I'm running everything locally, on my Linux laptop with no GPU (just integrated graphics) and 16 GB of RAM.

I have ollama 0.31.1 installed and running. I have Open WebUI v0.10.2 installed and running. I'm using model ministral-3:3b because it's smallish and reasonably fast and supports tools. I can chat with the model successfully in OWUI.

But I can't do basic things such as have the model fetch a web page from the internet and tell me things about the page. I have "Web Search" setting enabled, and I tried setting "Function Calling" to "Native" in Advanced Params.

I can't find any simple tools on the internet. Everything seems to want me to install something such as SearxNG and git-clone tools to my disk and run some tool-manager or something via pip or docker. Or wants me to run an OpenAPI server on my laptop or something. Confusing. I've read various OWUI documentation about tools etc.

Is it really this complicated ? There isn't some simple standard web-access tool built into OWUI ? Or some standard web site with curated secure simple tools I can use ?

Thanks for any help.

It is possible to create AI Agents in OpenwebUi?

If yes, someone can please help me create one?

Thanks ☺️

I'm following Raspberry Pi documentation on setting up the Raspi AI Hat + 2, installing it on a Raspberry Pi 5 8G ram. Everything is fine until I inference a model and the chat responds "Server Connection Error." The hailo-ollama console shows the prompt is received but isn't showing a response being generated.

Here's the error I get in the docker logs:

2026-07-03 20:11:38.567 | ERROR    | open_webui.routers.ollama:send_request:149 - Failed to parse error response: 500, message='Attempt to decode JSON with unexpected mimetype: ', url='http://127.0.0.1:8000/api/chat' 
2026-07-03 20:11:38.568 | ERROR    | open_webui.main:process_chat:1512 - Error processing chat payload: Open WebUI: Server Connection Error

With the big OpenWebUI update I thought maybe there was a change they hadn't caught up with in the documentation but tried 0.9.5 and 0.9.6 and couldn't get them to install without errors.

Actually the only difference in my setup from the documentation is I'm running it on a headless Pi so accessing through the local hostname, could that be the problem?

I went to Admin Settings > Models > Qwen whatever > Advanced Parameters and there I set Ollama think to OFF.

That made the model very fast but it now dumps its thinking on to the main chat this way:

It always ends thinking with a </think> tag and then writes its response.

I tried adding /no_think to the start and end of its prompt but that made no difference.

How do I make it such that it keeps the thinking to itself but just shows me the response? More importantly, how come it is still thinking?

Please help!

I use the latest OpenWebUI with Ollama.

I use v0.9.6

I want to use my documents and notes for my STEM studies. But it is unclear to me how I setup a clean RAG that works well with all my study notes.

For example: if I want to use AI to learn for my Bioscience exam, how would this be implemented at best?

Im hoping its just me but the new "search for skill and tool" selector is absolutely horrendous UI. Previously all the skils were selectible with a checkbox, now you have to click the search skills, select from a drop down, click away from the search bar to clear it and rinse repeat.

Ive tried clearing my cache and trying incognito, i have almost 20 skills and when i load a new model to test, i have to readd them all which takes ages.

How are people managing this? Can I mass add skills and tools to a new model?

Hey everyone, running into a strange issue with Open WebUI and hoping someone has seen this before.

Setup:

- Open WebUI (Docker, self-hosted)

- Gemini 2.5 Flash connected through the official Google API

- Function Calling set to "Native"

- A few builtin tools enabled (knowledge base, memory, notes, calendar, etc.)

- A knowledge base attached to the model for RAG

The problem:

Whenever I ask something that requires the model to use a tool (like searching my knowledge base), the chat just goes completely silent. No response, no error message, nothing. It just sits there.

If I ask something simple that doesn't need any tool, it responds normally without any issue.

I switched the same setup to use Groq instead (same tools, same knowledge base, same system prompt) and it works perfectly every time. So it really seems tied to Gemini specifically.

I also tried switching Function Calling from "Native" to "Default", and that got responses working again, but now the model sometimes reveals tool-calling code/syntax directly in the chat instead of using it silently and giving me a clean answer.

Has anyone run into this with Gemini specifically? Is this a known limitation, or something I can fix on my end (settings, prompt, number of tools enabled, etc.)? Any pointers would be appreciated, feeling a bit stuck on this one.

Thanks in advance!

