service type:', serviceType)
+  const { startWechatBot } = await import('./platforms/wechat/bot.js')
+  startWechatBot({ serviceType })
+}
+
+async function promptAndStart() {
+  if (env.SERVICE_TYPE) {
+    await startWechat(env.SERVICE_TYPE)
+    return
+  }
+
+  const answer = await inquirer.prompt([
+    {
+      type: 'list',
+      name: 'serviceType',
+      message: '请先选择服务类型',
+      choices: serveList,
+    },
+  ])
+
+  await startWechat(answer.serviceType)
+}
+
+function printAnalysisResult(result) {
+  console.log(`分析对象：${result.target}`)
+  console.log(JSON.stringify(result.stats, null, 2))
+  if (result.analysis) {
+    console.log('\n分析结果：')
+    console.log(result.analysis)
+  }
+}
+
+const program = new Command(name)
+program.alias('we').description('一个基于 WeChaty 结合 AI 服务实现的微信机器人。').version(version, '-v, --version, -V')
+
+program.option('-s, --serve <type>', '跳过交互，直接设置启动的服务类型').action(async () => {
+  const { serve } = program.opts()
+  if (serve) {
+    await startWechat(serve)
+    return
+  }
+  await promptAndStart()
+})
+
+program
+  .command('start')
+  .description('启动微信 IM，终端展示二维码扫码登录')
+  .option('-s, --serve <type>', '跳过交互，直接设置启动的服务类型')
+  .action(async (options) => {
+    if (options.serve) {
+      await startWechat(options.serve)
+      return
+    }
+    await promptAndStart()
+  })
+
+program
+  .command('agent')
+  .description('启动外部 IM 通道，并使用指定 agent 处理消息')
+  .option('--im <channel>', '外部通信渠道：wechat', 'wechat')
+  .option('--agent <agent>', '消息处理 agent：pi 或其他 serve 类型', 'pi')
+  .action(async (options) => {
+    if (options.im !== 'wechat') {
+      console.log('当前 agent 命令只支持 --im wechat。飞书可先使用 wb lark login/send/messages/search。')
+      return
+    }
+
+    await startWechat(options.agent)
+  })
+
+program
+  .command('analyze')
+  .description('分析本地捕获的微信聊天记录')
+  .option('--room <name>', '按群聊名称分析')
+  .option('--friend <name>', '按好友昵称或备注分析')
+  .option('--query <keyword>', '只分析包含关键词的消息')
+  .option('--start <iso>', '开始时间 ISO 8601')
+  .option('--end <iso>', '结束时间 ISO 8601')
+  .option('--limit <number>', '最多读取最近 N 条本地消息', '5000')
+  .option('-s, --serve <type>', '用于生成深度分析的 AI 服务', env.SERVICE_TYPE || 'ChatGPT')
+  .option('--stats-only', '只输出统计，不调用 AI 服务')
+  .action(async (options) => {
+    const config = getWechatRuntimeConfig()
+    const result = await analyzeWechatMessages({
+      ...options,
+      serviceType: options.serve,
+      dataDir: config.dataDir,
+      limit: Number(options.limit),
+    })
+    printAnalysisResult(result)
+  })
+
+const lark = program.command('lark').description('飞书 IM 登录、发消息和读取消息')
+
+lark
+  .command('login')
+  .description('使用 lark-cli device flow 登录飞书 IM')
+  .option('--scope <scope>', '指定 scope，例：im:message:readonly')
+  .option('--domain <domain>', '按 domain 授权', 'im')
+  .option('--no-wait', '只生成授权链接/扫码信息，不阻塞等待授权完成')
+  .option('--device-code <code>', '继续完成上一次 --no-wait 返回的 device_code')
+  .action(async (options) => {
+    await larkLogin(options)
+  })
+
+lark
+  .command('status')
+  .description('查看当前飞书授权状态')
+  .action(async () => {
+    await larkStatus()
+  })
+
+lark
+  .command('send')
+  .description('发送飞书 IM 文本消息')
+  .option('--as <identity>', 'user 或 bot', 'user')
+  .option('--chat-id <chatId>', '群聊 ID，oc_xxx')
+  .option('--user-id <userId>', '用户 open_id，ou_xxx')
+  .requiredOption('--text <text>', '文本内容')
+  .action(async (options) => {
+    await larkSendText(options)
+  })
+
+lark
+  .command('messages')
+  .description('读取某个飞书群聊或 P2P 会话消息')
+  .option('--as <identity>', 'user 或 bot', 'user')
+  .option('--chat-id <chatId>', '群聊 ID，oc_xxx')
+  .option('--user-id <userId>', '用户 open_id，ou_xxx')
+  .option('--start <iso>', '开始时间 ISO 8601')
+  .option('--end <iso>', '结束时间 ISO 8601')
+  .option('--page-size <number>', '分页大小', '50')
+  .option('--format <format>', 'json | pretty | table | ndjson | csv', 'pretty')
+  .action(async (options) => {
+    await larkListMessages(options)
+  })
+
+lark
+  .command('search')
+  .description('搜索飞书 IM 消息')
+  .option('--query <keyword>', '搜索关键词')
+  .option('--chat-id <chatId>', '限制群聊 ID')
+  .option('--chat-type <type>', 'group 或 p2p')
+  .option('--start <iso>', '开始时间 ISO 8601')
+  .option('--end <iso>', '结束时间 ISO 8601')
+  .option('--page-all', '自动翻页')
+  .option('--page-limit <number>', '最多翻页数', '20')
+  .option('--format <format>', 'json | pretty | table | ndjson | csv', 'pretty')
+  .action(async (options) => {
+    await larkSearchMessages(options)
+  })
+
+program
+  .command('opencli')
+  .description('透传调用 OpenCLI，用于本地微信、朋友圈或其他本机工具')
+  .allowUnknownOption(true)
+  .argument('[args...]')
