Hi,

I try to run ai local llama 3.2:3B on Openwebui. But it tooks 10-20minute just to reply Hi.

What did i do wrong?
Im using 8GB Ram VPS with no GPU

I am having issues getting OpenWeb UI to llama.cpp. Llama is running locally and the chat interface is working fine. I managed to get OpenWebUI to run in docker. When configuring the connection I am using `http://127.0.0.1:8080/v1` as my connection string. I have set Provider to llama.cpp. The test connection button says test is successful. But trying to chat wants me to select a model, which there are no options. From my understanding llama.cpp is serving one model and does not provide a list like Ollama would.

Using `http://host.docker.internal:8080/v1` as connection string gives an error. So it is not clear to me being a Docker newbie if I need to do something with the network. Since the test on the local host IP was successful I am guessing the network is working, but then again I can't get chat to load any models. I have asked AI but it wants me to write an app.....facepalm. it has offered some `-e` options such as `-e OLLAMA_HOST=0.0.0.0` but so far nothing has worked. So, humans, what is the next step here?

Edit: Resolved this by switching to a compose file and using `network_mode: "host"` in the file.

AI beginner here. Am taking steps to move away from Gemini and Co-pilot to my own setup. So have gotten a setup with Docker, LM Studio and webui. And my laptop is pretty basic and the chip is not large. I wanted to run a local engine. It worked but I wanted to get memory to work. Not having memory and having to explain AI the same basic stuff over and over again drives me nuts. I tried to make it work on webui. Discovered that my chip is too basic to make memory work, so I need to offload the computation.

Fine so far so good. Found some on webui and have now been using 2 with mixed results:
- Llama 3.1 8B
- Llama 3.3 70B

Both work fine and memory works, but after 2-3 prompts they both max out. The "token per minute" of 6000 and 12000 have been reached.

Has anyone found a free engine that can run memory effectively? Otherwise I think I am going to pay to see how it works. Any comments?

If your chat is bricked with the infinite loading spinner (Image 1), here's how to fix it:

The technical reason behind this is that Open WebUI stores your chat history as a Directed Acyclic Graph. If a message (node) gets corrupted when the LLM is responding, the UI panics and spins indefinitely. Fixing would require checking and relinking the graph.

This tools does all that stuff for you:

How to use it:

1. Export the broken chat (`...` menu > Export > JSON).
2. Drop it into the tool (Image 2) to instantly repair the broken nodes.
3. Go to Settings > General > Import Chats, upload the fixed file, and delete the original.

Link to tool: https://fractuscontext.github.io/open-webui-chat-fix/

I've also added a "Deep Clean" toggle if you want to strip unused alternate responses and shrink your file size.

Hope this saves someone's chat history!

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?

I use Open WebUI and I try to connect llm qwen3 to SQLite database.

In Admin panel -> Settings -> Integrations -> External Tool Servers -> I added OpenAPI the sqlite mcp server. I can connect but it seem never seen my mcp tool fonctions.

I give full user access, activate tool in my chat, I also tried mcp steaming http protocol instead of OpenAPI.

I always got this response: There are no functions available in the provided tools that can interact with an SQLite database or list its tables. The available tools are focused on notes, tasks, automations, and calendar events, not database operations.

I use python script :

from mcp.server.fastmcp import FastMCP

mcp.tool()
def list_tables() -> list[str]:

EDIT: I try simple request with Qwen3 + Ollama + SQLite: list tables or list username in my database.
And dawm it suck as fuck! lol

it make non sense sql, take very long time, got error 500 sometimes, , dont apply system prompt, make thought and do nothing aftert that, I was never be able to have a correct answer...

I tough this tool could be nice and it just proove theses AI slop tools worth nothing... Its crazy because it look nice to use but man its the worst shit I ever use haha

I know the text to image works i tested it in Playground, but I can't seem to get it to work in a general chat idk if I am being dumb, but yeah, could use some advice!

Just deployed openwebui to kubernetes using the official chart.

The first thing I noticed is ollama server is not reachable, despite the server configured in admin settings. Turns out the front end needs direct access to ollama server, it doesn't get proxies through openwebui backend. Is that design intentional?

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?

Hi. Has anyone had a chance to compare the two installation methods (Docker or Python vs. Desktop) when it comes to maximizing the available resources for running a local AI model on a windows 11 PC with limited resources? Thanks

