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"

# Attachment send-back switch for `cc-connect send --image/--file`.
# Independent from the agent's /mode. Set to "off" to block IM image/file send-back.
# `cc-connect send --message` without attachments is unaffected.
# 附件回传开关，用于控制 `cc-connect send --image/--file`。
# 它与 agent 的 /mode 独立；设为 "off" 会禁用通过 IM 回传图片/文件。
# 不带附件的 `cc-connect send --message` 不受影响。
# attachment_send = "on"

# 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）

# Agent idle timeout: max minutes between consecutive agent events before
# considering the session stuck. Set to 0 to disable the timeout entirely.
# Agent 空闲超时：两次 agent 事件之间的最大等待分钟数，超时则认为会话卡住。设为 0 禁用。
# idle_timeout_mins = 120  # default: 120 (2 hours) / 默认 120（2 小时）

# =============================================================================
# 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）

# =============================================================================
# Outgoing Rate Limit / 出站速率限制
# Throttle how fast messages are sent TO platforms.
# Prevents account bans on platforms with strict API rate limits (e.g. WeChat Work).
# 限制向平台发送消息的速率，防止因频率过高被封号（如企业微信）。
# =============================================================================
# [outgoing_rate_limit]
# max_per_second = 0         # Global default msgs/sec; 0 = unlimited (default) / 全局默认每秒消息数；0 = 无限制
# burst = 3                  # Max burst size; default = ceil(max_per_second) / 最大突发数量
#                            # For fractional rates (e.g. 0.2), default burst becomes ceil(max_per_second).

# Per-platform overrides / 每平台覆盖配置:
# [outgoing_rate_limit.platforms.wecom]
# max_per_second = 1
# [outgoing_rate_limit.platforms.telegram]
# max_per_second = 25
# [outgoing_rate_limit.platforms.feishu]
# max_per_second = 5

# =============================================================================
# Relay Settings / Relay 设置
# =============================================================================
# Bot-to-bot relay timeout. Controls how long cc-connect waits for the target
# bot to finish responding during `cc-connect relay send`.
# Bot 间 relay 超时。控制 `cc-connect relay send` 时等待目标 bot 完成回复的最长时间。

# [relay]
# timeout_secs = 120        # Max relay wait in seconds; 0 = disabled (default: 120) / relay 最大等待秒数；0 = 禁用（默认 120）

# =============================================================================
# Auto-Compress / 自动压缩
# =============================================================================
# Automatically trigger /compress when estimated token usage exceeds threshold.
# 当估算 token 超过阈值时自动触发 /compress。
#
# [projects.auto_compress]
# enabled = true
# max_tokens = 12000     # estimated token threshold to trigger compression
# min_gap_mins = 30      # minimum minutes between auto-compress runs (default 30)

# =============================================================================
# Cron Settings / 定时任务设置
# =============================================================================
# Controls cron job behavior.
# 控制定时任务行为。

# [cron]
# silent = false             # Suppress "⏰ task name" notification when cron starts (default: false)
#                            # 静默模式：不发送定时任务开始执行的通知消息（默认 false）