+  .action(async (args) => {
+    await runOpenCli(args)
+  })
+
+program
+  .command('wx')
+  .description('通过 OpenCLI wx-cli 访问本地微信聊天、联系人、群成员和朋友圈缓存')
+  .allowUnknownOption(true)
+  .argument('[args...]')
+  .action(async (args) => {
+    await runWxCli(args)
+  })
+
+program
+  .command('pi')
+  .description('透传调用 Pi coding agent')
+  .allowUnknownOption(true)
+  .argument('[args...]')
+  .action(async (args) => {
+    await runPi(args)
+  })
+
+program.parseAsync().catch((error) => {
+  console.error(error.message)
+  process.exitCode = 1
+})
--- a/src/kimi/test.js
+++ b/src/kimi/test.js
@@ -0,0 +1,8 @@
+import { getKimiReply } from './index.js'
+
+// 测试 open ai api
+async function test() {
+  const message = await getKimiReply('你好!')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+test()
--- a/src/kimi/index.js
+++ b/src/kimi/index.js
@@ -0,0 +1,94 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+const env = dotenv.config().parsed // 环境参数
+
+const domain = 'https://api.moonshot.cn'
+const server = {
+  chat: `${domain}/v1/chat/completions`,
+  models: `${domain}/v1/models`,
+  files: `${domain}/v1/files`,
+  token: `${domain}/v1/tokenizers/estimate-token-count`,
+  // 这块还可以实现上传文件让 kimi 读取并交互等操作
+  // 具体参考文档： https://platform.moonshot.cn/docs/api-reference#api-%E8%AF%B4%E6%98%8E
+  // 由于我近期非常忙碌，这块欢迎感兴趣的同学提 PR ，我会很快合并
+}
+
+const configuration = {
+  // 参数详情请参考 https://platform.moonshot.cn/docs/api-reference#%E5%AD%97%E6%AE%B5%E8%AF%B4%E6%98%8E
+  /* 
+    Model ID, 可以通过 List Models 获取
+    目前可选 moonshot-v1-8k | moonshot-v1-32k | moonshot-v1-128k
+  */
+  model: 'moonshot-v1-8k',
+  /* 
+    使用什么采样温度，介于 0 和 1 之间。较高的值（如 0.7）将使输出更加随机，而较低的值（如 0.2）将使其更加集中和确定性。
+    如果设置，值域须为 [0, 1] 我们推荐 0.3，以达到较合适的效果。
+  */
+  temperature: 0.3,
+  /* 
+    聊天完成时生成的最大 token 数。如果到生成了最大 token 数个结果仍然没有结束，finish reason 会是 "length", 否则会是 "stop"
+    这个值建议按需给个合理的值，如果不给的话，我们会给一个不错的整数比如 1024。特别要注意的是，这个 max_tokens 是指您期待我们返回的 token 长度，而不是输入 + 输出的总长度。
+    比如对一个 moonshot-v1-8k 模型，它的最大输入 + 输出总长度是 8192，当输入 messages 总长度为 4096 的时候，您最多只能设置为 4096，
+    否则我们服务会返回不合法的输入参数（ invalid_request_error ），并拒绝回答。如果您希望获得“输入的精确 token 数”，可以使用下面的“计算 Token” API 使用我们的计算器获得计数。
+  */
+  max_tokens: 5000,
+  /* 
+    是否流式返回, 默认 false, 可选 true
+  */
+  stream: true,
+}
+
+export async function getKimiReply(prompt) {
+  try {
+    const res = await axios.post(
+      server.chat,
+      Object.assign(configuration, {
+        /* 
+        包含迄今为止对话的消息列表。
+        要保持对话的上下文，需要将之前的对话历史并入到该数组
+        这是一个结构体的列表，每个元素类似如下：{"role": "user", "content": "你好"} role 只支持 system,user,assistant 其一，content 不得为空
+      */
+        messages: [
+          {
+            role: 'user',
+            content: prompt,
+          },
+        ],
+        model: 'moonshot-v1-128k',
+      }),
+      {
+        timeout: 120000,
+        headers: {
+          'Content-Type': 'application/json',
+          Authorization: `Bearer ${env.KIMI_API_KEY}`,
+        },
+        // pass a http proxy agent
+        // proxy: {
+        //   host: 'localhost',
+        //   port: 7890,
+        // }
+      },
+    )
+    if (!configuration.stream) return res.data.choices[0].message.content
+
+    let result = ''
+    const lines = res.data.split('\n').filter((line) => line.trim() !== '')
+    for (const line of lines) {
+      if (line.startsWith('data: ')) {
+        const messageObj = line.substring(6)
+        if (messageObj === '[DONE]') break
+        const message = JSON.parse(messageObj)
+        if (message.choices && message.choices[0].delta && message.choices[0].delta.content) {
+          result += message.choices[0].delta.content
+        }
+      }
+    }
+    return result
+  } catch (error) {
+    console.log('Kimi 错误对应详情可参考官网： https://platform.moonshot.cn/docs/api-reference#%E9%94%99%E8%AF%AF%E8%AF%B4%E6%98%8E')
+    console.log('常见的 401 一般意味着你鉴权失败, 请检查你的 API_KEY 是否正确。')
+    console.log('常见的 429 一般意味着你被限制了请求频次，请求频率过高，或 kimi 服务器过载，可以适当调整请求频率，或者等待一段时间再试。')
+    console.error(error.code)
+    console.error(error.message)
+  }
+}
--- a/src/ollama/test.js
+++ b/src/ollama/test.js
@@ -0,0 +1,9 @@
+import { getDifyReply } from './index.js'
+
+// 测试 dify api
+async function testMessage() {
+  const message = await getDifyReply('hello')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/ollama/index.js
+++ b/src/ollama/index.js
@@ -0,0 +1,45 @@
+import axios from 'axios'
+import dotenv from 'dotenv'
+// 加载环境变量
+dotenv.config()
+const env = dotenv.config().parsed // 环境参数
+const url = env.OLLAMA_URL
+const bot_name = env.BOT_NAME
+const model_name = env.OLLAMA_MODEL
+function createRequest(prompt) {
+  return {
+    method: 'post',
+    url: url,
+    headers: {
+      'Content-Type': 'application/json',
+      Accept: 'application/json',
+    },
+    data: JSON.stringify({
+      model: model_name,
