Ollama for API, which you can integrate into Open WebUI. You can also integrate image generation with ComfyUI I believe.
It's less of a hassle to use Docker for Open WebUI, but ollama works as a regular CLI tool.
Ollama for API, which you can integrate into Open WebUI. You can also integrate image generation with ComfyUI I believe.
It's less of a hassle to use Docker for Open WebUI, but ollama works as a regular CLI tool.
I've discovered jan.ai which is far faster than GPT4All, and visually a little nicer.
EDIT: After using it for an hour or so, it seems to crash all the time, I keep on having to reset it, and currently am facing it freezing for no reason.
I also started using this recently and it’s very plug and play. Just open and run. It’s the only client so far that feels like I could recommend to non-geeks.
I agree. it looks nice, explains the models fairly well, hides away the model settings nicely, and even recommends some initial models to get started that have low requirements. I like the concept of plugins but haven't found a way to e.g. run python code it creates yet and display the output in the window
Took ages to produce answer, and only worked once on one model, then crashed since then.
Maybe LocalAI? It doesn't do python code execution, but pretty much all of the rest.
This looks interesting - do you have experience of it? How reliable / efficient is it?
I think many people use it and it works. But sorry - no, I don't have any first-hand experience. I've tested it for a bit and it looked fine. Has a lot of features and it should be as efficient as any other ggml/llama.cpp based inference solution at least for text. I myself use KoboldCPP for the few things I do with AI and my computer is lacking a GPU so I don't really do a lot of images with software like this. And it's likely going to be less for you than the 15 minutes it takes me to generate an image on my unsuited machine.
LocalAI is pretty good but resource-intensive. I ran it on a vps in the past.
The main limitation is the VRAM, but I doubt any model is going to be particularly fast.
I think phi3:mini on ollama might be an okish fit for python, since it's a small model, but was trained on python codebases.
You can tell Open Interpreter to run commands based on you human-language input. If you want local only LLM, you can pair it with Ollama. It works for "interactive" use where you're asked for confirmation before a command is run.
I set this up in a VM because I wanted a full automatic coding "agent" which can run commands without my intervention and I did not want it to blow up main system. It did not really work though because as far as I know Open Interpreter does not have a way to "pipe" a command's output back into the LLM so that it could create feedback with linters and stuff.
Another issue was that Starcoder2, which is the only LLM trained on permissive licensed code I could find, only has a 15B "human-like" model. The smaller models only speak code so I don't know how that would work for agentic usage and the 15B is really slow running on DDR4 CPU. I think agents are cool though so I would like to try Aider which is a supposedly good open source agent and unlike Open Interpreter is not abandonware.
Thanks for coming to my blabering talk, hope this might be useful for someone.
You should try https://cherry-ai.com/ .. It's the most advanced client out there. I personally use Ollama for running the models and Mistral API for advnaced tasks.
all 20 comments