Open Source ChromeOS Software - Page 97
Sort By:
Software for ChromeOS
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
Jspicl
A Javascript to PICO-8 Lua transpiler
Jspicl is a JavaScript to PICO-8 Lua transpiler that allows developers to write their game logic in JavaScript, which is then transpiled into the Lua subset supported by PICO-8. This enables developers more comfortable with JavaScript to create games for the PICO-8 platform. -
2
Jspreadsheet CE
Javascript plugin to create web-based tables & spreadsheets
Jspreadsheet CE is a lightweight Vanilla JavaScript data grid plugin to create amazing web-based interactive HTML tables, and spreadsheets compatible data grid with other spreadsheet software. You can create an online spreadsheet table from a JS array, JSON, CSV or XSLX files. You can copy from excel and paste straight to your Jspreadsheet CE spreadsheet and vice versa. It is very easy to integrate any third party JavaScript plugins to create your own custom columns, custom editors, and customize any feature into your application. Jspreadsheet CE has plenty of different input options through its native column types to cover the most common web-based application requirements. It is a complete solution for web data management. Create amazing applications with Jspreadsheet CE JavaScript spreadsheet. -
3
Julia.jl
Curated decibans of Julia programming language
Julia.jl is a curated collection of knowledge resources for the Julia programming language, designed to support high-performance numerical analysis and computational science. The repository aggregates diverse content across domains such as mathematics, physics, data science, optimization, machine learning, and supercomputing. It functions as a structured index, helping developers, researchers, and learners easily find materials to deepen their understanding of Julia’s ecosystem. The project emphasizes community contributions, encouraging users to expand and refine the resource pool. With a wide range of topic-focused documents, it provides both academic and practical references for applied research and development. By centralizing these resources, Julia.jl supports continuous learning and growth for users at all experience levels in the Julia community. -
4
Jvedio
Jvedio is a local video management software
Jvedio is a desktop-based local video management system designed to organize and enhance personal media libraries with automation and metadata enrichment. It scans local directories, imports video files, and builds a structured library by extracting unique identifiers and categorizing content automatically. The software supports tagging, filtering, and advanced search, enabling users to manage large collections efficiently. It integrates AI-based features such as actor recognition and translation of metadata, improving the usability and accessibility of stored content. Jvedio also includes media processing tools powered by FFmpeg, allowing users to generate screenshots and GIF previews directly from videos. Its plugin system enables customization through themes and synchronization tools, while its modern interface provides a smooth user experience. Designed primarily for Windows, it combines media organization and lightweight editing into a single platform. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
KCP C#
KCP C# version. Thread safe, no alloc at runtime, no pressure on gc
KumoKyaku KCP is a C# implementation of the KCP reliable UDP protocol designed for high-performance .NET applications. It provides ready-to-use APIs while also allowing advanced users to customize segment handling and memory behavior. The project uses unsafe code and unmanaged memory internally to reduce garbage collection pressure, which is important for real-time systems. It supports Span<byte>, external buffer rental, and a generic KcpCore<Segment> architecture for performance-focused implementations. The library is partly thread-safe, allowing concurrent Send and Input calls while restricting concurrent Recv and Update calls for correctness. It is useful for game networking, real-time communication, and other latency-sensitive C# applications that need reliable delivery over UDP. -
6
KG-LLM-Papers
Papers integrating knowledge graphs (KGs) and large language models
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge graph-guided prompting, retrieval-augmented generation, reasoning over structured data, and hybrid architectures combining symbolic and neural systems. By gathering these papers into a single organized repository, the project helps researchers quickly discover relevant literature and track the evolution of the field. -
7
Kami
Good content deserves good paper
Kami is a minimalistic productivity tool designed to help users organize tasks, notes, and daily workflows in a clean and distraction-free interface. It focuses on simplicity, enabling users to capture ideas quickly and manage them efficiently without unnecessary complexity. The application is built with a modern design philosophy that emphasizes clarity and usability. It supports lightweight task management and note-taking features for personal productivity. Kami is suitable for users who prefer streamlined tools over feature-heavy productivity suites. Its design encourages focus and reduces cognitive overload. The project reflects a trend toward minimalist digital tools for everyday organization. -
8
Karpathy
An agentic Machine Learning Engineer
karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. The system is tightly integrated with the Claude Scientific Skills ecosystem, enabling the agent to leverage specialized scientific and machine learning tools. It is intended primarily for research and experimentation with autonomous ML workflows rather than as a polished production platform. Overall, karpathy represents an early step toward fully automated machine learning engineering driven by agentic AI systems. -
9
Kaset
The missing YouTube Music macOS app
Kaset is a social audio platform framework that allows users to host, share, and interact with audio content in community-oriented spaces, combining elements of podcasting, voice rooms, and feedback-driven discovery. It provides an interface where creators can upload episodes, host live or scheduled voice sessions, and cultivate listener communities through comments, reactions, and follow systems. The platform emphasizes audio discovery with playlists, curated channels, and trending audio feeds, helping users find relevant voice content without sifting through noise. Listeners can subscribe to channels, get personalized recommendations, and join ongoing discussions around episodes or live broadcasts. Creators also receive analytics on engagement, playback patterns, and audience demographics so they can iterate on content strategies. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
