easytrader is a Python library for automating Chinese stock trading. It supports multiple broker types through three parallel branches: (1) Windows desktop GUI automation using pywinauto for brokers like ιΆζ²³, εζ³°, ε½ι, etc.; (2) Web API trading for Xueqiu (ιͺη) portfolio rebalancing; (3) Official QMT SDK integration via miniqmt for θΏ ζ-based brokers. Additionally, it provides strategy following from JoinQuant, RiceQuant, and Xueqiu platforms, enabling mirroring of simulated trades into real accounts. The architecture uses a factory pattern (easytrader.use() and easytrader.follower()) to create broker-specific trader instances, with abstract base classes (ClientTrader, WebTrader, BaseFollower) implementing common operations like buy/sell/query. A Flask-based remote server mode allows separation of trading client and strategy execution machines. The code is well-structured with clear separation of concerns: config files define broker-specific UI control IDs, strategy patterns for grid data extraction (Copy, Xls) and data refresh (Switch, Toolbar) allow customization without changing core logic. The follower framework includes command expiration, slippage modeling, and multi-user/multi-strategy support. The miniqmt module wraps the proprietary xtquant SDK into the same easy-to-use interface. While the desktop GUI components are Windows-only and tightly coupled to specific broker client binaries, the web-based trader and follower modules are more portable. The library has been actively maintained for years with a large user base (10k+ stars), though some dependencies like pywinauto 0.6.6 and Python 3.6+ show signs of technical drift.
AutoPy is a cross-platform GUI automation library implemented in Rust and exposed to Python through PyO3. It provides programmatic control of the mouse and keyboard, screen capture, bitmap pixel inspection, and color detection. The library abstracts over Windows, macOS, and X11 backends, so the same Python API works across desktop platforms. It is distributed as a Python extension module built with maturin/setuptools-rust and is also usable as a Rust crate.
UFO (UI-Focused agent) and Galaxy constitute a multi-agent AI framework for automating GUI-based tasks across Windows, Linux, and mobile platforms. The system uses LLM-driven agents (AppAgent, HostAgent, ConstellationAgent) that interact with desktop applications via UI automation (UIA, COM) and execute distributed task workflows modeled as DAGs (task constellations). It includes a client-server architecture with WebSocket-based Agent Interaction Protocol (AIP), MCP tool servers, a configurable RAG knowledge substrate, and a Web UI (React+FastAPI) for real-time monitoring and control. The framework is primarily an application with strong research elements: it supports trajectory analysis, evaluation agents, demonstration learning, and configurable LLM backends (OpenAI, Claude, Gemini, DeepSeek, Ollama).
This repository is a comprehensive family of GUI automation agents (Mobile-Agent series) developed by Tongyi Lab, Alibaba Group. It provides end-to-end solutions for automating interactions across mobile (Android), desktop (Windows/macOS/Linux), and web platforms using vision-language models. The system perceives GUI elements through screenshots, grounds natural language instructions to actionable commands (click, type, scroll), and executes tasks via platform-specific controllers. The architecture includes multiple agent versions (v1-v3.5, E, UI-S1, PC-Agent) with shared core modules for perception, action parsing, and controller interfaces, alongside training frameworks (VERL) and evaluation suites (Android World, MiniWoB, Mind2Web). Key entry points are version-specific run scripts (e.g., run_ma35.py) and API services for remote agent control. The system relies on external dependencies like ADB for Android, PyAutoGUI for desktop, Playwright for web, and VLMs (Qwen series) for reasoning.
Open-AutoGLM (Phone Agent) is an AI-powered mobile automation framework that uses vision-language models to understand phone screens and execute user tasks through automated touch, swipe, and text input operations. The system works by repeatedly capturing device screenshots, sending them to a vision model (AutoGLM-Phone-9B or compatible API), parsing the model's decision into actionable commands, and executing those commands via platform-specific debugging tools (ADB for Android, HDC for HarmonyOS, WebDriverAgent for iOS). The architecture employs a device factory pattern to abstract platform differences behind a unified interface, an OpenAI-compatible model client with streaming and performance metrics, and a command-based action handler that supports tap, type, swipe, launch, back, home, long press, and takeover operations. The repository is structured as both a CLI application and a Python library, with comprehensive configuration for 50+ Android apps, 60+ HarmonyOS apps, and 100+ iOS apps, along with bilingual system prompts (Chinese/English), configurable timing parameters, and callback hooks for sensitive operation confirmation and manual intervention. Notable features include remote debugging support, verbose step-by-step execution with model thinking output, and integration with third-party model hosting services.