Open Source Unix Shell Software for ChromeOS
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Unix Shell Software for ChromeOS
Browse free open source Unix Shell Software for ChromeOS and projects below. Use the toggles on the left to filter open source Unix Shell Software for ChromeOS by OS, license, language, programming language, and project status.
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place.Incredable streamlines and simplifies the complex process of medical credentialing for hospitals and medical facilities, helping you save valuable time, reduce costs, and minimize risks. With Incredable, you can effortlessly manage all your healthcare providers and their credentials within a single, unified platform. Our state-of-the-art technology ensures top-notch data security, giving you peace of mind.
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Pootle, Virtaal & Translate Toolkit
Localization tools built by localizers for localizers
Tools for localization: - Pootle: web based translation management system. - Virtaal: Computer Aided Translation (CAT) tool. - Translate Toolkit: QA, format conversion and support (PO, Java .properties, OpenOffice, Mozilla, XLIFF, TMX, TBX, CSV, Qt .ts). -
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Crosvm
The Chrome OS Virtual Machine Monitor
crosvm (ChromeOS Virtual Machine Monitor) is a secure, lightweight virtual machine monitor built on top of the Linux KVM hypervisor. Developed for ChromeOS, it is designed to isolate and execute Linux and Android guests efficiently while maintaining strong security boundaries. Unlike general-purpose emulators like QEMU, crosvm avoids full hardware emulation and focuses on modern paravirtualized I/O using the virtio standard, reducing complexity and attack surface. Written in Rust, it emphasizes memory safety and modularity, allowing sandboxed device emulation with fine-grained privilege separation. crosvm underpins several ChromeOS subsystems, including Android Runtime for Chrome (ARCVM) and Crostini Linux containers, enabling rich application compatibility within a tightly controlled environment. -
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Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also supports agent self-learning by distilling structured skills and experiences from previously completed tasks, which can later be reused or searched to improve future performance. It includes tools to interact with session data, background agents that monitor progress, and a dashboard that visualizes success rates, artifacts, and learned skills. By combining persistent storage, observability, and learning capabilities, Acontext aims to make AI agents more scalable, reliable, and capable. -
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Gin Config
Gin provides a lightweight configuration framework for Python
Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter values, scoped configurations, and modular references to functions, classes, or instances, resulting in highly composable and dynamic experiment setups. Gin is particularly popular in TensorFlow and PyTorch projects, where researchers and developers need to tune numerous interdependent parameters across models, datasets, optimizers, and training pipelines. -
The complete IT asset and license management platformThe platform seamlessly integrates with 100+ IT systems, including MDM, RMM, IDP, SSO, HR, finance, helpdesk tools, and more.
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss models operate correctly, as they are trained to rely on this structure for generating and organizing their responses. For users accessing gpt-oss through third-party providers like HuggingFace, Ollama, or vLLM, Harmony formatting is handled automatically, but developers building custom inference setups must implement it directly. With its flexible design, Harmony serves as the foundation for creating more interpretable, controlled, and extensible interactions with open-weight language models. -
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YouTube-DL-PyTK
Video Downloader - Cross Platform
YouTube-DL-PyTK (formerly known as YouTube-DL-GTK) is just a graphical launcher for yt-dlp. Its purpose is simple; to facilitate the downloading of non-copyright-protected videos from certain internet websites including YouTube. Source code is included and can be executed directly if you have Python and the proper dependencies available. I digitally sign some files in my releases. If you'd like to verify those signatures, you can find my PGP/GPG keys at: https://marcusadams.me/keys.html If you'd like to read the source code without downloading anything, you can do so on the project's Gitlab at: https://gitlab.com/gerowen/youtube-dl-pytk If you'd like to donate there's several ways to do so: PayPal: https://paypal.me/gerowen Bitcoin (BTC): bc1q86c5j7wvf6cw78tf8x3szxy5gnxg4gj8mw4sy2 Monero (XMR): 42ho3m9tJsobZwQDsFTk92ENdWAYk2zL8Qp42m7pKmfWE7jzei7Fwrs87MMXUTCVifjZZiStt3E7c5tmYa9qNxAf3MbY7rD -
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Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks. -
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GLM-130B
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
GLM-130B is an open bilingual (English and Chinese) dense language model with 130 billion parameters, released by the Tsinghua KEG Lab and collaborators as part of the General Language Model (GLM) series. It is designed for large-scale inference and supports both left-to-right generation and blank filling, making it versatile across NLP tasks. Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple benchmarks, while also showing significant improvements on Chinese datasets compared to other large models. The model supports efficient inference via INT8 and INT4 quantization, reducing hardware requirements from 8× A100 GPUs to as little as a single server with 4× RTX 3090s. Built on the SwissArmyTransformer (SAT) framework and compatible with DeepSpeed and FasterTransformer, it supports high-speed inference (up to 2.5× faster) and reproducible evaluation across 30+ benchmark tasks. -
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Public APIs
A collective list of free APIs
public-apis is a collaboratively maintained repository that provides an extensive, categorized list of publicly available APIs for developers. Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and free-to-use APIs. Developers can leverage this list to enhance their products, prototypes, or research projects without the need to build data sources from scratch. The repository’s open nature encourages contributions, allowing anyone to submit new APIs or updates through pull requests. Over time, public-apis has evolved into a trusted and frequently updated reference point within the developer community. It also provides an active community space, including a Discord server. -
Yeastar: Business Phone System and Unified CommunicationsUser-friendly, optimized, and scalable, the Yeastar P-Series Phone System redefines business connectivity by bringing together calling, meetings, omnichannel messaging, and integrations in one simple platform—removing the limitations of distance, platforms, and systems.