# =============================================================================
# Webhook / 外部 Webhook 端点
# =============================================================================
# Exposes an HTTP endpoint for external systems (git hooks, CI/CD, file watchers)
# to trigger agent prompts or shell commands.
# 暴露一个 HTTP 端点，供外部系统（git hook、CI/CD、文件监听）触发 agent 或 shell 命令。
#
# [webhook]
# enabled = true
# port = 9111                  # Listen port (default: 9111) / 监听端口（默认 9111）
# token = "your-secret-token"  # Shared secret for auth; empty = no auth / 认证密钥；为空则不验证
# path = "/hook"               # URL path (default: "/hook") / URL 路径（默认 "/hook"）
#
# Usage / 使用方式:
#
#   # Trigger an agent prompt / 触发 agent 执行
#   curl -X POST http://localhost:9111/hook \
#     -H "Authorization: Bearer your-secret-token" \
#     -H "Content-Type: application/json" \
#     -d '{"session_key":"telegram:123:123","prompt":"review latest commit","event":"git:commit"}'
#
#   # Execute a shell command / 执行 shell 命令
#   curl -X POST http://localhost:9111/hook \
#     -H "Authorization: Bearer your-secret-token" \
#     -H "Content-Type: application/json" \
#     -d '{"session_key":"telegram:123:123","exec":"git log -3 --oneline","event":"git:push"}'
#
#   # Git post-commit hook example (.git/hooks/post-commit):
#   # #!/bin/sh
#   # MSG=$(git log -1 --pretty=format:"%s")
#   # curl -sX POST http://localhost:9111/hook \
#   #   -H "Authorization: Bearer your-secret-token" \
#   #   -H "Content-Type: application/json" \
#   #   -d "{\"session_key\":\"telegram:123:123\",\"event\":\"git:commit\",\"prompt\":\"New commit: $MSG. Review it briefly.\"}"

# =============================================================================
# Bridge Platform (External Adapters via WebSocket)
# Bridge 平台（通过 WebSocket 接入外部适配器）
# =============================================================================
# Allow external adapters written in any language to connect at runtime.
# 允许使用任何语言编写的外部适配器在运行时动态接入。
# See docs/bridge-protocol.md for the full protocol specification.
# 完整协议规范请参阅 docs/bridge-protocol.md。
#
# [bridge]
# enabled = true
# port = 9810                         # WebSocket listen port (default: 9810) / 监听端口
# token = "your-bridge-secret"        # Auth token (required) / 认证密钥（必填）
# path = "/bridge/ws"                 # URL path (default: "/bridge/ws") / URL 路径

# =============================================================================
# Management API (External Management Tools)
# 管理 API（外部管理工具）
# =============================================================================
# HTTP REST API for external apps (web dashboards, TUI, GUI, Mac tray apps).
# 为外部应用（Web 管理面板、TUI、GUI、Mac 托盘应用）提供 HTTP REST API。
# See docs/management-api.md for the full API specification.
# 完整 API 规范请参阅 docs/management-api.md。
#
# [management]
# enabled = true
# port = 9820                           # HTTP listen port (default: 9820) / 监听端口
# token = "your-mgmt-secret"            # Auth token (required) / 认证密钥（必填）
# cors_origins = ["http://localhost:3000"]  # Allowed CORS origins / 允许的 CORS 来源

# =============================================================================
# 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", "groq", or "qwen" / "openai"、"groq" 或 "qwen"
# 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"

# =============================================================================
# Text-to-Speech (Voice Reply) / 文字转语音（语音回复）
# =============================================================================
# Enable to synthesize AI replies into voice messages sent back to users.
# 启用后，AI 的文字回复会合成为语音消息发送给用户。
#
# tts_mode:
#   "voice_only" (default) - only reply with voice when user sends a voice message
#                            仅当用户发送语音消息时，AI 才用语音回复
#   "always"               - always send a voice reply regardless of input type
#                            无论用户发文字还是语音，AI 始终额外发一条语音回复
#
# Runtime command: /tts [always|voice_only]
# 运行时命令：/tts [always|voice_only]
#
# Requires ffmpeg for WAV → Opus conversion (needed by Feishu audio messages).
# 需要安装 ffmpeg 进行 WAV → Opus 转换（飞书语音消息要求 Opus 格式）。

