Open Source ChromeOS Software - Page 95
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Software for ChromeOS
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Gemma Chat
Local AI chat + coding agent for Apple Silicon, powered by Gemma 4
Gemma Chat is a local-first AI chat and coding assistant designed to run fully on-device, particularly optimized for Apple Silicon machines. It leverages Google’s Gemma family of lightweight language models, which are built on the same underlying technology as Gemini and designed for efficient local inference and reasoning tasks. The project enables users to interact with AI through a chat interface while also supporting code generation and editing workflows. It emphasizes privacy and independence by avoiding cloud dependencies, allowing all interactions and data to remain local. The system integrates model selection and execution directly into the app, giving users control over performance and behavior. It is particularly aligned with the “vibe coding” approach, where users iteratively build and modify projects through conversational prompts. Overall, gemma-chat provides a streamlined, developer-focused environment for local AI experimentation and productivity. -
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GenStage
Producer and consumer actors with back-pressure for Elixir
GenStage is a specification and set of behaviours for building demand-driven data pipelines on the BEAM. It formalizes the roles of producers, consumers, and producer-consumers, using back-pressure so that fast producers don’t overwhelm downstream stages. Developers implement callbacks like handle_demand and handle_events to control how items are emitted, transformed, and consumed across asynchronous boundaries. Because stages are OTP processes, you gain fault tolerance, supervised restarts, and concurrency tuned via configurable demand and partitioning. GenStage underpins higher-level libraries like Flow and Broadway, but it can also be used directly for custom pipelines where timing and throughput matter. Its clear separation of concerns encourages testable, composable stages that can be rearranged as requirements evolve. In production, this leads to predictable, resilient dataflows for event ingestion, batching, and parallel processing. -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and production-ready usage. The repository architecture is organised into folders like gemini/, search/, vision/, audio/, and rag-grounding/, which helps developers locate use cases by modality. It is licensed under Apache-2.0, opensourced and maintained by Google, meaning it's designed with enterprise-grade practices in mind. Overall, it serves as a practical entry point and reference library for building real-world generative AI systems on Google Cloud. -
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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
Generative AI Docs is Google’s official documentation repository for Gemini, Vertex AI, and related generative AI APIs. It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively. -
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Generative Models
Collection of generative models, e.g. GAN, VAE in Pytorch
This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch and TensorFlow. These models are widely used in artificial intelligence to generate new data that resembles the training data, such as images, text, or other structured outputs. The repository serves as an educational and experimental environment where users can study how generative models work internally and replicate results from academic research papers. -
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Gigi
Framework for rapid prototyping and development of real-time rendering
Gigi is software designed for rapid prototyping and rapid development of real-time rendering techniques. It is meant for use by professionals, researchers, students, and hobbyists. The goal is to allow work at the speed of thought, and then easily use what was created in real applications using various APIs or engines. Gigi is being actively used and developed but is young software. You may hit bugs or missing features. Please report these so we can improve Gigi and push forward in the most useful directions. Pull requests are also appreciated. Currently, only dx12 code generation is available in this public version of Gigi, but we are hoping to support other APIs, and engines as well, in the future. -
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Git History
Quickly browse the history of a file from any git repository
Git History is a web-based tool for visually browsing the history of a file from a Git repository. It lets users inspect how a file changed over time by replacing a supported repository URL with the Git History domain. The tool works with GitHub, GitLab, and Bitbucket file URLs, making it useful across several common code-hosting platforms. It presents changes as an animated, readable timeline instead of requiring users to manually step through commits. The project also offers browser extensions, a bookmarklet, a CLI, and a VS Code extension for different workflows. Git History is especially useful for developers who want to understand the evolution of code, documentation, or configuration files quickly. -
