Open Source ChromeOS Software - Page 91
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Software for ChromeOS
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BrowserNode
Make websites accessible for AI agents. Automate tasks online
Browsernode is an open-source TypeScript framework that allows AI agents to interact directly with web browsers in order to automate tasks and gather information from websites. The project acts as a bridge between AI models and browser automation tools, enabling language models to control web pages programmatically. Built as an implementation compatible with the Browser-use ecosystem, Browsernode allows agents to perform actions such as navigating pages, extracting information, filling forms, or interacting with dynamic web interfaces. The system integrates with Playwright to control Chromium-based browsers and execute automation scripts in a reliable environment. Developers can configure the framework to connect to different language model providers so that AI agents can interpret instructions and decide which browser actions to perform. -
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Browserless
The headless Chrome/Chromium driver on top of Puppeteer
Browserless is an open-source headless browser automation library and service built on top of Puppeteer that simplifies the process of running and scaling Chromium-based browser tasks in production environments. It provides a high-level API for interacting with headless Chrome, allowing developers to perform operations such as generating PDFs, capturing screenshots, extracting text or HTML, and automating web navigation. The project is designed to act as a production-ready abstraction layer over Puppeteer, offering improved reliability, error handling, and scalability for real-world applications. Browserless includes built-in optimizations such as request blocking, automatic retries, and sensible defaults that improve performance when processing web pages. It can be used as a standalone library, a command-line tool, or a hosted API service that scales browser instances on demand. -
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BuilderBot
Build automated conversation flows agnostic to the WhatsApp provider
With this library, you can build automated conversation flows agnostic to the WhatsApp provider, set up automated responses for frequently asked questions, receive and respond to messages automatically, and track interactions with customers. Additionally, you can easily set up triggers to expand functionalities limitlessly. -
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Bytecoder
Framework to interpret and transpile JVM bytecode to JavaScript
Bytecoder is a Rich Domain Model for Java Bytecode and Framework to interpret and transpile it to other languages such as JavaScript, OpenCL or WebAssembly. The JVM Bytecode is parsed and transformed into an intermediate representation. This intermediate representation is passed thru optimizer stages and sent to a backend implementation for target code generation. The JavaScript backend transforms the intermediate representation into JavaScript. -
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Byterover Cipher
Byterover Cipher is an opensource memory layer
Cipher is an open-source infrastructure component designed to provide a persistent memory layer for AI coding agents and developer tools. The system captures contextual information about codebases, past interactions, and reasoning steps generated by AI assistants so that agents can maintain long-term context while generating code. By storing structured knowledge about programming concepts, project logic, and previous development sessions, Cipher allows AI agents to operate with improved awareness of the software environment they are working within. The framework integrates with multiple AI coding tools and development environments through the Model Context Protocol, enabling seamless interoperability between different agents and IDEs. Cipher also supports collaborative workflows by allowing teams to share AI-generated memories and insights across development environments. -
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C-ARES
A C library for asynchronous DNS requests
This is C-ARES, an asynchronous resolver library. It is intended for applications that need to perform DNS queries without blocking, or need to perform multiple DNS queries in parallel. The primary examples of such applications are servers that communicate with multiple clients and programs with graphical user interfaces. The full source code is available in the 'C-ARES' release archives. -
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CLIP
CLIP, Predict the most relevant text snippet given an image
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language. -
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CSS Grid Generator
Generate basic CSS Grid code to make dynamic layouts
CSS Grid Generator is a visual tool built to help web designers and developers quickly create CSS Grid layout code without writing the grid definitions manually. You select the number of columns, rows, and units (e.g., fr, px, %), then visually drag and place items, resize them and position them within the grid to prototype layouts by hand. Once the layout is arranged, the tool generates the corresponding HTML and CSS you can copy into your project—thus bridging the gap between design and code. The interface supports drag-and-drop of “divs” into grid cells, and you can experiment with grid gaps, spans and layout refinements in real time. Because it removes the barrier of hand-writing complex grid-template or grid-area definitions, it’s particularly useful for designers who are less comfortable with CSS or want rapid prototyping of grid layouts. -
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CUDA Containers for Edge AI & Robotics
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
CUDA Containers for Edge AI & Robotics is an open-source project that provides a modular container build system designed for running machine learning and AI workloads on NVIDIA Jetson devices. The repository contains container configurations that package the latest AI frameworks and dependencies optimized for Jetson hardware. These containers simplify the deployment of complex machine learning environments by bundling libraries such as CUDA, TensorRT, and deep learning frameworks into reproducible container images. The project is particularly useful for developers building edge AI and robotics systems that rely on GPU-accelerated inference and real-time computer vision. By using containerized environments, developers can ensure that their applications run consistently across different Jetson platforms and JetPack versions. The repository also includes build tools and package management utilities that help automate the process of assembling machine learning environments. -
