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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
The first open-source Artificial Narrow Intelligence generalist agentic framework Computer-Using-Agent that fully operates graphical-user-interfaces (GUIs) by using only natural language. Uses Visualization-of-Thought and Chain-of-Thought reasoning to elicit spatial reasoning and perception, emulates, plans and simulates synthetic HID interactions.
| Date | Stars |
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| 2026-07-31 | 1344 |
| 2026-08-02 | 1344 |
| 2026-08-06 | 1344 |
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**PyWinAssistant: An artificial assistant** – **MIT Licensed** | **Public Release: December 31, 2023** | Complies with federal coordinations AI Standards for Complex Adaptive Systems, Asilomar AI Principles and IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. --- PyWinAssistant is the first open-source Artificial Narrow Intelligence to elicit spatial reasoning and perception as a generalist agentic framework Computer-Using-Agent that fully operates graphical-user-interfaces (GUIs) for Windows 10/11 **through direct OS-native semantic interaction**. It functions as a Computer-Using-Agent / Large-Action-Model, forming the foundation for a pure **symbolic spatial cognition framework** that enables artificial operation of a computer using only natural language, **without relying on computer vision, OCR, or pixel-level imaging**. PyWinAssistant emulates, plans, and simulates synthetic Human-Interface-Device (HID) interactions through **native Windows Accessibility APIs**, eliciting human-like abstraction across geometric, hierarchical, and temporal dimensions at an Operating-System level. This OS-integrated approach simulating spatial utilization of a computer provides a future-proof, generalized, modular, and dynamic ANI orchestration framework for multi-agent-driven automation, marking an important step in symbolic reasoning towards AGI. **Key Features:** * **Not relying only on Imaging Pipeline**: Operates exclusively through Windows UI Automation (UIA) and programmatic GUI semantics, enabling universal workflow orchestration. * **Symbolic Spatial Mapping**: Hierarchical element tracking via OS-native parent/child relationships and coordinate systems. * **Non-Visual Perception**: Real-time interface understanding through direct metadata extraction (control types, states, positions). * **Visual Perception**: A single screenshot can elicit comprehension and perception with attention to detail by visualizing goal intent and environment changes in a spatial space over time, can be fine-tuned to look up for visual cues, bugs, causal reasoning bugs, static, semantic grounding, errors, corruption... * **Unified Automation**: Automatic element detection. Combines GUI, system, and web automation under one Python API. Eliminates context-switching between tools. * **AI-Powered Script Generation**: Translates natural language or demonstrations into any kind of code inside any IDE or text edit areas. * **Self-Healing Workflows**: Auto-adjusts to UI changes (e.g., element ID shifts). Reducing maintenance overhead, making PyWinAssistant's algorithm future-proof. * **AI/ML Integration**: Using NLP to generate scripts (e.g., “Automate Application” → plan of test execution steps in JSON) with self-correcting selectors. * **Cross-Context Automation**: Seamlessly combining GUI, web, and API workflows in a Pythonic way, unifying disjointed automation methods (GUI, API, web) into a single framework. * **Accessibility**: Enhancing accessibility for users with different needs, enabling voice or simple text commands to control complex actions. * **Generalization**: Elicits spatial cognition to understand and execute a wide range of commands in a natural, intuitive manner. * **Small and compact**: PyWinAssistant functions as an example algorithm of a modular and generalized computer assistant framework that elicits spatial cognition. PyWinAssistant has its own set of **reasoning agents**, utilizing Visualization-of-Thought (VoT) and Chain-of-Thought (CoT) to enhance generalization, dynamically simulating actions through abstract GUI semantic dimensions rather than visual processing, making it **future-proof** for next-generation **LLM models**. By **visualizing interface contents** to dynamically **simulate and plan actions** over **abstract GUI semantic dimensions, concepts, and differentials**, PyWinAssistant **redefines computer vision automation**, enabling **high-efficiency vi
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b77241c54a4be8d0, desc:agentic