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GitHub Copilot SDK
Multi-platform SDK for integrating GitHub Copilot Agent into apps
The GitHub Copilot SDK is a developer toolkit that enables creators to build custom AI-assisted experiences powered by Copilot models within their own applications, editors, and workflows. Instead of being limited to editors like VS Code, this SDK lets teams embed Copilot-style code suggestions, natural language assistance, and predictive completions anywhere they see fit—such as internal IDEs, browser extensions, documentation portals, or bespoke tools tailored to specific languages or frameworks. It provides a structured API surface for invoking the Copilot model in context with the surrounding user state, capturing document content, cursor position, and invocation triggers so suggestions are relevant and responsive. The SDK includes helpers for streaming completions, managing rate limits, handling authentication, and integrating with telemetry and analytics pipelines. -
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GitHub Dark
Dark GitHub style
GitHub-Dark is a userstyle that transforms GitHub’s interface into a coherent dark theme, covering repositories, issues, pull requests, gists, and profile pages. Distributed as a CSS stylesheet intended for the Stylus browser extension, it applies a comprehensive palette, rebalances contrast, and refines syntax colors for code views to ensure readability in low-light settings. The project goes beyond simple inversion by thoughtfully adjusting backgrounds, borders, badges, and diff highlights so the UI feels native rather than “flipped.” It includes targeted fixes for edge cases across GitHub’s many subpages, aiming for consistency while preserving the information hierarchy of the original design. Users can apply the theme selectively, override variables, or combine it with other userstyles to fit personal preference. Even with GitHub’s own theme options, GitHub-Dark remains a carefully tuned alternative for people who want a specific aesthetic or more granular control. -
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GitHubPoster
Make everything a GitHub svg poster and Skyline
GitHubPoster is a Python project that turns personal activity data into GitHub-style SVG posters and skyline visualizations. It can transform data from many sources, such as GitHub, Strava, WakaTime, Kindle, Duolingo, Apple Health, ChatGPT exports, NeoDB, AutoSleep, and Google Keep. The project is built around loaders that import data and render it as visually recognizable contribution-style graphics. It is useful for people who want to display habits, reading, coding, health, language learning, or other quantified-life records in a GitHub-inspired format. It can be run locally from the command line and can also be automated through GitHub Actions. Its modular approach makes it possible for contributors to add new data sources over time. -
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Gitingest
Create prompt-friendly codebase digests from any Git repository URL
Gitingest is a developer utility that converts an entire Git repository into a structured, prompt-friendly text digest suitable for use with large language models. It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local directory or a remote repository by supplying a repository path or URL. The generated output is optimized for prompt usage, helping AI models understand codebases more effectively without requiring manual file aggregation. In addition to producing the code digest, Gitingest also calculates statistics about the extracted content such as repository structure, total size of the extract, and token count. Gitingest can be used as a command line utility or integrated directly into Python applications. -
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Gitnuro
A FOSS Git multiplatform client for newbies and pros
A FOSS Git client based on (Jetbrains) Compose and JGit. The main goal of Gitnuro is to provide a multiplatform open-source Git client without any kind of constraint to how you can use it or rely on web technologies. -
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Gitrob
Scans GitHub repositories for potentially sensitive files
Gitrob is an open source reconnaissance tool designed to identify potentially sensitive files that have been committed to public GitHub repositories. It helps security professionals, researchers, and organizations detect accidental data exposure by scanning repositories associated with specific GitHub users or organizations. The tool works by cloning repositories and analyzing their commit history to search for files that match predefined signatures of sensitive data. These signatures are used to flag items such as credentials, private keys, configuration files, and other materials that may expose confidential information. By automatically inspecting repository histories, Gitrob simplifies the process of identifying security risks that might otherwise remain unnoticed in publicly accessible codebases. The results of the scan are presented through a built-in web interface that allows users to browse findings, review flagged files, and analyze potential leaks more efficiently. -