# [tts]
# enabled  = true
# provider = "qwen"          # "qwen" | "openai" | "minimax"
# voice    = "Cherry"        # default voice / 默认音色（千问支持：Cherry/Serena/Ethan/Chelsie 等）
# tts_mode = "voice_only"    # "voice_only" (default) | "always"
# max_text_len = 0           # max rune count before skipping TTS; 0 = no limit
#                            # 超过此长度则跳过 TTS；0 表示不限制
#                            # Qwen TTS 建议参考官方文档：https://help.aliyun.com/zh/model-studio/qwen-tts
#                            # OpenAI TTS 限制请参考：https://platform.openai.com/docs/guides/text-to-speech
#
# # Qwen TTS (Alibaba DashScope / 阿里百炼)
# [tts.qwen]
# api_key  = "sk-xxx"        # DashScope API key / 阿里百炼 API Key
# base_url = ""              # optional: leave empty for default endpoint / 留空使用默认地址
# model    = "qwen3-tts-flash"   # "qwen3-tts-flash" | "qwen3-tts-instruct-flash"
#
# # Alternative: OpenAI TTS (OpenAI-compatible)
# # 备选：OpenAI TTS（兼容 OpenAI 接口）
# [tts.openai]
# api_key  = "sk-xxx"
# base_url = ""              # optional: custom endpoint / 可选：自定义端点
# model    = "tts-1"         # "tts-1" | "tts-1-hd"
#
# # Alternative: MiniMax TTS (T2A v2 streaming API)
# # 备选：MiniMax TTS（T2A v2 流式 API）
# # Docs: https://platform.minimaxi.com/document/T2A%20V2
# [tts.minimax]
# api_key  = "your-minimax-api-key"
# base_url = ""              # optional: default "https://api.minimax.io" / 留空使用默认地址
# model    = "speech-2.8-hd" # "speech-2.8-hd" | "speech-2.8"

# =============================================================================
# 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）。
#
# Two types of commands are supported / 支持两种类型的命令：
#   1. Prompt commands — expand template and send to AI agent
#      Prompt 命令 — 展开模板后发送给 AI Agent
#   2. Exec commands — execute shell command directly
#      Exec 命令 — 直接执行 shell 命令
#
# Placeholders (for both prompt and exec) / 占位符（prompt 和 exec 都支持）:
#   {{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 / 用法:
#   /finduser 张三  →  expands prompt with "张三" and sends to agent
#   /push           →  executes "git push" directly

# [[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."

# Exec commands - execute shell commands directly
# Exec 命令 — 直接执行 shell 命令

# [[commands]]
# name = "push"
# description = "Push to remote / 推送到远程"
# exec = "git push"

# [[commands]]
# name = "status"
# description = "Show git status / 显示 git 状态"
# exec = "git status {{args}}"

# [[commands]]
# name = "branch"
# description = "Create and checkout new branch / 创建并切换到新分支"
# exec = "git checkout -b {{1}}"

# [[commands]]
# name = "build"
# description = "Build the project / 构建项目"
# exec = "npm run build"
# work_dir = "/path/to/project"  # Optional: override working directory / 可选：指定工作目录

#
# 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 addexec push git push
#   /commands addexec --work-dir /path/to/project build npm run build
#   /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
#

# =============================================================================
# Multi-workspace Mode / 多工作区模式
# =============================================================================
# Single bot, multiple workspaces. Channel name maps to ~/workspace/<channel-name>
# automatically. Use /workspace init <url> to clone and bind a new repo.
# 单个 bot 服务多个工作区。频道名称自动映射到 ~/workspace/<频道名>。
# 使用 /workspace init <url> 克隆并绑定新仓库。
#
# [[projects]]
# name = "claude-multi"
# mode = "multi-workspace"
# base_dir = "~/workspace"
#
# [projects.agent]
# type = "claudecode"
# permission_mode = "yolo"
#
# [[projects.platforms]]
# type = "slack"
# [projects.platforms.options]
# bot_token = "xoxb-..."
# app_token = "xapp-..."

