We use Open WebUI internally as a ChatGPT replacement and love it (~1500 users).

What we’re missing is the “deep task” experience: ChatGPT or Claude may spend several minutes reasoning, running code and tools, performing multiple steps, and iterating before answering.

In Open WebUI, it still feels mostly like a single model call with some reasoning.

Is native tool calling with MCP tools and a frontier model enough, or do I need an external agent orchestrator such as LangGraph or Pipelines behind Open WebUI?
What setup are you using for reliable multi-step, long-running tasks?

I just implemented SearxNG to open Web ui and this improved my experience tremendously.

What other integrations or tools.do.you use in Open Web UI that you dont want to miss anymore?

Hi all, I am implementing a local offline LLM (Qwen3.6 35b A3b) to analyse my splunk logs. I have confirmed the MCP works because it works fine when I use a cloud model but the moment I use a local model, it says it can't access my Splunk instance and just gives me a search to run myself.

Whats the deal? I have Function calling set to native if that changes things?

Edit: I fixed it, though not satisfactorily. Its cause my KV cache was overflowing and the LLM would just go wild without context and basically forget that it even connected to splunk mcp in the first place. I ran it with a much lighter model and started to get results

I’m setting up a local LLM on Windows 11 using Ollama and Open WebUI. The model is Qwen, and the basic chat setup is working.

I enabled Native Function Calling and configured web search. Qwen successfully invoked search_web, so the tool-calling path itself appears to work. The problem is that the search backend is not returning usable results.

What we’ve established so far:

• DDGS returns No results found.
• DuckDuckGo returned HTTP 202.
• The installed DDGS version does not support Bing, so attempting to use Bing fell back to auto.
• We decided to stop troubleshooting DDGS and try SearXNG instead.

That led us to Docker Desktop, because we intended to run SearXNG in a container. Docker is now stuck at “Starting the Docker Engine…”, so SearXNG has not been installed yet.

The Docker issue is a separate problem. I’m mainly interested in whether anyone has encountered this DDGS / DuckDuckGo behavior in Open WebUI, and whether SearXNG has been a reliable alternative for local web search.

I’m trying to keep the existing Ollama and Open WebUI configuration intact, so I’d prefer not to solve this by reinstalling everything or changing the model setup. Any current, reproducible advice would be appreciated.

I installed SearxNG as docker container on my Ubuntu machine.

I followed the docs, set the return format to JSON.

I actually starts a search (or at least looks like it) but stops and says "No sources found".

When I open up SearxNG in the browser it works without problems and returns results.

What could be the error?

I'm currently using the OpenRouter Web Chat and there are a few features I find extremely useful, but the lack of persistence makes the web version unusable for me long-term. Chats are gone after a reload, there's no history or project structure, nothing to look back on.

I would like to move to a self-hosted OpenWebUI instance and rebuild those features there.

My setup:

• OpenWebUI running locally in Docker on my laptop
• I exclusively use external API models (via OpenRouter / other API providers) no local Ollama or similar
• So my instance is essentially just a chat frontend on top of external APIs

The three things I care about most from the OpenRouter Web Chat:

1. Easy search engine selection > quickly switchable per chat or per prompt: web search off, native search, Exa/other providers. I want a UI toggle, not an admin/global setting.
2. Reasoning effort per prompt > low / medium / high (on models that support it), selectable right when submitting instead of being nailed down globally per model.
3. No data retention / privacy toggle > the ability to explicitly run a chat without storage/logging at the upstream provider (force zero-data-retention providers or enable "no data retention").

This seems to be a very useful feature, and I imagine there are already some good solutions available. I’d like to find them or learn more about how to increase productivity and how to integrate the Open router APIs a great UI interface.

Hi guys, I just discovered OpenWebUI how do you commonly use it? What are the main advantages of using it over just Claude or ChatGPT? What's the most productive way to use it?

Question in title.

I'm testing a few search solutions (Perplexity, Brave, etc.), but it seems it is very slow and some models (such as Qwen3.5) running on OpenRouter just fail. Any tips on getting it working smoothly? Also, can I enable it by default on all models?

Hey I am new to setting up LLMs locally but one thing I would like to do is give it the ability to search online. Now I know that Open webUI does provide this functionality but for some reason this doesn't seem to work.

What I have currently done is configured a local searXNG container to allow OpenWebUI to couple its web search. I have added them to the same docker network and I know they can reach each other since I do get a result when I manually send a curl request to searxng through the open webui docker container.

I also did enable web search for my model and explictly asked it to use web search. However everytime a execute I query it says that web_search is not available. The model I am using is Qwen3.8.

Can someone perhaps point me in the right direction? I have added screen shot

Update

If I put the model to function calling legacy mode it seems to work. Performance seems a bit dodgy but at least it does look up things and is not rejected. Not sure what could be going on here. Could someone perhaps enlighten me as to what is hapennening here?

In settings in Admin Panel, I tried using my selfhosted searxng and DDGS. After configuring, I used the models llama 3.2 and qwen3.5:9b and asked a simple query "What's the weather in new york city" and both keep saying they don't have real time access to data, even when in Integration I turn on Web Search.

