Open Source ChromeOS Software - Page 71
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Software for ChromeOS
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MemMachine
Universal memory layer for AI Agents
MemMachine is a universal memory layer designed for AI agents that provides persistent, rich memory storage and retrieval capabilities so autonomous agent systems can recall context, personal preferences, and long-term interaction history across sessions, models, and use cases. Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. It offers flexible APIs, a Python SDK, REST interfaces, and MCP (Model Context Protocol) connectivity to integrate seamlessly with agent frameworks receiving and storing memories over time, effectively boosting relevance, continuity, and tailored behavior. -
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MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching. It aims to support advanced workflows like persistent in-memory data structures, crash-resilient state handling, and seamless sharing of data across tasks without copying. By abandoning some of the historical assumptions of Unix-style operating systems, MemOS attempts to unlock new performance and scalability tradeoffs for applications that need high throughput and low latency on memory-intensive workloads. -
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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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Mike
OSS AI Legal Platform
Mike is a software project that appears to focus on automation or tooling, likely designed to streamline workflows related to development, deployment, or data processing. It may function as a command-line utility or lightweight framework that integrates with existing systems to improve efficiency. The project emphasizes simplicity and clarity, providing focused functionality without unnecessary overhead. Its design likely supports extensibility, allowing users to adapt it to specific use cases or integrate it into larger pipelines. The repository may include scripts, utilities, or abstractions that reduce repetitive tasks and improve productivity. Overall, mike represents a pragmatic approach to solving targeted technical problems through concise tooling. -
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.
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Milkdown
Plugin driven WYSIWYG markdown editor framework
A plugin-driven WYSIWYG markdown Editor, inspired by Typora, built on top of prose-mirror and remark. The website is designed by Meo and Mirone. Powered by Theme Nord and Material Design. A plugin driven framework to build WYSIWYG Markdown editor. -
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MirageOS
MirageOS is a library operating system that constructs unikernels
A programming framework for building type-safe, modular systems. MirageOS is a library operating system that constructs unikernels for secure, high-performance network applications across a variety of cloud computing and mobile platforms. Code can be developed on a normal OS such as Linux or macOS, and then compiled into a fully standalone, specialized unikernel that runs under a Xen or KVM hypervisor. This lets your services run more efficiently, securely and with finer control than with a full conventional software stack. -
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Mix Space Core
The next generation of RESTful API service
MX-Space Core is a content management platform designed for blogging and personal websites, with a focus on customization and user experience. -
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ModernGL
Modern OpenGL binding for Python
ModernGL is a Python wrapper over OpenGL, designed to simplify the creation of high-performance, modern graphics applications. It provides an intuitive API for rendering 2D and 3D graphics, making it accessible to both beginners and experienced developers. ModernGL is suitable for applications such as games, simulations, and data visualizations. -
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MoonShine
Laravel Admin panel and more. Simple for beginners and experts
You are on an open source project dedicated to the "MoonShine" admin panel. Everything is already ready for use in your projects, documentation has been created describing the installation, configuration and features. -
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Music Source Separation
Separate audio recordings into individual sources
Music Source Separation is a PyTorch-based open-source implementation for the task of separating a music (or audio) recording into its constituent sources — for example isolating vocals, instruments, bass, accompaniment, or background from a mixed track. It aims to give users the ability to take any existing song and decompose it into separate stems (vocals, accompaniment, etc.), or to train custom separation models on their own datasets (e.g. for speech enhancement, instrument isolation, or other audio-separation tasks). The repository provides training scripts (e.g. using datasets such as MUSDB18), preprocessing steps (audio-to-HDF5 packing, indexing), evaluation pipelines, and inference scripts to perform separation on arbitrary audio files. This makes the project useful both for researchers in music information retrieval / audio machine learning and for hobbyists or practitioners who want to experiment with remixing, karaoke, or audio editing. -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference pipelines for models that combine data-driven learning with physics-based constraints. It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations. -
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NaveGo
NaveGo: an open source MATLAB/GNU Octave toolbox for processing integr