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Cactus Needle
26m function call model that runs on incredibly small devices
Needle is an experimental 26-million-parameter function-calling model designed to run on extremely small devices such as phones, watches, glasses, and low-power personal AI hardware. It is based on a Simple Attention Network architecture and was distilled from a much larger model to focus on fast, compact tool-use behavior. The project provides open weights, training details, dataset generation resources, and a playground for testing the model with custom tools. Needle is optimized for single-shot function calling rather than broad conversational ability, so its core use case is selecting the right tool and producing structured arguments. It can be fine-tuned locally, including on consumer machines, which makes it useful for experimentation with small personalized agents. The project is best suited for researchers and developers exploring tiny AI models, edge inference, and lightweight tool-calling systems. -
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CallMe
Minimal plugin that lets Claude Code call you on the phone
CallMe is a minimalist plugin for Claude Code that bridges computational tasks with real-world alerts by letting the AI call your phone, smartwatch, or even a landline when an operation finishes, gets stuck, or needs a user decision. It is designed to let users start a long-running task, leave their device, and then be notified in a natural way with a phone call instead of second-guessing progress in the console. The plugin uses a local MCP server alongside a webhook tunnel (typically via ngrok) to connect with voice providers like Telnyx or Twilio for outbound calls, with prompts and responses flowing between Claude Code and the user’s voice device. Multi-turn conversations are supported, so users can respond in real time to questions the agent asks during execution, giving it a practical human-in-the-loop capability for complex workflows. -
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Chat UI
The open source codebase powering HuggingChat
Hugging Face Chat UI is an open-source web interface designed for interacting with large language models through a modern conversational interface. The project serves as the codebase behind HuggingChat and can be deployed locally or on cloud infrastructure to create customizable AI chat applications. Built with modern web technologies such as SvelteKit and backed by MongoDB for persistence, the interface provides a responsive environment for multi-turn conversations, file handling, and configuration management. Chat UI connects to any service that exposes an OpenAI-compatible API endpoint, allowing it to work with a wide range of models and inference providers. The platform supports advanced capabilities such as multimodal input, tool integration through Model Context Protocol servers, and intelligent routing that selects the most appropriate model for each request. -
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Chat UI Kit React
Build your own chat UI with React components in few minutes
Build your own chat UI with React components in a few minutes. The Chat UI Kit from Chatscope is an open-source UI toolkit for developing web chat applications. Tired of struggling with sticky scrollbars, content editable, responsiveness, and CSS hacks? This kit is for you. Headless chat library, React hook for state management in chat applications. -
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ChatOllama
ChatOllama is an open-source AI chatbot
ChatOllama is an open-source chatbot platform built with Nuxt 3 and designed to provide a private, extensible interface for working with multiple modern language model providers. It goes beyond a basic chat UI by supporting a broad model ecosystem that includes OpenAI, Azure OpenAI, Anthropic, Google Gemini, Groq, Moonshot, Ollama, and other OpenAI-compatible services. The platform also includes higher-level capabilities such as AI agents, document-backed knowledge bases, real-time voice chat, and Model Context Protocol integration for external tools. Its RAG functionality allows document upload and knowledge-base-driven interaction, while vector database support adds more scalable retrieval options. Deployment is streamlined with Docker Compose, and the project also includes internationalization and modular feature toggles for controlling what parts of the system are enabled. As a result, ChatOllama feels less like a single chatbot and more like a flexible self-hosted AI workspace. -
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Chicory
Native JVM WebAssembly runtime
Chicory is a WebAssembly runtime designed specifically for the Java Virtual Machine, enabling developers to run Wasm modules entirely within Java applications without requiring native dependencies or JNI. Implemented in pure Java, it provides a portable and secure execution environment that can run anywhere the JVM is available, including cloud, desktop, and embedded systems. The runtime loads WebAssembly binaries and exposes their functions as callable Java APIs, allowing seamless integration with existing Java codebases. Chicory emphasizes simplicity and safety, ensuring that execution remains sandboxed while maintaining compatibility with standard WebAssembly features. Its design eliminates the need for external system libraries, making deployment straightforward and consistent across platforms. The project also supports integration into frameworks and build systems, enabling developers to embed Wasm-based functionality into larger applications. -
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ChineseBQB
Chinese sticker pack, more joy/museum of emoticon
ChineseBQB is an openly shared repository of Chinese-style stickers and memes, essentially a “meme pack / sticker museum” — curated and maintained to collect, categorize, and make accessible a large collection of expressive GIFs and images often used in chats. The repository organizes stickers contributed by many people, and uses a Node.js build script to automatically generate an index of all images, so that users can browse the entire gallery online. The goal is cultural and social: making it easy for “sticker warriors” to find, contribute, and reuse Chinese-style memes for chat, social media, or projects. Because all assets are stored in the repo (or can be downloaded via Git), the collection is transparent, free to use (subject to any licensing / reuse norms), and publicly visible — so contributors get credit for their submissions. -
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Chisel
A fast TCP/UDP tunnel over HTTP
