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teamclawtestv101

A high-performance Agent subsystem designed for complex multi-agent orchestration (OASIS),automated computer use tasks, and real-time visual monitoring via a dedicated Web UI.

Audits

Warn
ClawScanWarn

Agentic behavior and permission review.

Static analysisPending

Pattern checks against bundled files.

VirusTotalPass

Multi-engine malware detections and file reputation.

Install

openclaw skills install teamclawtestv101

Language: English | 中文

<a name="english-version"></a>

Teamclaw — Agent Subsystem Skill (English)

Overview

Teamclaw is a multifunctional AI Agent service providing:

  • Conversational Agent: A multi-tool AI assistant based on LangGraph that supports streaming/non-streaming conversations
  • OASIS Forum: A multi-expert parallel discussion/execution engine that orchestrates collaboration among multiple Agents
  • Scheduled Tasks: A task scheduling center based on APScheduler
  • Bark Push: Mobile push notifications
  • Web UI Frontend: A complete chat interface

Skill Scripts

All scripts are located in selfskill/scripts/ and are called uniformly through the run.sh entry point. All are non-interactive.

selfskill/scripts/
├── run.sh          # Main entry (start/stop/status/setup/add-user/configure)
├── adduser.py      # Non-interactive user creation
└── configure.py    # Non-interactive .env configuration management

Quick Start

All commands are executed from the project root directory.

1. Initial Deployment

# Install dependencies
bash selfskill/scripts/run.sh setup

# Initialize configuration file
bash selfskill/scripts/run.sh configure --init

# Configure LLM (required)
bash selfskill/scripts/run.sh configure --batch \
  LLM_API_KEY=sk-your-key \
  LLM_BASE_URL=https://api.deepseek.com \
  LLM_MODEL=deepseek-chat

# Create user
bash selfskill/scripts/run.sh add-user system MySecurePass123

2. Start/Stop/Status

bash selfskill/scripts/run.sh start     # Start background service
bash selfskill/scripts/run.sh status    # Check status
bash selfskill/scripts/run.sh stop      # Stop service

3. Configuration Management

# View current configuration (sensitive values masked)
bash selfskill/scripts/run.sh configure --show

# Set single item
bash selfskill/scripts/run.sh configure PORT_AGENT 51200

# Batch set
bash selfskill/scripts/run.sh configure --batch TTS_MODEL=gemini-2.5-flash-preview-tts TTS_VOICE=charon

Configurable Items

Configuration ItemDescriptionDefault Value
LLM_API_KEYLLM API key (required)—
LLM_BASE_URLLLM API addresshttps://api.deepseek.com
LLM_MODELModel namedeepseek-chat
LLM_PROVIDERProvider (google/anthropic/deepseek/openai, auto-inferred)Auto
LLM_VISION_SUPPORTImage support (auto-inferred)Auto
PORT_AGENTMain Agent service port51200
PORT_SCHEDULERScheduling port51201
PORT_OASISOASIS forum port51202
PORT_FRONTENDWeb UI port51209
PORT_BARKBark push port58010
TTS_MODELTTS model (optional)—
TTS_VOICETTS voice (optional)—
INTERNAL_TOKENInternal communication key (auto-generated)Auto

Ports and Services

PortService
51200AI Agent main service
51201Scheduled tasks
51202OASIS forum
51209Web UI

API Authentication

Method 1: User Authentication

Authorization: Bearer <user_id>:<password>

Method 2: Internal Token (inter-service calls, recommended)

Authorization: Bearer <INTERNAL_TOKEN>:<user_id>

INTERNAL_TOKEN is auto-generated on the first startup and can be viewed via configure --show-raw.

Core APIs

Base URL: http://127.0.0.1:51200

Chat (OpenAI Compatible)

POST /v1/chat/completions
Authorization: Bearer <token>

{"model":"mini-timebot","messages":[{"role":"user","content":"Hello"}],"stream":true,"session_id":"my-session"}

System Trigger (Internal Call)

POST /system_trigger
X-Internal-Token: <INTERNAL_TOKEN>

{"user_id":"system","text":"Execute task","session_id":"task-001"}

Cancel Session

POST /cancel

{"user_id":"<user_id>","session_id":"<session_id>"}

OASIS Discussion/Execution

POST http://127.0.0.1:51202/topics

{"question":"Discussion topic","user_id":"system","max_rounds":3,"discussion":true,"schedule_yaml":"...","callback_url":"http://127.0.0.1:51200/system_trigger","callback_session_id":"my-session"}

Example Configuration Reference

Below is a sample configuration from an actual running instance (sensitive information masked):

bash selfskill/scripts/run.sh configure --init
bash selfskill/scripts/run.sh configure --batch \
  LLM_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx4c74 \
  LLM_BASE_URL=https://deepseek.com \
  LLM_MODEL=deepseek-chat \
  LLM_VISION_SUPPORT=true \
  TTS_MODEL=gemini-2.5-flash-preview-tts \
  TTS_VOICE=charon \
  PORT_AGENT=51200 \
  PORT_SCHEDULER=51201 \
  PORT_OASIS=51202 \
  PORT_FRONTEND=51209 \
  PORT_BARK=58010 \
  OPENAI_STANDARD_MODE=false
bash selfskill/scripts/run.sh add-user system <your-password>

Output of configure --show after configuration:

  PORT_SCHEDULER=51201
  PORT_AGENT=51200
  PORT_FRONTEND=51209
  PORT_OASIS=51202
  OASIS_BASE_URL=http://127.0.0.1:51202
  PORT_BARK=58010
  INTERNAL_TOKEN=f1aa****57e7          # Auto-generated, do not leak
  LLM_API_KEY=sk-7****4c74
  LLM_BASE_URL=https://deepseek.com
  LLM_MODEL=deepseek-chat
  LLM_VISION_SUPPORT=true
  TTS_MODEL=gemini-2.5-flash-preview-tts
  TTS_VOICE=charon
  OPENAI_STANDARD_MODE=false

Note: INTERNAL_TOKEN is auto-generated on first startup, PUBLIC_DOMAIN / BARK_PUBLIC_URL are auto-written by tunnel, no manual configuration needed.

Typical Usage Workflow

cd /home/avalon/Teamclaw

# Initial configuration
bash selfskill/scripts/run.sh setup
bash selfskill/scripts/run.sh configure --init
bash selfskill/scripts/run.sh configure --batch LLM_API_KEY=sk-xxx LLM_BASE_URL=https://api.deepseek.com LLM_MODEL=deepseek-chat
bash selfskill/scripts/run.sh add-user system MyPass123

# Start service
bash selfskill/scripts/run.sh start

# Access Web UI
# Open browser and navigate to: http://127.0.0.1:51209
# Log in with username: system and password: MyPass123

# Call API
curl -X POST http://127.0.0.1:51200/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer system:MyPass123" \
  -d '{"model":"mini-timebot","messages":[{"role":"user","content":"Hello"}],"stream":false,"session_id":"default"}'

# Stop service
bash selfskill/scripts/run.sh stop

Important Notes

  • All skill scripts are located in selfskill/scripts/ and do not affect the original project functionality
  • Process management via PID files; start supports idempotent calls
  • Do not leak INTERNAL_TOKEN
  • Log path: logs/launcher.log
  • How to Enable Visualization & Login:
    • After starting the service, open your browser and navigate to http://127.0.0.1:51209
    • Use the credentials you created with add-user command (default: username system, password MySecurePass123)
    • You can now access the chat interface and participate in OASIS forum discussions

<a name="中文版本"></a>

Teamclaw — Agent 子系统 Skill (中文)

简介

Teamclaw 是一个多功能 AI Agent 服务，提供：

  • 对话 Agent：基于 LangGraph 的多工具 AI 助手，支持流式/非流式对话
  • OASIS 论坛：多专家并行讨论/执行引擎，可编排多个 Agent 协作
  • 定时调度：基于 APScheduler 的任务调度中心
  • Bark 推送：移动端推送通知
  • 前端 Web UI：完整的聊天界面

Skill 脚本

所有脚本位于 selfskill/scripts/，统一通过 run.sh 入口调用，全部非交互式。

selfskill/scripts/
├── run.sh          # 主入口（start/stop/status/setup/add-user/configure）
├── adduser.py      # 非交互式用户创建
└── configure.py    # 非交互式 .env 配置管理

快速启动

所有命令在项目根目录下执行。

1. 首次部署

# 安装依赖
bash selfskill/scripts/run.sh setup

# 初始化配置文件
bash selfskill/scripts/run.sh configure --init

# 配置 LLM（必填）
bash selfskill/scripts/run.sh configure --batch \
  LLM_API_KEY=sk-your-key \
  LLM_BASE_URL=https://api.deepseek.com \
  LLM_MODEL=deepseek-chat

# 创建用户
bash selfskill/scripts/run.sh add-user system MySecurePass123

2. 启动/停止/状态

bash selfskill/scripts/run.sh start     # 后台启动
bash selfskill/scripts/run.sh status    # 检查状态
bash selfskill/scripts/run.sh stop      # 停止服务

3. 配置管理

# 查看当前配置（敏感值脱敏）
bash selfskill/scripts/run.sh configure --show

# 设置单项
bash selfskill/scripts/run.sh configure PORT_AGENT 51200

# 批量设置
bash selfskill/scripts/run.sh configure --batch TTS_MODEL=gemini-2.5-flash-preview-tts TTS_VOICE=charon

可配置项

配置项说明默认值
LLM_API_KEYLLM API 密钥（必填）—
LLM_BASE_URLLLM API 地址https://api.deepseek.com
LLM_MODEL模型名称deepseek-chat
LLM_PROVIDER厂商（google/anthropic/deepseek/openai，可自动推断）自动
LLM_VISION_SUPPORT是否支持图片（可自动推断）自动
PORT_AGENTAgent 主服务端口51200
PORT_SCHEDULER定时调度端口51201
PORT_OASISOASIS 论坛端口51202
PORT_FRONTENDWeb UI 端口51209
PORT_BARKBark 推送端口58010
TTS_MODELTTS 模型（可选）—
TTS_VOICETTS 声音（可选）—
INTERNAL_TOKEN内部通信密钥（自动生成）自动