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Glean
A self-hosted RSS reader and personal knowledge management tool
Glean is a self-hosted RSS reader and personal knowledge management platform designed to help information-heavy users efficiently aggregate, browse, and organize content from feeds. It centralizes RSS/Atom subscriptions, offering clean reading views, tagging, and organization features such as folders and bookmarks, while giving users full control over their data by deploying on their own infrastructure. Glean also includes real-time background synchronization, enabling feeds to update at regular intervals without manual refresh, and it supports importing and exporting subscription lists for portability. With a modern responsive UI and optional admin dashboard, Glean balances readability with lightweight performance, making it suited for both individual readers and teams. Its knowledge management capabilities are augmented by features like smart filtering, “read later” queues, and future plans for AI-driven summaries and preference-based recommendations. -
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Globally Unique ID Generator
xid is a globally unique id generator thought for the web
Globally Unique ID Generator is a Go library for generating globally unique identifiers that are compact, sortable, and safe to use directly in server-side code. It uses a MongoDB ObjectID-inspired structure with a timestamp, machine identifier, process identifier, and counter. The binary form is 12 bytes, while the string form uses lowercase base32hex encoding to create a 20-character URL-safe representation. This makes xid shorter than standard UUID strings while preserving chronological sortability. It does not require a central generator server or explicit machine and data-center configuration, which makes it convenient for distributed web services. It is well suited for database records, API resources, logs, events, and other systems that need practical unique IDs without the length and randomness tradeoffs of UUIDs. -
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Godot Minimal Theme
Godot Minimal Theme
Godot Minimal Theme is not a game engine itself, but rather a custom editor theme designed for Godot Engine — aiming to offer a clean, minimalistic, and visually comfortable interface for the Godot editor. The theme adjusts base colors, accent colors, contrast, icon saturation, corner radii, fonts, and other UI settings to deliver a more modern, streamlined, and easier-on-the-eyes editor appearance. It has been tested and confirmed compatible with several recent Godot versions (4.3, 4.4, 4.5), and many users believe it significantly improves the usability and aesthetic of the Godot editor, especially for extended coding or scene-building sessions. By offering a well-tuned default set of UI parameters (color scheme, font recommendations, layout tweaks), it saves users the trouble of configuring their own setup — and ensures consistency across different projects or machines. Because it’s open source, users can further customize or fork it to suit their personal preferences. -
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Gollama
Go manage your Ollama models
Gollama is a macOS and Linux tool for managing Ollama models through an interactive terminal-based interface. It provides a TUI that lets users list, inspect, sort, filter, edit, run, unload, copy, rename, delete, and push models from one place rather than relying entirely on manual command-line workflows. The project is aimed at developers and local AI users who frequently work with multiple Ollama models and want a more efficient operational layer for everyday maintenance. Beyond standard model management, Gollama can display metadata such as size, quantization level, model family, and modification date, which helps users compare models quickly. One of its more distinctive capabilities is a VRAM estimation system that can calculate memory requirements, estimate context limits, and help users choose quantization settings that fit available hardware. -
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Google CTF
Google CTF
Google CTF is the public repository that houses most of the challenges from Google’s Capture-the-Flag competitions since 2017 and the infrastructure used to run them. It’s a learning and practice archive: competitors and educators can replay tasks across categories like pwn, reversing, crypto, web, sandboxing, and forensics. The code and binaries intentionally contain vulnerabilities—by design—so users can explore exploit chains and patching in realistic settings. The repo also includes infrastructure components and links to a scoreboard implementation, giving organizers reference material for hosting their own events. As a living archive, it documents changes in exploitation trends and defensive techniques year over year. Clear warnings advise against deploying challenge infrastructure in production due to purposeful insecurities. -
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Google Cloud Dataflow Template Pipelines
Cloud Dataflow Google-provided templates for solving data tasks
