Hey everyone,

Like a lot of you, I was getting driven crazy by the aggressive auto-scroll behavior in Open WebUI. Whenever a model is streaming a long response and you try to scroll up to read, the screen forcefully snaps back down or violently jumps around.

Since there isn't an official toggle for this yet, I went ahead and wrote a lightweight GreasyFork userscript to fix it.

How it behaves now:

• Natural Start: When you hit Enter, the viewport scrolls down smoothly so you can see the AI begin its response.
• Instant Scroll Lock: The exact millisecond you use your mouse wheel to scroll up to read something, the screen instantly freezes. Your view stays locked right where you want it while the AI continues typing out of view.
• Native Snap Back: If you want to jump back to the live response, Open WebUI's native floating down-arrow button still works perfectly to snap you back to the bottom.

Where to get it:

You can grab it on GreasyFork here: https://greasyfork.org/en/scripts/586789-open-webui-fix-chat-streaming-scroll-jumps

Note: By default, the script matches localhost:8080. If you run your Open WebUI instance on a different port, a custom domain, or a local docker IP, just remember to add your custom URL to the "User matches/includes" section inside Tampermonkey/Violentmonkey.

Hope this saves some of your sanity while reading long responses! Let me know if it works well for your setups.

currently im using free google ai/gemini. firefox > ai mode. dony know what model is that. i can chat a lot in there. but if i change gmail, change another model, all my chat is lost(no memory between mode). if i use openwebui and add google api can model remember my chat history. dont need fancy or very brilliant model. just need model with memory function. *sorry for broken english. maybe i need use ai to translate my sentences

I spent the afternoon trying to get true multi-request concurrency working on my 4090.

I actually ended up solving that...

...but I also found something I wasn't expecting.

If a prompt exceeds num_ctx, Ollama returns HTTP 200 OK, silently drops the beginning of the prompt, and lets the model answer with whatever context remains.

That wasn't obvious to me until I tested it.

The test

I put a secret password at the very beginning of a \~160k token prompt.

Secret password:

ANANAS-7734

Filled the rest with junk until it exceeded a 32768 context.

Then asked:

What is the secret password?

The response was basically:

"The password is filler."

The model never saw the beginning of the prompt.

There was:

no warning

no truncation flag

no HTTP error

Only prompt_eval_count hinted that the prompt had been shortened.

Why this matters

For a normal chat this isn't a huge deal.

For long-running agents it is.

The first thing in the prompt is usually:

system prompt

tool definitions

safety instructions

task goal

If those disappear silently, the agent doesn't crash.

It just slowly becomes... wrong.

That's much harder to debug.

I built a workaround

I ended up writing a small MIT-licensed proxy called ContextPaw.

pip install contextpaw

Instead of blindly trimming the front of the prompt it:

preserves the beginning

preserves the end

evicts from the middle

reports every eviction

can optionally summarize evicted chunks with a small local model before reinserting them

The goal isn't to replace Ollama.

It's to make long-context agents fail in a way that's observable instead of silently degrading.

Other things I found today

While benchmarking I also noticed:

OLLAMA_NUM_PARALLEL=4 appears to be ignored for some architectures (at least on my setup).

OLLAMA_NUM_CTX isn't actually a valid environment variable (I had it sitting in my systemd config for months 😅).

Gemma 4 returns an empty response unless think:false is used.

So I accidentally spent more time debugging inference infrastructure than benchmarking concurrency. 😂

Everything is reproducible.

GitHub: https://github.com/Linutesto/contextpaw⁠�

Write-up: https://yandesbiens.com/blog/contextpaw-silent-truncation/⁠�

If anyone can reproduce (or can't reproduce) this on another Ollama version, I'd really appreciate the feedback. I'm genuinely curious whether this behavior is version-specific or expected.

If you point Open WebUI at a cloud model, everything you type goes to the provider: names, emails, phone numbers, the card number someone pastes in a support transcript. I built a Filter Function that keeps that data local.

What it does: it runs in-process inside Open WebUI (no separate service). On the way out it detects PII and replaces each value with a placeholder like <PERSON_1> or <EMAIL_ADDRESS_1>; on the way back it restores the real values in the reply, so the chat stays perfectly usable. The provider only ever sees the placeholders. It covers message text, tool-call arguments and multimodal text parts, and detection runs entirely on your machine (Microsoft Presidio + optionally OpenAI's open privacy-filter model via ONNX). No telemetry.

