Open Source Unix Shell Artificial Intelligence Software
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Unix Shell Artificial Intelligence Software
View 13452 business solutionsBrowse free open source Unix Shell Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source Unix Shell Artificial Intelligence Software by OS, license, language, programming language, and project status.
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Umbrel
A beautiful personal server OS for Raspberry Pi or any Linux distro
Run your personal server with a Bitcoin and Lightning node in your home, self-host open source apps like Nextcloud and Matrix to break away from big tech, and take full control of your data. For free. All our interactions on the internet today are mediated by a few companies who offer “free” services in exchange for storing our data on their servers to spy on us. Running a personal server fundamentally changes that. You and your family’s photos, videos, files, notes, passwords, everything, have nothing to do with someone else’s computer. They’re a part of your private life, and now they can all be stored by you, in your home, on your Umbrel. The Bitcoin network is made up of thousands of nodes that verify every single transaction in the blockchain. Some of them mine Bitcoin too, but unlike a mining node, running a non-mining node doesn’t require expensive hardware. Achieve unparalleled privacy by connecting your wallet directly to the Bitcoin node on your Umbrel. -
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Replica Dataset
High-fidelity indoor 3D dataset for AI simulation and robotics
Replica Dataset is a high-quality 3D dataset of realistic indoor environments designed to advance research in computer vision, robotics, and embodied AI. Developed by Facebook Research (now Meta AI), it features accurate geometric reconstructions, high-resolution and high dynamic range textures, and comprehensive semantic annotations. Each environment contains detailed models of real-world spaces, including rooms, furniture, glass, and mirror surfaces. The dataset also provides semantic and instance segmentations, planar decomposition, and navigation meshes, making it highly suitable for simulation, visual perception, and autonomous navigation tasks. Replica integrates seamlessly with AI Habitat, Meta’s framework for embodied AI training, enabling large-scale agent simulation and photorealistic rendering for reinforcement learning and robotics. Researchers can use Replica’s ReplicaViewer to interactively explore the 3D scenes. -
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CogVideo
text and image to video generation: CogVideoX (2024) and CogVideo
CogVideo is an open source text-/image-/video-to-video generation project that hosts the CogVideoX family of diffusion-transformer models and end-to-end tooling. The repo includes SAT and Diffusers implementations, turnkey demos, and fine-tuning pipelines (including LoRA) designed to run across a wide range of NVIDIA GPUs, from desktop cards (e.g., RTX 3060) to data-center hardware (A100/H100). Current releases cover CogVideoX-2B, CogVideoX-5B, and the upgraded CogVideoX1.5-5B variants, plus image-to-video (I2V) models, with options for BF16/FP16/FP32—and INT8 quantized inference via TorchAO for memory-constrained setups. The codebase emphasizes practical deployment: prompt-optimization utilities (LLM-assisted long-prompt expansion), Colab notebooks, a Gradio web app, and multiple performance knobs (tiling/slicing, CPU offload, torch.compile, multi-GPU, and FA3 backends via partner projects). -
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AnyClaw
Android app running two AI coding agents with a built-in Linux runtime
openclaw-android-assistant, also known as AnyClaw, is an Android application that packages two AI coding agents into a single mobile app environment. It bundles the OpenClaw personal AI assistant together with the OpenAI Codex CLI so developers can interact with AI agents directly from an Android device. Both agents run inside a self-contained Linux userland that is embedded within the APK, allowing command execution, coding tasks, and agent interactions without requiring root access or external tools. openclaw-android-assistant provides a control dashboard interface where users can manage agents, sessions, skills, and conversations from a unified interface. Through the embedded runtime, the agents can read codebases, write code, and execute shell commands within the packaged Linux environment. It also supports parallel conversations with separate working contexts, enabling multi-threaded development workflows on a mobile device. -
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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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art performance compared to other open models like InCoder and CodeGen. CodeGeeX also powers IDE plugins for VS Code and JetBrains, offering features like code completion, translation, debugging, and annotation. The model supports Ascend 910 and NVIDIA GPUs, with optimizations like quantization and FasterTransformer acceleration for faster inference. -
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AI File Sorter
Local AI file organization with categorization and rename suggestions
AI File Sorter is a cross-platform desktop application that uses AI (local LLMs run on your computer) to organize files and suggest meaningful file names based on real content, not just filenames or extensions. The app can analyze images locally and propose descriptive rename suggestions (for example, IMG_2048.jpg → clouds_over_lake.jpg). It can also analyze document text to improve categorization and renaming. Supported formats include PDF, DOCX, XLSX, PPTX, ODT, ODS, ODP, and common text files. For supported audio and video files, AI File Sorter can read embedded metadata (such as ID3, Vorbis, and MP4 tags) to suggest normalized names like year_artist_album_title.ext. AI analysis runs read-only, and all suggestions must be reviewed before being applied. AI File Sorter can run fully offline using local models like Mistral or LLaMA, so files and metadata stay on your device unless you configure a remote endpoint. -