NaveGo is an open source MATLAB/GNU Octave toolbox designed for processing integrated navigation systems, simulating inertial sensors and GNSS receivers, and profiling inertial sensors using methods like Allan variance—providing a community-driven simulation framework for navigation system design and analysis. I am reaching out to share an important update regarding the NaveGo project. Due to a shift in both my professional career and personal interests away from navigation systems, I have made the difficult decision to step down from my role as the lead developer of NaveGo. Effective immediately, NaveGo will transition to a community-driven project. This change opens up new opportunities for collaboration, innovation, and leadership within our vibrant community. I encourage each of you to actively participate, whether by answering questions in the discussion forum, contributing to the development of new features, or sharing your unique insights and expertise. -
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Nestia
NestJS Helper + AI Chatbot Development
Nestia is a high-performance toolkit and ecosystem built on top of NestJS that enhances backend development by introducing strongly typed APIs, automated SDK generation, and advanced tooling for scalable server applications. It is designed to eliminate much of the boilerplate typically associated with API development by leveraging pure TypeScript types to automatically generate validation logic, API documentation, and client SDKs. One of its defining advantages is its focus on performance optimization, offering dramatically faster runtime validation and serialization compared to traditional libraries commonly used in NestJS environments. Nestia also integrates advanced capabilities such as automatic end-to-end test generation and mock server simulation, allowing developers to test and prototype applications with minimal manual setup. -
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NextUI
Beautiful, fast and modern React UI library.
Make beautiful websites regardless of your design experience. Beautiful, fast, and modern React UI library. Provides a plugin to customize default themes, you can change all semantic tokens or create an entirely new theme. Built on top of Tailwind CSS, which means no runtime styles, and no unnecessary classes in your bundle. Automatic dark mode recognition, NextUI automatically changes the theme when detects HTML theme prop changes. NextUI is fully-typed to minimize the learning curve and provide the best possible developer experience. NextUI comes with a fully well-scaled default dark theme that you can apply to your application by just adding the dark attribute to your HTML. -
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Niquests
Drop-in replacement for Requests. Automatic HTTP/1.1, HTTP/2, and HTTP
Niquests is a modern Python HTTP client designed as a drop-in replacement for Requests. It keeps the familiar Requests-style API while adding newer protocol support that the original library does not prioritize. The library can automatically work across HTTP/1.1, HTTP/2, and HTTP/3, and it also includes WebSocket and Server-Sent Events support. Niquests provides both synchronous and asynchronous usage patterns, making it suitable for scripts, backend services, crawlers, API clients, and modern async Python applications. It aims to preserve compatibility with common Requests ecosystem tools while expanding what Python HTTP clients can do. It is especially useful for developers who like Requests but need stronger protocol coverage, async support, and a more actively evolving feature set. -
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Norish
A realtime, self-hosted recipe app for families & friends
Norish is a realtime, self-hosted recipe and meal-planning app built for families, friends, and collaborative cooks who want to maintain a shared catalogue of recipes and grocery lists. The project emphasizes simplicity and immediacy, syncing changes across multiple clients using WebSockets so that updates to recipes, groceries, or meal plans appear instantly for all users. The app allows users to import recipes from URLs and even fallback to AI parsing when needed, with multimedia support that includes video import from popular platforms when AI is configured. Norish also handles grocery list management with recurring items and calendar meal planning, giving household groups an organized view of upcoming meals. Built with modern web technologies and designed for self-hosting, the app includes support for single sign-on via OIDC providers, a mobile-friendly interface, and user permissions for editing or viewing recipes and lists. -
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Numba CUDA Target
The CUDA target for Numba
Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. The project supports the SIMT programming model, allowing developers to control threads, blocks, and memory hierarchies similarly to native CUDA programming. It is also used as a foundation for accelerating higher-level libraries such as RAPIDS, where custom user-defined GPU functions are required. The repository represents the continuation of CUDA support after its deprecation in core Numba, ensuring ongoing development and optimization under NVIDIA’s ecosystem. -
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Nutgram
The Telegram bot framework that doesn't drive you nuts
This framework takes advantage of the latest PHP 8.2 features and tries to make the speed, scalability and flexibility of use its strength, it will allow you to quickly make simple bots, but at the same time, it provides more advanced features to handle even the most complicated flows. The Telegram bot framework doesn't drive you nuts. -
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Odigos
