Overview
WebLLM is a high-performance in-browser LLM inference engine that brings language model inference directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU.
WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including streaming, JSON-mode, function-calling (WIP), etc.
We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.
You can use WebLLM as a base npm package and build your own web application on top of it by following the examples below. This project is a companion project of MLC LLM, which enables universal deployment of LLM across hardware environments.
Key Features
In-Browser Inference : WebLLM is a high-performance, in-browser language model inference engine that leverages WebGPU for hardware acceleration, enabling powerful LLM operations directly within web browsers without server-side processing.
Full OpenAI API Compatibility : Seamlessly integrate your app with WebLLM using OpenAI API with functionalities such as streaming, JSON-mode, logit-level control, seeding, and more.
Structured JSON Generation : WebLLM supports state-of-the-art JSON mode structured generation, implemented in the WebAssembly portion of the model library for optimal performance. Check WebLLM JSON Playground on HuggingFace to try generating JSON output with custom JSON schema.
Extensive Model Support : WebLLM natively supports a range of models including Llama 3, Phi 3, Gemma, Mistral, Qwen(通义千问), and many others, making it versatile for various AI tasks. For the complete supported model list, check MLC Models.
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