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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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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to experiment with new algorithms, as well as for practitioners who want robust, production-ready ASR pipelines. It includes extensive tools for data preparation, feature extraction, acoustic and language modeling, decoding, and evaluation. With its modular design, Kaldi allows users to adapt the system to a wide range of languages and domains. As one of the most influential projects in speech recognition, it has become a foundation for much of the modern work in ASR. -
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PasteMD
Paste Markdown and AI responses into Word Excel instantly fast
PasteMD is a lightweight desktop utility designed to streamline the process of transferring formatted content from the clipboard into office applications such as Word, WPS, and Excel. It primarily targets users who frequently copy content from AI chat tools or web pages and encounter formatting issues, especially with Markdown, tables, and LaTeX formulas. PasteMD operates from the system tray and monitors clipboard content, automatically converting Markdown or HTML into properly formatted documents using Pandoc. With a single global hotkey, users can paste structured content directly into the active application without manual cleanup or reformatting. It includes intelligent detection mechanisms that distinguish between Markdown tables, rich HTML content, and plain text, ensuring the correct output format is used for each target application. PasteMD also introduces extensible workflows that allow users to configure different paste behaviors. -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. Each lesson includes a short video, a written guide, runnable samples for Azure OpenAI, the GitHub Marketplace Model Catalog, and the OpenAI API, plus a “Keep Learning” section for deeper study. -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and coding assistants to automate tasks such as code research, planning, and implementation while maintaining a structured development process. HumanLayer introduces advanced context management techniques that help AI agents understand large repositories and operate effectively across multiple tasks. It also supports collaborative workflows where developers and AI agents can work together with human oversight and control. -
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Olares
Olares: An Open-Source Sovereign Cloud OS for Local AI
Olares is an AI-powered chatbot framework designed to support real-time natural language understanding and response generation. -
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CodeGeeX2
CodeGeeX2: A More Powerful Multilingual Code Generation Model
CodeGeeX2 is the second-generation multilingual code generation model from ZhipuAI, built upon the ChatGLM2-6B architecture and trained on 600B code tokens. Compared to the first generation, it delivers a significant boost in programming ability across multiple languages, outperforming even larger models like StarCoder-15B in some benchmarks despite having only 6B parameters. The model excels at code generation, translation, summarization, debugging, and comment generation, and it supports over 100 programming languages. With improved inference efficiency, quantization options, and multi-query/flash attention, CodeGeeX2 achieves faster generation speeds and lightweight deployment, requiring as little as 6GB GPU memory at INT4 precision. Its backend powers the CodeGeeX IDE plugins for VS Code, JetBrains, and other editors, offering developers interactive AI assistance with features like infilling and cross-file completion. -
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Open Semantic Search
Open source semantic search and text analytics for large document sets
Open Semantic Search is an open source research and analytics platform designed for searching, analyzing, and exploring large collections of documents using semantic search technologies. It provides an integrated search server combined with a document processing pipeline that supports crawling, text extraction, and automated analysis of content from many different sources. Open Semantic Search includes an ETL framework that can ingest documents, process them through analysis steps, and enrich the data with extracted information such as named entities and metadata. It also supports optical character recognition to extract text from images and scanned documents, including images embedded inside PDF files. It integrates text mining and analytics capabilities that allow users to examine relationships, topics, and structured data within document collections. -
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civitai
Open platform for sharing and discovering Stable Diffusion models
Civitai is an open source project that provides the codebase for a platform designed to share and manage generative AI models used for image generation. It focuses primarily on models compatible with Stable Diffusion and related technologies, allowing creators to upload, organize, and distribute custom AI models and related resources. These resources can include textual inversions, hypernetworks, aesthetic gradients, and variational autoencoders that modify or extend the capabilities of diffusion-based image generation systems. Civitai encourages collaboration by allowing users to publish their models, explore models created by others, and learn from the techniques used in the community. It also supports user accounts, model browsing, and interaction features that help creators showcase their work and receive feedback from other users. Developers can deploy the project to run their own instance of the platform and integrate with its available API to retrieve models. -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. At its core, Claude-Flow integrates Dynamic Agent Architecture (DAA) for self-organizing agent management, neural pattern recognition accelerated by WebAssembly SIMD, and a SQLite-based memory system for context retention and knowledge persistence across tasks. It automates development workflows via pre- and post-operation hooks, providing seamless coordination, code formatting, validation, and performance optimization. -