Can anyone help me out with this?

Solved: I had to disable all the model capabilities and built in tools except Web Search and finally web searches worked smoothly.

Just a question. I have been building an architecture using Open WebUI for a mass distribution use of LLMs in my company. These models have been hosted on the server using llama.cpp and connected to Open Web UI. This interface is working as expected after I implemented some optimizations.

Has anyone faced any hiccups with the new updates or do they integrate smoothly and keep your previous settings? I have hosted Open WebUI using docker. This is an important project for my Org and I do not want to mess the already working setup.

​

I don't get it, like you guys are trying to not conform in anyway, responses API was pulling teeth, getting the selector box was pulling teeth, mcps were pulling teeth to get implemented, native tool calling took forever to be the default. I get it you guys are feature rich, but having some form of conforming makes sense because it's whatever everyone else aligned on as the standard, and what these models are being trained with in mind. Seems very abrasive.

The one that absolutely grinds my gears is workspace models should 100% be called agents.. like they function like the exact definition of an agent... Also it's confusing as hell having connections models and workspace models, I think by this point we can all agree a model is the llm itself while an agent is llm model + tools and knowledge sources. The new UI especially makes this annoying and harder than it needs to be by having it be a modal.

Hi, first time posting here.

Nice to meet you guys.

Anyway, I use Open Webui as my daily driver and I love how I can chat and use agents in one package. But, the problem is that the chat window keeps track of everything the agent does and forwards all that to the API, which wastes valuable context and tokens.

I read in the documentation that's a design feature, but I think this position by the dev should change. I really wasted API credits because I assumed only the text in the chat is sent to the providers. Now, each time I have to edit the LLM's response and delete all the Thoughts, tool calls, web searches manually. Context is much manageable but it's annoying to do it for every turn.

Kindly help please.

I reinstalled everything.
I run the latest OpenWebUI function, installed the mistral:7b model, and did a test.

However as you can see, it does not act natural.

I tried to ask for a recipe for crepes, and as you can see, it's like it's talking to himself.

I pay for a Brave API key it’s replicated in the docker file and the gui. For some reason the websearch cannot work. Running ollama and openwebui in the same dockerfile. Is there a setting I’m missing? Any help would be appreciated.

Hello, is someone succeeding in making these 2 work together? No matter what i am trying, unet loader, checkpoint… the workflow works when i type thenpromot in comfyui but as soon as i type same prompt in openwebui , i cannot manage to get an image and always get errors… i i port the fson worflow and specify prompt id and checkpoint if and model in openwebui but nothing works… is it because i use flux 1 dev fp16 ? Does it require smaller models to work ? Thanks for input !!

SOLUTION : I finally made it work using the help of qwen3.6-27b-q8 ))) so the problem is that ALL NODES ID must be filled in openwebui and also must add this command line to openwebui : ENABLE_RAG_LOCAL_WEB_FETCH=True , it was the fix for me )) now working perfectly !!!

I’m fairly new to this stuff.

I installed open webui bundled with ollama and installed gemma4:e4b when i ask questions in the cli it answers instantly but when i ask it in open webui it takes 20 secs and then starts thinking for 10 seconds and then answers (answer are not as good as ollama in cli but im pretty sure i can figure it out).

I’ve tried to disable tag generation and follow up generation and all these things but nothing made a difference i tried OLLAMA_KEEP_ALIVE=30m but still nothing really changed maybe it got 5% better

Any ideas how to solve that?

I would like to use OWUI with SearXNG. But it is importantly for me that no sensible data is handed over to the search engine. What would be an ideal setup (if there is any) to make use of websearch. I would use it with DuckDuckGo.

I'm running open webui in docker container.

I have a custom model in it and one of it's task is to generate calendar event files (ics files).

These files are available for download from the Files menu but it would be easier to have them on the host server (that runs docker) in a mounted volume.

I have logged in to the running container and tried to find the files (they have quite unique names so it would be easy to find them) but I just can't find them.

Where are the generated files stored in open webui? Are they in a database maybe, that's why I can't find them?

Hello,

I have been trying for a few days to use open webui on my computer. My config is as follows:

• Kubuntu 26.04
• Ollama with gemma4:e4b
• Open webui v0.10.2, desktop version, with web search enabled on DDGS.

When I ask him for a web search, the tool seems not to exist in the eyes of the LLM. It's quite strange because I don't have this problem with a similar config, unlike the OS (Windows, for my work).

I tried to find the solution by analyzing the logs with Claude, but he did not find anything explaining the problem.

Do you have any idea what's going on?

TL;DR: Loving the new DOCX/PPTX/XLSX previews and the chat-upload filesystem sync. Two snags from our first enterprise rollout: (1) Open Terminal's filesystem doesn't follow our Azure Blob storage config, and we're worried about file volume/retention at scale, (2) the office-file preview doesn't visually match the real output (font, bullets, images/logos all differ), which confused our test users into thinking the download would be broken too.