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

[[projects]]
name = "my-backend"
# show_context_indicator = false  # Hide the “[ctx: ~N%]” suffix on assistant replies (default: true / show)
#                                   # 不在助手回复末尾显示「[ctx: ~N%]」上下文占用提示（默认 true 显示）
# 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
#
# admin_from controls who can run privileged commands (/dir, /shell, /restart, /upgrade, /commands addexec).
# admin_from 控制谁可以执行特权命令（/dir, /shell, /restart, /upgrade, /commands addexec）。
#
# 💡 TIP: Send /whoami or /status to the bot to get your User ID for allow_from / admin_from.
# 💡 提示：向机器人发送 /whoami 或者 /status  即可获取你的 User ID，用于填写 allow_from / admin_from。
#
# Not set (default): privileged commands are blocked for all users.
# 未设置（默认）：所有用户均无法使用特权命令。
#
# Explicit user list: only these users can run privileged commands.
# 指定用户列表：仅这些用户可执行特权命令。
# admin_from = "user_id_1,user_id_2"
#
# ⚠️ RISK WARNING / 风险提示:
# Setting admin_from = "*" grants ALL allowed users full shell access to the host machine.
# Only use this for personal single-user deployments where you trust every allowed user.
# 设置 admin_from = "*" 将授予所有已允许的用户对主机的完整 shell 访问权限。
# 仅在个人单用户部署中使用此配置，确保所有允许的用户均可信任。
# admin_from = "*"

# Multi-user mode — per-user rate limits and role-based command ACL
# 多用户模式 — 按用户速率限制和基于角色的命令权限控制
#
# When [projects.users] is configured, each user is matched to a role.
# Roles control which commands are available and the rate limit for that user.
# If not configured, behavior is unchanged (backward compatible).
#
# 配置 [projects.users] 后，每个用户会被分配到一个角色。
# 角色控制该用户可用的命令和速率限制。未配置时行为不变（向后兼容）。
#
# [projects.users]
# default_role = "member"
#
# [projects.users.roles.admin]
# user_ids = ["platform_user_id_1", "platform_user_id_2"]
# disabled_commands = []                                     # no restrictions
# rate_limit = { max_messages = 50, window_secs = 60 }
#
# [projects.users.roles.member]
# user_ids = ["*"]                                           # matches all unassigned users
# disabled_commands = ["*"]                                  # disable all built-in commands
# rate_limit = { max_messages = 10, window_secs = 60 }

# Heartbeat — periodic awareness check / 心跳 — 周期性巡检
# The agent wakes up at a fixed interval to check the environment.
# Agent 会按固定间隔唤醒，检查环境状态。
#
# Unlike cron (precise scheduling, isolated tasks), heartbeat runs in the
# main session with full context — ideal for status monitoring and continuing
# unfinished work.
# 与 cron（精确调度、独立任务）不同，heartbeat 在主会话中运行并共享上下文
# —— 适合状态监控和继续未完成的工作。
#
# [projects.heartbeat]
# enabled = true
# interval_mins = 30             # Interval in minutes (default: 30) / 间隔分钟数（默认 30）
# session_key = "telegram:123:123"  # Target session key (required) / 目标会话 key（必填）
# only_when_idle = true          # Skip if session is busy (default: true) / 会话忙碌时跳过（默认 true）
# silent = true                  # Suppress "💓" notification (default: true) / 不发送心跳通知（默认 true）
# timeout_mins = 30              # Max execution time (default: 30) / 最大执行时间（默认 30 分钟）
# prompt = "check inbox and tasks"  # Explicit prompt; if empty, reads HEARTBEAT.md from work_dir
#                                    # 显式提示词；为空时从 work_dir 读取 HEARTBEAT.md
#
# HEARTBEAT.md example / HEARTBEAT.md 示例:
#   On heartbeat:
#   - check inbox
#   - check background tasks
#   - continue unfinished work

[projects.agent]
type = "claudecode"

[projects.agent.options]
work_dir = "/path/to/backend"
mode = "default" # "default" | "acceptEdits" (edit) | "plan" | "auto" | "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。
# - "auto": Claude automatically decides when a permission prompt is needed. / Claude 自动判断何时需要确认。
# - "bypassPermissions" (yolo): All tool calls auto-approved. Use with caution. / 全部自动通过，请谨慎使用。
# - "dontAsk" (dont-ask): Auto-deny tools unless pre-approved via allowed_tools or settings allow rules. / 未预授权的工具自动拒绝，安全推荐。
#
# 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"]

