cc-connect/config.example.toml

# cc-connect configuration
# cc-connect 配置文件
#
# Copy this file to config.toml and fill in your credentials.
# 复制此文件为 config.toml，填入你的凭证信息。
#
# Each [[projects]] entry binds one code directory to its own agent + platforms.
# A single cc-connect process can manage multiple projects simultaneously.
# 每个 [[projects]] 将一个代码目录绑定到独立的 agent 和平台。
# 单个 cc-connect 进程可以同时管理多个项目。

# =============================================================================
# Global Settings / 全局设置
# =============================================================================

# Language for bot messages / 机器人消息语言
# - "en": English
# - "zh": 中文
# - "" (empty/not set): Auto-detect from user's first message / 留空自动检测
# language = "en"

# Session data storage directory (default: ~/.cc-connect)
# Stores conversation history and session state as JSON files.
# 会话数据存储目录（默认 ~/.cc-connect），以 JSON 文件保存对话历史和会话状态。
# data_dir = "/path/to/custom/dir"

[log]
level = "info" # debug, info, warn, error

# =============================================================================
# Speech-to-Text (Voice Messages) / 语音转文字（语音消息）
# =============================================================================
# Enable to transcribe voice messages to text before sending to agents.
# 启用后，语音消息会先转为文字再发送给 Agent。
#
# Requires ffmpeg for audio format conversion (AMR/OGG → MP3).
# 需要安装 ffmpeg 进行音频格式转换（AMR/OGG → MP3）。

# [speech]
# enabled = true
# provider = "openai"    # "openai" or "groq" / "openai" 或 "groq"
# language = ""          # e.g. "zh", "en"; empty = auto-detect / 如 "zh"、"en"；留空自动检测
#
# [speech.openai]
# api_key = "sk-xxx"     # OpenAI API key
# base_url = ""          # optional: custom endpoint (OpenAI-compatible) / 可选：自定义端点（兼容 OpenAI 接口）
# model = "whisper-1"    # default model / 默认模型
#
# # Alternative: Groq (faster, free tier available)
# # 备选：Groq（更快，有免费额度）
# [speech.groq]
# api_key = "gsk_xxx"
# model = "whisper-large-v3-turbo"

# =============================================================================
# Project 1 / 项目 1
# =============================================================================

[[projects]]
name = "my-backend"

[projects.agent]
type = "claudecode"

[projects.agent.options]
work_dir = "/path/to/backend"
mode = "default" # "default" | "acceptEdits" (edit) | "plan" | "bypassPermissions" (yolo)

# Mode options / 模式说明:
# - "default":            Every tool call requires user approval. / 每次工具调用都需要用户确认。
# - "acceptEdits" (edit): File edit tools auto-approved; other tools still ask. / 文件编辑自动通过，其他仍需确认。
# - "plan":               Claude only plans — no execution until you approve. / 只做规划不执行，审批后再执行。
# - "bypassPermissions" (yolo): All tool calls auto-approved. Use with caution. / 全部自动通过，请谨慎使用。
#
# When using IM platforms, you can reply "允许"/"allow" to grant permission.
# 在 IM 平台中，可回复"允许"或"allow"来授权操作。

# In default/acceptEdits mode, you can pre-approve specific tools:
# 在 default/acceptEdits 模式下，可预授权特定工具：
# allowed_tools = ["Read", "Grep", "Glob", "Bash", "Edit", "Write"]

# Optional: specify a model / 可选：指定模型
# model = "claude-sonnet-4-20250514"

# Active provider (matches a name in [[projects.agent.providers]])
# 当前激活的 provider（对应下方 providers 中的 name）
# provider = "anthropic"

# API Providers — switch between them via /provider command in chat
# or via CLI: cc-connect provider add --project my-backend --name relay --api-key sk-xxx
# API Provider 管理 — 可通过聊天命令 /provider 或 CLI 命令切换
#
# [[projects.agent.providers]]
# name = "anthropic"
# api_key = "sk-ant-xxx"
#
# [[projects.agent.providers]]
# name = "relay"
# api_key = "sk-xxx"
# base_url = "https://api.relay-service.com"
# model = "claude-sonnet-4-20250514"
#
# # For special setups (Bedrock, Vertex, etc.), use the env map:
# # 特殊环境（Bedrock、Vertex 等）使用 env 字段：
# [[projects.agent.providers]]
# name = "bedrock"
# env = { CLAUDE_CODE_USE_BEDROCK = "1", AWS_PROFILE = "bedrock" }