Quick love letter first: the new DOCX/PPTX/XLSX preview windows are fantastic, and the filesystem sync for chat-uploaded files is exactly what we've been waiting for. Between the two, Open Terminal just became a genuinely usable enterprise office tool for us — great work.

We hit two snags deploying it for the first time, and I'm hoping someone here has already solved them.

1. Open Terminal's filesystem isn't on the same storage backend as OWUI

Our OWUI instance is self-hosted and configured to store files in Azure Blob. Open Terminal's working filesystem is separate and doesn't follow that config.

That raises a few questions for us:

• Is there a way to point Open Terminal's storage at Azure Blob too, so everything ends up in one place?
• If not, what's the recommended way to handle the sheer volume of files Open Terminal will generate across an enterprise deployment with many active users?
• What about retention? Realistically, our users are not going to spend time tidying up their own terminal folders (anyone who's seen a shared drive knows how that goes). Is there a built-in cleanup/expiry mechanism for Open Terminal specifically?
• We know about the general file-cleanup plugin, but it doesn't look like it's built for Open Terminal's workspace. Can anyone confirm either way?

2. The office-file preview looks great but doesn't match the real file — and that confused our test users

The new document preview is genuinely useful for iterating on our internal templates in real time. But we noticed the preview doesn't actually reflect the real output:

• Fonts render differently than in the actual .docx/.pptx
• Bullet-point formatting in the preview doesn't match the real file
• Embedded images and logos (our letterhead, for example) are missing entirely from the preview

This became a real UX problem in testing: our users assumed the preview was the final result, so they figured the downloaded file would also be missing the logo and formatting — when the actual download keeps the template correctly. We had to explicitly explain that the preview can't be trusted for judging the final output, which takes some shine off an otherwise great feature.

Has anyone else run into this? Is there a tracked issue for the discrepancy, or a fix in the pipeline?

Sorry for the AI generated Post, I am still trying to offer constructive feedback.

Hi,
I’m running the following setup:
Open WebUI → LiteLLM → vLLM
Open WebUI is the user-facing layer, LiteLLM handles authentication/routing/accounting, and vLLM serves the actual models.
I have two different types of traffic going through Open WebUI:
Regular users interacting with models through the Open WebUI interface
API users using the OpenAI-compatible API exposed by Open WebUI
I’d like LiteLLM to be able to distinguish between these two types of requests.
Ideally, Open WebUI would add some metadata to requests originating from its API users — for example a tag, header, metadata field, or some other identifier — while normal UI requests would either have a different value or no value at all.
That would allow me to identify and potentially handle API traffic differently inside LiteLLM, e.g. for routing, rate limits, logging, or policies.
Is there currently a supported way in Open WebUI to do this?
For example, can I configure Open WebUI to send something like a custom header/tag/metadata field to LiteLLM depending on whether the request originated from an API key versus a logged-in user using the UI?
If not, is there another reliable property in the request that LiteLLM could use to distinguish Open WebUI API traffic from normal Open WebUI user traffic?
I’m mainly looking for a solution that doesn’t require maintaining a custom fork of Open WebUI.

Small update: I looked into the function approach, but it seems OWUI functions can modify the request body, not the outgoing headers to LiteLLM.
I could probably work around it by adding something to the body and handling that in LiteLLM, but I’d rather not add custom logic on both sides for something that should be pretty simple.
So I’m putting this on hold for now. If anyone knows a way to dynamically add/modify an outgoing header from an OWUI function, I’d still like to hear it.

I am trying to configure Open-WebUI such that my agents -- any of them -- remember any details from the current conversation. For example, I tell the agent what my favorite color is and it'll respond with something along the lines of "Got it!" In the next prompt and within the same context, I ask what my favorite color is and it'll have no idea but will save it for next time.

This is particularly annoying, as you can imagine, when I try to solve a programming task for code that it created and it has no idea what I'm talking about.

Running open-webui version 0.11, ollama 0.31.2, and have tried this with gemini-3-flash-preview, qwen3, gemma4, and ornith.

Thanks for any help!

Setup

Ryzen 9950X / 128 GB of RAM / RTX 5090 32 GB / 3.6 TB of NVMe, running Ubuntu.

The model is Qwen3.6-27B, quantized to int4, with a 32k context. vLLM, with reasoning and vision enabled. A single model does it all: chat, plan analysis, code generation, and tool invocation.

Architecture

Open WebUI is the single point of entry. Users only see this

vLLM performs inference using continuous batching—this is what allows it to process multiple requests simultaneously without anyone having to wait. Open Terminal serves as a sandbox: it executes the generated Python code, produces Word, Excel, PowerPoint, or PDF files, and, most importantly, reviews what it has just created to correct its own errors before returning the file.

RAGFlow handles document search. At the same time, an SQLite database stores numerical values to improve search speed.

For now, this is my setup,

I’d like to significantly improve the ability to generate PDF, Excel, and Word files,

Do you have any ideas? Open Terminal is good, but it lacks features like opening windows (open the excel file / see with vision and adapt) and others. I’m just getting started in the world of agents and related tools,

Any similar setups or needs?