# You can also disallow specific tools (passed to --disallowedTools):
# 也可以禁用特定工具（传递给 --disallowedTools）：
# disallowed_tools = ["WebSearch", "WebFetch"]

# 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"
# # Optional: pre-configure available models shown by /model command (alias - model)
# # /model switch [alias] switches to the model; omit to auto-fetch from the API.
# # 可选：预先配置 /model 命令显示的可用模型列表，格式为 alias - model
# # 使用 /model switch [alias] 切换模型；留空则自动从 API 获取
# [[projects.agent.providers.models]]
# model = "claude-sonnet-4-20250514"
# alias = "sonnet"
# [[projects.agent.providers.models]]
# model = "claude-opus-4-20250514"
# alias = "opus"
# [[projects.agent.providers.models]]
# model = "claude-haiku-3-5-20241022"
# alias = "haiku"
#
# # 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"
#
# # MiniMax — OpenAI-compatible provider with 1M context window
# # MiniMax — 兼容 OpenAI 接口的大模型，支持 1M 超长上下文
# # Models: MiniMax-M2.7 (flagship, 1M context), MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed
# # Docs: https://platform.minimaxi.com
# [[projects.agent.providers]]
# name = "minimax"
# api_key = "your-minimax-api-key"
# base_url = "https://api.minimax.io/v1"
# model = "MiniMax-M2.7"
# thinking = "disabled"
# [[projects.agent.providers.models]]
# model = "MiniMax-M2.7"
# alias = "m27"
# [[projects.agent.providers.models]]
# model = "MiniMax-M2.7-highspeed"
# alias = "m27fast"
# [[projects.agent.providers.models]]
# model = "MiniMax-M2.5"
# alias = "m25"
# [[projects.agent.providers.models]]
# model = "MiniMax-M2.5-highspeed"
# alias = "m25fast"
#
# # 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
# Quick setup via CLI:
#   cc-connect feishu setup --project <project_name>
# （可通过 CLI 快速配置：cc-connect feishu setup --project <project_name>）
# 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"
# enable_feishu_card = true  # Enable Feishu interactive cards (default: true); set false to force plain-text replies
#                              # 启用飞书交互式卡片（默认 true）；设为 false 时强制回退纯文本回复
# allow_from = "*"          # Allowed user open_ids, comma-separated; "*" = all (default). Use /whoami to get your open_id.
#                              # 允许的用户 open_id，逗号分隔；"*" 表示所有（默认）。发送 /whoami 获取你的 open_id。
# 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）
# share_session_in_channel = false  # If true, all users in a group share one agent session
#                                   # 设为 true 时，群聊内所有用户共享同一个 Agent 会话
# thread_isolation = false  # If true, group messages use Feishu reply threads as session boundaries (one thread/root = one agent session)
#                           # 设为 true 时，群聊按飞书话题/根消息隔离会话（一个 thread/root 对应一个 Agent 会话）
# reply_to_trigger = true   # Default: bot uses “reply to message” API (quotes the user’s message). Set false to post plain chat messages instead.
#                           # 默认 true：用「回复消息」API（引用用户消息）。设为 false 则在会话里发普通消息、不引用触发消息。
# progress_style = "legacy" # Progress rendering style: legacy | compact | card
#                           # 进度消息展示风格：legacy（逐条消息）| compact（单消息持续更新）| card（结构化卡片）

# Lark (International Version) / Lark 国际版
# Lark uses Webhook mode instead of WebSocket long-connection.
# Lark 使用 Webhook 模式而非 WebSocket 长连接。
# 1. Create an app at https://open.larksuite.com / 在 https://open.larksuite.com 创建应用
# 2. Enable Bot capability / 开启机器人能力
# 3. Add im.message.receive_v1 event, configure Webhook URL (requires public IP)
#    添加 im.message.receive_v1 事件，配置 Webhook URL（需要公网 IP）
# 4. Fill in app_id, app_secret, port, callback_path below
#    填入下方 app_id、app_secret、port、callback_path