Distributed tracing without code changes
Odigos supports any application written in Java, Python, .NET, Node.js and Go. Historically, compiled languages like Go have been difficult to instrument without code changes. Odigos solves this problem by uniquely leveraging eBPF. Odigos currently supports all the popular managed and open source destinations. By producing data in the OpenTelemetry format, Odigos can be used with any observability tool that supports OTLP. Odigos automatically scales OpenTelemetry collectors based on observability data volume. Manage and configure collectors via a convenient web UI. Installing Odigos takes less than 5 minutes, and requires no code changes. -
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OllamaSharp
The easiest way to use Ollama in .NET
OllamaSharp is an open-source .NET library that provides strongly typed bindings for interacting with the Ollama API, making it easier for developers to integrate local large language models into C# and .NET applications. The project acts as a wrapper around the Ollama API, exposing all endpoints through asynchronous methods that allow developers to perform tasks such as generating text, creating embeddings, and managing models. It supports both local and remote Ollama instances, enabling developers to run AI models on their own hardware or connect to remote model servers. The library is designed to simplify integration by allowing developers to interact with AI models using just a few lines of code while still supporting advanced functionality. OllamaSharp also includes real-time streaming capabilities that allow applications to display generated responses incrementally as they are produced. -
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Ollamac
Mac app for Ollama
Ollamac is an open-source native macOS application that provides a graphical interface for interacting with local large language models running through the Ollama inference framework. The project was created to simplify the process of using local AI models, which typically require command-line interaction, by offering a clean and intuitive desktop interface. Through this interface, users can run and chat with a variety of LLM models installed through Ollama directly on their own machines. The application focuses on delivering a lightweight and responsive experience that integrates seamlessly with the macOS ecosystem. Because the models run locally, the system enables private AI workflows without sending data to external APIs or cloud services. Ollamac supports different Ollama models and provides features designed to improve usability such as syntax highlighting and configurable settings. -
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One Dark Pro
Atom's iconic One Dark theme for Visual Studio Code
One Dark Pro is a popular Visual Studio Code theme inspired by the Atom One Dark theme, designed to provide a visually appealing and consistent coding environment. It focuses on readability and aesthetics, using a carefully selected color palette that reduces eye strain while maintaining strong contrast between code elements. The theme supports a wide range of programming languages, ensuring consistent syntax highlighting across different file types. It also integrates seamlessly with VS Code features, enhancing the overall developer experience. The design emphasizes clarity, making it easier to navigate and understand complex codebases. It is widely adopted due to its balance between style and functionality. Overall, OneDark-Pro serves as a high-quality customization option for developers seeking a polished coding interface. -
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Open Vision Agents by Stream
Build Vision Agents quickly with any model or video provider
Open Vision Agents by Stream is an open source framework from Stream for building real time, multimodal AI agents that watch, listen, and respond to live video streams. It focuses on combining video understanding models, such as YOLO and Roboflow based detectors, with real time large language models like OpenAI Realtime and Gemini Live to create interactive experiences. The framework uses Stream’s ultra low latency edge network so agents can join sessions quickly and maintain very low audio and video latency while processing frames and generating responses. Developers work with an agent abstraction that connects video edge providers, LLMs, and processors into pipelines, making it easier to orchestrate tasks like object detection, pose estimation, and conversational guidance. The project includes SDKs for React, Android, iOS, Flutter, React Native, and Unity, enabling integration into a wide variety of client environments such as mobile apps, web apps, and games. -
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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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OpenArchiver
An open-source platform for legally compliant email archiving
OpenArchiver is a comprehensive, self-hosted email archiving and compliance platform built to help organizations ingest, index, store, and search email communication data across diverse sources like Gmail, Microsoft 365, IMAP, PST, and more. It’s designed for scenarios where reliable, tamper-proof archiving and full-text search across both emails and attachments are essential for legal discovery, compliance, or long-term records retention. The platform combines a modern web UI with powerful backend services, including fast indexing, deduplication, encryption at rest, and asynchronous ingestion workflows, making it suitable for both small teams and enterprise deployments. Beyond simply capturing email, it emphasizes security and auditability with features like secure storage formats, file integrity verification, and detailed audit trails of user interactions.