DataflowTemplates is the source repository for Google-provided Dataflow templates that are intended to solve large-scale in-cloud data processing tasks without requiring users to build everything from scratch in a full development environment. The repository is centered on templated pipelines powered by Google Cloud Dataflow and Apache Beam, making it easier to run common integration and movement jobs such as data import, export, backup, restore, and bulk API operations. Its structure shows support for multiple generations of templates, including v1 and v2 implementations, as well as related metadata, YAML assets, plugins, and Python components that support broader template execution and maintenance. This design makes the project more than a sample set, because it acts as the implementation base for official Google-provided templates used in real cloud data workflows. -
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Google Cloud Node.js Client
Google Cloud Client Library for Node.js
The Google Cloud Node.js Client is an official library that provides idiomatic Node.js interfaces for Google Cloud services, simplifying the integration of these services into Node.js applications. -
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Google Cloud Platform Python Samples
Code samples used on cloud.google
Google Cloud Platform Python Samples repository is a large, curated collection of Python code examples that demonstrate how to use a wide range of Google Cloud services in real-world scenarios. It serves as a practical companion to official documentation, providing runnable snippets that illustrate how to authenticate, configure environments, and interact with APIs across products such as storage, AI services, and data processing tools. The repository is organized into product-specific directories, allowing developers to quickly locate examples relevant to their use case and adapt them into production workflows. It emphasizes hands-on learning by guiding users through setup steps such as creating virtual environments, installing dependencies, and running scripts locally. These samples are designed to accelerate development by showing best practices for connecting services, handling data, and managing cloud resources programmatically. -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases, such as landmark detection and mobile photo analysis with label and face detection, so developers can see how Vision API outputs are consumed in real interfaces and workflows. Although the repository has been marked as deprecated in favor of language-specific repositories for new work, it still serves as a broad reference hub for legacy examples and multi-language implementation patterns. -
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Google Style Guides
Style guides for Google-originated open source projects
Google Styleguide is a comprehensive collection of coding style guides created and maintained by Google to ensure consistency, readability, and maintainability across its vast array of software projects. These guides define best practices and conventions for writing code in multiple programming languages, from C++ and Python to JavaScript, Go, and Swift. By adhering to these standards, developers can more easily collaborate, review code, and maintain high-quality software across teams and open source contributions. Each guide covers a wide range of topics, including naming conventions, file organization, indentation, documentation, and usage of specific language features. The repository also provides supplementary resources such as an Emacs configuration file for Google’s C++ style and references to related guidelines like Effective Dart and Kotlin Style Guide. -
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GraphHopper Routing Engine
Open source routing engine for OpenStreetMap
GraphHopper invests in an active open source community. Our flagships are the GraphHopper routing engine and jsprit, the toolkit for solving rich vehicle routing problems. We promote a fair & diverse mindset. jsprit is a Java based toolkit for solving rich traveling salesman problems (TSP) and vehicle routing problems (VRP). It is lightweight, flexible, easy-to-use, and based on a single all-purpose meta-heuristic. The GraphHopper routing engine is fast and memory-efficient, using Java. It runs server side, offline on Android and iOS. It uses OpenStreetMap data, but can import other data sources as well. GraphHopper is a fast and memory-efficient routing engine released under Apache License 2.0. It can be used as a Java library or standalone web server to calculate the distance, time, turn-by-turn instructions and many road attributes for a route between two or more points. Beyond this "A-to-B" routing it supports "snap to road", Isochrone calculation, mobile navigation and more. -
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GreenSock AS3
Public repository for GreenSock's ActionScript 3 libraries
The public repository for GreenSock’s ActionScript 3 animation libraries (such as GSAP’s TweenLite, TweenMax, and LoaderMax), widely used for creating rich animations in AS3 projects. Public repository for GreenSock's ActionScript 3 libraries like GSAP (TweenLite, TweenMax, etc.) and LoaderMax. For AS2, see the GreenSock-AS2 repository and for JavaScript, see the GreenSock-JS repository. LoaderMax for managing asset loading. Well‑documented and highly modular libraries.