# [[projects.platforms]]
# type = "lark"
#
# [projects.platforms.options]
# app_id = "your-lark-app-id"
# app_secret = "your-lark-app-secret"
# port = "8080"                  # Webhook server port / Webhook 服务器端口
# callback_path = "/feishu/webhook"  # Webhook callback path / Webhook 回调路径
# encrypt_key = ""               # Event encrypt key (optional) / 事件加密密钥（可选）
# enable_feishu_card = true
# allow_from = "*"
# reaction_emoji = "OnIt"
# progress_style = "legacy"  # legacy | compact | card

# 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
# share_session_in_channel = false  # If true, all users in a group share one agent session / 群聊共享会话

# 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
# share_session_in_channel = false  # If true, all users in a group share one agent session / 群聊共享会话

# 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
# share_session_in_channel = false  # If true, all users in a channel share one agent session / 频道共享会话

# 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
# share_session_in_channel = false  # If true, all users in a channel share one agent session / 频道共享会话
# thread_isolation = false  # If true, cc-connect creates/uses Discord threads as session boundaries when the channel supports threads
#                           # 设为 true 时，cc-connect 会在支持 thread 的 Discord 频道内按 thread 隔离会话
# respond_to_at_everyone_and_here = false  # If true, treat @everyone/@here as a direct mention so the bot responds
#                              # 设为 true 时，将 @everyone/@here 视为直接 @ 机器人，使机器人响应

# 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
# Inbound (HTTP callback): text, image, voice, and file messages are passed to the agent.
# 入站（HTTP 回调）：文本、图片、语音与文件会交给 Agent（如 Claude Code）处理。
# WebSocket 智能机器人：文本、语音（转文字）、图片、文件、图文混排与引用中的图片/文件（URL+aeskey 下载解密）。
# 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

# WeChat Work WebSocket / 企业微信长连接模式 (uncomment to enable / 取消注释以启用)
# No public URL, no message encryption, no IP allowlist needed!
# 无需公网 URL、无需消息加解密、无需 IP 白名单！
# 1. Create a "智能机器人" (AI Bot) in WeChat Work admin console
#    在企业微信管理后台创建「智能机器人」
# 2. Get BotID and Secret / 获取 BotID 和 Secret
# 3. Fill in config below / 填入下方配置
# Connection: WebSocket long-connection (client-initiated, no public URL needed)
# 连接方式：WebSocket 长连接（客户端主动连接，无需公网 URL）

# [[projects.platforms]]
# type = "wecom"
#
# [projects.platforms.options]
# mode = "websocket"
# bot_id = "your-bot-id"
# bot_secret = "your-bot-secret"
# allow_from = "*"  # Allowed user IDs / 允许的用户 ID

# Weixin personal (ilink bot) / 微信个人号（ilink 机器人网关）
# Same HTTP API as OpenClaw @tencent-weixin/openclaw-weixin: long-poll getUpdates + sendMessage.
# 与 OpenClaw 插件 openclaw-weixin 使用同一套网关：长轮询收消息 + sendMessage 下发。
#
# 1. Easiest: run `cc-connect weixin setup --project <name>` — terminal shows a QR; scan with WeChat to obtain token.
#    Or: `cc-connect weixin bind --project <name> --token <bearer>` if you already have a token (e.g. from OpenClaw).
# 2. Manual: set token below. Optional: base_url (default https://ilinkai.weixin.qq.com).
# 3. allow_from: comma-separated Weixin user IDs (e.g. user@im.wechat) or "*".
# State files (get_updates cursor + context_token cache) live under:
#   <data_dir>/weixin/<project>/<account_id>/
#
# Inbound images / files / video / raw voice (SILK) are downloaded from Weixin CDN and AES-128-ECB decrypted
# when encrypt_query_param + aes_key are present (aligned with OpenClaw openclaw-weixin).
# 入站图片、文件、视频、无转写文字时的语音会从微信 CDN 拉取并按 AES-128-ECB 解密（与 OpenClaw 插件一致）。

