Awesome
llama-cpp-wasm
WebAssembly (Wasm) Build and Bindings for llama.cpp and supported by Tangled Group, Inc.
Online Demos
https://tangledgroup.github.io/llama-cpp-wasm/
Build
git clone https://github.com/tangledgroup/llama-cpp-wasm.git
cd llama-cpp-wasm
./build-single-thread.sh
./build-multi-thread.sh
Once build is complete you can find llama.cpp
built in dist/llama-st
and dist/llama-mt
directory.
Deploy
Basically, you can copy/paste dist/llama-st
or dist/llama-mt
directory after build to your project and use as vanilla JavaScript library/module.
index.html
<!DOCTYPE html>
<html lang="en">
<body>
<label for="prompt">Prompt:</label>
<br/>
<textarea id="prompt" name="prompt" rows="25" cols="80">Suppose Alice originally had 3 apples, then Bob gave Alice 7 apples, then Alice gave Cook 5 apples, and then Tim gave Alice 3x the amount of apples Alice had. How many apples does Alice have now? Let’s think step by step.</textarea>
<br/>
<label for="result">Result:</label>
<br/>
<textarea id="result" name="result" rows="25" cols="80"></textarea>
<br/>
<script type="module" src="example.js"></script>
</body>
</html>
example.js
// import { LlamaCpp } from "./llama-st/llama.js";
import { LlamaCpp } from "./llama-mt/llama.js";
const onModelLoaded = () => {
console.debug('model: loaded');
const prompt = document.querySelector("#prompt").value;
document.querySelector("#result").value = prompt;
app.run({
prompt: prompt,
ctx_size: 4096,
temp: 0.1,
no_display_prompt: true,
});
}
const onMessageChunk = (text) => {
console.log(text);
document.querySelector('#result').value += text;
};
const onComplete = () => {
console.debug('model: completed');
};
const models = [
'https://huggingface.co/Qwen/Qwen1.5-0.5B-Chat-GGUF/resolve/main/qwen2-beta-0_5b-chat-q8_0.gguf',
'https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat-GGUF/resolve/main/qwen1_5-1_8b-chat-q8_0.gguf',
'https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b/resolve/main/stablelm-2-zephyr-1_6b-Q4_1.gguf',
'https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf',
'https://huggingface.co/TheBloke/phi-2-GGUF/resolve/main/phi-2.Q4_K_M.gguf'
];
const model = models[2]; // stablelm-2-zephyr-1_6b
const app = new LlamaCpp(
model,
onModelLoaded,
onMessageChunk,
onComplete,
);
Run Example
First generate self-signed certificate.
openssl req -newkey rsa:2048 -new -nodes -x509 -days 3650 -keyout key.pem -out cert.pem
Run Single Thread Example
npx http-server -S -C cert.pem
Run Multi-threading Example
Copy docs/server.js
to your working directory.
npm i express
node server.js
Then open in browser: https://127.0.0.1:8080/