Open Source Linux Artificial Intelligence Software - Page 68
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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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Bindu
Bindu: Turn any AI agent into a living microservice
Bindu is an open-source infrastructure layer that transforms any AI agent into a production-ready microservice capable of interacting, communicating, and transacting within a broader network of agents. It abstracts away the complexity of deployment, authentication, communication protocols, and payment systems by allowing developers to “bindufy” an agent with minimal configuration. Once integrated, the agent gains a decentralized identity, standardized communication capabilities through protocols such as A2A and AP2, and built-in support for authentication and monetization. The system is designed to be framework-agnostic, meaning developers can build agents using tools like LangChain, OpenAI SDK, or custom implementations and still deploy them seamlessly. Bindu also introduces the concept of an “Internet of Agents,” where multiple specialized agents collaborate, discover each other, and exchange services autonomously. -
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Blinko
An open-source, self-hosted personal AI note tool prioritizing privacy
Blinko is a self-hosted, open-source personal AI note-taking and idea capture tool built primarily in TypeScript and designed to keep your data private and under your control. It allows users to quickly jot down fleeting thoughts, draft content, and organize ideas with Markdown support, making it easy to record insights as they happen. What sets Blinko apart is its AI-enhanced retrieval — users can search their notes using natural language queries and get relevant results instantly rather than relying solely on keyword matches. Thanks to its lightweight architecture powered by Tauri and React, Blinko runs smoothly across platforms including Windows, macOS, Linux, and mobile, while remaining responsive and efficient even with large notebooks. The project emphasizes extensibility and open collaboration, offering a plugin marketplace and documentation for developers to build and share enhancements. -
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Botonic
Build chatbots and conversational experiences using React
Botonic is a full-stack Javascript framework to create chatbots and modern conversational apps that work on multiple platforms, web, mobile and messaging apps (Messenger, Whatsapp, Telegram, etc). Building modern applications on top of messaging apps like Whatsapp or Messenger is much more than creating simple text-based chatbots. Botonic is a full-stack serverless framework that combines the power of React and Tensorflow.js to create amazing experiences at the intersection of text and graphical interfaces. With Botonic you can focus on creating the best conversational experience for your users instead of dealing with different messaging APIs, AI/NLP complexity or managing and scaling infrastructure. It also comes with a battery of plugins so you can easily integrate popular services into your project. -
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Browser MCP
Browser MCP is a Model Context Provider (MCP) server
Browser MCP is an MCP server plus browser integration that lets AI apps automate the user’s real browser instead of launching a separate automation session. By adapting a Playwright-style approach to control the running browser profile, it reuses logged-in sessions and cookies, which reduces re-authentication friction and helps avoid some bot-detection heuristics. The server exposes structured tools for navigation, element interaction, and artifact capture (DOM, screenshots, logs), all discoverable via MCP schemas. Because it runs against the user’s primary browser, it’s well-suited to repetitive web tasks, authenticated dashboards, and debugging workflows inside MCP-capable IDEs. A public website and extension streamline installation and connect the local server to clients like Claude, Cursor, VS Code, and Windsurf. The repository shows active development and a growing star count, reflecting rapid adoption across agent tooling. -
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Browser Use MCP Server
Browse the web, directly from Cursor etc.
A browser automation server implementing the Model Context Protocol, designed to allow AI assistants to browse the web directly from applications like Cursor. It supports natural language commands for web navigation and interaction. -
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Byzer-lang
A low-code open-source programming language for data pipeline
Byzer (former MLSQL) is a low-code, open-sourced, and distributed programming language for data pipeline, analytics, and AI in a cloud-native way. Design protocol: Everything is a table. Byzer is a SQL-like language, to simplify data pipeline, analytics, and AI, combined with built-in algorithms and extensions. We believe that everything is a table, a simple and powerful SQL-like language can significantly reduce human efforts of data development without switching different tools. -
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CC Mirror
Create multiple isolated Claude Code variants with custom providers
CC Mirror is an opinionated distribution and environment manager for Claude Code that lets you create multiple isolated Claude Code variants with custom configurations, providers, and feature packs on demand. Rather than running a single global Claude Code installation, cc-mirror creates separate instances — each with its own config, session store, prompt packs, theme tweaks, and optional preloaded skills — so you can tailor different environments for specific tasks, teams, or experimentation without polluting your primary setup. It also includes an interactive terminal UI for discovering, creating, and launching these isolated variants with a single command, making setup and switching effortless. For teams, cc-mirror’s team mode brings shared task storage and coordinated multi-agent workflows using shared goals and task lists that agents can collaborate on; this is useful for scaling up agentic coding across complex projects. -
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CLIP Guided Diffusion
A CLI tool/python module for generating images from text
A CLI tool/python module for generating images from text using guided diffusion and CLIP from OpenAI. Text to image generation (multiple prompts with weights). Non-square Generations (experimental) Generate portrait or landscape images by specifying a number to offset the width and/or height. Uses fewer timesteps over the same diffusion schedule. Sacrifices accuracy/alignment for quicker runtime. options: - 25, 50, 150, 250, 500, 1000, ddim25,ddim50,ddim150, ddim250,ddim500,ddim1000 (default: 1000) Prepending a number with ddim will use the ddim scheduler. e.g. ddim25 will use the 25 timstep ddim scheduler. This method may be better at shorter timestep_respacing values. Multiple prompts can be specified with the | character. You may optionally specify a weight for each prompt. -
