Open Source Linux ChatGPT Apps
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ChatGPT Apps for Linux
View 4 business solutionsBrowse free open source ChatGPT Apps and projects for Linux below. Use the toggles on the left to filter open source ChatGPT Apps by OS, license, language, programming language, and project status.
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ChatGPT Desktop Application
🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
ChatGPT Desktop Application (Mac, Windows and Linux) -
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Chatbox
The Ultimate AI Copilot on Your Desktop
Chatbox is a cross-platform desktop AI client designed to give you a fast, polished, and private way to work with modern language models. It runs locally on Windows, macOS, and Linux, keeping your conversations and data stored on your own device. Chatbox acts as a unified interface for popular LLMs like ChatGPT, Claude, Gemini, and local models via Ollama, making it easy to switch providers without changing tools. Built with an ergonomic UI, it’s optimized for long sessions, prompt experimentation, and everyday productivity. The app supports rich formatting, streaming responses, and advanced prompting to help you get clearer, more useful outputs. For individuals and teams alike, Chatbox serves as a powerful desktop copilot that blends simplicity with flexibility. -
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AutoGPT
Powerful tool that lets you create and run intelligent agents
AutoGPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. -
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gpt-2-simple
Python package to easily retrain OpenAI's GPT-2 text-generating model
A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifically the "small" 124M and "medium" 355M hyperparameter versions). Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to start with a given phrase. For finetuning, it is strongly recommended to use a GPU, although you can generate using a CPU (albeit much more slowly). If you are training in the cloud, using a Colaboratory notebook or a Google Compute Engine VM w/ the TensorFlow Deep Learning image is strongly recommended. (as the GPT-2 model is hosted on GCP) You can use gpt-2-simple to retrain a model using a GPU for free in this Colaboratory notebook, which also demos additional features of the package. Note: Development on gpt-2-simple has mostly been superceded by aitextgen, which has similar AI text generation capabilities with more efficient training time. -
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AXEM-SX
AXEM-SX is a modular, performance-driven operating system
AXEM-SX is a modular operating system engineered on a stable openSUSE Leap foundation, designed for performance, resilience, and clarity. Developed over several months of focused work, it reflects a philosophy of simplicity, control, and efficiency without unnecessary overhead. The system is distributed in two editions, both on Wayland: • AXEM-SX Light — a minimal, fast, lightweight LXQt accessible environment designed for essential computing and lower-resource systems. • AXEM-SX Pro — a more complete and capable environment with extended tools and features for advanced users and professional workflows, a modern KDE Plasma experience. AXEM-SX is not a generic redistribution, but a structured system built with intentional design choices to improve usability, responsiveness, and operational clarity, Each release is packaged as a bootable ISO image for direct testing, installation, or deployment. This project serves as the official distribution point for AXEM-SX releases. -
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Alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint with a modified script and then quantized with llama.cpp the regular way. -
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ChatALL
Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vincuna, etc.
Concurrently chat with ChatGPT, Bing Chat, bard, Alpaca, Vincuna, Claude, ChatGLM, MOSS, iFlytek Spark, ERNIE and more, discover the best answers. Large Language Models (LLMs) based AI bots are amazing. However, their behavior can be random and different bots excel at different tasks. If you want the best experience, don't try them one by one. ChatALL (Chinese name: 齐叨) can send prompt to several AI bots concurrently, help you to discover the best results. -
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. NB, while neo can technically run a training step at 200B+ parameters, it is very inefficient at those scales. This, as well as the fact that many GPUs became available to us, among other things, prompted us to move development over to GPT-NeoX. All evaluations were done using our evaluation harness. Some results for GPT-2 and GPT-3 are inconsistent with the values reported in the respective papers. We are currently looking into why, and would greatly appreciate feedback and further testing of our eval harness. -
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PyGPT
Open source personal AI Assistant for Linux, Windows and Mac
PyGPT is a desktop application that allows you to talk to OpenAI's LLM models such as GPT4 and GPT3 using your own computer and OpenAI API. It allows you to talk in chat mode and in completion mode, as well as generate images using DALL-E 2. PyGPT also adds access to the Internet for GPT via Google Custom Search API and Wikipedia API and includes voice synthesis using Microsoft Azure Text-to-Speech API. Moreover, the application has implemented context memory support, context storage, history of contexts, which can be restored at any time and e.g. continue the conversation from point in history, and also has a convenient and intuitive system of presets that allows you to quickly and pleasantly create and manage your prompts. Plugins support is also available. -
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ChatGPT DAN
ChatGPT DAN, Jailbreaks prompt
ChatGPT_DAN is a repository that explores prompt engineering techniques designed to alter or expand the behavior of AI language models by crafting specific instructions that influence how responses are generated. The project focuses on creating and refining prompts that encourage models to operate outside of their default constraints, often simulating alternative personas or unrestricted modes of interaction. It serves as a collection of experimental prompt patterns that demonstrate how language models can be guided through carefully structured input. The repository is often used as a learning resource for understanding the mechanics of prompt design and model behavior manipulation. It highlights both the capabilities and limitations of large language models when exposed to unconventional instructions. The project reflects ongoing experimentation within the AI community around control, alignment, and creative use of generative systems. -
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Edge GPT
Reverse engineered API of Microsoft's Bing Chat
EdgeGPT is a reverse-engineered client project that exposed a programmatic interface to Microsoft’s Bing Chat experience (often associated with “Edge” due to access patterns and requirements at the time). It was built to let developers run prompts and retrieve responses through scripts and applications, effectively turning the chat experience into something that could be automated and integrated into tools. The repository gained popularity because it provided a practical way to experiment with Bing Chat programmatically, including CLI-style usage patterns and developer-oriented documentation. As with many reverse-engineered clients, it depended on upstream behavior that could change, and the project’s lifecycle reflected that reality. The repository was later archived, meaning it is read-only and no longer actively maintained, but it remains a reference point for how developers approached unofficial access to Bing Chat. In essence, EdgeGPT served as a bridge between an interactive chat -
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FreedomGPT
React and Electron-based app that executes the FreedomGPT LLM locally
FreedomGPT is a locally executed large language model (LLM) application built using React and Electron, allowing users to interact with AI models privately on their Mac or Windows devices. The app enables offline operation, ensuring privacy and security while providing a chat-based interface for seamless communication with the AI. It supports integration with models like Liberty Edge and offers an open-source solution for those seeking more control over their AI interactions. The app's setup is simple, and it includes clear installation guides for both macOS and Windows platforms, as well as detailed instructions for building necessary libraries like llama.cpp. -
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GPT-NeoX
Implementation of model parallel autoregressive transformers on GPUs
This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we recommend Mesh Transformer JAX. If you are not looking to train models with billions of parameters from scratch, this is likely the wrong library to use. For generic inference needs, we recommend you use the Hugging Face transformers library instead which supports GPT-NeoX models. -
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StoryTeller
Multimodal AI Story Teller, built with Stable Diffusion, GPT, etc.
A multimodal AI story teller, built with Stable Diffusion, GPT, and neural text-to-speech (TTS). Given a prompt as an opening line of a story, GPT writes the rest of the plot; Stable Diffusion draws an image for each sentence; a TTS model narrates each line, resulting in a fully animated video of a short story, replete with audio and visuals. To develop locally, install dev dependencies and install pre-commit hooks. This will automatically trigger linting and code quality checks before each commit. The final video will be saved as /out/out.mp4, alongside other intermediate images, audio files, and subtitles. For more advanced use cases, you can also directly interface with Story Teller in Python code. -
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ChatGPT API
Node.js client for the official ChatGPT API. 🔥
This package is a Node.js wrapper around ChatGPT by OpenAI. TS batteries included. ✨ The official OpenAI chat completions API has been released, and it is now the default for this package! 🔥 Note: We strongly recommend using ChatGPTAPI since it uses the officially supported API from OpenAI. We may remove support for ChatGPTUnofficialProxyAPI in a future release. 1. ChatGPTAPI - Uses the gpt-3.5-turbo-0301 model with the official OpenAI chat completions API (official, robust approach, but it's not free) 2. ChatGPTUnofficialProxyAPI - Uses an unofficial proxy server to access ChatGPT's backend API in a way that circumvents Cloudflare (uses the real ChatGPT and is pretty lightweight, but relies on a third-party server and is rate-limited) -
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ChatGPT Client
A ChatGPT client written in Rust
A ChatGPT client written in Rust. The ChatGPT model is a large language model trained by OpenAI that is capable of generating human-like text. By providing it with a prompt, it can generate responses that continue the conversation or expand on the given prompt. -
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ChatGPT Java
A Java client for the ChatGPT API
ChatGPT Java is a Java client for the ChatGPT API. Use official API with model gpt-3.5-turbo. -
