Open Source ChromeOS Software - Page 99
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Software for ChromeOS
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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Lobe Icons
Brings AI/LLM brand logos to your React & React Native apps
Lobe Icons is an open-source icon library designed to provide developers with a comprehensive collection of logos and visual assets representing popular artificial intelligence platforms, language models, and related technologies. The project focuses on making it easy for developers to include recognizable AI brand icons in applications such as dashboards, AI tools, documentation sites, or developer portals. The library includes icons for a wide range of AI providers and models, allowing developers to visually represent integrations with tools such as large language models, AI APIs, and machine learning platforms. These icons are distributed in multiple formats including SVG, PNG, and WebP so they can be used in both web and mobile applications. -
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Locker Password Manager
Open source secure password manager
Locker is a password manager that goes beyond the mere concept of password management. Whatever your previous password manager provided, we offer even more. Store passwords, passkeys and personal data in one encrypted vault. Manage effectively with categories and folders. Save your passwords with a click, login and checkout made effortlessly with auto-saving and auto-fill features from passwords, payment details to two-factor authentication passcodes. Locker password manager is available anytime on any platform and device, whether it is a web browser, extensions, mobile apps or desktop apps. Share passwords and sensitive data with your friends and colleagues quickly and securely. Or share items with anyone, even if they don't use Locker. -
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Loggifly
Get Alerts from your Docker Container Logs
LoggiFly is a lightweight, open-source monitoring tool designed to watch Docker container logs in real time and trigger alerts, notifications, or automated actions based on predefined keywords or regular expression patterns. Instead of manually scanning logs for issues or relying solely on centralized monitoring stacks, LoggiFly proactively inspects streams of container output and notifies users through services like Ntfy, Slack, Discord, Telegram, or webhooks when significant events occur. It supports plain text, regex, and multi-line pattern matching, and its flexible alert templating lets operators tailor messages for clarity and context, including attaching relevant log excerpts. Beyond notifications, LoggiFly can take automated actions such as restarting or stopping containers when specific critical patterns are detected, which is especially useful for preventing damage from misbehaving services. -
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LongWriter
Unleashing 10,000+ Word Generation from Long Context LLMs
LongWriter is an open-source framework and set of large language models designed to enable ultra-long text generation that can exceed 10,000 words while maintaining coherence and structure. Traditional large language models can process large inputs but often struggle to generate long outputs due to limitations in training data and alignment strategies. LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer responses. The system uses an agent-based pipeline called AgentWrite that decomposes large writing tasks into smaller subtasks, allowing the model to produce long documents section by section. Researchers also created the LongWriter-6k dataset containing thousands of examples with outputs ranging from a few thousand to tens of thousands of words. -
Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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Lucet
Lucet, the Sandboxing WebAssembly Compiler.
Lucet is a native WebAssembly compiler and runtime designed to securely execute untrusted code with high performance and strong isolation guarantees. Developed by the Bytecode Alliance, it focuses on ahead-of-time compilation, converting WebAssembly modules into native machine code before execution to achieve fast startup times and predictable performance. Lucet is particularly notable for its use in edge computing environments, where low latency and efficient resource usage are critical, such as in content delivery networks. It leverages the Cranelift code generator to produce optimized native binaries and provides a runtime that enforces strict sandboxing, ensuring that untrusted code cannot compromise the host system. The project is designed to embed easily into applications, allowing developers to extend systems with plugin-like architectures powered by WebAssembly. -
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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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MATLAB Robotics
MATLAB sample codes for mobile robot navigation
MATLABRobotics is a collection of robotics-related algorithms and simulation tools implemented in MATLAB. The repository brings together a wide range of robotics functionality, including path planning, control, localization, and mapping. It provides practical algorithmic implementations such as A*, RRT, Kalman filters, particle filters, and SLAM, making it a valuable resource for students, researchers, and developers learning or prototyping robotics applications. The code is written to be accessible and easy to adapt, enabling experimentation with both classical and modern robotics techniques. By using MATLAB’s visualization and numerical capabilities, the repository offers intuitive demonstrations of algorithms in action. As an open resource, it encourages contributions and serves as a foundation for building and testing robotics concepts in simulation. -
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MCP Proxy
A TypeScript SSE proxy for MCP servers that use stdio transport
mcp-proxy is a lightweight bridge that converts between MCP transports, letting you run a server on stdio and expose it over Streamable HTTP (SSE) or do the reverse. This enables existing desktop-style MCP servers to be reused by web services and IDEs that prefer HTTP, without modifying the server. The tool can multiplex multiple named STDIO servers behind one proxy instance, simplifying fleet deployments or local development with many tools. It ships prebuilt artifacts and a Homebrew formula for quick install on macOS and Linux, with container images published for broader environments. Releases show steady improvements focused on developer experience and operational flexibility. Overall, it lowers the friction of composing diverse MCP tools into a single reachable endpoint. -
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MCP Shrimp Task Manager
Shrimp Task Manager is a task tool built for AI Agents
Shrimp Task Manager is an MCP server that converts natural-language requests into structured development tasks with dependencies, status, and style/format rules—built for agents that reason step-by-step. It emphasizes chain-of-thought and reflection loops, allowing an assistant to plan, refine, and re-prioritize work like a human project assistant. The server exposes typed tools so clients can create tasks, link prerequisites, record progress, and enforce writing or coding standards for consistent output. It ships with a web/GUI experience and works smoothly inside MCP-capable IDEs, making it useful as both a personal organizer and a programmable task substrate for software projects. Stars, registry listings, and docs point to active usage across the MCP community. The result is a practical “task brain” that agents can query and evolve over time. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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MDCx
Movie metadata scraper and organizer for media libraries and NFO
MDCx is an open source media metadata scraping and organization tool designed to automate the process of collecting detailed information for movie files. It retrieves metadata from multiple online sources and applies it to local media collections, helping users maintain structured and well-organized libraries. MDCx can download information such as titles, cast data, artwork, and other metadata, then generate standardized NFO files compatible with media management systems. It also supports image processing tasks such as downloading and cropping artwork used by media centers. It includes several interfaces, allowing users to operate it through a graphical desktop application, a browser-based web interface, or command-line utilities depending on their workflow. Its architecture separates core scraping logic from the user interfaces, allowing the same metadata processing system to be reused across different modes. -
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MIME Component
Allows manipulating MIME messages
Symfony Mime is a component that facilitates the creation, manipulation, and parsing of MIME messages. It is commonly used for handling email content and attachments in Symfony applications. The component supports building complex email structures, including multi-part messages, and correctly encoding text and binary data. Mime is an essential part of Symfony Mailer but can be utilized independently to handle MIME message generation. -
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MIT License
Hosted MIT License with details controlled through this repo
The MIT License repository is a simple GitHub project that hosts the full text of the MIT License and provides a stable reference for developers who want to include permissive licensing details in their work. The MIT License itself is one of the most widely used open-source licenses because it allows reuse, modification, distribution, and even proprietary use, as long as copyright notices and license texts are preserved. This repository offers an easy way to copy the license text, understand its legal language, and see example usage in a context that is separate from any specific software project. It can also be useful for automated tooling and templates where a standard license file is needed across multiple repositories or as part of a code generation process. While not a software library or application, the repository serves an important role in open-source governance by centralizing a commonly adopted license with clear formatting. -
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MJML 4
The only framework that makes responsive-email easy
MJML is a markup language created by Mailjet and designed to reduce the pain of coding a responsive email. Its semantic syntax makes the language easy and straightforward while its rich standard components library shortens your development time and lightens your email codebase. MJML’s open-source engine takes care of translating the MJML you wrote into responsive HTML. -
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ML Intern
ML engineer that reads papers, trains models, and ships ML models
ML Intern is a repository by Hugging Face that provides educational content and projects aimed at helping learners gain practical experience in machine learning and AI development. It is designed to simulate the experience of working as a machine learning intern, offering tasks and exercises that mirror real-world workflows. The project includes tutorials, datasets, and example implementations that guide users through different aspects of ML development. It emphasizes hands-on learning, encouraging users to build and experiment rather than passively consume information. The repository also introduces tools and libraries commonly used in the Hugging Face ecosystem. It is structured to help users progressively build skills and confidence in AI development. Overall, ML Intern is a practical learning platform for aspiring machine learning engineers. -
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ML Visuals
ML Visuals contains figures and templates which you can reuse
ML Visuals is an open-source project that provides a collection of reusable diagrams, templates, and visual resources designed to improve communication in machine learning research and education. The repository contains professional-quality figures that illustrate machine learning concepts such as neural networks, optimization methods, model architectures, and common deep learning techniques. These visuals are intended to help researchers, educators, and students create clearer presentations, blog posts, and scientific papers. The project is maintained as a collaborative community effort where contributors can add new diagrams or visual components. Many of the visuals are designed using editable formats such as Google Slides, making it easy for users to customize them for their own work. -
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MLX Engine
LM Studio Apple MLX engine
MLX Engine is the Apple MLX-based inference backend used by LM Studio to run large language models efficiently on Apple Silicon hardware. Built on top of the mlx-lm and mlx-vlm ecosystems, the engine provides a unified architecture capable of supporting both text-only and multimodal models. Its design focuses on high-performance on-device inference, leveraging Apple’s MLX stack to accelerate computation on M-series chips. The project introduces modular VisionAddOn components that allow image embeddings to be integrated seamlessly into language model workflows. It is bundled with newer versions of LM Studio but can also be used independently for experimentation and development. Overall, mlx-engine serves as a specialized high-efficiency runtime for local AI workloads on macOS systems. -
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MLX42
Codam's own fixed, functioning alternative of the miniLibX