端口与服务

端口服务
51200AI Agent 主服务
51201定时调度
51202OASIS 论坛
51209Web UI

API 认证

方式 1：用户认证

Authorization: Bearer <user_id>:<password>

方式 2：内部 Token（服务间调用，推荐）

Authorization: Bearer <INTERNAL_TOKEN>:<user_id>

INTERNAL_TOKEN 首次启动自动生成，可通过 configure --show-raw 查看。

核心 API

Base URL: http://127.0.0.1:51200

对话（OpenAI 兼容）

POST /v1/chat/completions
Authorization: Bearer <token>

{"model":"mini-timebot","messages":[{"role":"user","content":"你好"}],"stream":true,"session_id":"my-session"}

系统触发（内部调用）

POST /system_trigger
X-Internal-Token: <INTERNAL_TOKEN>

{"user_id":"system","text":"请执行某任务","session_id":"task-001"}

终止会话

POST /cancel

{"user_id":"<user_id>","session_id":"<session_id>"}

OASIS 讨论/执行

POST http://127.0.0.1:51202/topics

{"question":"讨论主题","user_id":"system","max_rounds":3,"discussion":true,"schedule_yaml":"...","callback_url":"http://127.0.0.1:51200/system_trigger","callback_session_id":"my-session"}

案例配置参考

以下是一份实际运行的配置示例（敏感信息已脱敏）：

bash selfskill/scripts/run.sh configure --init
bash selfskill/scripts/run.sh configure --batch \
  LLM_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx4c74 \
  LLM_BASE_URL=https://deepseek.com \
  LLM_MODEL=deepseek-chat \
  LLM_VISION_SUPPORT=true \
  TTS_MODEL=gemini-2.5-flash-preview-tts \
  TTS_VOICE=charon \
  PORT_AGENT=51200 \
  PORT_SCHEDULER=51201 \
  PORT_OASIS=51202 \
  PORT_FRONTEND=51209 \
  PORT_BARK=58010 \
  OPENAI_STANDARD_MODE=false
bash selfskill/scripts/run.sh add-user system <your-password>

配置完成后 configure --show 输出：

  PORT_SCHEDULER=51201
  PORT_AGENT=51200
  PORT_FRONTEND=51209
  PORT_OASIS=51202
  OASIS_BASE_URL=http://127.0.0.1:51202
  PORT_BARK=58010
  INTERNAL_TOKEN=f1aa****57e7          # 自动生成，勿泄露
  LLM_API_KEY=sk-7****4c74
  LLM_BASE_URL=https://deepseek.com
  LLM_MODEL=deepseek-chat
  LLM_VISION_SUPPORT=true
  TTS_MODEL=gemini-2.5-flash-preview-tts
  TTS_VOICE=charon
  OPENAI_STANDARD_MODE=false

说明：INTERNAL_TOKEN 首次启动自动生成，PUBLIC_DOMAIN / BARK_PUBLIC_URL 由 tunnel 自动写入，无需手动配置。

典型使用流程

cd /home/avalon/Teamclaw

# 首次配置
bash selfskill/scripts/run.sh setup
bash selfskill/scripts/run.sh configure --init
bash selfskill/scripts/run.sh configure --batch LLM_API_KEY=sk-xxx LLM_BASE_URL=https://api.deepseek.com LLM_MODEL=deepseek-chat
bash selfskill/scripts/run.sh add-user system MyPass123

# 启动
bash selfskill/scripts/run.sh start

# 访问 Web UI
# 打开浏览器导航到：http://127.0.0.1:51209
# 使用用户名：system，密码：MyPass123 登录

# 调用 API
curl -X POST http://127.0.0.1:51200/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer system:MyPass123" \
  -d '{"model":"mini-timebot","messages":[{"role":"user","content":"你好"}],"stream":false,"session_id":"default"}'

# 停止
bash selfskill/scripts/run.sh stop

注意事项

  • 所有 skill 脚本位于 selfskill/scripts/，不影响项目原有功能
  • 通过 PID 文件管理进程，start 支持幂等调用
  • INTERNAL_TOKEN 勿泄露
  • 日志路径: logs/launcher.log
  • 如何开启可视化界面和登录：
    • 启动服务后，打开浏览器导航到 http://127.0.0.1:51209
    • 使用通过 add-user 命令创建的凭证（默认：用户名 system，密码 MySecurePass123）
    • 即可访问聊天界面并参与 OASIS 论坛讨论