10
Kendo UI Core
An HTML5, jQuery-based widget library for building modern web apps
Kendo UI is everything you need to build sites and apps with HTML5 & JavaScript. Kendo UI Core is the free and open-source version of Kendo UI that provides access to the web's best UI widgets and key framework features, essential for developing great experiences for the web and mobile. Kendo UI Core is a free and open-source subset of Kendo UI. The following table details the widgets and features available in Kendo UI Core, as well as the additional features available via a commercial Kendo UI license. -
11
Keychron Hardware Design
Industrial design files for Keychron keyboards and mice
The Keychron-Keyboards-Hardware-Design project is a source-available repository that provides production-grade industrial design files for a wide range of Keychron keyboards and mice. It includes over one hundred device models with detailed CAD assets, allowing users to explore real-world hardware engineering practices and understand how commercial peripherals are constructed. The repository contains multiple file formats such as STEP, DXF, DWG, and PDF, enabling compatibility with professional CAD software and fabrication workflows. It is designed both as an educational resource and as a foundation for creating compatible accessories, giving users the ability to measure, remix, and prototype hardware components. The project encourages experimentation and learning by providing structured documentation, guides, and model organization across product families. -
12
Khazix Skills
Digital Life Kazik Open Source AI Skills Collection
Khazix Skills project is an automation framework designed to transform GitHub repositories into structured, reusable AI agent skills. It acts as a pipeline that analyzes a repository’s metadata, extracts relevant information such as README content and commit hashes, and converts it into a standardized skill format that can be integrated into agent ecosystems. The system emphasizes lifecycle management by embedding versioning, traceability, and metadata directly into generated skill files, allowing future updates and synchronization with the original repository. It also generates wrapper scripts that enable AI agents to interact with the underlying repository functionality without requiring deep manual integration. By enforcing a consistent schema, the project ensures interoperability between skills and simplifies deployment across environments. This makes it especially useful for teams building modular AI agents that rely on external tools or open-source repositories. -
13
Kiln
Open source platform for managing, testing, and deploying AI apps
Kiln is an open source platform designed to help developers build, evaluate, and deploy AI-powered applications with greater structure and reliability. It provides a unified environment for managing prompts, datasets, and evaluation workflows, allowing teams to iterate on AI behavior in a controlled and measurable way. Kiln emphasizes reproducibility, enabling users to track changes to prompts and models while comparing outputs across different configurations. Kiln also supports systematic testing of AI systems by defining evaluation criteria and running experiments to assess performance over time. Its workflow-oriented approach helps teams move from experimentation to production by organizing assets and results in a consistent format. It is particularly useful for teams working with large language models who need visibility into how changes impact outputs and overall system quality. -
14
Kimi k1.5
Scaling Reinforcement Learning with LLMs
Kimi-k1.5 is an advanced open-source multimodal large-language model project that explores scaling reinforcement learning with long-context chains of thought, achieving performance that rivals or surpasses state-of-the-art models on benchmarks like LiveCodeBench, AIME, and MATH-500. The project emphasizes a simplistic yet powerful framework where the context window scales up to 128k tokens, enabling reasoning that resembles planning, reflection, and correction over a much longer sequence of data than typical models. By using techniques like partial rollouts to improve training efficiency and applying sophisticated policy optimization methods, the developers demonstrate that strong ability can emerge without relying on complex solutions like Monte Carlo tree search or value functions. Kimi-k1.5 is trained jointly on text and vision data, giving it true multimodal reasoning capabilities where it can interpret and generate content across modalities in a unified way. -
15
Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. It uses a novel model setup that combines continuous acoustic features with discrete semantic tokens to richly capture sound and meaning across speech, music, and environmental audio. -
16
Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. Developers can integrate via Python/TypeScript SDKs or REST API, with support for OpenAI, Claude, Gemini, LangChain, LlamaIndex, and CrewAI. Features include built-in authentication, multi-tenancy, hosted servers, Docker support, and enterprise security guardrails. Licensed under Apache 2.0, Klavis simplifies AI development by eliminating complex authentication management and enabling seamless workflow automation across multiple applications. -
17
Knit
Lightweight game framework for Roblox
Lightweight game framework for Roblox. A lightweight framework that simplifies communication between core parts of your Roblox experience and seamlessly bridges the gap between the server and the client. Services and controllers are the core of Knit. These objects provide a foundation for Roblox experiences. By orienting core game logic around services and controllers, developers will inherit cleaner organization across codebases and easier maintainability. Services and controllers are easy to create, and provide a built-in networking layer. Knit automatically provides networking between the client and services. Since Knit handles the networking infrastructure, developers are not left with the burden of manually creating RemoteEvent and RemoteFunction objects throughout the hierarchy. Each service has the ability to expose specific endpoints to the client through declarative code. -
18
Knock Knock
Get notified when your training ends