MLX42 is a modern C graphics and windowing library built on top of GLFW and inspired by the original MLX library used in 42 school projects. It aims to provide a higher-level, beginner-friendly abstraction for students learning about graphical programming, while also embracing modern practices like event-driven input, texture rendering, and transparency. MLX42 is structured to reduce boilerplate and simplify the creation of games or interactive applications in C, making it an excellent learning and teaching tool for graphics programming fundamentals. -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement. The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized evaluation scripts and dictionaries. By mapping languages into a common vector space, MUSE makes it straightforward to build cross-lingual applications where resources are scarce for some languages. The training and evaluation pipeline is lightweight and fast, so experimenting with different languages or initialization strategies is easy. Beyond dictionary induction, the learned embeddings are often used as building blocks for downstream tasks like classification, retrieval, or machine translation. -
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
Machine Learning Foundations repository contains the code, notebooks, and teaching materials used in Jon Krohn’s Machine Learning Foundations curriculum. The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. The repository includes Jupyter notebooks with explanations and examples that demonstrate how these mathematical principles relate to real machine learning applications. Each section introduces theoretical concepts and then illustrates them through practical coding examples to reinforce understanding. The project is designed for students and practitioners who want to strengthen their foundational knowledge before working with more advanced machine learning frameworks. -
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Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
Machine Learning for Software Engineers is an open-source learning roadmap designed to help software engineers transition into machine learning roles through a structured, practical study plan. The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a multi-month study schedule that covers topics such as machine learning fundamentals, algorithm understanding, data preparation, and practical experimentation. It aggregates a wide range of resources including books, online courses, Kaggle competitions, podcasts, conferences, and community learning opportunities. The repository is structured to help learners gradually build the skills required for machine learning engineering positions while maintaining a focus on real-world application development. -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. This makes the repo suitable for students, hobbyists, or developers who want to deeply understand how ML algorithms work under the hood and experiment with parameter tuning or custom data. Because it's part of the author’s learning-path repositories, it likely is integrated with tutorials, sample datasets, and contextual guidance, which helps users bridge theory. -
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Magnitude
Vision AI browser agent for automation, testing, and extraction
Browser Agent by Magnitude is an open source, vision-first browser automation framework that enables users to control web interfaces using natural language instructions. It leverages visually grounded AI models to interpret and interact with web pages based on what is seen on the screen rather than relying solely on the DOM structure. This approach allows the agent to generalize better across complex and modern websites, making it more robust than traditional selector-based automation tools. Browser Agent by Magnitude supports a wide range of capabilities including navigation, interaction, data extraction, and automated verification through built-in testing features. Developers can use it to automate repetitive web tasks, integrate services without APIs, or build advanced browser-based agents. It also provides flexible abstraction levels, allowing both high-level task execution and precise low-level control of actions like mouse movements and keyboard input. -
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Mall Learning
Tutorial and sample-code repository
mall-learning is a tutorial and sample-code repository that explores an entire e-commerce system architecture from backend to frontend. The associated “mall” project (with tens of thousands of stars) is an open-source full-stack e-commerce platform built with Spring Boot, MyBatis, Elasticsearch, RabbitMQ, Redis, MongoDB, MySQL and containerized via Docker. The learning repository breaks down architecture, business modules (products, orders, marketing, members), deployment (Linux, Docker, Jenkins) and technical points in detail. For each topic it provides sample code, explanations of why design decisions were made, trade-offs and how to implement real-world features like search, caching, delayed messaging, file storage. It’s aimed at developers who want to understand how to build scalable e-commerce systems rather than just copy-paste modules. With clearly organized “tiny” modules (mall-tiny-01 etc) the repo supports step-by-step incremental learning. -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
MarkPDFdown is an open-source document processing tool designed to convert PDF files into structured Markdown output that can be easily used for documentation, content pipelines, and AI processing workflows. The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. By producing Markdown rather than raw text, the tool makes it easier to integrate documents into knowledge bases, documentation systems, or language model pipelines that rely on structured input. The software is particularly useful for developers working with technical documents, academic papers, or reports that need to be indexed, summarized, or processed by downstream AI systems. -
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Master Spring and Spring Boot
Spring and Spring Boot Tutorial For Absolute Beginners
Master Spring and Spring Boot is a comprehensive educational project that teaches how to build enterprise-grade Java applications using the Spring ecosystem. It guides learners through creating web applications, REST APIs, and full-stack systems using technologies like JPA, Hibernate, and React. The course emphasizes hands-on development, allowing users to build real applications step by step. It also covers essential topics such as security, testing, and deployment. The repository includes guidance on containerization and cloud deployment using Docker and AWS. It is designed for beginners aiming to become proficient Spring developers. Overall, it provides a complete learning path from fundamentals to advanced concepts.
