# 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" # Default quiet mode (suppress thinking/tool progress messages) / 默认静默模式(隐藏思考和工具进度消息) # Can be overridden per-project. Users can still toggle with /quiet command. # 可被项目级配置覆盖。用户仍可通过 /quiet 命令切换。 # quiet = true [log] level = "info" # debug, info, warn, error # ============================================================================= # Display Settings / 显示设置 # ============================================================================= # Controls how intermediate messages (thinking, tool use) are shown in chat. # 控制中间消息(思考过程、工具调用)在聊天中的显示方式。 # # Set to 0 to disable truncation (show full content). # 设为 0 表示不截断(显示完整内容)。 # [display] # thinking_max_len = 300 # Max chars for thinking messages (default: 300) / 思考消息最大字符数(默认 300) # tool_max_len = 500 # Max chars for tool use messages (default: 500) / 工具调用消息最大字符数(默认 500) # ============================================================================= # Streaming Preview / 流式预览 # ============================================================================= # Real-time message preview: shows agent output as it streams, updating the # message in-place (like a "typing" indicator). Supported on Telegram, Discord, # and Feishu. The message is edited periodically until the final response is sent. # 实时流式预览:Agent 输出时实时更新消息(类似"正在输入"效果)。 # 支持 Telegram、Discord 和飞书。消息会定期编辑,直到最终回复发送。 # [stream_preview] # enabled = true # Enable/disable streaming preview (default: true) / 启用/禁用流式预览(默认 true) # interval_ms = 1500 # Min ms between updates (default: 1500) / 更新最小间隔毫秒数(默认 1500) # min_delta_chars = 30 # Min new chars before sending update (default: 30) / 发送更新前最少新增字符数(默认 30) # max_chars = 2000 # Max preview length (default: 2000) / 预览最大长度(默认 2000) # ============================================================================= # Rate Limiting / 速率限制 # ============================================================================= # Per-session sliding-window rate limiter. Prevents users from flooding the bot # with too many messages. When exceeded, a friendly "slow down" message is sent. # 每会话滑动窗口速率限制。防止用户刷消息。超限时返回友好的提示。 # [rate_limit] # max_messages = 20 # Max messages per window; 0 = disabled (default: 20) / 窗口内最大消息数;0 = 禁用(默认 20) # window_secs = 60 # Window size in seconds (default: 60) / 窗口时间秒数(默认 60) # ============================================================================= # 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" # ============================================================================= # Daemon Mode / 守护进程模式 # ============================================================================= # Run cc-connect as a background service (systemd user / launchd LaunchAgent). # 将 cc-connect 作为后台服务运行(systemd 用户服务 / launchd LaunchAgent)。 # # CLI: cc-connect daemon install|uninstall|start|stop|restart|status|logs # Install: --log-file PATH, --log-max-size N (MB), --work-dir DIR, --force # Logs: -f/--follow, -n N, --log-file PATH # 配置均通过 CLI 参数,无需在此文件中设置。 # ============================================================================= # Custom Skills (Slash Commands) / 自定义命令 # ============================================================================= # Define reusable prompt templates as global slash commands (available in all projects). # 定义可复用的 prompt 模板作为全局 slash 命令(所有项目通用)。 # # Placeholders / 占位符: # {{1}}, {{2}} — positional argument / 位置参数 # {{1:default}} — positional with default value / 带默认值的位置参数 # {{2*}} — argument N and everything after / 第 N 个及之后所有参数 # {{2*:default}} — same, with default / 同上,带默认值 # {{args}} — all arguments / 所有参数 # {{args:default}} — all arguments, with default if none / 所有参数,无参数时使用默认值 # (no placeholder — args appended to end / 无占位符则参数追加到末尾) # # Default values are used when the corresponding argument is not provided. # 当对应参数未提供时,使用默认值替代。 # # Usage: /finduser 张三 → expands prompt with "张三" and sends to agent # 用法: /finduser 张三 → 展开模板并发送给 Agent # [[commands]] # name = "finduser" # description = "Look up user info by name / 按姓名查找用户信息" # prompt = "Search the database for user「{{1}}」and return details including registration time, last login, and permissions." # [[commands]] # name = "review" # description = "Code review with focus area / 代码审查(可指定关注点)" # prompt = "Please review {{1}} focusing on: {{2*:code quality and potential bugs}}" # [[commands]] # name = "translate" # description = "Translate text to specified language / 翻译文本到指定语言" # prompt = "Translate the following text to {{1:English}}:\n{{2*}}" # [[commands]] # name = "daily" # description = "Generate daily progress report / 生成每日进度报告" # prompt = "Summarize today's code changes and project progress. Generate a concise daily report." # # You can also add/remove commands at runtime via chat: # 也可以在聊天中动态添加/删除命令: # /commands add finduser Search the database for user「{{1}}」 # /commands del finduser # /commands — list all custom commands # # In addition, cc-connect auto-discovers .md files from the agent's commands # directory (e.g. .claude/commands/*.md, .gemini/commands/*.md). # 此外,cc-connect 还会自动发现 Agent 的 commands 目录下的 .md 文件。 # ============================================================================= # Banned Words / 违禁词 # ============================================================================= # # Messages containing any of these words will be blocked and NOT forwarded to # the AI agent. Matching is case-insensitive. # 消息中包含以下任一违禁词时,将被拦截,不会转发给 AI Agent。匹配不区分大小写。 # banned_words = ["违禁词1", "违禁词2", "secret_project"] # ============================================================================= # Command Aliases / 命令别名 # ============================================================================= # # Create aliases for commands — like Linux shell aliases. # 为命令创建别名,类似 Linux shell 的 alias。 # # When a user sends a message matching the alias trigger (exact match on first # word), it is automatically replaced with the target command. # 当用户发送的消息首词匹配别名触发词时,自动替换为目标命令。 # # Example: typing "帮助" triggers "/help", typing "新建 测试" triggers "/new 测试". # 示例:输入"帮助"触发 "/help",输入"新建 测试"触发 "/new 测试"。 # [[aliases]] # name = "帮助" # command = "/help" # [[aliases]] # name = "新建" # command = "/new" # [[aliases]] # name = "列表" # command = "/list" # # You can also add/remove aliases at runtime via chat: # 也可以在聊天中动态添加/删除别名: # /alias add 帮助 /help # /alias del 帮助 # /alias — list all aliases # # ============================================================================= # Project 1 / 项目 1 # ============================================================================= [[projects]] name = "my-backend" # quiet = true # Override global quiet for this project / 覆盖全局静默模式 # disabled_commands = ["restart", "upgrade", "cron"] # Disable specific commands for this project # # 禁用该项目的指定命令 [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" # Claude Code Router Integration / Claude Code Router 集成 # Route Claude Code requests through Claude Code Router to use different model providers. # 通过 Claude Code Router 路由 Claude Code 请求,使用不同的模型提供商。 # See: https://github.com/musistudio/claude-code-router # # router_url = "http://127.0.0.1:3456" # Claude Code Router URL (default: http://127.0.0.1:3456) # router_api_key = "your-router-api-key" # Optional: API key if router requires authentication / 可选:如果 router 需要认证 # # When router_url is set, cc-connect will automatically: # 设置 router_url 后,cc-connect 会自动: # - Set ANTHROPIC_BASE_URL to router_url # - Set NO_PROXY=127.0.0.1 to prevent proxy interference # - Disable telemetry and cost warnings for cleaner integration # # Note: When using router, provider settings below are ignored as the router handles model selection. # 注意:使用 router 时,下方的 provider 设置将被忽略,因为 router 负责模型选择。 # 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" # # # Third-party provider with thinking override / 第三方 Provider 并覆盖 thinking 参数 # # Some providers (e.g. SiliconFlow) don't support Claude's adaptive thinking. # # Set thinking = "disabled" to auto-rewrite via a local proxy. # # 部分第三方 Provider(如硅基流动)不支持 Claude 的 adaptive thinking, # # 设置 thinking = "disabled" 后 cc-connect 会通过本地代理自动改写请求。 # [[projects.agent.providers]] # name = "siliconflow" # api_key = "sk-xxx" # base_url = "https://api.siliconflow.cn" # model = "deepseek-ai/DeepSeek-V3" # thinking = "disabled" # # # 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" # allow_from = "*" # Allowed user open_ids, comma-separated; "*" = all (default) / 允许的用户 open_id,逗号分隔;"*" 表示所有(默认) # reaction_emoji = "OnIt" # Emoji reaction on incoming messages (default: "OnIt"); set to "none" to disable # # 收到消息时添加的表情回复(默认 "OnIt");设为 "none" 可禁用 # group_reply_all = false # If true, respond to ALL group messages without requiring @mention # # 设为 true 时,群聊中无需 @机器人 也会响应所有消息(默认 false) # 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" # allow_from = "*" # Allowed staff IDs / 允许的员工 ID # 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" # allow_from = "*" # Allowed Telegram user IDs, e.g. "123456789,987654321"; "*" = all # # 允许的 Telegram 用户 ID,如 "123456789,987654321";"*" 表示所有 # group_reply_all = false # If true, respond to ALL group messages without @mention / 设为 true 群聊无需 @ 也响应 # 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" # allow_from = "*" # Allowed Slack user IDs / 允许的 Slack 用户 ID # 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 with OAuth2 URL Generator: # 通过 OAuth2 URL 邀请 Bot 到服务器: # Scopes: bot + applications.commands (BOTH required for slash command menu) # Scopes 需要同时勾选: bot + applications.commands(缺少后者则 / 菜单不会出现) # Bot Permissions: Send Messages, Use Slash Commands # Bot 权限: Send Messages, Use Slash Commands # Connection: Gateway WebSocket (no public URL needed) / 无需公网 IP # # NOTE: Global slash commands may take up to 1 hour to appear in Discord. # Set guild_id for instant per-guild registration (recommended for testing). # 注意:全局 slash 命令最多需 1 小时生效。