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Stanford Machine Learning Course
machine learning course programming exercise
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises. -
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NGINX Admin’s Handbook
How to improve NGINX performance, security, and other important things
nginx-admins-handbook is a practical, in-depth guide for configuring, securing, and operating NGINX across real-world deployments. It distills years of research, notes, and field experience into a single handbook that complements the official docs with concrete rules, explanations, and curated external references. The handbook spans fundamentals and advanced topics alike, from HTTP and SSL/TLS basics to reverse proxy patterns, performance tuning, debugging workflows, and hardening strategies. A centerpiece is its prioritized checklist of 79 rules, grouped by criticality, helping readers focus on what most impacts security, reliability, and speed. Instead of copy-paste snippets in isolation, it emphasizes understanding trade-offs, avoiding common pitfalls, and balancing security with usability. Designed for system administrators and web application engineers, it aims to be a living companion that encourages experimentation, measurement, and continuous improvement of NGINX configurations -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation. -
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System Design Primer
Learn how to design large-scale systems
System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview questions with sample solutions, diagrams, and code. The repository also contains study guides for short, medium, and long interview timelines, allowing learners to focus on both breadth and depth depending on their preparation needs. In addition, it includes flashcard decks designed to reinforce learning through spaced repetition, making it easier to retain key system design knowledge. -
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. The project also provides scripts to fetch and preprocess monolingual data, learn BPE codes, and train cross-lingual embeddings that bootstrap unsupervised alignment between languages. Beyond the core EMNLP 2018 setup, the codebase exposes additional, optional capabilities such as multi-language training, language model pretraining with shared parameters, and adversarial training. -
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Master/node to gather and graph "everything" on your systems using Tobi Oetiker's rrdtool. It can optionally warn your surveillance software. This software package was originally called LRRD. The project. Please see http://munin-monitoring.org/
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Portable Linux
Portable Ubuntu Linux for Scientific Computing
Released August 22, 2013 Lubuntu Blends: Biochemistry 13.04 (Raring) v5.44 Linux Kernel Image 3.8.0-29 Lubuntu Blends are pre-installed Wubi disk image remixes of Ubuntu and Debian Science meta packages, A custom boot loader allows installations to be copied and automatically booted from most external or USB flash drives. Once up and running, use earlier Lubuntu Remix README instructions here until documentation is updated. https://sourceforge.net/projects/portable-linux/files/ Installation 1. Download the Wubi installer http://releases.ubuntu.com/saucy/wubi.exe 2. Install any flavor of Ubuntu. 3. Swap out the root.disk with the ones provided here. Overview LAMP stack running on localhost (127.0.0.1). Scientific, productivity & media packages include R (Rattle Data Miner), GridEngine, Condor, cooperative computing tools, WINE, LibreOffice, Evolution, Clinica, Neuro Debian Desktop, PsycoPy, OpenVibe, 3DSlicer, Paraview, Openshot. Cheers, Gregory Remington -
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Nostalgic Photo DataBase (platform)
Active repository of jpeg-photos with tags suitable for personal needs
NPDB offers a comprehensive platform for creating and maintaining a database of both old, digitized images and new snapshots captured by smartphones. This versatile system allows users to organize and search through their collection using customizable tags, catering to images of any vintage. One of NPDB's key features is its flexible tagging system, which allows users to categorize their images using an arbitrary set of tags tailored to their preferences. This intuitive approach streamlines the organization process, making it easier than ever to locate specific images amidst a vast collection. Powered by an embedded SQL database, NPDB delivers lightning-fast search results, ensuring that users can access the images they need almost instantaneously. Whether searching by tags or entering free-text queries, NPDB executes SQL queries efficiently, providing accurate results in no time. Developed primarily in C++, NPDB ensures seamless operation on Linux, Windows (via WSL), and Chrome OS. -
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Strasheela is a constraint-based music composition system. The user defines music theories by sets of compositional rules and the system creates music which complies with these theories. User-interface is the programming language Oz.
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littleutils
Various small and useful command-line utilities
The littleutils include duplicate file finders (repeats, repeats.pl, repeats.py), image optimizers (opt-jpg, opt-png, opt-gif, recomp-jpg), file rename tools (lowercase, uppercase, pren), archive recompressors (to-gzip, to-bzip2, to-bzip3, to-7zip, to-lzma, to-lzip, to-xz), a tempfile utility (tempname), file property tools (filedate, filemode, filenode, fileown, filesize, and lrealpath), and others. See the README file for more details. -
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Kojoney is an easy of use, secure, robust and powerfull Honeypot for the SSH Service written in Python. With the kojoney daemon are distributeds other tools such as kip2country (IP to Country) and kojreport, a tool to generate reports from the log fi
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An intelligent platform-independent offline translation and localization program working internally with XLIFF, but also supporting other formats. It uses Glossaries, TM and other information to facilitate production of good quality translations.
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Aelius Brazilian Portuguese POS-Tagger
Python, NLTK-based package for shallow parsing of Brazilian Portuguese
Aelius is an ongoing open source project aiming at developing a suite of Python, NLTK-based modules and interfaces to external freely available tools for shallow parsing of Brazilian Portuguese. It also includes language resources such as language models, sample texts, and gold standards. Presently, Aelius already offers facilities for POS-tagging and chunking corpora and outputting annotations in different formats, such as in XML in the TEI P5 encoding scheme. -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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This game is an MMORPG in various UNIX scripting languages, with a graphical shell accessed by SSH for the client. It will support Linux, Windows, and MacOS X. It is meant to be immersive and allows in-game coding.
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A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.