Chisel is a lightweight tunneling tool designed to move TCP and UDP traffic through HTTP while securing the connection with SSH. It packages both client and server functionality into a single Go-based executable, which makes it practical for fast deployment across different environments. The project is especially useful when direct network access is restricted but HTTP or HTTPS traffic is still allowed. It can expose internal services, create secure endpoints, and support reverse forwarding when the reachable side needs to initiate the tunnel. Chisel also supports proxy-aware setups, including SOCKS5 and HTTP CONNECT scenarios. Its design favors simplicity, portability, and reliable reconnection behavior for practical network tunneling workflows. -
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Chonkie
The no-nonsense RAG chunking library
Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support. -
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Chronicle Queue
Micro second messaging that stores everything to disk
Micro second messaging that stores everything to disk. With millions of users worldwide, Chronicle Queue is a leading choice for organizations of all sizes seeking a low-latency, high-performance messaging framework. The Chronicle Queue Enterprise version eliminates compatibility issues and allows for the seamless integration and sharing of data between Java, Rust, Python, and C++ libraries. Chronicle Queue is available as a fully native Java, Rust or C++ library, and also supports a Python API. All versions are fully binary compatible. -
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Claude Code Plugins
Intelligent automation and multi-agent orchestration for Claude Code
Claude Code Plugins is a lightweight framework designed to define, manage, and execute AI agents in a modular and extensible way, typically focusing on orchestrating tasks using large language models and tool integrations. The project provides abstractions for building agents that can interpret instructions, execute commands, and interact with external systems in a structured workflow. It emphasizes simplicity and composability, allowing developers to define agent behaviors through reusable components rather than monolithic logic. The framework supports integration with various tools and APIs, enabling agents to perform actions such as data retrieval, automation, and decision-making processes. It is particularly useful for experimenting with autonomous or semi-autonomous systems that rely on prompt-driven logic and tool usage. The design encourages transparency and control over how agents operate, making it suitable for both prototyping and production scenarios. -
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Claude Code Plugins Directory
Official, Anthropic-managed directory of high quality Claude Plugins
Claude Code Plugins Directory repository provides a collection of plugins intended to extend Claude’s capabilities by turning the model into a specialized assistant tailored to specific workflows, teams, or organizational needs. These plugins define how Claude should access tools, retrieve data, and execute structured tasks so that outputs become more consistent and production-ready. The project emphasizes customizable automation by allowing developers to encode preferred workflows, domain knowledge, and operational rules directly into plugin configurations. It is built to work with Claude Cowork and Claude Code environments, enabling teams to standardize how AI assistance behaves across different use cases. By exposing slash commands and workflow logic, the repository helps organizations operationalize AI in real business contexts rather than relying on generic prompting. -
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Claude Code SDK Python
Python SDK for Claude Agent
claude-code-sdk-python is the Python SDK for Claude Code, Anthropic’s agentic coding system. It provides abstractions to easily query Claude Code (with streaming support) and conduct interactive sessions. The SDK includes core client classes, asynchronous query functions, and support for custom tools and hooks within Claude sessions. It is designed to integrate with local Python workflows and allow developers to embed Claude Code capabilities directly in their applications or scripts. The repo is MIT-licensed and includes documentation and installation instructions (requires Python 3.10+, Node installation of Claude Code). Example usage shows how to stream responses, parse structured message blocks, or create persistent client sessions. -
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Claude Code Skills & Plugins
232+ Claude Code skills & agent plugins for Claude Code, Codex
Claude Skills is a repository that provides a collection of structured skill definitions designed to enhance the capabilities of Claude-based AI systems. Each skill encapsulates a specific capability, such as coding, analysis, or workflow execution, allowing the model to perform tasks more effectively. The project emphasizes modularity, enabling skills to be combined and reused across different contexts. It is designed to integrate seamlessly into AI workflows, providing a plug-and-play approach to extending functionality. The repository also includes examples and templates, making it easier for developers to create their own custom skills. It supports a wide range of use cases, from development to content generation. Overall, Claude Skills acts as a library of reusable expertise modules for AI systems. -
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Claude Code Skills & Plugins Hub
270+ Claude Code plugins with 739 agent skills
Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and AI workflow orchestration. The project also includes orchestration patterns and best practices that guide how multiple AI agents or tools can collaborate effectively in software development workflows. Developers can install plugins through a package-style plugin system and integrate them with their Claude Code environment using standardized commands. -
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ClawRouter
Smart LLM router
ClawRouter is a flexible networking and routing framework designed to support AI-oriented distributed systems and agent ecosystems by managing how messages, requests, and responses are routed between components. It provides a programmable router abstraction that can handle complex traffic patterns, enabling dynamic message forwarding, load balancing, and custom routing logic based on content, context, or policy rules. Because distributed AI systems often involve many services, agents, and runtime components interacting with each other and with external APIs, ClawRouter helps ensure that communication paths remain clear, efficient, and adaptable as systems scale. The framework supports plugin-based extensions so developers can define custom protocols, transformation hooks, and monitoring handlers without modifying core routing logic. It also offers operational features like health checking, metrics reporting, and failure handling that make production deployments more reliable.
