How does this compare to the already established open source solutions such as Chatbox (https://github.com/chatboxai/chatbox), or Lobechat (https://github.com/lobehub/lobe-chat)?

Been using both, like Chatbox for how snappy it is, but is local only, vs Lobechat which allows you to setup centralized host to have shared host across clients but feels a bit clunkier.

It would be good to share other OSS alternatives here, some alternatives I've seen mentioned in Reddit threads:

   - jan.ai
   - librechat.ai
   - AnythingLLM

I hoped that someone would fork OpenWebUI before the license change an maintain a OSS Version. Like Valkey¹ is the OSS Fork of Redis and OpenSearch² is the OSS Fork of ElasticSearch.

[1]: https://github.com/valkey-io/valkey

[2]: https://github.com/opensearch-project/OpenSearch

I’ve created a native, cross-platform ollama client in Qt C++ called Vox (https://get-vox.com). For those interested, you can join the waitlist.

Isn’t openwebui also oss?

I've always thought it was incredibly rude to call this project something as incredibly generic as "Open WebUI". For one it's impossible to find documentation because it's so generic as tl be utterly meaningless, and also you're intentionally confusing any and all open web UI projects past and future.

Not to mention it's just janky and hard to work with. And of course every bit of the official documentation is LLM slop. The only way I've been able to navigate is to use another LLM to tell me what these settings are for. Said LLM, having ingested the LLM slop documentation, also produces garbage that's barely correct.

It's a bad project.

OpenWebUI and similar ChatGPT-lite interfaces are a bad UI/UX for LLMs. "Normies" should not be using local models and those who want local models should be exposed to the settings/complexity that projects like oobabooga/sillytavern/comfyUI force a user to educate themselves about (i.e. LLM sampler settings, chat templates, etc). It's telling that the best AI generated content is made by people using these prosumer style projects, and not using simplified trash like OpenWebUI.

The proliferation of bad UI in consumption of AI systems has done unfathomable damage to discoverability of LLM features, especially new innovations in LLMs like far better sampling algorithms (i.e. min_p). Users are massively harmed by the features they don't know about and wish they were using but don't/can't because they are shepherded into the most brain-dead simple UI possible.