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"

# 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）

# =============================================================================
# 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)://<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"
# 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)://<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"）
# 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=<QQ号> -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 <prompt> -f stream-json` under the hood.
# Qoder CLI 底层使用 `qodercli -p <prompt> -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"