+      messages: [
+        {
+          role: 'system',
+          content: env.OLLAMA_SYSTEM_MESSAGE,
+        },
+        {
+          role: 'user',
+          content: prompt,
+        },
+      ],
+      stream: false,
+    }),
+  }
+}
+
+export async function getOllamaReply(prompt) {
+  try {
+    console.log('=============== ollama request start ======================')
+    const request = createRequest(prompt)
+    const res = await axios(request)
+    console.log('=============== ollama request finished ======================')
+    return res.data.message.content
+  } catch (error) {
+    console.error(error.code)
+    console.error(error.message)
+  }
+}
--- a/src/openai/test.js
+++ b/src/openai/test.js
@@ -0,0 +1,9 @@
+import { getGptReply } from './index.js'
+
+// 测试 open ai api
+async function testMessage() {
+  const message = await getGptReply('hello')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/openai/index.js
+++ b/src/openai/index.js
@@ -0,0 +1,37 @@
+import { remark } from 'remark'
+import stripMarkdown from 'strip-markdown'
+import OpenAIApi from 'openai'
+import dotenv from 'dotenv'
+const env = dotenv.config().parsed // 环境参数
+import fs from 'fs'
+import path from 'path'
+
+const __dirname = path.resolve()
+// 判断是否有 .env 文件, 没有则报错
+const envPath = path.join(__dirname, '.env')
+if (!fs.existsSync(envPath)) {
+  console.log('❌ 请先根据文档，创建并配置.env文件！')
+  process.exit(1)
+}
+
+let config = {
+  apiKey: env.OPENAI_API_KEY,
+  organization: '',
+}
+if (env.OPENAI_PROXY_URL) {
+  config.baseURL = env.OPENAI_PROXY_URL
+}
+const openai = new OpenAIApi(config)
+const chosen_model = env.OPENAI_MODEL || 'gpt-4o'
+export async function getGptReply(prompt) {
+  console.log('🚀🚀🚀 / prompt', prompt)
+  const response = await openai.chat.completions.create({
+    messages: [
+      { role: 'system', content: env.OPENAI_SYSTEM_MESSAGE },
+      { role: 'user', content: prompt },
+    ],
+    model: chosen_model,
+  })
+  console.log('🚀🚀🚀 / reply', response.choices[0].message.content)
+  return `${response.choices[0].message.content}`
+}
--- a/src/pi/index.js
+++ b/src/pi/index.js
@@ -0,0 +1,13 @@
+import { askPi } from '../adapters/pi.js'
+
+export async function getPiReply(prompt) {
+  const agentPrompt = [
+    '你是当前 wechat-bot 项目的 Pi agent，通过 IM 渠道和外部用户沟通。',
+    '请直接回答用户问题；如果需要访问本地微信聊天、朋友圈、群成员或统计数据，优先建议或使用项目中的 wb wx / wb analyze 能力。',
+    '不要编造本地数据；没有读取到数据时要明确说明。',
+    '',
+    `用户消息：${prompt}`,
+  ].join('\n')
+
+  return askPi(agentPrompt)
+}
--- a/src/platforms/wechat/bot.js
+++ b/src/platforms/wechat/bot.js
@@ -0,0 +1,75 @@
+import { WechatyBuilder, ScanStatus, log } from 'wechaty'
+import qrTerminal from 'qrcode-terminal'
+import { defaultMessage } from '../../wechaty/sendMessage.js'
+import { captureWechatMessage } from './messageStore.js'
+import { getWechatRuntimeConfig } from '../../config/env.js'
+
+function onScan(qrcode, status) {
+  if (status === ScanStatus.Waiting || status === ScanStatus.Timeout) {
+    qrTerminal.generate(qrcode, { small: true })
+    const qrcodeImageUrl = ['https://api.qrserver.com/v1/create-qr-code/?data=', encodeURIComponent(qrcode)].join('')
+    console.log('onScan:', qrcodeImageUrl, ScanStatus[status], status)
+  } else {
+    log.info('onScan: %s(%s)', ScanStatus[status], status)
+  }
+}
+
+function onLogin(user) {
+  console.log(`${user} has logged in`)
+  const date = new Date()
+  console.log(`Current time:${date}`)
+  console.log('Automatic robot chat mode has been activated')
+}
+
+function onLogout(user) {
+  console.log(`${user} has logged out`)
+}
+
+async function onFriendShip(friendship) {
+  const friendShipRe = /chatgpt|chat/
+  if (friendship.type() === 2 && friendShipRe.test(friendship.hello())) {
+    await friendship.accept()
+  }
+}
+
+export function createWechatBot(options = {}) {
+  const config = getWechatRuntimeConfig()
+  const chromeBin = process.env.CHROME_BIN ? { endpoint: process.env.CHROME_BIN } : {}
+  const serviceType = options.serviceType || ''
+
+  const bot = WechatyBuilder.build({
+    name: 'WechatEveryDay',
+    puppet: 'wechaty-puppet-wechat4u',
+    puppetOptions: {
+      uos: true,
+      ...chromeBin,
+    },
+  })
+
+  bot.on('scan', onScan)
+  bot.on('login', onLogin)
+  bot.on('logout', onLogout)
+  bot.on('friendship', onFriendShip)
+  bot.on('message', async (message) => {
+    await captureWechatMessage(message, bot, {
+      dataDir: config.dataDir,
+      storeMessages: config.storeMessages,
+    })
+    await defaultMessage(message, bot, serviceType)
+  })
+  bot.on('error', (error) => {
+    console.error('bot error handle: ', error)
+  })
+
+  return bot
+}
+
+export function startWechatBot(options = {}) {
+  const bot = createWechatBot(options)
+  bot
+    .start()
+    .then(() => console.log('Start to log in wechat...'))