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CS-Ebook
Curated list of classic, high-quality computer science books
CS-Ebook is a curated repository that compiles high-quality and classic computer science books across a wide range of software-related fields. It focuses on depth over volume, selecting only well-regarded titles that support structured learning and long-term skill development. It spans core areas such as computer fundamentals, programming languages, software engineering, mathematics, data science, and artificial intelligence, making it suitable for learners at different stages. Rather than hosting files, the project serves as a discovery guide, helping users identify essential reading materials and build a strong technical foundation. CS-Ebook is actively maintained and updated to reflect relevant and modern resources while preserving foundational texts. Its organized structure allows users to navigate topics efficiently and follow a progressive learning path. Contributions are encouraged, ensuring the list evolves with community input and continues to highlight valuable resources. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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CVPR 2026
Collection of CVPR 2026 Papers and Open Source Projects
CVPR2026-Papers-with-Code is a community-maintained repository that collects research papers and corresponding open-source implementations from the CVPR 2026 conference and related computer vision research. The repository acts as a continuously updated catalog of cutting-edge research across a wide range of topics including computer vision, multimodal AI, generative models, diffusion systems, autonomous driving, medical imaging, and remote sensing. Each entry typically links to the research paper as well as the public code repository associated with the work, allowing researchers and developers to quickly access reproducible implementations. The project serves as a centralized index that makes it easier for practitioners to explore the latest advances presented at major computer vision conferences. In addition to the current CVPR cycle, the repository also references related lists covering earlier conferences such as ECCV and ICCV, creating a broader archive of vision research. -
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CakeChat
CakeChat: Emotional Generative Dialog System
CakeChat is a backend for chatbots that are able to express emotions via conversations. The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always bidirectional. By default, CuDNNGRU implementation is used for ~25% acceleration during inference. Thought vector is fed into decoder on each decoding step. Decoder can be conditioned on any categorical label, for example, emotion label or persona id. May be initialized using w2v model trained on your corpus. Embedding layer may be either fixed or fine-tuned along with other weights of the network. -
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ChatGPT Academic
ChatGPT extension for scientific research work
ChatGPT extension for scientific research work, specially optimized academic paper polishing experience, supports custom shortcut buttons, supports custom function plug-ins, supports markdown table display, double display of Tex formulas, complete code display function, new local Python/C++/Go project tree Analysis function/Project source code self-translation ability, newly added PDF and Word document batch summary function/PDF paper full-text translation function. All buttons are dynamically generated by reading functional.py, you can add custom functions at will, and liberate the pasteboard. Support for markdown tables output by GPT. If the output contains a formula, it will be displayed in tex form and rendered form at the same time, which is convenient for copying and reading. -
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ChatLLM Web
Chat with LLM like Vicuna totally in your browser with WebGPU
Chat with LLM like Vicuna totally in your browser with WebGPU, safely, privately, and with no server. Powered By web-llm. To use this app, you need a browser that supports WebGPU, such as Chrome 113 or Chrome Canary. Chrome versions ≤ 112 are not supported. You will need a GPU with about 6.4GB of memory. If your GPU has less memory, the app will still run, but the response time will be slower. The first time you use the app, you will need to download the model. For the Vicuna-7b model that we are currently using, the download size is about 4GB. After the initial download, the model will be loaded from the browser cache for faster usage. -
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ChatTTS
A generative speech model for daily dialogue
ChatTTS is an open-source conversational text-to-speech model optimized for dialogue, developed by 2Noise. Trained on 100,000+ hours of English and Chinese conversation data, it excels at generating expressive prosody—pauses, interjections, laughter—for more natural-sounding speech synthesis in assistant and chatbot applications. -
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ChatWiki
ChatWiki WeChat official account's AI knowledge base workflow agent
ChatWiki is an open-source AI knowledge base and workflow automation platform designed to help organizations build intelligent question-answering systems using large language models and retrieval-augmented generation techniques. The system enables companies to transform internal documents and data into searchable knowledge bases that can power AI assistants capable of answering domain-specific questions. It provides a complete pipeline for ingesting documents, preprocessing and segmenting content, generating vector embeddings, and retrieving relevant information during conversations. The platform supports multiple large language models and allows developers to easily connect cloud-based or local models to power the chatbot. ChatWiki also integrates workflow automation features that allow AI responses, messaging triggers, and customer interaction flows to be configured visually. -
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Chatterbox TTS Server
Self-host the powerful Chatterbox TTS model
