MemGPT VS llama.cpp

On a side note: working over longer contexts also reminds me of MemGPT(https://github.com/cpacker/MemGPT)

The MemGPT project is taking on this challenge.

Long Term Memory - Voyager, MemGPTand LongMem

Blog: https://memgpt.ai/

Github: https://github.com/cpacker/MemGPT

Hey all, MemGPT authors here! Happy to answer any questions about the implementation.

If you want to try it out yourself, we have a Discord bot up-and-running on the MemGPT server (https://discord.gg/9GEQrxmVyE) where you can see the memory editing in action - as you chat you'll see MemGPT update its profile about you (and itself).

Everything's open source, so can also try running MemGPT locally using the code here: https://github.com/cpacker/MemGPT. In the repo we also have a document-focused example where you can chat with MemGPT about the LlamaIndex API docs.

if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp

the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...

And you can search for any GGUF on huggingface

Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182

For anyone interested in exploring this, llama.cpp has an example implementation here:

https://github.com/ggerganov/llama.cpp/tree/master/examples/...

Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.

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