+    .catch((error) => console.error('botStart error: ', error))
+
+  return bot
+}
--- a/src/platforms/wechat/commandRouter.js
+++ b/src/platforms/wechat/commandRouter.js
@@ -0,0 +1,81 @@
+import { analyzeWechatMessages } from '../../analysis/wechatAnalyzer.js'
+import { getWechatRuntimeConfig } from '../../config/env.js'
+import { runOpenCli } from '../../adapters/opencli.js'
+
+function stripMention(content, botName) {
+  return content.replace(botName, '').trim()
+}
+
+function parseTarget(tokens) {
+  const type = tokens[1]
+  const value = tokens.slice(2).join(' ').trim()
+
+  if (['群', '群聊', 'room', 'group'].includes(type)) {
+    return { room: value }
+  }
+
+  if (['好友', 'friend', 'contact'].includes(type)) {
+    return { friend: value }
+  }
+
+  return {}
+}
+
+export async function handleWechatCommand(content, context = {}) {
+  const config = getWechatRuntimeConfig()
+  const normalized = stripMention(content, config.botName)
+
+  if (!normalized.startsWith(config.commandPrefix)) {
+    return { handled: false }
+  }
+
+  const commandLine = normalized.slice(config.commandPrefix.length).trim()
+  const tokens = commandLine.split(/\s+/).filter(Boolean)
+  const command = tokens[0]
+
+  if (['分析', 'analyze', '统计', 'stats'].includes(command)) {
+    const statsOnly = ['统计', 'stats'].includes(command)
+    const target = parseTarget(tokens)
+    const result = await analyzeWechatMessages({
+      ...target,
+      serviceType: context.serviceType,
+      dataDir: config.dataDir,
+      statsOnly,
+    })
+
+    if (statsOnly || !result.analysis) {
+      return {
+        handled: true,
+        reply: [
+          `${result.target}`,
+          `消息数：${result.stats.totalMessages}`,
+          `文本消息：${result.stats.textMessages}`,
+          `平均长度：${result.stats.averageTextLength}`,
+          `高频发言：${result.stats.topSpeakers.map((item) => `${item.name}(${item.count})`).join('，') || '无'}`,
+        ].join('\n'),
+      }
+    }
+
+    return {
+      handled: true,
+      reply: result.analysis,
+    }
+  }
+
+  if (command === 'opencli') {
+    if (!config.enableRemoteOpenCli) {
+      return {
+        handled: true,
+        reply: '远程 OpenCLI 执行未开启。需要在 .env 中显式设置 ENABLE_REMOTE_OPENCLI=true。',
+      }
+    }
+
+    await runOpenCli(tokens.slice(1))
+    return {
+      handled: true,
+      reply: 'OpenCLI 命令已执行，结果请看本机控制台。',
+    }
+  }
+
+  return { handled: false }
+}
--- a/src/platforms/wechat/messageStore.js
+++ b/src/platforms/wechat/messageStore.js
@@ -0,0 +1,96 @@
+import fs from 'fs'
+import path from 'path'
+
+const MESSAGE_FILE = 'messages.jsonl'
+
+function ensureDir(dir) {
+  fs.mkdirSync(dir, { recursive: true })
+}
+
+export function getMessageStorePath(dataDir = '.data/wechat') {
+  return path.resolve(process.cwd(), dataDir, MESSAGE_FILE)
+}
+
+export async function captureWechatMessage(message, bot, options = {}) {
+  const dataDir = options.dataDir || '.data/wechat'
+  const storeMessages = options.storeMessages !== false
+  if (!storeMessages) return null
+
+  const talker = message.talker()
+  const receiver = message.to()
+  const room = message.room()
+  const isText = message.type() === bot.Message.Type.Text
+  const roomName = room ? await room.topic() : ''
+  const talkerAlias = talker ? await talker.alias() : ''
+  const talkerName = talker ? await talker.name() : ''
+  const receiverName = receiver ? await receiver.name() : ''
+
+  const record = {
+    id: message.id,
+    timestamp: new Date().toISOString(),
+    type: message.type(),
+    typeName: bot.Message.Type[message.type()] || String(message.type()),
+    isText,
+    isRoom: Boolean(room),
+    roomName,
+    talkerName,
+    talkerAlias,
+    receiverName,
+    text: isText ? message.text() : '',
+    self: Boolean(talker?.self?.()),
+  }
+
+  const storePath = getMessageStorePath(dataDir)
+  ensureDir(path.dirname(storePath))
+  fs.appendFileSync(storePath, `${JSON.stringify(record)}\n`, 'utf8')
+
+  return record
+}
+
+export function loadWechatMessages(options = {}) {
+  const storePath = getMessageStorePath(options.dataDir)
+  if (!fs.existsSync(storePath)) return []
+
+  const lines = fs
+    .readFileSync(storePath, 'utf8')
+    .split('\n')
+    .map((line) => line.trim())
+    .filter(Boolean)
+
+  const limit = Number(options.limit || 0)
+  const selectedLines = limit > 0 ? lines.slice(-limit) : lines
+
