A while ago, I had requested help with using LLMs to manage all my teaching notes. I have since installed Ollama and been playing with it to get a feel for the setup.
I was also suggested the use of RAG (Retrieval Augmented Generation ) and CA (cognitive architecture). However, I am unclear on good self hosted options for these two tasks. Could you please suggest a few?
For example, I tried ragflow.io and installed it on my system, but it seems I need to setup an account with a username and password to use it. It remains unclear if I can use the system offline like the base ollama model, and that information won’t be sent from my computer system.
Pretty much everything has an API :P
ollama is OK because its easy and automated, but you can get higher performance, better vram efficiency, and better samplers from either kobold.cpp or tabbyAPI, with the catch being that more manual configuration is required. But this is good, as it “forces” you to pick and test an optimal config for your system.
I’d recommend kobold.cpp for very short context (like 6K or less) or if you need to partially offload the model to CPU because your GPU is relatively low VRAM. Use a good IQ quantization (like IQ4_M, for instance).
Otherwise use TabbyAPI with an exl2 quantization, as it’s generally faster (but GPU only) and much better at long context through its great k/v cache quantization.
They all have OpenAI APIs, though kobold.cpp also has its own web ui.