# [[projects.platforms]]
# type = "weixin"
#
# [projects.platforms.options]
# token = "your-ilink-bot-bearer-token"
# base_url = "https://ilinkai.weixin.qq.com"   # optional / 可选
# cdn_base_url = "https://novac2c.cdn.weixin.qq.com/c2c"   # optional; CDN download/upload / 可选 CDN 根路径
# allow_from = "*"                             # or "user1@im.wechat,user2@im.wechat"
# account_id = "default"                       # optional: isolate state dirs / 可选：区分多账号状态目录
# route_tag = ""                               # optional SKRouteTag header / 可选路由头
# long_poll_timeout_ms = 35000                 # optional / 可选
# state_dir = ""                               # optional: override persistence directory / 可选覆盖状态目录
# proxy = ""                                   # optional HTTP proxy / 可选代理
# proxy_username = ""
# proxy_password = ""

# =============================================================================
# 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"）
# timeout_mins = 30  # 每次对话超时时间（分钟），0 表示不限制
#
# 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"
#
# Optional: specify Codex reasoning effort / 可选：指定 Codex 推理强度
# reasoning_effort = "high"  # "minimal" | "low" | "medium" | "high" | "xhigh"
#
# # 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"
#
# # MiniMax — OpenAI-compatible, works natively with Codex
# # MiniMax — 兼容 OpenAI 接口，可直接用于 Codex
# [[projects.agent.providers]]
# name = "minimax"
# api_key = "your-minimax-api-key"
# base_url = "https://api.minimax.io/v1"
# model = "MiniMax-M2.7"
#
# [[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
# share_session_in_channel = false  # If true, all users in a group share one agent session / 群聊共享会话

# QQ Bot (Official / 官方 QQ 机器人) (uncomment to enable / 取消注释以启用)
# Uses the official QQ Bot Platform API — no third-party adapter needed.
# 使用 QQ 官方机器人 API，无需第三方适配器。
# 1. Register at https://q.qq.com → create bot → get AppID & AppSecret
#    在 https://q.qq.com 注册 → 创建机器人 → 获取 AppID 和 AppSecret
# 2. Connection: WebSocket (no public IP needed) / WebSocket 连接（无需公网 IP）
# 3. In group chats, bot only receives messages when @mentioned
#    群聊中，机器人仅在被 @ 时收到消息

# [[projects.platforms]]
# type = "qqbot"
#
# [projects.platforms.options]
# app_id = ""           # Bot AppID / 机器人 AppID
# app_secret = ""       # Bot AppSecret / 机器人 AppSecret
# sandbox = false       # Use sandbox API endpoint / 使用沙箱环境
# allow_from = "*"      # Allowed user openids, e.g. "OPEN_ID_1,OPEN_ID_2"; "*" = all
#                       # 允许的用户 openid，如 "OPEN_ID_1,OPEN_ID_2"；"*" 表示所有
# share_session_in_channel = false  # If true, all users in a group share one agent session / 群聊共享会话
# markdown_support = false  # Enable Markdown messages (msg_type: 2). Requires bot permission. / 启用 Markdown 消息（msg_type: 2）。需要机器人具备该权限。

# =============================================================================
# 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: ACP (Agent Client Protocol) agent / 使用 ACP 子进程
# =============================================================================
# Runs any binary that speaks ACP over stdio (newline-delimited JSON-RPC 2.0).
# See: https://agentclientprotocol.com/
# 启动符合 ACP 的 Agent 进程，通过标准输入输出进行 JSON-RPC 通信。
# Same agent type works for Cursor Agent CLI, OpenClaw bridge, GitHub Copilot CLI, etc.:
# set command + args to match each tool's documented ACP entrypoint.
# 同一 type=acp：通过 command/args 指向各工具文档中的 ACP 启动方式即可。