+  return selectedLines
+    .map((line) => {
+      try {
+        return JSON.parse(line)
+      } catch (error) {
+        return null
+      }
+    })
+    .filter(Boolean)
+}
+
+export function filterWechatMessages(records, filters = {}) {
+  const startTime = filters.start ? new Date(filters.start).getTime() : null
+  const endTime = filters.end ? new Date(filters.end).getTime() : null
+  const query = filters.query ? filters.query.toLowerCase() : ''
+
+  return records.filter((record) => {
+    if (filters.room && record.roomName !== filters.room) return false
+    if (filters.friend) {
+      const names = [record.talkerName, record.talkerAlias, record.receiverName].filter(Boolean)
+      if (!names.includes(filters.friend)) return false
+    }
+    if (
+      query &&
+      !String(record.text || '')
+        .toLowerCase()
+        .includes(query)
+    )
+      return false
+    if (startTime && new Date(record.timestamp).getTime() < startTime) return false
+    if (endTime && new Date(record.timestamp).getTime() > endTime) return false
+    return true
+  })
+}
--- a/src/tongyi/index.js
+++ b/src/tongyi/index.js
@@ -0,0 +1,42 @@
+import fs from 'fs'
+import path from 'path'
+import dotenv from 'dotenv'
+import OpenAI from 'openai'
+
+const env = dotenv.config().parsed // 环境参数
+// 加载环境变量
+dotenv.config()
+const url = env.TONGYI_URL
+const api_key = env.TONGYI_API_KEY
+const model_name = env.TONGYI_MODEL || 'qwen-plus'
+
+const openai = new OpenAI({
+  apiKey: api_key,
+  baseURL: url,
+  temperature: 0,
+})
+
+const __dirname = path.resolve()
+// 判断是否有 .env 文件, 没有则报错
+const envPath = path.join(__dirname, '.env')
+if (!fs.existsSync(envPath)) {
+  console.log('❌ 请先根据文档，创建并配置 .env 文件！')
+  process.exit(1)
+}
+
+export async function getTongyiReply(prompt) {
+  const completion = await openai.chat.completions.create({
+    messages: [
+      {
+        role: 'user',
+        content: prompt + ' ,用中文回答',
+      },
+    ],
+    model: model_name,
+  })
+
+  console.log('🚀🚀🚀 / prompt', prompt)
+  const Content = await completion.choices[0].message.content
+  console.log('🚀🚀🚀 / reply', Content)
+  return `${Content}`
+}
--- a/src/utils/process.js
+++ b/src/utils/process.js
@@ -0,0 +1,53 @@
+import { spawn } from 'child_process'
+
+export function splitCommand(command) {
+  if (!command) return []
+  return command.match(/(?:[^\s"']+|"[^"]*"|'[^']*')+/g)?.map((part) => part.replace(/^["']|["']$/g, '')) || []
+}
+
+export function runCommand(command, args = [], options = {}) {
+  return new Promise((resolve, reject) => {
+    const child = spawn(command, args, {
+      cwd: options.cwd || process.cwd(),
+      env: options.env || process.env,
+      stdio: options.stdio || ['ignore', 'pipe', 'pipe'],
+    })
+
+    let stdout = ''
+    let stderr = ''
+
+    if (child.stdout) {
+      child.stdout.on('data', (chunk) => {
+        stdout += chunk.toString()
+        if (options.echo) process.stdout.write(chunk)
+      })
+    }
+
+    if (child.stderr) {
+      child.stderr.on('data', (chunk) => {
+        stderr += chunk.toString()
+        if (options.echo) process.stderr.write(chunk)
+      })
+    }
+
+    child.on('error', reject)
+    child.on('close', (code) => {
+      resolve({ code, stdout, stderr })
+    })
+  })
+}
+
+export async function streamCommand(command, args = [], options = {}) {
+  const result = await runCommand(command, args, {
+    ...options,
+    stdio: options.stdio || 'inherit',
+  })
+
+  if (result.code !== 0) {
+    const error = new Error(`${command} exited with code ${result.code}`)
+    error.result = result
+    throw error
+  }
+
+  return result
+}
--- a/src/wechaty/sendMessage.js
+++ b/src/wechaty/sendMessage.js
@@ -0,0 +1,136 @@
+import { getServe } from './serve.js'
+import { getWechatRuntimeConfig } from '../config/env.js'
+import { handleWechatCommand } from '../platforms/wechat/commandRouter.js'
+
+/**
+ * 默认消息发送
+ * @param msg
+ * @param bot
+ * @param ServiceType 服务类型 'GPT' | 'Kimi'
+ * @returns {Promise<void>}
+ */
+export async function defaultMessage(msg, bot, ServiceType = 'GPT') {
+  const { botName, autoReplyPrefix, aliasWhiteList, roomWhiteList, commandPrefix } = getWechatRuntimeConfig()
+  console.log({ botName, autoReplyPrefix, aliasWhiteList, roomWhiteList, commandPrefix })
+  const getReply = getServe(ServiceType)
+  const contact = msg.talker() // 发消息人