# Feishu / Lark / 飞书
# 1. Create an app at https://open.feishu.cn / 在 https://open.feishu.cn 创建应用
# 2. Enable Bot capability / 开启机器人能力
# 3. Add im.message.receive_v1 event, select WebSocket long-connection mode
#    添加 im.message.receive_v1 事件，选择 WebSocket 长连接模式
# 4. Fill in app_id and app_secret below / 填入下方 app_id 和 app_secret
# Note: No WebSocket URL needed — the SDK auto-negotiates the connection.
# 注意：无需配置 WebSocket URL，SDK 会自动通过凭证建立连接。

[[projects.platforms]]
type = "feishu"

[projects.platforms.options]
app_id = "your-feishu-app-id"
app_secret = "your-feishu-app-secret"

# DingTalk / 钉钉 (uncomment to enable / 取消注释以启用)
# 1. Create an app at https://open-dev.dingtalk.com / 在钉钉开放平台创建应用
# 2. Under "App Features > Bot", enable bot and select Stream mode
#    在"应用功能 > 机器人"中启用机器人并选择 Stream 模式
# 3. Fill in client_id (AppKey) and client_secret (AppSecret) below
#    填入下方 client_id (AppKey) 和 client_secret (AppSecret)

# [[projects.platforms]]
# type = "dingtalk"
#
# [projects.platforms.options]
# client_id = "your-dingtalk-client-id"
# client_secret = "your-dingtalk-client-secret"

# Telegram (uncomment to enable / 取消注释以启用)
# 1. Message @BotFather on Telegram, send /newbot to create a bot
#    在 Telegram 中找 @BotFather，发送 /newbot 创建机器人
# 2. Copy the bot token below / 复制 token 到下方
# Connection: Long polling (no public URL needed) / 长轮询（无需公网 IP）

# [[projects.platforms]]
# type = "telegram"
#
# [projects.platforms.options]
# token = "123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11"

# Slack (uncomment to enable / 取消注释以启用)
# 1. Create an app at https://api.slack.com/apps / 创建应用
# 2. Enable Socket Mode (Settings > Socket Mode) / 开启 Socket Mode
# 3. Subscribe to bot events: message.channels, message.im
#    订阅事件：message.channels, message.im
# 4. Install app to workspace, copy Bot Token (xoxb-...) and App Token (xapp-...)
#    安装应用到工作区，复制 Bot Token 和 App Token
# Connection: Socket Mode WebSocket (no public URL needed) / 无需公网 IP

# [[projects.platforms]]
# type = "slack"
#
# [projects.platforms.options]
# bot_token = "xoxb-your-bot-token"
# app_token = "xapp-your-app-level-token"

# Discord (uncomment to enable / 取消注释以启用)
# 1. Create an app at https://discord.com/developers/applications / 创建应用
# 2. Under "Bot", create a bot and copy the token / 创建 Bot 并复制 token
# 3. Enable "Message Content Intent" under Privileged Gateway Intents
#    在 Privileged Gateway Intents 中开启 Message Content Intent
# 4. Invite bot to server with OAuth2 URL Generator (scopes: bot; permissions: Send Messages)
#    通过 OAuth2 URL 邀请 Bot 到服务器（权限：Send Messages）
# Connection: Gateway WebSocket (no public URL needed) / 无需公网 IP

# [[projects.platforms]]
# type = "discord"
#
# [projects.platforms.options]
# token = "your-discord-bot-token"

# LINE (uncomment to enable / 取消注释以启用)
# 1. Create a channel at https://developers.line.biz/console/ (Messaging API)
#    在 LINE Developers 创建 Messaging API Channel
# 2. Copy Channel Secret and Channel Access Token (long-lived)
#    复制 Channel Secret 和 Channel Access Token
# 3. Set your webhook URL to: http(s)://<your-domain>:<port>/callback
#    设置 Webhook URL：http(s)://<你的域名>:<端口>/callback
# Connection: HTTP Webhook — you need a public URL (use ngrok, cloudflared, etc.)
# 连接方式：HTTP Webhook — 需要公网 URL（可用 ngrok、cloudflared 等）