# --- Example: Cursor Agent CLI (npm: @anthropic-ai/cursor-agent) ---
# [[projects]]
# name = "cursor-acp"
#
# [projects.agent]
# type = "acp"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# command = "agent"
# args = ["acp"]
# auth_method = "cursor_login"
# display_name = "Cursor ACP"

# --- Example: OpenClaw (Gateway-backed ACP bridge) ---
# Docs: https://docs.openclaw.ai/cli/acp
# Install the OpenClaw CLI, run a Gateway, then point cc-connect at `openclaw acp`.
# [[projects]]
# name = "openclaw-acp"
#
# [projects.agent]
# type = "acp"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# command = "openclaw"
# args = ["acp"]
# # Remote gateway (use token-file on shared hosts — avoid --token in argv):
# # args = ["acp", "--url", "wss://gateway-host:18789", "--token-file", "/path/to/gateway.token"]
# # Optional: bind to an existing session key
# # args = ["acp", "--session", "agent:main:main"]
# display_name = "OpenClaw ACP"
# # env = { OPENCLAW_GATEWAY_TOKEN = "..." }

# --- Example: GitHub Copilot CLI (public preview) ---
# Docs: https://docs.github.com/en/copilot/reference/copilot-cli-reference/acp-server
# Requires Copilot CLI installed and authenticated; no auth_method for ACP subprocess.
# [[projects]]
# name = "copilot-acp"
#
# [projects.agent]
# type = "acp"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# command = "copilot"
# args = ["--acp", "--stdio"]
# display_name = "Copilot ACP"
# # command = "/absolute/path/to/copilot"   # if not on PATH (see COPILOT_CLI_PATH in GitHub docs)

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

# =============================================================================
# Project 7: Using iFlow CLI / 项目 7：使用 iFlow CLI (uncomment to enable / 取消注释以启用)
# =============================================================================
# Requires: npm install -g @iflow-ai/iflow-cli
# 需要安装：npm install -g @iflow-ai/iflow-cli
# Uses `iflow -i` in interactive mode with session resume (`-r`) and execution info output (`-o`).
# 底层使用 `iflow -i` 交互模式，结合 `-r` 会话续聊和 `-o` 执行信息输出。

# [[projects]]
# name = "my-iflow-project"
#
# [projects.agent]
# type = "iflow"
#
# [projects.agent.options]
# work_dir = "/path/to/project"
# mode = "default"  # "default" | "auto-edit" | "plan" | "yolo"
# cmd = "iflow"     # CLI binary name (default: "iflow") / CLI 二进制名称（默认 "iflow"）
#
# Mode options / 模式说明:
# - "default":   Manual approval mode / 手动审批模式
# - "auto-edit": Auto-edit mode / 自动编辑模式
# - "plan":      Read-only planning mode / 只读规划模式
# - "yolo":      Auto-approve all tool calls / 自动批准所有工具调用
#
# Optional: specify a model / 可选：指定模型
# model = "Qwen3-Coder"
#
# # Active provider / 当前激活的 provider
# # provider = "iflow-openai-compatible"
#
# [[projects.agent.providers]]
# name = "iflow-openai-compatible"
# api_key = "sk-xxx"
# base_url = "https://api.example.com/v1"
# model = "Qwen3-Coder"
# env = { IFLOW_selectedAuthType = "openai-compatible" }
#
# [[projects.platforms]]
# type = "telegram"
#
# [projects.platforms.options]
# token = "your-telegram-bot-token"

# =============================================================================
# Project 8: Another example / 项目 8：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 = "auto"
# mode = "bypassPermissions"
#
# [[projects.platforms]]
# type = "discord"
#
# [projects.platforms.options]
# token = "your-discord-bot-token"