+  const receiver = msg.to() // 消息接收人
+  const content = msg.text() // 消息内容
+  const room = msg.room() // 是否是群消息
+  const roomName = (await room?.topic()) || null // 群名称
+  const alias = (await contact.alias()) || (await contact.name()) // 发消息人昵称
+  const remarkName = await contact.alias() // 备注名称
+  const name = await contact.name() // 微信名称
+  const isText = msg.type() === bot.Message.Type.Text // 消息类型是否为文本
+  const isRoom = roomWhiteList.includes(roomName) && content.includes(`${botName}`) // 是否在群聊白名单内并且艾特了机器人
+  const isAlias = aliasWhiteList.includes(remarkName) || aliasWhiteList.includes(name) // 发消息的人是否在联系人白名单内
+  const isBotSelf = botName === `@${remarkName}` || botName === `@${name}` // 是否是机器人自己
+  const isBotSelfDebug = content.trimStart().startsWith('你是谁') // 是否是机器人自己的调试消息
+  const isAuthorizedCommand = (room && isRoom) || (!room && isAlias)
+  // TODO 你们可以根据自己的需求修改这里的逻辑
+  if ((isBotSelf && !isBotSelfDebug) || !isText) return // 如果是机器人自己发送的消息或者消息类型不是文本则不处理
+  try {
+    if (content.replace(`${botName}`, '').trimStart().startsWith(commandPrefix)) {
+      if (!isAuthorizedCommand) return
+      const commandResult = await handleWechatCommand(content, {
+        serviceType: ServiceType,
+        roomName,
+        alias,
+        name,
+      })
+      if (commandResult.handled) {
+        if (commandResult.reply) {
+          await (room || contact).say(commandResult.reply)
+        }
+        return
+      }
+    }
+
+    // 区分群聊和私聊
+    // 群聊消息去掉艾特主体后，匹配自动回复前缀
+    if (isRoom && room && content.replace(`${botName}`, '').trimStart().startsWith(`${autoReplyPrefix}`)) {
+      const question = (await msg.mentionText()) || content.replace(`${botName}`, '').replace(`${autoReplyPrefix}`, '') // 去掉艾特的消息主体
+      console.log('🌸🌸🌸 / question: ', question)
+      const response = await getReply(question)
+      await room.say(response)
+    }
+    // 私人聊天，白名单内的直接发送
+    // 私人聊天直接匹配自动回复前缀
+    if (isAlias && !room && content.trimStart().startsWith(`${autoReplyPrefix}`)) {
+      const question = content.replace(`${autoReplyPrefix}`, '')
+      console.log('🌸🌸🌸 / content: ', question)
+      const response = await getReply(question)
+      await contact.say(response)
+    }
+  } catch (e) {
+    console.error(e)
+  }
+}
+
+/**
+ * 分片消息发送
+ * @param message
+ * @param bot
+ * @returns {Promise<void>}
+ */
+export async function shardingMessage(message, bot) {
+  const talker = message.talker()
+  const isText = message.type() === bot.Message.Type.Text // 消息类型是否为文本
+  if (talker.self() || message.type() > 10 || (talker.name() === '微信团队' && isText)) {
+    return
+  }
+  const text = message.text()
+  const room = message.room()
+  if (!room) {
+    console.log(`Chat GPT Enabled User: ${talker.name()}`)
+    const response = await getChatGPTReply(text)
+    await trySay(talker, response)
+    return
+  }
+  let realText = splitMessage(text)
+  // 如果是群聊但不是指定艾特人那么就不进行发送消息
+  if (text.indexOf(`${botName}`) === -1) {
+    return
+  }
+  realText = text.replace(`${botName}`, '')
+  const topic = await room.topic()
+  const response = await getChatGPTReply(realText)
+  const result = `${realText}\n ---------------- \n ${response}`
+  await trySay(room, result)
+}
+
+// 分片长度
+const SINGLE_MESSAGE_MAX_SIZE = 500
+
+/**
+ * 发送
+ * @param talker 发送哪个  room为群聊类 text为单人
+ * @param msg
+ * @returns {Promise<void>}
+ */
+async function trySay(talker, msg) {
+  const messages = []
+  let message = msg
+  while (message.length > SINGLE_MESSAGE_MAX_SIZE) {
+    messages.push(message.slice(0, SINGLE_MESSAGE_MAX_SIZE))
+    message = message.slice(SINGLE_MESSAGE_MAX_SIZE)
+  }
+  messages.push(message)
+  for (const msg of messages) {
+    await talker.say(msg)
+  }
+}
+
+/**
+ * 分组消息
+ * @param text
+ * @returns {Promise<*>}
+ */
+async function splitMessage(text) {
+  let realText = text
+  const item = text.split('- - - - - - - - - - - - - - -')
+  if (item.length > 1) {
+    realText = item[item.length - 1]
+  }
+  return realText
+}
--- a/src/wechaty/serve.js
+++ b/src/wechaty/serve.js
@@ -0,0 +1,42 @@
+function lazyServe(loader, exportName) {
+  return async (...args) => {
+    const module = await loader()
+    return module[exportName](...args)
+  }
+}
+
+/**
+ * 获取 AI 服务
+ * @param serviceType 服务类型
+ * @returns {Function}
+ */
+export function getServe(serviceType) {
+  switch (serviceType) {
+    case 'ChatGPT':