设置 guild_id 可秒级生效(推荐测试时使用)。 # To find your guild ID: Discord Settings > Advanced > Developer Mode ON, then right-click server > Copy Server ID # 获取 guild_id:Discord 设置 > 高级 > 开启开发者模式,然后右键服务器 > 复制服务器 ID # [[projects.platforms]] # type = "discord" # # [projects.platforms.options] # token = "your-discord-bot-token" # allow_from = "*" # Allowed Discord user IDs / 允许的 Discord 用户 ID # guild_id = "" # Optional: set for instant slash command registration (per-guild) # # 可选:设置后 slash 命令秒级生效(仅该服务器) # group_reply_all = false # If true, respond to ALL guild messages without @mention / 设为 true 群聊无需 @ 也响应 # 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)://:/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" # allow_from = "*" # Allowed LINE user IDs / 允许的 LINE 用户 ID # 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)://:/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") # allow_from = "*" # Allowed WeChat Work user IDs / 允许的企业微信用户 ID # 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 # proxy_username = "" # optional: proxy authentication username / 代理认证用户名 # proxy_password = "" # optional: proxy authentication password / 代理认证密码 # ============================================================================= # 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" # QQ (via NapCat / OneBot v11) (uncomment to enable / 取消注释以启用) # Requires a OneBot v11 implementation running alongside your QQ client: # 需要一个 OneBot v11 实现配合 QQ 客户端运行: # - NapCat (recommended / 推荐): https://github.com/NapNeko/NapCatQQ # - Docker: docker run -d --name napcat -e ACCOUNT= -p 3001:3001 -p 6099:6099 mlikiowa/napcat-docker:latest # - Enable Forward WebSocket in NapCat WebUI (http://localhost:6099), default port 3001 # 在 NapCat WebUI 中启用正向 WebSocket,默认端口 3001 # - LLOneBot: https://github.com/LLOneBot/LLOneBot (NTQQ plugin / NTQQ 插件) # # allow_from: comma-separated QQ user IDs that are allowed to interact, or "*" for all. # 允许交互的 QQ 号列表(逗号分隔),设为 "*" 允许所有人。 # token: optional access_token for WebSocket authentication (must match NapCat config). # 可选的 WebSocket 鉴权 token(需与 NapCat 配置一致)。 # [[projects.platforms]] # type = "qq" # # [projects.platforms.options] # ws_url = "ws://127.0.0.1:3001" # NapCat Forward WebSocket URL # token = "" # optional: access_token / 可选鉴权 token # allow_from = "*" # allowed QQ user IDs, e.g. "12345,67890" or "*" for all # # 允许的 QQ 号,如 "12345,67890","*" 表示所有 # ============================================================================= # Project 5: Using Qoder CLI / 项目 5:使用 Qoder CLI (uncomment to enable / 取消注释以启用) # ============================================================================= # Requires: curl -fsSL https://qoder.com/install | bash # 需要安装:curl -fsSL https://qoder.com/install | bash # Qoder CLI uses `qodercli -p -f stream-json` under the hood. # Qoder CLI 底层使用 `qodercli -p -f stream-json` 命令。 # [[projects]] # name = "my-qoder-project" # # [projects.agent] # type = "qoder" # # [projects.agent.options] # work_dir = "/path/to/project" # mode = "default" # "default" | "yolo" # # Mode options / 模式说明: # - "default": Standard permissions / 标准权限模式 # - "yolo": Skip all permission checks (--dangerously-skip-permissions) / 跳过所有权限检查 # # Optional: specify a model tier / 可选:指定模型级别 # model = "auto" # "auto" | "ultimate" | "performance" | "efficient" | "lite" # # [[projects.platforms]] # type = "telegram" # # [projects.platforms.options] # token = "your-telegram-bot-token" # ============================================================================= # Project 6: Using OpenCode / 项目 6:使用 OpenCode (uncomment to enable / 取消注释以启用) # ============================================================================= # Requires: OpenCode CLI — https://github.com/opencode-ai/opencode # 需要安装:OpenCode CLI # Uses `opencode run --format json` under the hood. # 底层使用 `opencode run --format json` 命令。 # [[projects]] # name = "my-opencode-project" # # [projects.agent] # type = "opencode" # # [projects.agent.options] # work_dir = "/path/to/project" # mode = "default" # "default" | "yolo" # # Mode options / 模式说明: # - "default": Standard mode / 标准模式 # - "yolo": Auto-approve all tool calls / 自动批准所有工具调用 # # Optional: specify a model (provider/model format) / 可选:指定模型 # model = "anthropic/claude-sonnet-4-20250514" # # [[projects.platforms]] # type = "telegram" # # [projects.platforms.options] # token = "your-telegram-bot-token" # ============================================================================= # Project 7: Another example / 项目 7: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"