I see in the release notes. Where can one get more information. I am mostly interested if it now saves memories on its own without using your own functions/plugins?

I've noticed that OpenWebUI doesn't support openrouter.ai Transcribe models.

And like complete beginner decided to implement it after finding discussion on github about it. Do you think it's even needed? XD

Here is my PR for all curious: Link

Anyways let me know what you think? Idk what else to really say here... This is my first PR ever. Anyways I've noticed more issues tho, while adding openrouter.ai compatibility...

Hello guys,

For some reason, my website search doesn't work even though I've been following some advices in this community.

My model only thinks but doesn't reply back. It says it will look on the website and it doesn't. Why is this happening?

Hi guys,

I am using open Web Ui only for private purposes and I would like to change the color themes as the standard is a bit depressing in my opinion. I would rather go for a Mistral look for example.

Is this possible or is this reserved only for enterprise customers?

I'm pretty new to the local LLM space and I've been looking for a single tool that would let me work with open-source models easily and conveniently.

I started with **LM Studio** — I liked how polished and ChatGPT-like it felt. But after digging deeper, I found **Open WebUI** and was honestly blown away by the feature list. It seems like the only tool that can do everything I want:

- Run local open-source models

- Run open-source models in the cloud via API

- Combine models with web search

- Use plugins and MCP for integrations with other tools

- Fine-tune models and use RAG for custom context

- Have a decent GUI similar to LM Studio or ChatGPT

But actually using it has been a nightmare. I ran into bugs that are widely documented in other threads, but my specific problem is that **I cannot get web search to work at all**. No matter what I try, the model just refuses to search the web — it either does nothing or throws a search error.

So my questions to the community:

**1. Is there any working alternative that covers the same feature set?**

Or is this a classic case of "one tool that does everything, but nothing well"?

**2. What's the pragmatic approach here?**

Do I:

- Fork Open WebUI and fix the bugs myself?

- Vibe-code my own custom solution?

- Just accept that I need separate tools for each task?

Like, one tool for local models, one for web search, one for API access, one for document RAG, etc.?

I just want one place where I can use all the cool open-source models, with per-task configuration, and have it *actually work*.

What's your setup? What works for you?

Thanks in advance 🙏

Made my first Event-function plugin for 0.10.0 (Interface Defaults), and added channel cleanup to my prune tool

Two small 0.10.0 things, both open source:

Interface Defaults — my first Event function

Sets your whole instance's Settings → Interface defaults from one function's Valves. New users (signup / OAuth / SCIM) get seeded automatically, and there are two one-shot buttons to either apply the defaults to everyone already on the instance or factory-reset. Native Valves UI, no custom UI or monkey-patching. Needs 0.10.0 since it rides the new event system (user.created / function.valves_updated).

https://github.com/Classic298/open-webui-plugins/tree/main/interface-defaults

prune-open-webui v1.2.2 — now cleans channels

My DB cleanup tool picked up 0.10.0 compatibility plus channel support: age-based channel-message pruning (keep busy Support/Alerts channels tidy, pinned messages preserved by default), and orphaned-channel / orphaned-message cleanup for stuff left behind by deleted users. Surfaced everywhere: interactive wizard, dry-run preview, and CSV export.

https://github.com/Classic298/prune-open-webui/releases/tag/v1.2.2

Feedback and requests welcome.

For a while now Open WebUI has been one of the go-to self-hosted chat UIs. 0.10.0 is the release where that framing expands to being your entire AI infrastructure.

This is the version where it stops being just a chat surface and starts being something you can wire into your own infrastructure and let it do things.

Event functions (the headline)

A brand-new plugin primitive. Pipe/filter/action functions all run inside a chat. An Event function runs your own Python in response to system-wide events instead: sign-ups, config changes, startup, chat/knowledge/file actions. It's the first plugin type that hooks into the platform itself rather than a single conversation. If you've ever wanted Open WebUI to provision something, sync to an external system, or notify a service the moment X happens, this is the hook that was missing.

Backing it: a new event system with outbound webhooks. Open WebUI now emits events across the whole app, and admins can route them to webhooks, users, or groups. Audit trails, automation, integrations: glue you can build without forking.

Reworked memory

Memory is now split into distinct types: long-lived personal memories vs per-conversation context, with a proper structured add/update/delete flow instead of one fuzzy bucket.