+      return lazyServe(() => import('../openai/index.js'), 'getGptReply')
+    case 'doubao':
+      return lazyServe(() => import('../doubao/index.js'), 'getDoubaoReply')
+    case 'deepseek':
+      return lazyServe(() => import('../deepseek/index.js'), 'getDeepseekReply')
+    case 'Kimi':
+      return lazyServe(() => import('../kimi/index.js'), 'getKimiReply')
+    case 'Xunfei':
+      return lazyServe(() => import('../xunfei/index.js'), 'getXunfeiReply')
+    case 'deepseek-free':
+      return lazyServe(() => import('../deepseek-free/index.js'), 'getDeepSeekFreeReply')
+    case '302AI':
+      return lazyServe(() => import('../302ai/index.js'), 'get302AiReply')
+    case 'dify':
+      return lazyServe(() => import('../dify/index.js'), 'getDifyReply')
+    case 'ollama':
+      return lazyServe(() => import('../ollama/index.js'), 'getOllamaReply')
+    case 'tongyi':
+      return lazyServe(() => import('../tongyi/index.js'), 'getTongyiReply')
+    case 'claude':
+      return lazyServe(() => import('../claude/index.js'), 'getClaudeReply')
+    case 'pi':
+      return lazyServe(() => import('../pi/index.js'), 'getPiReply')
+    default:
+      return lazyServe(() => import('../openai/index.js'), 'getGptReply')
+  }
+}
--- a/src/wechaty/testMessage.js
+++ b/src/wechaty/testMessage.js
@@ -0,0 +1,105 @@
+import { getGptReply } from '../openai/index.js'
+import { getKimiReply } from '../kimi/index.js'
+import { getXunfeiReply } from '../xunfei/index.js'
+import dotenv from 'dotenv'
+import inquirer from 'inquirer'
+import { getDeepSeekFreeReply } from '../deepseek-free/index.js'
+import { get302AiReply } from '../302ai/index.js'
+import { getDifyReply } from '../dify/index.js'
+import { getOllamaReply } from '../ollama/index.js'
+const env = dotenv.config().parsed // 环境参数
+
+// 控制启动
+async function handleRequest(type) {
+  console.log('type: ', type)
+  switch (type) {
+    case 'ChatGPT':
+      if (env.OPENAI_API_KEY) {
+        const message = await getGptReply('hello')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 OPENAI_API_KEY')
+      break
+    case 'Kimi':
+      if (env.KIMI_API_KEY) {
+        const message = await getKimiReply('你好!')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 KIMI_API_KEY')
+      break
+    case 'Xunfei':
+      if (env.XUNFEI_APP_ID && env.XUNFEI_API_KEY && env.XUNFEI_API_SECRET) {
+        const message = await getXunfeiReply('你好!')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 XUNFEI_APP_ID，XUNFEI_API_KEY，XUNFEI_API_SECRET')
+      break
+    case 'deepseek-free':
+      if (env.DEEPSEEK_FREE_URL && env.DEEPSEEK_FREE_TOKEN && env.DEEPSEEK_FREE_MODEL) {
+        const message = await getDeepSeekFreeReply('你好!')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 DEEPSEEK_FREE_URL，DEEPSEEK_FREE_TOKEN，DEEPSEEK_FREE_MODEL')
+      break
+    case 'dify':
+      if (env.DIFY_API_KEY) {
+        const message = await getDifyReply('hello')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 DIFY_API_KEY, DIFY_URL')
+      break
+    case '302AI':
+      if (env._302AI_API_KEY) {
+        const message = await get302AiReply('hello')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 _302AI_API_KEY')
+      break
+    case 'ollama':
+      if (env.OLLAMA_URL) {
+        const message = await getOllamaReply('hello')
+        console.log('🌸🌸🌸 / reply: ', message)
+        return
+      }
+      console.log('❌ 请先配置.env文件中的 OLLAMA_URL')
+      break
+    default:
+      console.log('🚀服务类型错误')
+  }
+}
+
+const serveList = [
+  { name: 'ChatGPT', value: 'ChatGPT' },
+  { name: 'Kimi', value: 'Kimi' },
+  { name: 'Xunfei', value: 'Xunfei' },
+  { name: 'deepseek-free', value: 'deepseek-free' },
+  { name: '302AI', value: '302AI' },
+  { name: 'dify', value: 'dify' },
+  // ... 欢迎大家接入更多的服务
+  { name: 'ollama', value: 'ollama' },
+]
+const questions = [
+  {
+    type: 'list',
+    name: 'serviceType', //存储当前问题回答的变量key，
+    message: '请先选择服务类型',
+    choices: serveList,
+  },
+]
+function init() {
+  inquirer
+    .prompt(questions)
+    .then((res) => {
+      handleRequest(res.serviceType)
+    })
+    .catch((error) => {
+      console.log('🚀error:', error)
+    })
+}
+init()
--- a/src/xunfei/test.js
+++ b/src/xunfei/test.js
@@ -0,0 +1,9 @@
+import { getXunfeiReply } from './index.js'
+
+// 测试 科大讯飞 api
+async function testMessage() {
+  const message = await getXunfeiReply('秦始皇的儿子是谁?')
