# pc-agent-loop **Repository Path**: yngeek/pc-agent-loop ## Basic Information - **Project Name**: pc-agent-loop - **Description**: （Advantage AI Agent 实验室，由深圳夸夸菁领科技有限公司与复旦大学知识工场实验室联合成立的科研团队）研发的新型智能体：GenericAgent。 - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-03-02 - **Last Updated**: 2026-03-10 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # GenericAgent — 3,300 Lines to Full OS Autonomy [English](#english) | [中文](#chinese) A minimalist autonomous agent framework that gives any LLM physical-level control over your PC — browser, terminal, file system, keyboard, mouse, screen vision, and mobile devices — in ~3,300 lines of Python. No Electron. No Docker. No Mac Mini. No 500K-line codebase. No paid installation service. ## See It in Action

"Order me a milk tea" — navigates a delivery app, picks items, and checks out.
"Find GEM stocks with EXPMA golden cross, turnover > 5%" — quantitative screening via mootdx.

Autonomous web exploration — browses and summarizes on its own schedule.
"Find expenses over ¥2K in the past 3 months" — drives Alipay on a phone via ADB.
WeChat batch messaging — yes, it can drive WeChat too.
## What Happens When You Use It ``` You: "Read my WeChat messages" Agent: installs dependencies → reverse-engineers DB → writes reader script → saves as SOP Next time: instant recall, zero setup. You: "Monitor stock prices and alert me" Agent: installs mootdx → builds screening workflow → sets up scheduled task → saves as SOP Next time: one sentence to run. You: "Send this file via Gmail" Agent: configures OAuth → writes send script → saves as SOP Next time: just works. ``` **Dogfooding**: This repository — from installing Git to `git init`, writing this README, to every commit message — was built entirely by GenericAgent without the author opening a terminal once. Every task the agent solves becomes a permanent skill. After a few weeks, your instance has a unique skill tree — grown entirely from 3,300 lines of seed code. ## The Seed Philosophy Most agent frameworks ship as finished products. GenericAgent ships as a **seed**. The 5 core SOPs define how the agent thinks, remembers, and operates. From there, every new capability is discovered and recorded by the agent itself: 1. You ask it to do something new 2. It figures out how (install dependencies, write scripts, test) 3. It saves the procedure as a new SOP in its memory 4. Next time, it recalls and executes directly The agent doesn't just execute — it **learns and remembers**. ## Quick Start > 💡 **Windows零基础用户**：不知道Python是什么？[下载便携版](http://kw.fudan.edu.cn/resources/PC-Agent-Portable.zip)（19MB，解压即用） ```bash # 1. Clone git clone https://github.com/lsdefine/pc-agent-loop.git cd pc-agent-loop # 2. Install minimal deps pip install streamlit pywebview # 3. Configure API key cp mykey_template.py mykey.py # Edit mykey.py with your LLM API key # 4. Launch python launch.pyw ``` **Also runs on Android** — tested successfully on Termux with `python agentmain.py` (CLI frontend): ```bash # In Termux cd /sdcard/ga python agentmain.py ``` Once running, tell the agent: *"Execute web setup SOP to unlock browser tools"* — it handles the rest. See [WELCOME_NEW_USER.md](WELCOME_NEW_USER.md) for the full bootstrap sequence. ## vs. Alternatives | | GenericAgent | OpenClaw | Claude Code | |---|---|---|---| | Codebase | ~3,300 lines | ~530,000 lines | Open-source (large) | | Deploy | `pip install` + API key | Multi-service orchestration | CLI + subscription | | Browser | Injects into real browser (keeps login state) | Sandboxed/headless | Via MCP plugins | | OS Control | Keyboard, mouse, vision, ADB | Multi-agent delegation | File + terminal | | Self-evolution | Grows SOPs & tools autonomously | Plugin ecosystem | Stateless per session | | Core shipped | 10 .py + 5 SOPs | Hundreds of modules | Rich CLI toolkit | ## How It Works ``` User instruction ↓ ┌─────────────────────┐ │ agent_loop.py (92L) │ ← Sense-Think-Act cycle │ "What do I know? │ │ What should I do?" │ └────────┬────────────┘ ↓ ┌─────────────────────┐ │ 7 Atomic Tools │ ← All capabilities derive from these │ code_run │ Execute any Python/PowerShell │ file_read/write │ Direct disk access │ file_patch │ Surgical code edits │ web_scan │ Read live web pages │ web_execute_js │ Control browser DOM │ ask_user │ Human-in-the-loop └────────┬────────────┘ ↓ ┌─────────────────────┐ │ Memory System │ ← Persistent across sessions │ L0: Meta-SOP │ How to manage memory itself │ L2: Global Facts │ Environment, credentials, paths │ L3: Task SOPs │ Learned procedures (self-growing) └─────────────────────┘ ``` The agent starts with 7 primitive tools. Through `code_run`, it can install packages, write scripts, and interface with any hardware or API — effectively manufacturing new tools at runtime.