# [[projects.platforms]]
# type = "line"
#
# [projects.platforms.options]
# channel_secret = "your-line-channel-secret"
# channel_token = "your-line-channel-access-token"
# port = "8080"
# callback_path = "/callback"

# WeChat Work / 企业微信 (uncomment to enable / 取消注释以启用)
# 1. Log in to https://work.weixin.qq.com/wework_admin/frame
#    登录企业微信管理后台
# 2. App Management > Create a custom app > note AgentId + Secret
#    应用管理 > 创建自建应用 > 记录 AgentId 和 Secret
# 3. My Enterprise > note Corp ID / 我的企业 > 记录 Corp ID
# 4. App > Receive Messages > Set API Receive:
#    应用 > 接收消息 > 设置 API 接收：
#    URL: http(s)://<your-domain>:<port>/wecom/callback
#    Token: any random string / 任意随机字符串
#    EncodingAESKey: click "Random Generate" (43 chars) / 点击"随机生成"（43位）
#    (Start cc-connect FIRST, then save to pass verification)
#    （先启动 cc-connect，再保存以通过验证）
# 5. App > Trusted IP > add your server's outbound IP
#    应用 > 企业可信 IP > 添加服务器出口 IP
# 6. (Optional) My Enterprise > WeChat Plugin > scan QR to link personal WeChat
#    （可选）我的企业 > 微信插件 > 扫码关联个人微信
# Connection: HTTP Webhook — you need a public URL
# 连接方式：HTTP Webhook — 需要公网 URL

# [[projects.platforms]]
# type = "wecom"
#
# [projects.platforms.options]
# corp_id = "your-corp-id"
# corp_secret = "your-app-secret"
# agent_id = "1000002"
# callback_token = "your-callback-token"
# callback_aes_key = "your-43-char-encoding-aes-key"
# port = "8081"
# callback_path = "/wecom/callback"
# enable_markdown = false  # set true to send Markdown (only renders in WeChat Work app, NOT personal WeChat)
#                          # 设为 true 发送 Markdown（仅企业微信应用内可渲染，个人微信显示"暂不支持"）
# proxy = ""  # optional: forward proxy for API calls if your IP is dynamic
#             # 可选：正向代理，用于 IP 不固定的场景
#             # e.g. "http://your-vps-ip:8888" — the VPS IP goes into trusted IP list
#             # 示例："http://你的VPS-IP:8888" — 将 VPS IP 加入可信 IP 列表

# =============================================================================
# Project 2: Using Cursor Agent / 项目 2：使用 Cursor Agent (uncomment to enable / 取消注释以启用)
# =============================================================================
# Requires: Cursor Agent CLI (`agent`) — install via Cursor IDE or `npm i -g @anthropic-ai/cursor-agent`
# 需要安装：Cursor Agent CLI (`agent`) — 通过 Cursor IDE 或 npm 安装
# Uses `agent --print --output-format stream-json` under the hood.
# 底层使用 `agent --print --output-format stream-json` 命令。

# [[projects]]
# name = "my-cursor-project"
#
# [projects.agent]
# type = "cursor"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# mode = "force"  # "default" | "force" (yolo) | "plan" | "ask"
# cmd = "agent"   # CLI binary name (default: "agent") / CLI 二进制名称（默认 "agent"）
#
# Mode options / 模式说明:
# - "default": Trust workspace, ask before tool use / 信任工作区，工具调用前询问
# - "force":   Auto-approve all tool calls (same as --force/--yolo) / 自动批准所有工具调用
# - "plan":    Read-only analysis, no edits / 只读分析，不做修改
# - "ask":     Q&A style, read-only / 问答风格，只读
#
# Optional: specify a model / 可选：指定模型
# model = "claude-sonnet-4-20250514"
#
# [[projects.platforms]]
# type = "feishu"
#
# [projects.platforms.options]
# app_id = "your-feishu-app-id"
# app_secret = "your-feishu-app-secret"

