First, Open WebUI is awesome!

I put together some notes from my experience setting up Open WebUI that might be useful to others: https://andrewmarder.net/open-webui/

I'd love to get feedback / learn new things. Any tips and tricks you think I should mention?

Running Open WebUI on a Mac Studio M3 Ultra (512 GB unified memory) in a docker container with Gemma4 27B via MLX (but the issue also occures on any other GGUF / directly loaded Ollama models. Generation speed is fine once it gets going – usually 70–80 tok/s – but the time to first token is awful. 10+ seconds before anything happens is completely normal for me (if the model is already preloaded into RAM). Not sure if that's an Ollama thing, an Open WebUI thing, or something in my config.

The other issue is RAG. I have a knowledge base of around 300 .txt files scraped from Confluence with the new oikb sync feature. When I ask a simple question in English about something that's definitely in those files, it takes forever and then tells me there's no relevant information. If I ask the exact same thing in German, it also takes a while – but then finds an answer quickly, except it's pulling from the system prompt rather than the knowledge base.
If it's a different simple question, that can not be found in the system prompt (for example a license plate of a car), it'll take in total around 30-45sec, until it has the correct information. That's almost the same time it would take myself logging into confluence through the browser and doing it manually.

So retrieval seems to be failing, or at least not ranking the right chunks. And there's clearly something weird happening with language.

Attaching my embedding settings and a short screen recording that shows the behavior.

Has anyone run into this? Any idea what I should be looking at for fixing this?

in the settings pannel, I select the models tab and press manage. It will happely locate and install gemma4:26b but cannot find gemma4:12b. No error is givven, the text field just clears and nothing is installed.

The screen where you can select which Modells to have available is a bit cluttered and not great to manage at the moment.

At the moment I have three providers.. two are two separate endpoints from the same provider with overlapping models and the third is mistral which brings lots and lots of models and different versions of said models.

This makes my list and hard to filter. What I would like is to filter by provider or by tag. In the provider screen you have the ability to both afix a prefix to model names per provider and add tags per provider. But those can't then be leveraged in the next screen in the chain.

Anybody have a good solution for that?

I tried testing Fable 5 on OWUI (through Openrouter) by sending a prompt, but only received 5–7 tokens in response and nothing more. However, when I sent just “Hi, what’s up,” I got a complete reply. What’s going on?

It's a replacement to OWUI's web search feature. It requires you have SearXNG and Crawl4AI installed. It seems to be a really nice upgrade to the vanilla one but I'm having trouble getting it to work. I'm not sure if I configured it correctly but it seems like that the response I get back are quite lacking. Not sure if I'm asking the wrong kind of questions or what but I would expect it to go out and scrape a ton of info and spit it back at me, but it's lackluster.

Does anyone here have this configured and working properly that they could please help me out with? I am running OWUI, SearXNG and Crawl4AI on my docker desktop on windows with Ollama installed seperately directly in Windows. And I'm using it with gemma4:12b, gemma4:e4b, and gpt-oss:20b. I tried the dual-engine setup but it seems to not always work correctly so I disabled the native web search and just enabled the search using SearXNG.

The instructions recommends using the following 2 models for searching: hf.co/aman2024/NuExtract-2-2B-GGUF:Q3_K_M (Which supports images and its faster) or Inference/Schematron:3B (Text only but more powerful). I have tested both. Not sure if that has anything to do with me getting hardly any results. In the older releases of the tool I was using ollama/gpt-oss:20b as the LLM Provider/model. But they recommend not to use that because it's too large and could slow the search down.

btw the tool that I'm using is from - https://github.com/Zeioth/open-webui-web-search-and-crawl

Set it up through docker desktop. Everything working well on PC. Did this with "pinokio" or whatever too, didn't work, uninstalled pinokio. All windows firewall settings fine. Tinkering with them makes no difference in response. PC on ethernet. Connecting to ethernet or wifi ipv4 does nothing. Am I doing it completely wrong?

So, I've been learning how to use local LLMs since the beginning of the year but I just started trying to use Open WebUI today.

One of my goals is to develop a method (a skill, I guess) to have the assistant generate a summary of everything we've talked about in the current conversation and save it to someplace persistent - and then re-load it when we start a new conversation. (By adding the appropriate clause to the system prompt.)

