metal-cpp VS llama.cpp

My understanding is the proliferation of “XYZ-cpp” AI frameworks is due to the c++ support in Apple’s gpu library ‘Metal’, and the popularity of apple silicon for inference (and there are a few technical reasons for this): https://developer.apple.com/metal/cpp/

This is basically also what the "official" C++ API for Metal does (https://developer.apple.com/metal/cpp/), it's an automatically generated bindings wrapper which calls into ObjC runtime functions.

I also dabbled a bit with this idea by parsing clang AST-dumps of macOS system headers:

https://github.com/floooh/objc-ast-experiments

Unfortunately this is very brittle, and also broke on ARM CPUs, I guess the shim code needs some ABI adjustments (famously, objc_msgSend has multiple "ABI shapes": https://www.mikeash.com/pyblog/objc_msgsends-new-prototype.h...).

There's official C++-interface: https://developer.apple.com/metal/cpp/

It doesn't matter if the project driven by Microsoft or not, the cat (of automatically generated language bindings) is out of the bag. E.g. Zig is using the same approach without being an official MS project: https://github.com/marlersoft/zigwin32, and Apple has an automatically generated C++ API for Metal (https://developer.apple.com/metal/cpp/).

In the future, the question won't be "what language do I need to learn to code on this platform", but instead "are there language bindings for my favourite language".

this? https://developer.apple.com/metal/cpp/

Doesn't it just use objc/runtime.h and if anything is missing you can just add your custom api calls?

Metal has C++ bindings (which cover a full app lifecycle so you don’t have to touch Objective-C/Swift at all) but they’re based on the Objective-C memory model. There are some helper structs mimicking shared pointers, but you’ll still need to understand the basics of how an autorelease pool is used to avoid memory leaks and/or bad access crashes.

On https://developer.apple.com/metal/cpp/ check Foundation folder and all those nice Object::sendMessage().

well https://github.com/ggerganov/llama.cpp/issues/6849

Have just done this recently for local chat with pdf feature in https://recurse.chat. (It's a macOS app that has built-in llama.cpp server and local vector database)

Running an embedding server locally is pretty straightforward:

- Get llama.cpp release binary: https://github.com/ggerganov/llama.cpp/releases

Ah, thanks for this! I can't edit my parent comment that you replied to any longer unfortunately.

As I said, I only compared the contributors graphs [0] and checked for overlaps. But those apparently only go back about year and only list at most 100 contributors ranked by number of commits.

[0]: https://github.com/ollama/ollama/graphs/contributors and https://github.com/ggerganov/llama.cpp/graphs/contributors

KodiBot is a desktop app that enables users to run their own AI chat assistants locally and offline on Windows, Mac, and Linux operating systems. KodiBot is a standalone app and does not require an internet connection or additional dependencies to run local chat assistants. It supports both Llama.cpp compatible models and OpenAI API.

There are already some implementations out there which attempt to accomplish this!

Here's an example: https://github.com/silphendio/sliced_llama

A gist pertaining to said example: https://gist.github.com/silphendio/535cd9c1821aa1290aa10d587...

Here's a discussion about integrating this capability with ExLlama: https://github.com/turboderp/exllamav2/pull/275

And same as above but for llama.cpp: https://github.com/ggerganov/llama.cpp/issues/4718#issuecomm...

For those who might not be aware of this, there is also an open source project on GitHub called "Twinny" which is an offline Visual Studio Code plugin equivalent to Copilot: https://github.com/rjmacarthy/twinny

It can be used with a number of local model services. Currently for my setup on a NVIDIA 4090, I'm running both the base and instruct model for deepseek-coder 6.7b using 5_K_M Quantization GGUF files (for performance) through llama.cpp "server" where the base model is for completions and the instruct model for chat interactions.

llama.cpp: https://github.com/ggerganov/llama.cpp/

deepseek-coder 6.7b base GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-base-GGU...

deepseek-coder 6.7b instruct GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-instruct...