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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...
高性能代理子系统，专为复杂多代理编排（OASIS）、自动化计算机使用任务和实时视觉监控而设计，...
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未分类 clawhub v1.0.0 1 版本 99484.5 Key: 需要
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概述

> Language: English | 中文

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 Item | Description | Default Value |

|--------|------|--------|

| LLM_API_KEY | LLM API key (required) | — |

| LLM_BASE_URL | LLM API address | https://api.deepseek.com |

| LLM_MODEL | Model name | deepseek-chat |

| LLM_PROVIDER | Provider (google/anthropic/deepseek/openai, auto-inferred) | Auto |

| LLM_VISION_SUPPORT | Image support (auto-inferred) | Auto |

| PORT_AGENT | Main Agent service port | 51200 |

| PORT_SCHEDULER | Scheduling port | 51201 |

| PORT_OASIS | OASIS forum port | 51202 |

| PORT_FRONTEND | Web UI port | 51209 |

| PORT_BARK | Bark push port | 58010 |

| TTS_MODEL | TTS model (optional) | — |

| TTS_VOICE | TTS voice (optional) | — |

| INTERNAL_TOKEN | Internal communication key (auto-generated) | Auto |

Ports and Services

| Port | Service |

|------|------|

| 51200 | AI Agent main service |

| 51201 | Scheduled tasks |

| 51202 | OASIS forum |

| 51209 | Web 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

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_KEY | LLM API 密钥（必填） | — |

| LLM_BASE_URL | LLM 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_AGENT | Agent 主服务端口 | 51200 |

| PORT_SCHEDULER | 定时调度端口 | 51201 |

| PORT_OASIS | OASIS 论坛端口 | 51202 |

| PORT_FRONTEND | Web UI 端口 | 51209 |

| PORT_BARK | Bark 推送端口 | 58010 |

| TTS_MODEL | TTS 模型（可选） | — |

| TTS_VOICE | TTS 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 |

|------|------|

| 51200 | AI Agent 主服务 |

| 51201 | 定时调度 |

| 51202 | OASIS 论坛 |

| 51209 | Web 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

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-05-12 06:17 安全 安全

安全检测

腾讯云安全 (Keen)

安全，无风险
查看报告

腾讯云安全 (Sanbu)

安全，无风险
查看报告

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