+  console.log('🌸🌸🌸 / message: ', message)
+}
+
+testMessage()
--- a/src/xunfei/index.js
+++ b/src/xunfei/index.js
@@ -0,0 +1,9 @@
+import { xunfeiSendMsg } from './xunfei.js'
+
+export async function getXunfeiReply(prompt, name) {
+  console.log('🚀🚀🚀 / prompt', prompt)
+  let reply = await xunfeiSendMsg(prompt)
+
+  if (typeof name != 'undefined') reply = `@${name}\n ${reply}`
+  return `${reply}`
+}
--- a/src/xunfei/xunfei.js
+++ b/src/xunfei/xunfei.js
@@ -0,0 +1,133 @@
+import CryptoJS from "crypto-js";
+import dotenv from "dotenv";
+import WebSocket from "ws";
+
+const env = dotenv.config().parsed; // 环境参数
+
+// APPID，APISecret，APIKey在 https://console.xfyun.cn/services/cbm 获取
+const appID = env.XUNFEI_APP_ID;
+const apiKey = env.XUNFEI_API_KEY;
+const apiSecret = env.XUNFEI_API_SECRET;
+
+// 地址必须填写，代表着大模型的版本号
+const modelVersion = env.XUNFEI_MODEL_VERSION || "v4.0"; // 默认值 "v4.0"
+const httpUrl = new URL(`https://spark-api.xf-yun.com/${modelVersion}/chat`);
+
+// 判断 prompt 是否存在，如果不存在则使用默认值
+const prompt = env.XUNFEI_PROMPT || "你是一个专业的智能助手";
+
+// 动态映射模型版本到 domain 的逻辑
+const modelVersionMap = {
+  "v1.1": "general",
+  "v2.1": "generalv2",
+  "v3.1": "generalv3",
+  "v3.5": "generalv3.5",
+  "pro-128k": "pro-128k",
+  "max-32k": "max-32k",
+  "v4.0": "4.0Ultra",
+};
+
+// 获取模型域名
+function getModelDomain(httpUrl) {
+  try {
+    const modelPath = httpUrl.pathname.split("/")[1]; // 提取版本号或模型路径
+    return modelVersionMap[modelPath] || "unknown"; // 如果没有匹配，返回 "unknown"
+  } catch (error) {
+    console.error("获取模型域名失败:", error);
+    return "unknown";
+  }
+}
+
+let modelDomain = getModelDomain(httpUrl);
+
+// 签名生成逻辑（可复用）
+function generateSignature(httpUrl, apiKey, apiSecret) {
+  const host = "localhost:8080";
+  const date = new Date().toGMTString();
+  const algorithm = "hmac-sha256";
+  const headers = "host date request-line";
+
+  const signatureOrigin = `host: ${host}\ndate: ${date}\nGET ${httpUrl.pathname} HTTP/1.1`;
+  const signatureSha = CryptoJS.HmacSHA256(signatureOrigin, apiSecret);
+  const signature = CryptoJS.enc.Base64.stringify(signatureSha);
+
+  const authorizationOrigin = `api_key="${apiKey}", algorithm="${algorithm}", headers="${headers}", signature="${signature}"`;
+  const authorization = btoa(authorizationOrigin);
+
+  const url = `wss://${httpUrl.host}${httpUrl.pathname}?authorization=${authorization}&date=${date}&host=${host}`;
+  return url;
+}
+
+// 获取 WebSocket 地址
+function authenticate() {
+  return new Promise((resolve, reject) => {
+    try {
+      const url = generateSignature(httpUrl, apiKey, apiSecret);
+      resolve(url);
+    } catch (error) {
+      console.error("认证失败:", error);
+      reject(error);
+    }
+  });
+}
+
+// 发送消息并处理 WebSocket 逻辑
+export async function xunfeiSendMsg(inputVal) {
+  // 获取请求地址
+  let myUrl = await authenticate();
+  let socket = new WebSocket(String(myUrl));
+  let total_res = ""; // 清空回答历史
+
+  // 创建一个Promise
+  let messagePromise = new Promise((resolve, reject) => {
+    socket.addEventListener("open", () => {
+      const params = {
+        header: {
+          app_id: appID,
+          uid: "fd3f47e4-d",
+        },
+        parameter: {
+          chat: {
+            domain: modelDomain,
+            temperature: 0.8,
+            max_tokens: 1024,
+          },
+        },
+        payload: {
+          message: {
+            text: [
+              { role: "system", content: prompt },
+              { role: "user", content: inputVal }, // 最新的问题
+            ],
+          },
+        },
+      };
+      socket.send(JSON.stringify(params));
+    });
+
+    socket.addEventListener("message", (event) => {
+      const data = JSON.parse(String(event.data));
+      if (data.header.code !== 0) {
+        console.error("Socket 出错:", data.header.code, data.header.message);
+        socket.close();
+        reject("");
+      } else if (data.payload.choices.text && data.header.status === 2) {
+        total_res += data.payload.choices.text[0].content;
+        setTimeout(() => {
+          socket.close();
+        }, 1000);
+      }
+    });
+
+    socket.addEventListener("close", () => {
+      resolve(total_res);
+    });
+
+    socket.addEventListener("error", (event) => {
+      console.error("Socket 连接错误:", event);
+      reject("");
+    });
+  });
+
+  return await messagePromise;
+}