Knock Knock is a lightweight Python utility created by the Hugging Face team that allows developers to receive notifications when long-running machine learning tasks finish or fail. Training deep learning models often takes hours or even days, making it inconvenient for engineers to constantly monitor progress manually. The library solves this problem by adding simple decorators or command-line commands that automatically send notifications when a process completes or crashes. These alerts can be delivered through several communication platforms such as email, Slack, Telegram, or other messaging services. The goal of the project is to allow developers to monitor experiments remotely without needing to stay connected to the training environment. By adding only a few lines of code, the library can wrap around a training function and report execution status. -
19
Komari
A simple server monitor tool
Komari is a lightweight, self-hosted server monitoring solution designed to deliver simple and efficient infrastructure visibility with minimal resource overhead. The platform uses a lightweight agent to collect performance data from monitored nodes and presents the results through a clean web interface. Its architecture emphasizes ease of deployment and full data ownership, making it attractive for users who prefer private monitoring environments over managed services. Komari is designed to scale across servers of different sizes while maintaining low CPU and memory consumption. The dashboard provides real-time status views that allow administrators to quickly assess system health and uptime. Overall, Komari targets developers, homelab operators, and small infrastructure teams seeking a straightforward monitoring tool without the complexity of enterprise observability stacks. -
20
Kreuzberg
Polyglot document intelligence framework
Kreuzberg is a flexible task orchestration and agent workflow platform designed to help developers build, coordinate, and scale intelligent agents or automation pipelines that interact with external services, runtime environments, and multi-step business workflows. It emphasizes modular design so that developers can define discrete tasks or “actions” and then compose them into complex flows where dependencies, parallel steps, and error handling are declaratively managed. This structure makes it simpler to build resilient automation pipelines that span multiple technologies or APIs without needing to glue everything together manually. The platform also supports observability and monitoring, helping teams trace the progression of workflows, catch errors early, and evaluate performance trends in orchestrated systems. -
21
Kubernetes Capsule
Multi-tenancy and policy-based framework for Kubernetes
Capsule implements a multi-tenant and policy-based environment in your Kubernetes cluster. It is designed as a micro-services-based ecosystem with a minimalist approach, leveraging only on upstream Kubernetes. Kubernetes introduces the Namespace object type to create logical partitions of the cluster as isolated slices. However, implementing advanced multi-tenancy scenarios, it soon becomes complicated because of the flat structure of Kubernetes namespaces and the impossibility to share resources among namespaces belonging to the same tenant. To overcome this, cluster admins tend to provision a dedicated cluster for each groups of users, teams, or departments. As an organization grows, the number of clusters to manage and keep aligned becomes an operational nightmare, described as the well known phenomena of the clusters sprawl. -
22
Kubernetes The Hard Way
Bootstrap Kubernetes the hard way
Kubernetes The Hard Way is a hands-on guide to building a Kubernetes cluster from the ground up without using automation tools—no managed services, no scripts to hide the details. It walks you through every component: provisioning compute resources, generating TLS certificates, configuring etcd, bootstrapping the control plane, joining worker nodes, setting networking, and verifying everything works. The purpose is educational: by doing each step manually, you gain deep insight into how Kubernetes works under the hood—control plane components, kube-configs, networking, encryption, etc. The guide isn’t meant for production use; rather it’s a learning tool to build foundational understanding before using higher-level platforms. You’ll learn about certificate management, API server flags, etcd clustering, kubelet boot sequence, and how pods route traffic across nodes. Many practitioners use it to prep for Kubernetes certifications or deeply understand Kubernetes internals. -
23
Kyoo
A portable and vast media library solution
Kyoo is a self-hosted media streaming platform designed to organize, stream, and manage personal video libraries through a modern web interface. It is built around a containerized architecture using Docker, where multiple services handle media indexing, streaming, and configuration. The system allows users to access their content from a browser while maintaining control over storage and playback infrastructure. Kyoo supports hardware acceleration options for efficient video processing, making it suitable for high-resolution streaming environments. Its configuration relies on environment variables and Docker Compose, enabling flexible deployment across different systems. The platform emphasizes modularity, allowing users to customize storage locations, streaming settings, and performance parameters. With a focus on self-hosting and scalability, Kyoo provides an alternative to commercial media servers for users who want full control over their content. -
24
LIEF
LIEF - Library to Instrument Executable Formats (C++, Python, Rust)
LIEF (Library to Instrument Executable Formats) is a cross-platform library that enables parsing, modifying, and abstracting executable formats such as ELF, PE, and Mach-O. It's widely used in reverse engineering and binary analysis. -
25
LIFELINES
Survival analysis in Python
LIFELINES is a pure Python library for survival analysis, a statistical field focused on modeling time until an event occurs. It can be used for traditional cases like medical survival time, but also for business and product questions such as churn, subscription length, equipment failure, and customer retention. The library includes estimators such as Kaplan-Meier, Nelson-Aalen, and regression-based survival models. It is designed to be accessible to Python users and works well with common scientific computing workflows. Built-in plotting methods and datasets help users explore survival curves and compare groups visually. It is a practical tool for analysts, researchers, and data scientists who need event-time modeling without leaving Python.
