1.16.3

What's Changed

• sync to latest upstream source code by @ngxson in #125

Thanks to a small refactoring on llama.cpp, be binary size is now reduced from 1.78MB to 1.52MB

Full Changelog: 1.16.2...1.16.3

1.16.2

What's Changed

• decode/encode : do not fail on empty batch by @ngxson in #118
• Update to latest llama.cpp source code by @ngxson in #119

Full Changelog: 1.16.1...1.16.2

1.16.1

What's Changed

• v1.16.1 by @ngxson in #113

Full Changelog: 1.16.0...1.16.1

1.16.0

SmolLM-360m is added as a model in main example. Try it now --> https://huggingface.co/spaces/ngxson/wllama

Special thanks to @huggingface team for providing a such powerful model in a very small size!

What's Changed

• ability to use custom cacheManager by @ngxson in #109

Full Changelog: 1.15.0...1.16.0

1.15.0

New features

downloadModel()

Download model to cache without loading it. The use case would be to allow application to have a "model manager" screen that allows:

• Download model via downloadModel()
• List all downloaded models using CacheManager.list()
• Delete a downloaded model using CacheManager.delete()

KV cache reuse in createCompletion

When calling createCompletion, you can pass useCache: true as an option. It will reuse the KV cache from the last createCompletion call. It is equivalent to cache_prompt option on llama.cpp server.

wllama.createCompletion(input, {
  useCache: true,
  ...
});

For example:

• On the first call, you have 2 messages: user: hello, assistant: hi
• On the second call, you add one message: user: hello, assistant: hi, user: who are you?

Then, only the added message user: who are you? will need to be evaluated.

What's Changed

• Add downloadModel function by @ngxson in #95
• fix log print and downloadModel by @ngxson in #100
• Add main example (chat UI) by @ngxson in #99
• Improve main UI example by @ngxson in #102
• implement KV cache reuse by @ngxson in #103

Full Changelog: 1.14.2...1.15.0

1.14.2

Update to latest upstream llama.cpp source code:

• Fix support for llama-3.1, phi 3 and SmolLM

Full Changelog: 1.14.0...1.14.2

1.14.0

What's Changed

• save ETag metadata, add allowOffline option in #90
• Added experimental support for encoder-decoder architecture #91

Full Changelog: 1.13.0...1.14.0

1.13.0

What's Changed

• Update README.md by @flatsiedatsie in #78
• sync with upstream llama.cpp source code (+gemma2 support) by @ngxson in #81
• Fix exit() function crash if model is not loaded by @flatsiedatsie in #84
• Improve cache API by @ngxson in #80
• v1.13.0 by @ngxson in #85

New Contributors

• @flatsiedatsie made their first contribution in #78

Full Changelog: 1.12.1...1.13.0

1.12.1

What's Changed

• Sync with latest upstream source code + adapt to project structure change by @ngxson in #77

Full Changelog: 1.12.0...1.12.1

1.12.0

Important

In prior versions, if you initialize wllama with embeddings: true, you will still able to generate completions.

From v1.12.0, if you start wllama with embeddings: true, this will throws an error when you try to use createCompletion. You must add wllama.setOptions({ embeddings: false }) to turn of embeddings.

More details: This feature is introduced in ggml-org/llama.cpp#7477 , which allows models like GritLM to be used for both embeddings and text generation.

What's Changed

• Add wllama.setOptions by @ngxson in #73
• v1.12.0 by @ngxson in #74
• warn user if embeddings is incorrectly set by @ngxson in #75

Full Changelog: 1.11.0...1.12.0