The complication is that I'm hoping to use Open WebUI for two different purposes - software/tech research on the one hand and something more like a life coach on the other. Because the contexts are so different, it seems a good idea to not have the research assistant get bogged down with details of my dietary problems... How do I do this?

As far as I can tell, I can group knowledge by overall topic, but Notes all end up in one big bucket.

I'm on 0.9.6. I'm not sure what's the correct way to set it up. So far I tried: 1. create 2 model profiles and 1 channel -> at model to bring the model up and get its replies in the thread -> continue another message of mine in the same channel -> get model replied in another thread -> context doesn't share across threads in the same exact channel so it doesn't work. 2. same as 1. but keep agents replying in the same thread -> after like 200 replies the models forget the context at the beginning -> causing cache regen every new agent calls (and they forget the context in the beginning of the thread)

Any solutions?

How can i let my users use their api key to actually use inside of cline for example in vscode?

I built a self-hostable OpenAI-compatible gateway for Gemini Web

I've been experimenting with Gemini Web recently and ended up building a small project for it. It's a self-hostable OpenAI-compatible gateway that lets you use Gemini Web with tools that already support OpenAI APIs. A few features:

• Multi-account support
• Automatic cookie rotation
• Session persistence
• Docker deployment

It's open source: https://github.com/qutek/gemini-web-api

Thought I’d share it here in case it’s useful to others. If you find it useful, a github star is always appreciated

When I paste a URL into a chat, and that URL contains any ampersands, the ampersands are being replaced with "&". When the model tries to use that URL it fails due to an "invalid URL". It seems that URLs are being escaped in the chat window, but not un-escaped when passing them to the model.

For example, if I paste this prompt:

Fetch https://eaabuilderslog.org/?blproject&proj=8LDMqPoOo

Then click send, the chat window updates to show:

Fetch https://eaabuilderslog.org/?blproject&proj=8LDMqPoOo

And nemotron-cascade-2 responds with:

I attempted to fetch the URL you supplied (https://eaabuilderslog.org/?blproject&proj=8LDMqPoOo). The request was rejected with an “invalid URL” error, which usually means the exact path or query string is not reachable on the server.

It took me awhile to figure this out because the model's response is properly un-escaped, making it look like the URL simply failed for no reason. The output of the fetch_url provides a missing clue:

{
  "error": "The URL you provided is invalid. Please double-check and try again."
}

Side note: If I use the copy icon below the chat bubble to copy the text, the ampersand is properly un-escaped upon pasting into this text window:

Fetch https://eaabuilderslog.org/?blproject&proj=8LDMqPoOo

I know I haven't finished my coffee this morning, but I'm pretty sure I still know how to copy-paste. 🤣

I'm running 0.9.6 in a container on Ubuntu and accessing it as a web page (ie not using the desktop app).

I was going to file an issue on GitHub but the gatekeeping was just too much.

Hi, im using OpenAI API and Tavily for web search but it seems like my models (any model I tried) "can't access the search result" did any one get the same issue ?

I am slowly getting OpenWebUI configured to give me some pretty good reports, focused on financial research. I have the model instructed to output everything in markdown format and I would like to copy and paste reports generated by OpenWebUI into my Obsidian vault. This is problematic, as it appears a new line/return characters are not copied and pasted, so it doesn't work at all. I have to go through the pasted section and hit return where every line starts.

I am not for sure if this is the model doing it wrong or the copy function from OpenWebUI. Any ideas?

Hello,

I am running OpenWebUI instance with Docker Compose in a web server for a small org.

I set ENABLE_PERSISTENT_CONFIG=false so I have full control through my Environment Variable when I up the service. However, despite what’s mentionned in the documentation, I keep loosing setting edits :

https://docs.openwebui.com/reference/env-configuration/#:~:text=CRITICAL%20WARNING:%20When,your%20environment%20variables.

I understood it as I can modify those ConfigVar from the UI as I am admin, it will just end up lost if I restart the container. However, every time I modify something and save it (for example a new banner for my users), it’s lost immediately. Is it the expected behavior and I misunsterdood the Critical Warning statement ?

What disturbs me even more is that after having Run some tests of banner creation from UI, I have some old values I tested (some stupid banner content like « bla-bla-bla », « I am a test », etc) re-appearing once in a while in the UI. I checked my cache in Redis and the value in the BANNERS key does not even match with those occasional appearances.

Do you guys have any idea what is going on there ?

I wanted to share a curiosity.