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DeepAudit
AI multi-agent platform for automated code security auditing system
DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. DeepAudit performs deep semantic understanding of code, enabling it to detect complex vulnerabilities that span multiple files and business logic layers. It also includes automated proof-of-concept validation using a sandboxed environment, allowing detected issues to be tested for real exploitability. DeepAudit integrates retrieval-augmented generation techniques to enhance contextual understanding and reduce false positives during analysis. Users can import projects and trigger a full audit workflow that includes risk identification, exploit generation, validation, and final report creation. -
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Desktop Commander MCP
AI-powered MCP server for desktop file and terminal automation
Desktop Commander MCP is an advanced Model Context Protocol server designed to extend AI assistants with direct control over a user’s local machine, including the file system and terminal. It integrates with clients like Claude Desktop to enable AI-driven workflows such as editing files, executing commands, and automating development tasks from a single conversational interface. Desktop Commander MCP builds on top of an MCP filesystem server and enhances it with powerful search, replace, and code editing capabilities tailored for real-world development environments. It allows users to run terminal commands with streaming output, manage long-running processes, and even execute code in memory without saving files. It also supports working with structured and document formats such as Excel, PDF, and DOCX, enabling AI to read, modify, and generate these files directly. -
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LoLLMs WEBUI
Local AI WebUI for running and managing large language models offlineA
lollms-webui is a locally hosted web interface designed to run and manage large language models without relying on external services. It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users download, configure, and switch between different language models with ease. It is built to be user-friendly while still offering advanced customization options for power users who want deeper control over model behavior. Additionally, it supports extensibility through plugins or modular components, enabling users to expand functionality as needed. Overall, it serves as a flexible platform for running AI locally with a focus on usability and adaptability. -
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VMZ (Video Model Zoo)
VMZ: Model Zoo for Video Modeling
The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal integration strategies that influenced modern architectures like SlowFast and X3D. -
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ChatGLM2-6B
ChatGLM2-6B: An Open Bilingual Chat LLM
ChatGLM2-6B is the second-gen Chinese-English conversational LLM from ZhipuAI/Tsinghua. It upgrades the base model with GLM’s hybrid pretraining objective, 1.4 TB bilingual data, and preference alignment—delivering big gains on MMLU, CEval, GSM8K, and BBH. The context window extends up to 32K (FlashAttention), and Multi-Query Attention improves speed and memory use. The repo includes Python APIs, CLI & web demos, OpenAI-style/FASTAPI servers, and quantized checkpoints for lightweight local deployment on GPUs or CPU/MPS. -
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CogVLM
A state-of-the-art open visual language model
CogVLM is an open-source visual–language model suite—and its GUI-oriented sibling CogAgent—aimed at image understanding, grounding, and multi-turn dialogue, with optional agent actions on real UI screenshots. The flagship CogVLM-17B combines ~10B visual parameters with ~7B language parameters and supports 490×490 inputs; CogAgent-18B extends this to 1120×1120 and adds plan/next-action outputs plus grounded operation coordinates for GUI tasks. The repo provides multiple ways to run models (CLI, web demo, and OpenAI-Vision–style APIs), along with quantization options that reduce VRAM needs (e.g., 4-bit). It includes checkpoints for chat, base, and grounding variants, plus recipes for model-parallel inference and LoRA fine-tuning. The documentation covers task prompts for general dialogue, visual grounding (box→caption, caption→box, caption+boxes), and GUI agent workflows that produce structured actions with bounding boxes. -
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Rhasspy
Offline private voice assistant for many human languages
Rhasspy (ˈɹæspi) is an open-source, fully offline set of voice assistant services for many human languages that works well with Hermes protocol-compatible services (Snips.AI), Home Assistant and Hass.io, Node-RED, Jeedom, OpenHAB. Rhasspy will produce JSON events that can trigger action in home automation software, such as a Node-RED flow. Rhasspy comes with a snazzy web interface that lets you configure, program, and test your voice assistant remotely from your web browser. All of the web UI's functionality is exposed in a comprehensive HTTP API. You can easily extend or replace functionality in Rhasspy by using the appropriate messages. Many of these messages can be also sent and received over the HTTP API and the WebSocket API. Rhasspy is intended for savvy amateurs or advanced users that want to have a private voice interface to their chosen home automation software. -
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A series of open source files and programs available to use for developing programs to work with the WowWee Robotics RSMedia Robot. These include a USB serial console, a cross-compiler, a firmware dump program, text-to-speech and source code.
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ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
ChatGLM3 is ZhipuAI & Tsinghua KEG’s third-gen conversational model suite centered on the 6B-parameter ChatGLM3-6B. It keeps the series’ smooth dialog and low deployment cost while adding native tool use (function calling), a built-in code interpreter, and agent-style workflows. The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment.