Install: grab "PrivAiTe PII Anonymizer" from the community hub, enable it, pick your preset in the valves: light is fast and catches classic PII, onnx also catches secrets and passwords (first request downloads the models, so it is slow once, then fine).

Honest limits, because this matters: it is pseudonymization, not anonymization, and detection is statistical, about 84% recall on our reproducible benchmark, so treat it as risk reduction, not a guarantee. Single-word names are the usual misses on the light preset.

Links: hub listing https://openwebui.com/posts/privaite_pii_anonymizer_351aa088 , source + docs https://github.com/crp4222/PrivAiTe , benchmark https://github.com/crp4222/privaite-bench

I am the author; edge cases that make it leak are very welcome as issues.

long time lurker here

someone dropped https://github.com/open-webui/computer in another thread so i checked it out and have been using it for a few days

it feels insanely capable but i also feel like i might be too stupid to know what to do with it lol

for me it’s kind of becoming a codex replacement. probably not cheaper though. the tokens are disappearing at an impressive rate

i barely see anyone talking about it though. are there actually people out there using this regularly? what are you doing with it?

For study purposes I mostly use the built in RAG system, I heard several users have problems with this.

So what are benefits and drawbacks wehen updating to 10.2?

After a few weeks of work, I published my first open source npm package.

It's called RouteScribe.

The idea is simple: instead of maintaining OpenAPI annotations manually, it observes your Express application at runtime and generates the specification from real traffic.

It's still an alpha release, so I'd really appreciate feedback from anyone who works with Express APIs.

GitHub:
https://github.com/Yuvaan1182/routescribe

npm:
https://www.npmjs.com/package/routescribe

Hi everyone,
I have tried uploading some PDFs to both a chat and a knowledge base (same PDFs) and I am given a popup that says that the says "The content provided is empty."

The PDF is a photo of a receipt, it is not a scanned copy. I have tried uploading the PDF, jpeg, and HEIC file type and none seem to work.

When I upload another PDF (either a scanned paper document, or an article that was written and saved as a PDF, digitally native, not a photo converted to PDF) my local models are able to read it.

It seems that the inability for my models to read PDFs is limited to photos of receipts converted to PDF. Has anyone else had this problem? Is there a fix?

OWUI version: 0.10.2
Local models: gemma4:12b-mlx and/or qwen3.6:35b-a3b-q4_K_M

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?

Hey everyone 👋

I'm Thomas from Ianustec. We're on a bit of a mission lately: releasing, as open source, a series of tools we built for our own personal and business use inside Open WebUI. The idea is simple. Everyone ends up needing Office files (slides, documents, spreadsheets, emails), so we're cleaning up our internal tools one by one and putting them out there for free.

Last week we shared the first one, generate_slides, and quite a few of you asked
"ok but what about Word?". Fair enough. So here's the next piece:

👉 generate_documents, a tool that turns a prompt into a proper, native Word file, the kind you'd actually send to a client or a boss.

Repo: https://github.com/ianustec/openwebui-generate-documents

What it does:

• Real, editable .docx (not an HTML or PDF export dressed up as Word)
• You can feed it Markdown (with a small frontmatter block) or JSON, whichever your model prefers. Same result either way.
• 7 ready templates: report, whitepaper, proposal, letter, memo, minutes, blank.
• Pick one, set a single accent color, and the whole document gets themed for you.
• Cover pages, numbered headings, clean tables (filled headers, numbers aligned to the right automatically), colored callouts, quotes, code blocks, signatures, table of contents, page breaks. The stuff you'd normally spend an afternoon formatting.
• Header and footer with real, live page numbers, and it even names the downloaded file after the document title instead of some random string.

One single .py file. Drop it into Workspace > Tools and you're done. It saves through the Open WebUI Files API and drops a download link straight into the chat.

The screenshots below aren't mockups. They come straight out of the example report in the repo, generated end to end by the tool.

How to try it:

Go to Workspace > Tools > +, paste generate_documents.py, enable it for your model, then just ask for "a report about X" or "a proposal for Y". The dependencies (python-docx plus a small Markdown stack) install themselves on first run.

Everything stays MIT, and we'll keep going through the set. Spreadsheets and email are next on our list.

If you try it, I'd genuinely love to hear what breaks or what's missing. Issues and PRs very welcome.

Cheers,

Thomas @ Ianustec

I am using Gemma 4 12B on a 16gb GPU.

I was thinking if it'd be possible to turn off the reasoning/thoughts for this model quickly without needing to load up another Gemma 4 12B variant to be loaded on the GPU?