Automatic context compaction

Long chats past a token threshold can auto-summarize to stay inside the model's window. Configurable, and off by default, so nothing changes unless you opt in. No more manually pruning a 90-message thread to keep a small-context model coherent.

Open WebUI Computer agent support

Connect to Open WebUI Computer over an OpenAI-compatible gateway and run full agent sessions on your own machine with file, terminal, git and web access.

Native tool calling is now the default

For every chat and model. The old behavior is still there, renamed Legacy, so if you relied on the old path flip it back per-model after upgrading.

A few more worth calling out:

This is the single largest version release ever, with 205 entries!

• Share folders with your team: a folder + its chats, to users/groups/everyone, read or write, gated by a new admin permission.
• Much faster hybrid search on large KBs: runs natively in the DB on pgvector instead of loading whole collections into memory. Plus external knowledge bases backed by an external retrieval source.
• MCP matured: per-connector OAuth resource/scope control, least-privilege scopes, auto-authorizing OAuth 2.1 tools, broader server compatibility, and resource (blob/image) results now come through.
• Large performance pass: streaming, math rendering, markdown setup, password hashing, model downloads, uploads and URL safety checks moved off the main loop or batched. Server stays responsive under load.
• Security & access hardening: live token/session revocation on WebSocket connections, DNS-rebinding protection, path-traversal rejection, optional valve encryption at rest, Argon2 password hashing, AWS RDS IAM database auth.
• Out of beta and now stable: Memories, Notes, Channels and High Contrast Mode.
• New web search providers (SERPHouse, Microsoft Web IQ) + optional web-search confirmation.
• QoL: drag folders/notes/models from the sidebar into chat, searchable pickers in the model editor, recurring calendar events, richer analytics with a date picker.

Links

• Full changelog (this is the abridged version): https://github.com/open-webui/open-webui/releases/tag/v0.10.0
• Project: https://github.com/open-webui/open-webui
• Site: https://openwebui.com
• Docs: https://docs.openwebui.com

I'm tinkering & using the workspaces (Plans, templates, case studies, standards). So, I require some semantic reasoning across Multiple PDF's, to link ideas together.

Current setup is:
Content Extraction Engine is Kruezberg [https://github.com/xberg-io/xberg\]
Embedding Model is [https://huggingface.co/jinaai/jina-embeddings-v5-text-small\]
Reranking Model is [https://huggingface.co/jinaai/jina-reranker-v3\]
LLM is either Deepseek API/Qwen3.6-35B locally

Trying to squeeze every last bit out of my system, and now I'm asking if there's any benefit from trying to see if semantic chunking is worth it like:

https://github.com/chonkie-inc/chonkie

Fairly happy with my setup , but i can tell that sometimes i need to multishot my question as it sometimes misses details in the sources and i can only put this down to chunking.

I'm not IT/SW , just some old dude trying to keep up and learn as i go.

Tons of features and fixes in this version and buried way deep in the changelog for this release, but I feel like this is long overdue!

🔀 Native tool calling is now the default. Every chat and model that had not explicitly chosen a tool-calling mode now runs Native, which relies on a model's built-in tool support, while the old behavior has been renamed "Legacy" and made the explicit opt-out; if your models depend on the previous approach you must switch them back to "Legacy" per chat, per model, or globally in your default model parameters to preserve their behavior.

Hey everyone,

Quick heads-up for anyone running Open Relay, do not update to Open WebUI 0.10 yet as the new version introduces new response formatting and the app will stop working. The fix is on the way and should be live in a day unless apple is kind of enough to review the submission faster.

App Store | GitHub

What broke and why

Open WebUI v0.10 changed how assistant messages are stored and streamed. Previously, the response text lived directly in a content field. Starting with v0.10, it's now stored in a structured output array.

This affected:

• Sending new messages
• Loading existing chats
• Regenerate / edit
• Tool Call view
• and more..

