V2.0 introduces significant improvements in model management and caching. Key features include:
- Completely rewritten model downloader with service worker
- New
ModelManager
class providing comprehensive model handling and caching capabilities - Enhanced testing system built on the
vitest
framework
The new ModelManager
class provides a robust interface for handling model files:
// Example usage
const modelManager = new ModelManager();
// List all models in cache
const cachedModels = await modelManager.getModels();
// Add a new model
const model = await modelManager.downloadModel('https://example.com/model.gguf');
// Check if model is valid (i.e. it is not corrupted)
// If status === ModelValidationStatus.VALID, you can use the model
// Otherwise, call model.refresh() to re-download it
const status = await model.validate();
// Re-download if needed (useful when remote model file has changed)
await model.refresh();
// Remove model from cache
await model.remove();
// Load the selected model into llama.cpp
const wllama = new Wllama(CONFIG_PATHS);
await wllama.loadModel(model);
// Alternatively, you can also pass directly model URL like in v1.x
// This will automatically download the model to cache
await wllama.loadModelFromUrl('https://example.com/model.gguf');
Key features of ModelManager
:
- Automatic handling of split GGUF models
- Built-in model validation
- Parallel downloads of model shards
- Cache management with refresh and removal options
A new helper function to load models directly from Hugging Face Hub. This is a convenient wrapper over loadModelFromUrl
that handles HF repository URLs.
await wllama.loadModelFromHF(
'ggml-org/models',
'tinyllamas/stories260K.gguf'
);
In v2.0, the configuration paths have been simplified. You now only need to specify the *.wasm
files, as the *.js
files are no longer required.
Previously in v1.x:
const CONFIG_PATHS = {
'single-thread/wllama.js' : '../../esm/single-thread/wllama.js',
'single-thread/wllama.wasm' : '../../esm/single-thread/wllama.wasm',
'multi-thread/wllama.js' : '../../esm/multi-thread/wllama.js',
'multi-thread/wllama.wasm' : '../../esm/multi-thread/wllama.wasm',
'multi-thread/wllama.worker.mjs': '../../esm/multi-thread/wllama.worker.mjs',
};
const wllama = new Wllama(CONFIG_PATHS);
From v2.0:
// You only need to specify 2 files
const CONFIG_PATHS = {
'single-thread/wllama.wasm': '../../esm/single-thread/wllama.wasm',
'multi-thread/wllama.wasm' : '../../esm/multi-thread/wllama.wasm',
};
const wllama = new Wllama(CONFIG_PATHS);
Alternatively, you can use the *.wasm
files from CDN:
import WasmFromCDN from '@wllama/wllama/esm/wasm-from-cdn.js';
const wllama = new Wllama(WasmFromCDN);
// NOTE: this is not recommended
// only use this when you can't embed wasm files in your project
The Wllama
constructor now accepts an optional second parameter of type WllamaConfig
for configuration options:
Important
Most configuration options previously available in DownloadModelConfig
used with loadModelFromUrl()
have been moved to this constructor config.
const wllama = new Wllama(CONFIG_PATHS, {
parallelDownloads: 5, // maximum concurrent downloads
allowOffline: false, // whether to allow offline model loading
});
As mentioned earlier, some options are moved to Wllama
constructor, including:
parallelDownloads
allowOffline
Wllama.downloadModel
is removed. Please useModelManager.downloadModel
insteadloadModelFromUrl
won't check if cached model is up-to-date. You may need to manually callModel.refresh()
to re-download the model.- Changes in
CacheManager
:- Added
CacheManager.download
function CacheManager.open(nameOrURL)
now accepts both file name and original URL. It now returns aBlob
instead of aReadableStream
- Added
Notable internal improvements made to the codebase:
- Comprehensive test coverage using
vitest
, with browser testing for Chrome and Firefox (Safari support planned for the future) - Enhanced CI pipeline including validation for example builds, ESM compilation and lint checks