# =============================================================================
# Project 3: Using Gemini CLI / 项目 3：使用 Gemini CLI (uncomment to enable / 取消注释以启用)
# =============================================================================
# Requires: npm install -g @google/gemini-cli
# 需要安装：npm install -g @google/gemini-cli
# Gemini CLI uses `gemini -p --output-format stream-json` under the hood.
# Gemini CLI 底层使用 `gemini -p --output-format stream-json` 命令。
#
# Authentication / 认证方式:
#   - Google Account login (free: 60 req/min, 1000 req/day) / Google 账号登录（免费额度）
#   - GEMINI_API_KEY env var / 环境变量
#   - Vertex AI (GOOGLE_API_KEY + GOOGLE_GENAI_USE_VERTEXAI=true)

# [[projects]]
# name = "my-gemini-project"
#
# [projects.agent]
# type = "gemini"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# mode = "yolo"  # "default" | "auto_edit" | "yolo" | "plan"
# cmd = "gemini" # CLI binary name (default: "gemini") / CLI 二进制名称（默认 "gemini"）
#
# Mode options / 模式说明:
# - "default":   Prompt for approval on each tool use / 每次工具调用都需要确认
# - "auto_edit": Auto-approve edit tools, ask for others / 编辑工具自动通过，其他仍需确认
# - "yolo":      Auto-approve all tool calls (-y flag) / 自动批准所有工具调用
# - "plan":      Read-only plan mode, no execution / 只读规划模式，不做修改
#
# Optional: specify a model / 可选：指定模型
# model = "gemini-2.5-flash"
#
# # Provider with API key / 使用 API Key 的 Provider
# [[projects.agent.providers]]
# name = "google"
# api_key = "your-gemini-api-key"    # GEMINI_API_KEY
#
# # Vertex AI provider / Vertex AI 提供商
# [[projects.agent.providers]]
# name = "vertex"
# env = { GOOGLE_API_KEY = "your-key", GOOGLE_GENAI_USE_VERTEXAI = "true" }
#
# [[projects.platforms]]
# type = "feishu"
#
# [projects.platforms.options]
# app_id = "your-feishu-app-id"
# app_secret = "your-feishu-app-secret"

# =============================================================================
# Project 4: Using Codex agent / 项目 4：使用 Codex agent (uncomment to enable / 取消注释以启用)
# =============================================================================
# Requires: npm install -g @openai/codex
# 需要安装：npm install -g @openai/codex
# Codex uses `codex exec --json` under the hood.
# Codex 底层使用 `codex exec --json` 命令。

# [[projects]]
# name = "my-codex-project"
#
# [projects.agent]
# type = "codex"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# mode = "suggest"  # "suggest" | "auto-edit" | "full-auto" | "yolo"
#
# Mode options / 模式说明:
# - "suggest":   ask permission for every tool call (default, safest) / 每次调用都需确认（默认，最安全）
# - "auto-edit": auto-approve file edits, ask for shell commands / 文件编辑自动通过，Shell 命令仍需确认
# - "full-auto": auto-approve everything with workspace sandbox / 全部自动通过，工作区沙箱保护
# - "yolo":      bypass all approvals and sandbox (dangerous) / 跳过所有审批和沙箱（危险）
#
# Optional: specify a model / 可选：指定模型
# model = "o3"
#
# # Active provider / 当前激活的 provider
# # provider = "openai"
#
# [[projects.agent.providers]]
# name = "openai"
# api_key = "sk-xxx"
#
# [[projects.agent.providers]]
# name = "custom"
# api_key = "sk-xxx"
# base_url = "https://custom-api.com/v1"
# model = "gpt-4o"
#
# [[projects.platforms]]
# type = "telegram"
#
# [projects.platforms.options]
# token = "your-telegram-bot-token"

# =============================================================================
# Project 5: Another example / 项目 5：更多示例 (uncomment to enable / 取消注释以启用)
# =============================================================================

# [[projects]]
# name = "my-frontend"
#
# [projects.agent]
# type = "claudecode"
#
# [projects.agent.options]
# work_dir = "/path/to/frontend"
# mode = "bypassPermissions"
#
# [[projects.platforms]]
# type = "discord"
#
# [projects.platforms.options]
# token = "your-discord-bot-token"