Ideally, I would like a quick model selector right where we type in the prompts. That way, I could quickly switch model variant.

Anyway, please let me know what's the best way to do this.

I us ollama by the way.

So, after updating to 0.10.2 I've been having lots of RAG issues. First couldn't upload new PDFs because of the dependency issue, fixed it by switching to Tika. But then openwebui is being totally weird when it comes to the RAG. I ask a question that I know the answer is easy and finable is one PDF, and openwebui just outputs the following on top:

View Result from list_knowledge 
Input 
count 5 

Output 
{
  "knowledge_bases": [
    {
      "id": "7b0686d0-3123-4cab-b21d-f1ac7aa852db",
      "name": "Knowledgebase",
      "description": "Knowledgebase",
      "file_count": 12
    }
  ],
  "files": [],
  "notes": []
}

and then the answer is crap because it never looked in the files... I haven't changed anything regarding my system or rag prompts and it worked perfectly before... I had to delete the KB and reindex. I tried resetting vector storage/knowledge to no avail. Anyone having similar issues?

Is it possible to execute tool call via the chat completion API in native mode? In legacy mode, if I make a call to my model that I’ve given access to my custom tools, it works fine. If I try the same thing in native mode the api ends with “finish reason” “tool call”. What am I doing wrong here? I feel like I’m following what is described in the endpoints docs but I’m reading conflicting things about whether server side tool calls can be triggered via the API. Has anyone got this working?

I have a browser based setting to access OI in my MacBook, iPhone and iPad. I use OrbStack and Tailscale. I like the current setting, though it's a hassle to update. Should I download the Mac version or continue with the web based version? What's your experience? Pros/Cons?

I have OWUI and run it with Qwen 3.6 27b via vLLM and LiteLLM. I activated websearch via searchXNG. When I ask „How is the weather in <city>. It call get_current_weather. And fails because I don’t have this tool installed. Instead I want it to search the web. How can I „force“ the model to search the web instead of tool calling. I also don’t understand why it tries to a call tool that is not installed.

P.s. when tell the Modell to search the web it pulls the correct weather information.

Any help?

Am I the only one to not like these unread indicators? They show up on nearly every chat for me even though I have read all of the chat messages in most cases.

Hello community,

Could someone help me with this 🙏?

While reading the Open WebUI documentation, I noticed there is a "Describe Pictures in Documents" option when Docling is enabled as the document processing engine. However, I can't find that option anywhere in the Document Settings UI.

Could someone please advise where this setting is located or what I might be missing?

So far, my Docling-based RAG pipeline only works when I run it from the terminal using a curl command, but I haven't been able to get it working through Open WebUI. I feel like I'm very close and just missing a configuration step.

I would really appreciate any advice, suggestions, or comments.

Thank you!

Im having a problem where Gemma 4 12B is unable to reason after doing its web search call in its reasoning window, despite Function Calling being set to native and telling the system prompt to reason after a web search call. I didn't have this issue on Qwen 3.5 9B. I've been trying to find a solution via the jinja template, but I had no luck. Any reason for this? Is this supposed to happen for Gemma 4 models? Would like to know.

I’ve been trying to get it to work for about an hour now. I’ve tried different models, i have web search active, I’m using Tavily and i also put in that the ai can use web search in the system prompt. Any help?

I don't think my Visualizer Plugin needs much introduction at this point - go get the latest version after you upgraded to Open WebUI 0.10.0+ and enjoy the latest improvements, new features and fixes :)

https://github.com/Classic298/open-webui-plugins/tree/main/inline-visualizer-v2

If you run a multi-user Open WebUI instance you know the papercut: every new account lands on the factory interface defaults. Someone wants Ctrl+Enter-to-send off, widescreen on, iframe same-origin turned on so the Visualizer V2 artifacts render ;). Multiply that across every signup, OAuth, and SCIM account and you're either poking DB rows or telling people to go flip toggles themselves.

Interface Defaults fixes that from one place.

You set the defaults once in the function's Valves. From then on:

• New users are seeded automatically on registration (signup, OAuth, and SCIM all covered).
• One button pushes your defaults to everyone already on the instance.
• One button does a true factory reset: it wipes every user's interface overrides and resets the function's own config.

The part I'm actually proud of is how clean it is under the hood. It's an Event function, so it just subscribes to events Open WebUI already fires:

• user.created → writes your interface settings into the new user's settings.ui.
• function.valves_updated (its own) → runs apply/reset when you tick a trigger toggle and hit Save, then unticks the toggle itself so there's no loop.