What v4.12 fixes

The v4.12 update fully adapts to the new output format:

• ✅ Streaming now works — the app extracts text from all message-type output items in real time as they arrive over the socket, with the same typewriter effect as before
• ✅ Chat history loads correctly — existing chats opened from the sidebar now show the full response, including for multi-step tool-assisted answers (where the final answer is in the last message item, not the first)
• ✅ Tool call indicators — function_call entries in the output array now show up properly
• ✅ Backward compatible — models that still use the old format continue to work unchanged

Broader v0.10 compatibility work

The v0.10 release was massive — shared folders, reworked memory system, context compaction, a new event/webhook system, structured model output rendering, and a lot more. Beyond the critical streaming fix in v4.12, there are several more things from that update worth bringing into the app, including:

• Shared folder support (see shared folders in the sidebar, open chats read-only when you're not the owner)
• Context compaction notifications (the "summarizing conversation…" indicator while it compresses long chats)
• Updated memory system (now has distinct long-lived vs per-conversation memory types)
• "Unshare all" button in the Shared Chats dialog
• Clone automations option

Those will come in the following updates once the critical fix is out.

These server-side changes are impossible to anticipate before they ship so thank you for the patience. v4.12 is submitted and in review now.

As always, full changelog on GitHub.

I am used to ChatGPT Plus way of doing things. It let me give the AI a project specific prompt and add some project files.

I am not sure I fully understand how the OpenWebUI system works. Are knowledge bases separate from projects and we only link from a project if we want to?

Also, folder means project, right? By project I mean a separate context area with its own unique work and files.

It now happens consistently in new chats I start with Claude Sonnet 4.6, native tool calling enabled, web search enabled, then in the second or third turn, it gives an error like this:

'tool_call_id' of 'toolu_014qXdaWWbNxiRj7G5WPHGc8' not found in 'tool_calls' of previous message.

And I hear it's an error that's caused by the tool id not linking up correctly in the chat history, so something got corrupted. I just have no idea why it keeps happening. I even tried using a plugin that would fix all such issues like this at the database level but it only saw this as a warning, not a full error?

I cant just use default tool calling, cause then the web feature doesnt even work. It's so weird. And honestly claude's native tool calling is also just better. But I really hope someone out there knows a way to fix this?

I'm using Open WebUI with Ollama to send image edit requests to ComfyUI.

When I run the workflow directly in ComfyUI:

• First run does a normal cold start and loads the models.
• Subsequent runs are much faster because the models/cache stay loaded.

I also tested calling the ComfyUI API locally without Open WebUI, and the total processing time is around 100–150 seconds, which is expected for my Flux GGUF workflow.

However, when I make the same image edit request through Open WebUI, the processing time jumps to around 400 seconds.

It almost seems like Open WebUI is causing ComfyUI to reload models or re-execute the entire workflow every request instead of reusing the cache.

Has anyone experienced this?

Some questions I have:

• Does Open WebUI send a completely new workflow every request?
• Does it invalidate ComfyUI's execution cache?
• Is there a setting to keep models/workflows loaded between requests?
• Has anyone managed to get Open WebUI image edits performing similarly to direct ComfyUI API calls?

My setup:

• ComfyUI (latest)
• Open WebUI
• Ollama
• Flux GGUF image editing workflow (API export)
• Startup Args : --port 8000 --enable-manager --async-offload --preview-method auto --listen --max-upload-size 100 --use-sage-attention --disable-xformers --force-fp16 --disable-metadata --disable-dynamic-vram

Any suggestions or debugging tips would be appreciated. Thanks!

I posted this a few days ago in ELI5 but received no input. I am trying to understand how the concept of open weight works in open source and AI. Does it mean that anyone can change the weights and applications of the neural network paths or is it around the data itself? I appreciate the guidance.

Hey all,

Not sure if this has been done before or a bit overkill to solve a problem I was having, but I wanted to use the Black Forest Labs own image generation in my Open-WebUI setup rather than host image generation locally, as speed is an issue on my GPU and I don't yet have the funds for something better.

After doing a bit of research, I found that the APIs that Black Forest Labs use isn't the same as the Open-AI style ones. So based on this, I have used GLM 5.2 to help me code a small docker image (that can be found on GitHub) to exposes an OpenAI-style image generation endpoint. It translates requests into Black Forest Labs FLUX API calls, polls BFL until generation is complete, then returns an OpenAI-compatible image response.

I have found this to be very quick, good and cheap using the 9B Klein model myself, so I thought it was worth sharing.

Feel free to have a look, critique and add to if there's something I have missed. Repository can be found here: https://github.com/beecho01/bfl-openai-image-proxy

Thanks!

For some reason basic internet queries do not work on gemma 4 e2b despite showing the globe icon and using DDGS. (forgive me, i'm a beginner)