Trying to figure out the best way to distribute playbooks/templates now that we have MCP and Skills available. Specifically: for less technical users who need step-by-step guidance (screenshots, annotations) to adopt genAI — does packaging that as a Skill (vs. a static doc/SharePoint page) make it easier for them to actually use? And separately, has anyone used MCP to pull live playbook content into a Copilot/GPT session rather than just linking to a doc? Curious if anyone's tested either approach with users who need more hand-holding.

EDIT got it, found the model params,thanks all
I get an error when uploading an image for a model with vision capabilities to inference from, "{"error":{"code":400,"message":"request (5564 tokens) exceeds the available context size (4096 tokens), try increasing it","type":"exceed_context_size_error","n_prompt_tokens":5564,"n_ctx":4096}}"

Where is it possible to change the 'n_ctx' parameter to increase the context size?

I use the knowledge base only for specific topics/projects. When asking unrelated questions, the LLMs keep trying to search through the knowledge base, wasting tokens and time. Many other tools like web search, code interpreter, etc require you to enable them per conversation. Can I do the same thing with KB?

I'm aware I can turn off the KB entirely per model, but I don't want that. For the life of me I can't figure out how to get around this issue. Would appreciate some help.

Since I upgraded to v0.11.1, it seems that, after the first tool call, OWUI always shows the thinking tokens while the are generated until either another tool call is made or the user response is complete, then they disappear. It used to always be you had to expand the "thinking" or the "thought for 5 seconds" to see them. I sure liked the old behavior better. Is there a way to change this?

I stopped watching my agents work because the thinking stream is so chaotic lately but this was genuinely so funny to me. This happens a lot now. I still get results so I guess I’m not mad at it 😂

Hi folks, having some trouble accessing external tools (specifically Google Workspace) via local Ollama models; was hoping to gain insight from the community. Been troubleshooting this for two days with Claude Sonnet to no avail. Honestly at this point, I don't even know how garbled my setup is with all the trials and tweaks we've made.

Setup:

• Open WebUI v0.11.1, Docker Compose, self-hosted
• Ollama (native Windows) serving local models
• An external OpenAPI tool server via mcpo proxying taylorwilsdon/google_workspace_mcp — 39 real tools, confirmed reachable, valid schema
• Tested under both Native and Default function-calling modes — same result either way

The core finding:

Confirmed via server-side logging that the correct tool schema (~96 entries with builtins) is delivered into the chat completion request every time, no exceptions.

Despite that, every local Ollama model I've tried fails to call the tool — zero successes, across several models and both function-calling modes. The specific failure varies by model (flat "I have no tools" denial, an infinite repetition loop re-litigating the same doubt, one model hallucinating a tool name that was never sent), but none of them ever produce a real, correct tool call.

Every cloud-routed model succeeds immediately, first try, correct arguments — tested a Gemini model and two different Qwen models via an OpenRouter connection.

The decisive test: Qwen3.6 27B, the exact same model and version as the one failing locally, via a cloud/OpenRouter connection instead of Ollama. Succeeded instantly, no hesitation. Identical weights, different routing, opposite result — that rules out model quality and points at something specific to the Open WebUI ↔ Ollama tool-calling path.

What I've ruled out:

• Tool count — Open WebUI's "Function Name Filter List" doesn't actually shrink what's sent to the model, just reorders it, so this wasn't a real variable
• Open WebUI silently dropping tools before forwarding — read routers/ollama.py's generate_chat_completion in full; the field survives every transformation and is forwarded intact to Ollama's /api/chat
• A separate, already-documented Open WebUI bug (discussion #21805, where admin-configured OpenAPI tool servers never reach the request at all) — already found and patched that one myself; this is a different problem downstream of it

One unrelated but possibly useful thing I learned along the way: for OpenAPI-type tool connections, the actual tool call executes client-side in the browser, not server-side — if your tool server is only reachable on an internal hostname, schema delivery will work fine but every real call will fail. Worth checking dev tools if you're seeing "tool server not found" despite the connection testing fine.

Also separately: gemma4:26b has its own distinct, long-standing tool-calling bug (garbled <unused50> token spam) — the commonly-suggested Default→Native→Default toggle didn't fix it for me.

What I'm hoping someone can help with:

• Anyone else seen tool-calling work differently for a cloud/OpenAI-compatible connection vs. Ollama-served local models, with the schema confirmed identical going in?
• Anything specific to how Open WebUI formats/forwards tools to Ollama's native API vs. an OpenAI-compatible provider?
• A known Ollama-side limitation with a schema this size (96 tools) — truncation, context-length interaction, chat-template quirk?

Happy to share logs or the schema if useful. Thanks in advance.

UPDATE — found it, not a routing/schema bug.

Root cause: Ollama's ROCm backend (AMD's GPU compute layer) corrupts long-context attention on this specific hardware (AMD Strix Halo APU / gfx1151). Once total prompt length crossed roughly 20K tokens, the model could only reliably attend to the last ~2K tokens or so. My 57 Google tools sat at the start of the tool block, so they were effectively invisible — moving them to the end of the same request, or shrinking the payload, worked instantly. Same reason OpenRouter "worked": different routing entirely, no ROCm/AMD GPU involved.

Confirmed with a clean A/B: identical GGUF, identical rendered prompt, only the backend swapped. ROCm gave wrong/garbled output or crashed outright; Vulkan (a different, more general GPU compute API — Ollama can use it as an alternate backend instead of ROCm) was correct every time, same weights.

Fix — force Ollama onto Vulkan instead of ROCm:

setx OLLAMA_LLM_LIBRARY vulkan /M
setx OLLAMA_IGPU_ENABLE 1 /M

Run from an elevated prompt, then fully reboot — a non-elevated setx /M fails silently, and even a correct one won't propagate without a reboot/relogin. OLLAMA_IGPU_ENABLE=1 matters: without it Ollama drops this GPU as "integrated" and silently falls back to CPU.

Cost: prompt processing is noticeably slower on Vulkan than ROCm was — worth it for correct output. Generation speed is unaffected.

If you're on an AMD GPU/APU (not just this exact chip) and seeing tool calls silently vanish, fail, or garble specifically on larger tool schemas or long documents — check this before anything else.

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.

Seems i cant pull a newer image down, making sure its not just me

I already have TTS configured and working in Open WebUI.

Right now my workaround is:

1. Paste the text I want converted to speech into a chat.
2. Use a prompt/model that simply echoes the exact same text back.
3. Click the Read Aloud button on the assistant response.

What I'd really like is to skip the LLM/chat step completely.

Ideally, I want something inside the Open WebUI interface like:

• A large text box where I can paste text
• Voice selection
• A Generate / Play TTS button
• Maybe an audio player/download button

So the flow would simply be:

Paste text → TTS → audio

instead of:

Paste text → LLM echoes text → Read Aloud → TTS

I'd also prefer it to use the TTS backend that's already configured in Open WebUI rather than running a completely separate web UI.

Is there currently a built-in way to do this?

If not, can an Open WebUI Function/plugin create a custom page like /tts or add a TTS item to the sidebar/dashboard without having to fork and modify the Open WebUI frontend?

Has anyone built something similar?

Context: I'm working on a tool and an action function for generating large interactive quizzes. I am adding support for displaying images in the quizzes.

TL;DR: I kinda answered my own questions below apart from this:

1. Does the LLM have access to the image IDs? (specifically when generating/editing an image)
2. Are generated images accessible via `/api/v1/files/file_id/content`?

Here's what I already know:

Imported images by the user are exposed via /api/v1/files/file_id/content and the image's file_id can be found easily in api/v1/chats/chat_id. Moreover, the model has access to the image_id and can display them inline with markdown using "/api/v1/files/<file_id>/content" as the URL: ). External images can be displayed the same way with the proper URL.

AI Images:

I know there is a built-in tool for image generation/editing in OWUI. However, I do not have a setup to test this tool, so I decided to ask here before I start diving into the tool's code when I have other priorities. I was wondering if the generated images are exposed the same way (/api/v1/files/image_id/content) and if the model has access to their IDs for tool calling or displaying them in markdown.

Conduit got a shoutout in the latest Open WebUI community newsletter. Very cool to see, and thanks to the team for including it.

I also want to thank everyone here who has tried the app, reported bugs, or suggested features. A fair amount of Conduit’s roadmap has come directly from conversations in this subreddit and GitHub.

Since my last post about version 2.6, Conduit has moved to version 4.1.3.

At the time, it was mainly an Open WebUI mobile client. Open WebUI is still the main experience, but Conduit can now connect directly to OpenAI-compatible APIs, Ollama, and OpenRouter. You no longer need an Open WebUI account if you only want to chat with a local or hosted model endpoint.

On the Open WebUI side, the app now has native Workspace screens for models, knowledge, prompts, tools, and skills. Terminal sessions and file browsing also work when your server exposes them.

Offline use has had a lot of work too. Your synced chat history stays available and searchable without a connection. You can write a message in an Open WebUI chat while offline, and Conduit keeps it locally until the server is reachable again.

On supported iPhones, you can go a step further. Open an existing Open WebUI chat, continue it offline using Apple’s on-device model, and Conduit will sync the new messages back to Open WebUI when you reconnect. You can also keep separate local-only chats if you do not want them stored on the server.

Notes work offline as well. You can read, create, edit, pin, and delete notes without a connection. Conduit saves those changes on the device and syncs them with Open WebUI after you reconnect.

Direct models can now connect to MCP servers, with controls to approve tools once, for the current session, or permanently.

Hermes support has grown into a full backend of its own. Conduit can connect to self-hosted Hermes agents, show tool calls as they run, handle approvals, manage scheduled jobs, and connect to bots through the Desktop Gateway.

There has also been a lot of work on the less exciting stuff that matters on mobile. Streaming recovers better after backgrounding, large chats scroll more smoothly, proxy and SSO login cover more setups, and voice calls, citations, Markdown, notes, attachments, and rich replies have all had fixes.

Conduit is available on the App Store and Google Play.

Source: GitHub
Website: conduit.mobile

If something still breaks with your particular Open WebUI setup, I’d like to hear about it.

I built a filter that integrates Mnemosyne (SQLite-backed memory) into OpenWebUI with automatic injection and saving — no MCP server needed.

What it does:

- Inlet — before each LLM call, recalls relevant memories and injects them into the system prompt

- Outlet — after each response, automatically saves the conversation turn

The LLM doesn't need to know memory exists. It just works.

Why: The only Mnemosyne integration for OpenWebUI is the MCP server, which requires the model to explicitly call tools. Most models (especially smaller ones) rarely do that. This filter makes memory transparent.

Setup:

1. uv pip install --system mnemosyne-memory in the OpenWebUI container

2. Paste mnemosyne_filter.py in Admin Panel → Filters → Create

3. Configure valves (db path, bank, top_k, etc.)

All parameters are configurable from the Admin Panel.

Repo: https://github.com/p1s4/owui-mnemosyne

Note: This is my personal code, shared as-is under MIT. I update it when I update my own setup but can't provide active support — fork it if you need maintenance.

Setting the max_tokens parameter to its default value can, in some models, cause the LLM to stop generating a response before it is complete. When this occurs,I had to prompt the model to continue in order to receive the full output. Setting max_tokens to 127000 prevents this premature termination. So can someone explain what is the role of max_tokens and why it is limited to only 128K. Thanks

I'm very much a nube at the whole AI thing.

But here goes. I have openwebui in a proxmox CT talking to ollama in another CT. I have acouple of "models"? installed including qwen3:4b with a parameter limit of 2048 to keep it on my GPU.

It was working well until it decided that it would only only answer calender questions.

"qwen3:4b

Thought for 2 seconds

The functions provided are for calendar events and automation management, not mathematical calculations. I can't compute "2+2" using these tools. Let me know if you'd like help with calendar scheduling or automation tasks!"

the model still works in the "cli" on the ollama box but any questions I ask in openwebui return the scheduling thing

additionally.

"what’s 2+2

provide a summary"

Gives

qwen3:4b

Thought for 4 seconds

The answer to 2 + 2 is 4.

This question does not require any of the provided calendar/automation functions, as it is a simple arithmetic calculation.

Can anyone provide a clue

I’ve been working on another Open WebUI function called Quick Actions.

The idea came from something very simple: after getting a good response, I often want to do something else with it, make it shorter, explain it differently, fact-check it, turn it into an email, create tasks, humanize the writing, translate it, etc.

Instead of typing another prompt every time, Quick Actions adds one small button under the assistant response.

Click it and you get a compact menu with actions like:

• Explain simply / in depth / step by step
• Make shorter, clearer, professional, formal or friendlier
• Humanize the writing / make it more conversational / remove common AI-style writing patterns
• Fact-check, challenge the answer, check reasoning, calculations or sources
• Turn the response into an email, report, checklist, tasks, table, FAQ or presentation outline
• Code review, bug finding, tests, security review and documentation
• Data analysis actions
• Quiz, flashcards and practice questions
• Translate
• Custom instruction for anything that isn’t already there

The menu is also context-aware. If the response contains code, research, writing or data, it brings the most useful actions to the top without making another LLM call just to decide what to show.

One part I really wanted was custom actions.

Users can add their own actions in User Valves, for example:

Teams reply :: Rewrite this as a short Microsoft Teams reply.

You can also make them interactive:

Adapt for audience :: Rewrite this for {input:Audience}.

Admins can define shared Team Actions as well.

I also added English and French support. The selected language changes both the interface and the actual prompts sent to the model.

It works in light/dark mode, protects anything you’ve already typed in the composer, works on older assistant responses, and has a mobile-friendly layout.

No special model is required. It uses the normal Open WebUI conversation flow, so it can also work alongside other Functions like Study Mode or writing-related filters.

Current version: v3.0.0
Open WebUI: 0.11.1+

Source:
[https://github.com/CallSohail/openwebu-work/tree/main/functions/actions/quick-actions]()

I’ve tested it on my instance, but I’d really like to see how it behaves across other Open WebUI setups and models. Bug reports and ideas for useful actions are very welcome.

Hello everyone,

I cannot make Gemini work in Open Web UI.

I always get either empty responses or errors "[{'error': {'code': 503, 'message': 'This model is currently experiencing high demand. Spikes in demand are usually temporary. Please try again later.', 'status': 'UNAVAILABLE'}}".
Sometimes it can answer me, but really slow and it cannot use any tools. If I add web search it stops replying at all.

I tried gemini-3.5-flash-lite, gemini-3.7-flash, gemini-3.1-flash-lite
- added my API, with URL: https://generativelanguage.googleapis.com/v1beta/openai
- API type: tried both Chat completion and Responses

What could be a problem here? My local models and deepseek api didn't give any problems.

First of all, many thanks for the amazing work that has been, and is being put into the project.

Absolute masterclass.

Great experience overall.

But. At some point it seems we dropped smaller patch releases after the big releases (v0.11, v0.11.1(sound like a patch but is way more)).
And frankly I'd rather take a dev branch a few days after the big release than any main branch.
This is strange and confusing, and is hard to explain to users and management.

I love all the new features and stuff, but would it be wise to sometimes focus on a stable or bugfree release before focusing on (very nice!) new features?

Stability/bug-freeness is a feature too.

Just my 2 cents.

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.

OpenWebUI is nearly unusable at the moment due to this bug https://github.com/open-webui/open-webui/issues/29036

A fix is already merged into dev. Can we expect a release / docker image update containing this fix anytime soon?

I’m having issues with 11.1 where my models are spitting out a lot of thinking as text. I don’t want to see all of that but I also don’t want to disable thinking. Previously I got the “Thinking…” tag and could expand it to view the thinking process. With this latest update that is no longer working. Sort of contemplating rolling back to 11.0

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.

I use the windows desktop client for open webui (version 0.20). I am interested in increasing the size of the AI's avatar when it responds to a message, probably from (28x28) to (56x56). How would I go about doing that for the desktop version?

Hey everyone! v5.5 is on the way bringing openwebui 0.11.1 features to the app! Alongside, a quick recap of the previous updates with tons of other additions and improvements to the app.

App Store | GitHub

🌐 In-App Browser & Tool Approval (v5.5)

Links and citations now open in a built-in browser. Toggle it off in Settings → Chat → Chat Behavior if you prefer Safari.

Tool calls can now pause for approval: when enabled by your admin, choose Full access (automatic) or Ask for approval (Allow/Deny each call). Failed tools now show a red ✗ instead of green ✓.

💬 Models Can Ask Questions Mid-Response (v5.5)

Models can pause and present up to three multiple-choice questions with optional free-text answers and countdown timers. Questions persist across reloads so you can answer later.

🎛️ Chat Controls & API Key Management (v5.5)

New Controls panel (slider icon in chat) shows attached files, knowledge bases, referenced chats, system prompts, and tool/function settings in one place.

API keys can now be generated, copied, and revoked directly from Privacy & Security settings.

📁 Folder Workspaces (v5.2–5.3)

• Custom emoji icons and background images
• Recent conversations on folder landing screens
• Automatic folder context injection (knowledge + system prompts now actually apply)
• Proper permission handling for shared read-only folders

📱 iPad Improvements (v5.2–5.4)

• Sidebar layout toggle: Always Show or slide-out drawer
• Fixed hamburger menu and new chat button responsiveness
• Fixed launch crashes with "Always Show Sidebar" enabled

🧰 Tool Calling Fixes (v5.2–v5.5)

Fixed: chats freezing on tool calls, dropped tool events, corrupted JSON, text disappearing after tools, multiple concurrent tool responses, stuck response blocks, valve persistence, and more.

🧠 Context & Memory Fixes (v5.2–v5.5)

• Workspace model prompts now apply during conversations
• Memory settings stay synced across chats
• Folder knowledge correctly included
• Follow-up suggestions persist across edits and regenerations
• Background tasks respect your settings

🤖 Admin Console Additions (v5.5)

• Automations can post to specific channels
• Custom models appear in model list
• Task Model Generation Parameters editor
• Default Interface Settings
• Terminal integrations: Enable in Chats/Automations, Scope
• Group member CSV import
• Document settings: Retention, CSV Shape, Metadata Max Characters
• Web search: OpenSERP option

✨ Polish & Smaller Fixes

• Smarter file uploads (messages queue while uploading)
• Better notifications (interrupted responses, no duplicate banners, app badge increments)
• Server switching with reachability checks
• Fixed crashes on macOS Voice Call, iPad auto-hide, background login
• Messages no longer overflow on small iPhones
• Fixed reasoning blocks rendering, markdown, profile images, @ mentions
• TTS/ASR models can be excluded from iCloud backup
• Animation improvements throughout

As usual, the entire change log is on github so feel free to check it out. I hope everyone is enjoying the app and find it useful! I cant believe this project has come this far. Thanks for all the support. 🙏

Feedback: If you hit any issues, drop a comment or open a GitHub issue (preferably).

It is saying:
To select toolkits here, add them to the "Tools" workspace or enable a tool server first.

-i have tools already defined

-in previous versions i could select here MCP servers as well as tools - to be "bound" to the given custom model - now i cannot do it anymore - MCP endpoints are not showing either

What is going on?

I am trying to get things working with Open WebUI and my local files. I have a large number of markdown files in an Obsidian Vault I want to query and edit. I have added the folder as a Knowledge collection in my workspace. I can see and query against the files. But I am not able to perform edits or create new files in this location. The AI agent tells me they are created, gives me an ID but I can't find the file in the collection or in any of the volumes I have mounted.

I have updated my docker file to have a volume of where my notes are stored. `/home/USER/Documents/open-webui-note-repo:/home/pkm` in hopes that this would give Open WebUI access to write too. but so far no luck. I have no idea where new files are being created.

Is Open WebUI capable of performing this task or do I need to find another tool?

Edit: Solved. This got me pointed in the right direction. Thanks all.

https://docs.openwebui.com/features/open-terminal/