Search Results for "state machine editor"
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Showing 263 open source projects for "state machine editor"
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1
Monaco Editor
A browser based code editor
...For example, the model holds the text content, determines the language of the content, and tracks the edit history of the content. An editor is a user facing view of the model. This is what gets attached to the DOM and what your users see visually. Typical editor operations are displaying a model, managing the view state, or executing actions or commands. -
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FSM for Go
Finite State Machine for Go
FSM is a finite state machine for Go. It is heavily based on two FSM implementations. Javascript Finite State Machine, and Fysom for Python. Visualize outputs a visualization of a FSM in Graphviz format. VisualizeForMermaidWithGraphType outputs a visualization of a FSM in Mermaid format as specified by the graphType. VisualizeWithType outputs a visualization of a FSM in the desired format. -
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Spring Statemachine
Framework for application developers to use state machine concepts
The Spring Statemachine project aims to provide a common infrastructure to work with state machine concepts in Spring applications. It is advised to check the actual state of this project by referring to the latest releases found on the Spring Statemachine Project Page. The git repo default branch may be relatively unstable when new features are added to the source code. Spring Statemachine uses a Gradle-based build system. -
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XState
State machines and statecharts for the modern web
JavaScript and TypeScript finite state machines and statecharts for the modern web. Statecharts are a formalism for modeling stateful, reactive systems. This is useful for declaratively describing the behavior of your application, from the individual components to the overall application logic. XState is a library for creating, interpreting, and executing finite state machines and statecharts, as well as managing invocations of those machines as actors. The following fundamental computer... -
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5
zag
Finite state machines for building accessible design systems and UI
A collection of framework-agnostic UI components patterns like an accordion, menu, and dialog that can be used to build design systems for React, Vue, and Solid.js. Simple, resilient component logic. Write component logic once and use it anywhere. Built-in adapters that connect machine output to DOM semantics in a WAI-ARIA-compliant way. Component logic is largely JavaScript code and can be consumed in any JS framework. Zag machine APIs are completely headless and unstyled. Use your favorite styling solution and get it matching your design system. Finite state machines for building accessible design systems and UI components. ... -
6
ecode
Lightweight multi-platform code editor designed for modern hardware
ecode is a lightweight multi-platform code editor designed for modern hardware with a focus on responsiveness and performance. It has been developed with the hardware-accelerated eepp GUI, which provides the core technology for the editor. The project comes as the first serious project using the eepp GUI, and it's currently being developed to improve the eepp GUI library as part of one of its main objectives. -
7
Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. ... -
8
Flower
Flower: A Friendly Federated Learning Framework
...Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
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ARK
Unstyled, accessible UI components for your design System
Ark is a headless UI component library designed to provide the foundational logic required to build scalable and accessible design systems for modern web applications. The project focuses on separating component behavior from visual styling so developers can implement their own design language without being constrained by predefined styles. Built on top of Zag.js state machines, Ark delivers predictable and robust component logic that works consistently across multiple JavaScript frameworks.... -
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Vagrant
Vagrant is a tool for building and distributing environments
...Download the open-source Vagrant binary and run it locally or within your environments. Vagrant is designed for everyone as the simplest and fastest way to create a virtualized environment. Single workflow to build and manage virtual machine environments. Declarative configuration file describes all the requirements and builds them through a consistent workflow. Mirror production environments by providing the same operating system, packages, users, and configurations, all while giving users the flexibility to use their favorite editor, IDE, and browser. Share files and folders between a local machine and the Vagrant box. ... -
11
macOS (Dockur)
macOS inside a Docker container
dockur/macos packages a macOS virtual machine inside a Docker container using QEMU/KVM, making it easy to spin up a macOS environment on a Linux host. It provides sensible defaults for firmware, disk, and devices, plus a browser-accessible VNC console so you can complete installation and interact with the desktop remotely. Typical inputs—like environment variables and mounted volumes—control edition choice, storage persistence, and resource sizing, which makes runs repeatable and disposable. ... -
12
DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
14
VVV
An open source Vagrant configuration for developing with WordPress
...VVV is ideal for developing themes and plugins as well as for contributing to WordPress core. Approachable development environment with a modern server configuration. Stable state of software and configuration in default provisioning. Excellent and clear documentation to aid in learning and scaffolding. VVV requires recent versions of both Vagrant and VirtualBox to be installed. Vagrant is a “tool for building and distributing development environments”. It works with virtualization software such as VirtualBox to provide a virtual machine sandboxed from your local environment. ... -
15
FlowRedux
Kotlin Multiplatform Statemachine library with nice DSL based on Flow
Building async. running Kotlin Multiplatform state machine made easy with a DSL and coroutines. -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your... -
17
AvalonEdit
The WPF-based text editor component used in SharpDevelop
AvalonEdit is the name of the WPF-based text editor in SharpDevelop 4.x "Mirador" and beyond. It is also being used in ILSpy and many other projects. AvalonEdit is targeting net6.0-windows and net462 TFMs. Because of net6.0-windows, you must have the .NET 6.0 SDK installed on your machine. Visual Studio 2022 Community and up is required for working with the solution (global.json will select the proper SDK to use for building for you). -
18
HASS Configurator
Configuration UI for Home Assistant
The HASS Configurator is a small web app (you access it via a web browser) that provides a filesystem browser and text-editor to modify files on the machine the configurator is running on. It has been created to allow easy configuration of Home Assistant. It is powered by Ace editor, which supports syntax highlighting for various code/markup languages. YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. ... -
19
Pry
A runtime developer console and IRB alternative
...It offers command-driven navigation of objects and modules, syntax-highlighted input, command history, and the ability to switch contexts or “cd” into objects to inspect their methods and state. Features like show-source and show-doc reveal the implementation or documentation of methods without leaving the console, while edit-method lets you jump into an editor, modify code, and reload it on the fly. Dropping binding.pry into application code creates interactive breakpoints, making it easy to poke at variables, step through logic (with plugins like pry-byebug), and test hypotheses. ... -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU,... -
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reveal.js
The HTML Presentation Framework
reveal.js is a framework for creating beautiful interactive presentations using HTML. It comes with a wide range of features, including nested slides, auto-sliding, touch navigation, Markdown support, PDF export, speaker notes, theming and more. It also comes with a JavaScript API that allows you to control various other options, and a list of plugins that can be used to extend reveal.js further. reveal.js currently offers full support for any recently released version of the following... -
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The Acton programming language
The Acton Programming Language
...Acton programs, and the actor model, work well from simple script-style applications on a single machine up to large distributed systems across a Data Center. Run at your scale. -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
25
Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests.