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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Chat with AI large language models running natively in your browser. Enjoy private, server-free, seamless AI conversations.
| Date | Stars |
|---|---|
| 2026-07-24 | 1072 |
| 2026-07-25 | 1072 |
| 2026-07-28 | 1072 |
| 2026-07-30 | 1072 |
| 2026-07-31 | 1074 |
| 2026-08-06 | 1074 |
Today
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This week
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Momentum
0.0
growth rate 0.19%/day
<div align="center"> # WebLLM Chat <a href="https://github.com/mlc-ai/web-llm"><img alt="Related Repository: WebLLM" src="https://img.shields.io/badge/Related_Repo-WebLLM-fafbfc?logo=github"></a> <a href="https://chat.webllm.ai"><img alt="Web App Deployed on GitHub Pages" src="https://img.shields.io/badge/Web_App-Deployed-32a852?logo=pwa"></a> <a href="https://discord.gg/9Xpy2HGBuD"><img alt="Join Discord" src="https://img.shields.io/badge/Join-Discord-7289DA?logo=discord&logoColor=white"></a> **Private AI Conversations, Fully In-Browser.** [**Chat Now**](https://chat.webllm.ai/) [WebLLM Chat Demo Video](https://github.com/mlc-ai/web-llm-chat/assets/23090573/f700e27e-bb88-4068-bc8b-8a33ea5a4300) </div> ## Overview **WebLLM Chat** is a private AI chat interface that combines [WebLLM](https://github.com/mlc-ai/web-llm) with a user-friendly design, leveraging WebGPU to run large language models (LLMs) natively in your browser. Enjoy an unprecedented, private, and accessible AI conversation experience. ## Key Features - **Browser-Native AI**: Experience cutting-edge language models running natively within your web browser with WebGPU acceleration, eliminating the need for server-side processing or cloud dependencies. - **Ganranteed Privacy**: With the AI model running locally on your hardware and all data processing happening within your browser, your data and conversations never leave your computer, ensuring your privacy. - **Offline Accessibility**: Run entirely offline after the initial setup and download, allowing you to engage with AI-powered conversations without an active internet connection. - **Vision Model Support**: Chat with AI by uploading and sending images, making it easy to get insights and answers based on visual content. - **User-Friendly Interface**: Enjoy the intuitive and feature-rich user interface, complete with markdown support, dark mode, and a responsive design optimized for various screen sizes. - **Custom Models**: Connect to any custom language model on you local environment through [MLC-LLM](https://llm.mlc.ai/). For detail, check the [Use Custom Models](#use-custom-models) section. - **Open Source and Customizable**: Build and customize your own AI-powered applications with our open-source framework. WebLLM Chat is a pioneering initiative that combines the robust backend capabilities of WebLLM with the user-friendly interface of NextChat. As a part of the broader MLC.ai family, this project contributes to our mission of democratizing AI technology by making powerful tools accessible directly to end-users. By integrating with NextChat, WebLLM Chat not only enhances the chatting experience but also broadens the scope for deployment of self-hosted and customizable language models. ## Built-in Models WebLLM Chat natively supports WebLLM build-in models. You can find the full list [here](https://github.com/mlc-ai/web-llm?tab=readme-ov-file#built-in-models). ## Use Custom Models WebLLM Chat supports custom language models through [MLC-LLM](https://llm.mlc.ai/). Follow the following steps to use custom models on your local environment: 1. (Optional) Compile the model into MLC format by following [the instructions](https://llm.mlc.ai/docs/compilation/convert_weights.html). 2. Host REST API through MLC-LLM by following [the instructions](https://llm.mlc.ai/docs/deploy/rest.html). 3. Go to [WebLLM Chat](https://chat.webllm.ai/), select "Settings" in the side bar, then select "MLC-LLM REST API (Advanced)" as "Model Type" and type the REST API endpoint URL from step 2. ## Development ```shell # 1. install nodejs and yarn first # 2. config local env vars in `.env.local` # 3. run yarn install yarn dev ``` ## Deployment ### Build You can build the application as a Next.js build using `yarn build` or as a static site using `yarn export`. For more information, check [Next.js documentation](https://nextjs.org/docs/pages/building-your-application/deploying); ### Docker ```shell docker build -t
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:62f1d86babbd527c, topic:large-language-models, topic:llm, topic:llama