Chatterbox-TTS-Server is a self-hosted server for running the Chatterbox text-to-speech model through both a web interface and API endpoints. It is designed for users who want local or private speech generation without depending entirely on a hosted voice platform. The project supports predefined voices, voice cloning, and longer text workflows, making it useful for audiobooks, narration, content tools, and assistant-style applications. It also includes OpenAI-compatible API behavior, which helps developers connect it to existing tools that already expect that style of endpoint. The server can run on NVIDIA CUDA, AMD ROCm, or CPU, giving it flexibility across different hardware setups. Its main value is packaging a powerful TTS workflow into a practical service that can be accessed through a browser or integrated into other software. -
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Chemprop
Message Passing Neural Networks for Molecule Property Prediction
Chemprop is a repository containing message-passing neural networks for molecular property prediction. -
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Claude Ads
Comprehensive paid advertising audit & optimization skill
Claude Ads is an AI-powered auditing and optimization tool designed to analyze paid advertising campaigns across multiple platforms using Claude Code. It processes user-provided data such as exports or screenshots and evaluates campaigns using hundreds of predefined checks. The system generates structured reports, identifies inefficiencies, and suggests optimization strategies based on industry benchmarks. It supports platforms like Google Ads, Meta Ads, TikTok, LinkedIn, and more, offering a unified analysis workflow. The architecture uses parallel subagents to speed up audits and includes financial modeling and A/B testing guidance. It runs locally, ensuring privacy and control over sensitive advertising data. The project is aimed at replacing manual audit workflows with fast, automated, and repeatable analysis. -
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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 Security Reviewer
An AI-powered security review GitHub Action using Claude
The claude-code-security-review repository implements a GitHub Action that uses Claude (via the Anthropic API) to perform semantic security audits of code changes in pull requests. Rather than relying purely on pattern matching or static analysis, this action feeds diffs and surrounding context to Claude to reason about potential vulnerabilities (e.g. injection, misconfigurations, secrets exposure, etc). When a PR is opened, the action analyzes only the changed files (diff-aware scanning), generates findings (with explanations, severity, and remediation suggestions), filters false positives using custom prompt logic, and posts comments directly on the PR. It supports configuration inputs (which files/directories to skip, model timeout, whether to comment on the PR, etc). The tool is language-agnostic (it doesn’t need language-specific parsers), uses contextual understanding rather than simplistic rules, and aims to reduce noise with smarter filtering. -
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Claude HUD
A Claude Code plugin that shows what's happening
Claude HUD is a real-time monitoring add-on for Claude Code that places a persistent heads-up display directly in your interactive session, giving developers clear insight into what the AI engine is doing at every moment. Instead of guessing about hidden processes behind the scenes, users see the amount of context remaining in the current session, tools being used, active running agents, and the progress of TODO tasks that the AI has planned or is executing. This plugin was designed to reduce cognitive load and make agentic workflows more transparent, helping developers diagnose stalled tasks, understand resource usage, and manage multi-step reasoning sequences more effectively. It installs with zero configuration and appears immediately in Claude Code, making it helpful for both newcomers and seasoned users who want better situational awareness without interrupting their workflow. -
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Claudia Bot Builder
Create chat bots for Facebook Messenger, Slack, Amazon Alexa, etc.
Claudia Bot Builder helps developers create and deploy chat-bots for various platforms in minutes to AWS Lambda. It simplifies the messaging workflows, automatically sets up the correct web hooks, and guides you through configuration steps, so that you can focus on important business problems and not have to worry about infrastructure code. This code is enough to operate bots for all supported platforms. Claudia Bot Builder automatically parses the incoming messages into a common format, so you can handle it easily. It also automatically packages the response into the correct message template for the requesting bot, so you do not have to worry about individual bot protocols. Claudia Bot Builder doesn't have a stand-alone http server in the background (such as Express, Hapi, etc.), instead it uses API Gateway and it's not trivial to simulate similar environment locally. Deploy it with --version test to create a separate test environment directly in AWS Lambda. -
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Clay Foundation Model
The Clay Foundation Model - An open source AI model and interface
The Clay Foundation Model is an open-source AI model and interface designed to provide comprehensive data and insights about Earth. It aims to serve as a foundational tool for environmental monitoring, research, and decision-making by integrating various data sources and offering an accessible platform for analysis. -
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CleanRL
High-quality single file implementation of Deep Reinforcement Learning
CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should consider using CleanRL if you want to 1) understand all implementation details of an algorithm's variant or 2) prototype advanced features that other modular DRL libraries do not support (CleanRL has minimal lines of code so it gives you great debugging experience and you don't have to do a lot of subclassing like sometimes in modular DRL libraries). -
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Cloudflare OS
Agent workspace built on Cloudflare Workers for creating documents
Cloudflare OS is an open-source AI productivity environment originally developed for internal use across Cloudflare. It combines an agent chat interface, company-specific knowledge, sandboxed application creation, and a capability-based security framework. Users can ask agents to prepare documents, build dashboards, create collaborative tools, or work with connected services. Generated applications are called Gadgets and run as private, isolated instances that can be modified and securely shared. Gatekeepers control external access, manage authorization, log actions, restrict resources, and queue side effects for later human approval. Blueprints serve as reusable application templates rather than simple document templates. The system runs on Cloudflare Workers and is released as an early-access foundation that organizations can customize into their own company operating environment.