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ChatGPT UI
A ChatGPT web client that supports multiple users, and databases
A ChatGPT web client that supports multiple users, multiple database connections for persistent data storage, supports i18n. Provides Docker images and quick deployment scripts. Support gpt-4 model. You can select the model in the "Model Parameters" of the front-end. The GPT-4 model requires whitelist access from OpenAI. Added web search capability to generate more relevant and up-to-date answers from ChatGPT! This feature is off by default, you can turn it on in `Chat->Settings` in the admin panel, there is a record `open_web_search` in Settings, set its value to True. Add "open_registration" setting option in the admin panel to control whether user registration is enabled. You can log in to the admin panel and find this setting option under Chat->Setting. The default value of this setting is True (allow user registration). If you do not need it, please change it to False. -
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ChatGPT.Net
Unofficial .Net Client for ChatGPT
The ChatGPT.Net Unofficial .Net API for ChatGPT is a C# library that allows developers to access ChatGPT, a chat-based language model. With this API, developers can send queries to ChatGPT and receive responses in real-time, making it easy to integrate ChatGPT into their own applications. The new method operates without a browser by utilizing a server that has implemented bypass methods to function as a proxy. The library sends requests to the server, which then redirects the request to ChatGPT while bypassing Cloudflare and other bot detection measures. The server then returns the ChatGPT response, ensuring that the method remains effective even if ChatGPT implements changes to prevent bot usage. Our servers are continuously updated to maintain their bypass capabilities. -
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gpt-j-api
API for the GPT-J language mode. Including a FastAPI backend
An API to interact with the GPT-J language model and variants! You can use and test the model in two different ways. These are the endpoints of the public API and require no authentication. Just SSH into a TPU VM. This code was tested on both the v2-8 and v3-8 variants. -
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uweb browser: unlimited power
minimal suckless android web browser with unlimited power
- AI bot as search engine; append file content as input for complex query. - Powerful: html5 enhancement; any urls to host a website; javascript and shell scripting for general processing; and more with Termux. - Customizable: user-defined menus, (new) buttons and gestures for user agents, bookmarklets, url services, shell commands, internal functionality links and text processing etc. - Convenient: book/dictionary/txt/command line/app can be search engine. - Tiny: less than 200k - Fast: run fast, even with thousands of user provided css/scripts - Efficient: less touches, one click to reach any number of search engines without repeated input; automate online services. - URL bar command line support ("!" and .js files as commands). - user-defined site-specific JS/CSS/HTML/preprocessing. - Online play/preview/preprocess for downloadable resources. - Multiple type profiles: switch any data including logins/config orthogonally - web automation, crontab (alarm clock) -
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OpenChat for Linux
OpenChat for Linux — a fast, lightweight desktop client for ChatGPT
OpenChat for Linux is a desktop client for ChatGPT / OpenAI Chat designed specifically for Linux. It’s built with Tauri (Rust) for low resource usage and stability, and it uses a “message window” approach (keeps a small active slice of the conversation and loads more as you scroll) so long chats don’t bog down or crash the app. Downloads are available in common Linux formats (AppImage, Debian package, tarball), with additional packaging manifests for Flatpak, Snap, RPM, AUR, and Nix. -
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose) by training a text-generation model to generate conversation in a consistent structure. This structure is then leveraged to deploy a chatbot that is a "free-form" model that consistently replies like a human. Some of the trained models can be interacted with through the HuggingFace spaces and model inference APIs on the ETHZ Analytics Organization page on huggingface.co. -
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BingGPT
Desktop application of Bing's AI-powered chat (Windows, Mac, Linux)
Desktop application of new Bing's AI-powered chat 1. Get access to the early preview of new Bing 2. Sign in to your Microsoft account 3. Start chatting -
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ChatFred
Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting
Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting, image generation and more. Access ChatGPT, DALL·E 2, and other OpenAI models. Language models often give wrong information. Verify answers if they are important. Talk with ChatGPT via the cf keyword. Answers will show as Large Type. Alternatively, use the Universal Action, Fallback Search, or Hotkey. To generate text with InstructGPT models and see results in-line, use the cft keyword. ⤓ Install on the Alfred Gallery or download it over GitHub and add your OpenAI API key. If you have used ChatGPT or DALL·E 2, you already have an OpenAI account. Otherwise, you can sign up here - You will receive $5 in free credit, no payment data is required. Afterward you can create your API key. To start a conversation with ChatGPT either use the keyword cf, setup the workflow as a fallback search in Alfred or create your custom hotkey to directly send the clipboard content to ChatGPT.