What Ships in the Box **Core engine** (runs the agent): - `agent_loop.py` — Sense-Think-Act loop (92 lines) - `ga.py` — Tool definitions and execution - `sidercall.py` — LLM communication (multi-backend) - `agentmain.py` — Session orchestration **Interface** (talk to the agent): - `stapp.py` — Streamlit web UI - `tgapp.py` — Telegram bot interface - `launch.pyw` — One-click launcher with floating window **Infrastructure**: - `TMWebDriver.py` — Browser injection bridge (not Selenium — injects JS into your real browser via Tampermonkey) - `simphtml.py` — HTML→text cleaner for web perception **5 Core SOPs** (shipped, version-controlled): 1. `memory_management_sop` — L0 constitution: how the agent manages its own memory 2. `autonomous_operation_sop` — Self-directed task execution 3. `scheduled_task_sop` — Cron-like recurring tasks 4. `web_setup_sop` — Browser environment bootstrap 5. `ljqCtrl_sop` — Desktop physical control (keyboard, mouse, DPI-aware) Everything else — Gmail integration, WeChat automation, vision APIs, game downloaders, stock analysis workflows — the agent builds and memorizes on its own through use.
--- # GenericAgent — 3,300 行代码，完整 OS 级自主控制 一个极简自主 Agent 框架。用约 3,300 行 Python，让任意 LLM 获得对你 PC 的物理级控制能力——浏览器、终端、文件系统、键鼠、屏幕视觉、移动设备。 不需要 Electron，不需要 Docker，不需要 Mac Mini，不需要 53 万行代码，不需要付费安装服务。 ## 用起来是什么样的 ``` 你："帮我读取微信消息" Agent：安装依赖 → 逆向数据库 → 写读取脚本 → 保存为 SOP 下次：一句话直接调用，零配置。 你："帮我监控股票并提醒" Agent：安装 mootdx → 构建选股工作流 → 设置定时任务 → 保存为 SOP 下次：一句话启动。 你："用 Gmail 发这个文件" Agent：配置 OAuth → 写发送脚本 → 保存为 SOP 下次：直接能用。 ``` **自举实证**：本仓库从安装 Git、`git init`、编写 README 到每一条 commit message，全程由 GenericAgent 完成——作者没有打开过一次终端。 每个解决过的任务都会变成永久技能。用几周后，你的 Agent 实例会拥有一套独特的技能树——全部从 3,300 行种子代码中生长出来。 ## 自举哲学 多数 Agent 框架以成品形态发布。GenericAgent 以**种子**形态发布。 5 个核心 SOP 定义了 Agent 如何思考、记忆和行动。之后的一切能力，由 Agent 在使用中自主发现并记录： 1. 你让它做一件新事 2. 它自己摸索方法（安装依赖、写脚本、测试） 3. 把流程保存为新 SOP 4. 下次直接调用 Agent 不只是执行——它**学习并记忆**。 ## 快速开始 ```bash # 1. 克隆 git clone https://github.com/lsdefine/pc-agent-loop.git cd pc-agent-loop # 2. 安装最小依赖 pip install streamlit pywebview # 3. 配置 API Key cp mykey_template.py mykey.py # 编辑 mykey.py 填入你的 LLM API Key # 4. 启动 python launch.pyw ``` **同样可在 Android 上运行** — 已在 Termux 上测试通过，通过 `python agentmain.py`（CLI 前端）启动： ```bash # 在 Termux 中 cd /sdcard/ga python agentmain.py ``` 启动后告诉 Agent："执行 web setup SOP 解锁浏览器工具"——剩下的它自己搞定。完整引导流程见 [WELCOME_NEW_USER.md](WELCOME_NEW_USER.md)。 ## 对比 | | GenericAgent | OpenClaw | Claude Code | |---|---|---|---| | 代码量 | ~3,300 行 | ~530,000 行 | 已开源（体量大） | | 部署 | `pip install` + API key | 多服务编排 | CLI + 订阅 | | 浏览器 | 注入真实浏览器（保留登录态） | 沙箱/无头浏览器 | 通过 MCP 插件 | | OS 控制 | 键鼠、视觉、ADB | 多 Agent 委派 | 文件 + 终端 | | 自我进化 | 自主生长 SOP 和工具 | 插件生态 | 会话间无状态 | | 出厂配置 | 10 个 .py + 5 个 SOP | 数百模块 | 丰富 CLI 工具集 | ## 工作原理 Agent 拥有 7 个原子工具：`code_run`（执行任意代码）、`file_read/write/patch`（文件操作）、`web_scan`（网页感知）、`web_execute_js`（浏览器控制）、`ask_user`（人机协作）。 通过 `code_run`，它可以安装任何包、编写任何脚本、对接任何硬件——相当于在运行时制造新工具。学到的流程保存为 SOP，下次直接调用。 核心循环只有 92 行（`agent_loop.py`）：感知 → 思考 → 行动 → 记忆。
出厂清单 **核心引擎**： - `agent_loop.py` — 感知-思考-行动循环（92 行） - `ga.py` — 工具定义与执行 - `sidercall.py` — LLM 通信（多后端） - `agentmain.py` — 会话编排 **交互界面**： - `stapp.py` — Streamlit Web UI - `tgapp.py` — Telegram 机器人 - `launch.pyw` — 一键启动 + 悬浮窗 **基础设施**： - `TMWebDriver.py` — 浏览器注入桥接（非 Selenium，通过 Tampermonkey 注入真实浏览器） - `simphtml.py` — HTML→文本清洗 **5 个核心 SOP**（出厂自带，版本控制）： 1. `memory_management_sop` — L0 宪法：Agent 如何管理自身记忆 2. `autonomous_operation_sop` — 自主任务执行 3. `scheduled_task_sop` — 定时任务 4. `web_setup_sop` — 浏览器环境引导 5. `ljqCtrl_sop` — 桌面物理控制（键鼠、DPI 感知） 其余一切——Gmail、微信自动化、视觉 API、游戏下载、股票分析——都是 Agent 在使用中自主构建并记忆的。
## 许可 MIT