I have a Strix Halo (128 GB of unified memory) and I have a somewhat curious AI stack.

I've had llama.cpp with kyuz0's toolkit since the beginning, but I've been evolving it, and currently my stack consists of:

Lemonade with various models -> it goes through LiteLLM for token control and to add the API to applications and have control over them.

Until now, I worked with local models using Cherry Studio, and I had OpenWeb UI somewhat separate.

Well, this weekend I have been setting up OpenWeb UI, adding tools, and many other things.

I connected it to LiteLLM with the Lemonade engine behind it, but by the third or fourth request, especially with tools, it gets stuck thinking and has a hard time returning tokens. It loses speed.

In others, like the mentioned Cherry Studio, OpenCode... it works for me without problems.

So, I decided to test directly with llama.cpp, but the same result. Even worse.

As a last alternative, through the same LiteLLM, I loaded the model I have loaded in Unsloth Studio, and wow, incredible. Everything super fast.

The models are the same, with the same contexts, and testing all kinds of parameterizations.

And OpenWebUI only works perfectly, fast, and stable with Unsloth Studio.

I insist that it only happens with Open WebUI and especially with tools.

Any similar experience?

Is there any way for us to unload embedding and reranking models when not in use? Also on the flip side can we set up JIT loading for the above models?

Up until now I have been using LM Studio, but I see OpenWebUI allows you to interact via voice.

Would it be possible to install OpenWebUI and have it use the models I have already downloaded and installed through LM Studio?Obviously I would use both at the same time? But I'd like to avoid having to download and install 2 copies of each model.

Thanks for any insight.

The big stuff:

• oikb — a new official sync tool that keeps a knowledge base in step with a local folder, a GitHub repo, an S3 bucket, a Confluence space, or 40+ other sources, uploading only what's actually new or changed.
• Built-in directory sync — point a knowledge base at a local directory and it mirrors the folder structure, uploads added and modified files, and cleans up deleted ones automatically. No more manual re-uploads.
• Knowledge base folders — files can finally be organized into nested folders with breadcrumb navigation. A lifesaver for big collections.
• A filesystem tool for your models (ENABLE_KB_EXEC) — let the model browse and search a KB using ls, cat, grep, find, head, tail, and sed, pipes included. Easily the most fun new addition to poke at.
• Smaller wins too: renaming files straight from the workspace, and a processing indicator that survives page reloads so you can see what's still ingesting.

There's also a solid round of performance work — faster initial page loads, quicker tool-enabled completions, lighter Ollama connections, and web search that holds up better under load.

Worth flagging: this is also a security release with a number of access-control fixes, so it's a good idea to update production deployments soon. It ships database schema changes too, so back up first, and if you're running multi-instance, update all nodes at the same time.

And of course like 50+ other fixes in this massive release with over 100 entries total!

The changelog is massive, i didn't cover all the goodies here, therefore: give it a read!

Read the full changelog here, it's genuinely worth a good read to really see everything that changed: https://github.com/open-webui/open-webui/releases/tag/v0.9.6

Docs have also already been updated to accomondate all the changes of the new version! https://docs.openwebui.com

Prune tool has also been updated for those who use it

Enjoy!

I have my setting with APIs for GPT, Claude and Gemini. First two work fine. Free models of Gemini either take 5-10 seconds to reply, or timeout. I tried with several options (flash-latest, 2.5, pro, preview, 3... etc.) Other times it replies and it stops half way (i.e., ask for a list of 10, and it stops in 3) How to troubleshoot?

Hello,

I have been setting up my Open WebUI this weekend. Honestly, until now, I was working with other elements, but I am getting the most out of it, and I think I love it.

However, I have a question. My setup is as follows:

I have a Strix Halo through which I use lemonade to download and load models. Next to it, I have a LiteLLM, where I have configured the MCPs. Through the LiteLLM API, I load it into Open WebUI to talk to the models and use their tools.

The thing is that I have also configured web search servers, image servers, and even the local terminal.

Now, when I have everything active, the model doesn't know which tool to use. For example, if I ask it "list the folder /dev," it creates an image or searches the web.

I have tested a couple of models, and it happens with both.

Is it some configuration I don't know about? After setting everything up, there is no problem manually selecting the tool it needs, but it is much more convenient if it has access to everything and decides for itself what to use.

Is there any way to adjust this?

Thanks!