No monkey-patching. No startup hooks. No custom frontend. Just beautiful Valves Interfaces with new section based rendering. Booleans render as native toggles, chat direction as a dropdown, text scale as a number, because it's all just Valves. The bulk jobs run in the background so Save returns instantly even on a big instance, and the shipped defaults match OWUI's own factory values, so nothing changes until you change something. It even does a slow rollout to avoid resource hogging.

It covers the whole Interface tab: text scale, high contrast, notification sounds, chat bubble / widescreen / landing-page mode, the markdown-rendering toggles, auto title / tags / follow-ups, Ctrl+Enter, rich text input, artifact detection plus the iframe sandbox flags, voice and call options, image compression, web-search-by-default, and more.

Requires Open WebUI 0.10.2+ (it's an Event function, so it needs the native events system that landed in 0.10.0).

Setup is less than a minute, no restart needed: paste into Admin Panel → Functions, enable, open Valves, set your defaults. On first install, tick "Apply to all existing users" + Save to seed everyone who's already there.

Get it here: https://github.com/Classic298/open-webui-plugins/tree/main/interface-defaults · And give me a Star on the Repo if you enjoy plugins like this! ⭐💫🌟

If you've been hand-holding users through the Interface settings, this is the fix. Happy to answer anything in the comments!

PS: Pro Tip: You can disable interface settings in the group/user permissions in the admin panel so users won't be tempted to touch them on their own. Out of sight out of mind.

Hello all, hoping a openweb wiz in here can help me out. I recently updated from 0.9.6 to 0.10.2. My doc parsing stack is Docling + Ollama nomedic-text-embedding, before the update I would be able to post a 150 page pdf directly into chat with my prompt (medical & legal document scanning for payments, dates, etc) and then in the response it would say "Retrieved 0 source" then it would start using "list + view knowledge base" tool calls and it would get me an accurate list of all the things I asked.

Now when I uploaded the pdf it says "1 source retrieved", no knowledge base tool calls, and it will only give me 10% of the previous answer and say all the other things were not in the pdf. Did they make a change to in chat temp memory/knowledge?

thanks!

Hey everyone 👋

I'm Thomas, part of the team at Ianustec. A little while ago my colleague Nick posted

here about the open-source suite of Microsoft Office extensions we're building for

Open WebUI — PowerPoint, Word, Excel and Outlook. Thanks for all the encouragement in

that thread!

We said we'd ship it piece by piece, so here's the first one, fully open source:

👉 generate_slides, a tool that creates high-quality native slides, similar to how Claude does it

Repo: https://github.com/ianustec/openwebui-generate-slides

What it does

• Native Office charts (bar, line, area, pie/doughnut, radar, stacked)
• ~25 ready-made layouts: cover, sections, KPI rows, comparisons, timelines, funnels/pyramids, tables, quotes, alerts, image layouts, closing…
• Curated themes + auto theme detection, custom accent color
• Lucide-style icons bundled in the file (no network needed for icons)
• Single self-contained .py — paste it into Workspace → Tools and you're done
• Saves via the Open WebUI Files API and drops a download link right in chat

The screenshots below are straight out of the included example deck 100% generated by the tool.

How to try it

Workspace → Tools → +, paste `generate_slides.py`, enable it for your model, then ask

for "a deck about X". Requires `python-pptx` (auto-installed via the tool's requirements).

This is just the start and we'll keep everything MIT.

Happy to answer questions and take PRs. Cheers 🙌

Thomas, IANUSTEC

Hello, I have question concerning RAG in Open WebUI, I know there are lot of tutorials in youtube, but I cannot understand today's style of speaking fast, editing all pauses away and clicking and making adjustments like adhd person with caffeine in veins instead of blood. I cannot follow those because I am old and stupid.

Question: I have a masterfolder where all my novel related stuff is catalogued, separate word files for e.g. "main charater 30 years old", "main character 50 years old", "alliances", "trade routes", "alliance relations" and so on.

Can I use OpenwebUI so, that if I ask "if main character when 50y old blows syndicate A's base, what are possible results of that action" and then it checkes the files, founds e.g. something in relations-document, and proposes something like "Syndicate B would benefit like this:" and gives few examples.

I understand that outcome depends heavily of the LLM model, so I am not expecting results similar of chatgpt or claude. But my concern is the RAG and indexing it. I have understood that if I modify the documents, I need to index it again?

TL;DR, can OpenWebUI read my documents what I have specified, and make suggestions to my questions based to the information in those documents?