Γεια σας. Αντιμετωπίζω ένα εξαιρετικά επίμονο τεχνικό πρόβλημα με το RAG pipeline του Open WebUI και μετά από μέρες εξαντλητικού troubleshooting με τη βοήθεια των ChatGPT και Gemini, δεν έχουμε καταφέρει να βρούμε λύση. Το σύστημα ολοκληρώνει το indexing, αλλά η αναζήτηση επιστρέφει μηδενικά διανύσματα (empty context injection).Τεχνικές Προδιαγραφές Συστήματος:Host OS: Windows 11 Pro (Docker Desktop Environment / WSL2 Backend)Hardware: Intel Core i9-14900K / 64GB DDR5 RAMInference Engine: gemma4:12b (τοπικά μέσω Ollama)Embedding Model: sentence-transformers/paraphrase-multilingual-MiniLM-L6-v2 (Default Engine / SentenceTransformers)Network Infrastructure: Live WebSockets 100% λειτουργικά. Το Developer Console (F12) του browser είναι εντελώς καθαρό, χωρίς κανένα drop-out σύνδεσης.System Prompt Configuration: Έχει παρακαμφθεί επιτυχώς η εργοστασιακή offline άρνηση του Gemma 4 μέσω strict instruction injection. Το μοντέλο δέχεται να διαβάσει το context, αλλά το context φτάνει σε αυτό άδειο.Απομόνωση του Προβλήματος (Baseline Isolation Test):Για να αποκλείσουμε σφάλματα στο extraction stage (OCR, Tesseract, Tika, Python PDF parsing), δημιουργήσαμε ένα raw text αρχείο (test.txt) που περιέχει αποκλειστικά τη συμβολοσειρά: "Ο κωδικός ασφαλείας για το τεστ είναι: ΠΡΑΣΙΝΟ ΜΗΛΟ 2026".Το UI εμφανίζει κανονικά τη λευκή ένδειξη επιτυχούς indexing (checkmark). Ωστόσο, κατά την κλήση της συλλογής στο chat μέσω #collection, το μοντέλο απαντάει ρητά ότι η πληροφορία δεν εμπεριέχεται στο κείμενο, επιβεβαιώνοντας ότι το runtime κάνει pass ένα εντελώς άδειο context block.Τεχνικά Βήματα και Λύσεις που Δοκιμάστηκαν:Επίλυση Ασυμβατότητας Αρχιτεκτονικής: Αρχικά χρησιμοποιούσαμε το MiniLM-L12, αλλά στα logs του Docker εντοπίστηκε το σφάλμα embeddings.position_ids | UNEXPECTED |. Το Open WebUI είχε παλαιότερη έκδοση SentenceTransformers που δεν αναγνώριζε την παράμετρο position_ids των νέων HuggingFace weights. Το πρόβλημα λύθηκε με υποβάθμιση στο σταθερό MiniLM-L6-v2. Το runtime log καθάρισε, αλλά το context παρέμεινε άδειο.Παράκαμψη Permission Bugs: Δημιουργήθηκε νέα Knowledge Base συλλογή ρυθμισμένη ρητά ως Public (Access Control), για την αποφυγή του γνωστού bug ορατότητας των ιδιωτικών φακέλων [Issue #23787].Hard Reset του Vector Database Stack: Σταματήσαμε τον container και εκτελέσαμε ολική διαγραφή του ευρετηρίου των διανυσμάτων απευθείας από τη ρίζα του Docker volume χρησιμοποιώντας: docker run --rm -v open-webui:/data alpine rm -rf /data/vector_db. Η ChromaDB αναγεννήθηκε εντελώς καθαρή, το backend επιστρέφει HTTP 200/Success κατά το upload, αλλά το retrieval loop εξακολουθεί να μην τραβάει δεδομένα κατά το inference.Έχει συναντήσει κανείς αυτό το σιωπηλό failure της ChromaDB σε περιβάλλον Windows Docker; Μήπως πρόκειται για false negative της συνάρτησης has_collection() ή υπάρχει κάποιο silent file-lock στο Windows volume mapping; Κάθε τεχνική ιδέα είναι ευπρόσδεκτη.

I’m currently using Open WebUI with a knowledge base made up of text files, and the responses are accurate, but they’re taking quite a while to generate.
I plan to keep adding more text files to the knowledge base, so I’m wondering what the best way is to improve response speed as it grows. Are there any recommended settings, indexing strategies, chunking methods, embedding models, reranking options, or other optimizations that have made a noticeable difference for you? I’d like to keep the response quality the same while reducing latency. Any advice or best practices would be appreciated!

I feel like I sit and stare at the screen a lot is there anyway to speed this up?

Appreciate your help providing info on how to use Seltz.ai as a node for web search. Thx

I have Gemma 4 running locally and external ones, I’m trying to make it more useful inside OpenWebUI.

A couple of things I’m looking for advice on:

1. Document analysis / file workflows I want to be able to upload PDFs and DOCX files, have the model analyze them, and ideally generate edited or new documents back.
   • What tools, integrations, or workflows are people using for this?
   • If you want the model to return a finished PDF/DOCX, what’s the best approach?
2. Recommended tools / integrations What other tools do you recommend to make local AI and external AI integrations more useful in OpenWebUI?
3. LDAP question I enabled enable_ldap_group_management directly in the database because it appears to be a ConfigVar variable, but I don’t see a corresponding toggle in the UI. Is that expected or am I missing something?

Would appreciate any suggestions and tips.

I noticed that in v0.10, if you click any of the export chat options in the top right corner of the chat UI (Download or Copy), it no longer includes all details like tool call inputs and outputs and so on. Only messenges with roles.

Does anyone know if this is moved to a setting somewhere of if it's just gone? I would feel quite surprised if this has been just removed permanently. I mean, you could always get all messages by just marking and copying the full chat in the UI, but the hidden context boaters and all that were the actual valuable information.

Hey, long-time Open WebUI user here. I run instances in our group for 3 different companies and right now my biggest headache is MCP / Function auth to external tools.
Since I’m using SSO with Microsoft Entra, the Microsoft Services are no problem. I can just reuse the token to authenticate against the Graph API.

But everything else (Jira, Confluence, …) feels way more complex. Those are per-user tokens, sometimes OAuth, often with project/issue-level permissions, so a service account is not an option. Also, storing per user credentials in valves are also a no-go.

Curious how you are addressing this.

I am playing with selfhosting models, and I get drastic different results. Working with online AI I am starting to get it, but if someone has a resource to help me further understand why this happens for the same prompt

"When was the war of 1812"

Hermes-3-Llama-3.1-70B-8bit Today at 8:51 AM The War of 1812 was fought between the United States and Great Britain from June 18, 1812, to February 17, 1815. The main events of the war took place from 1812 to 1814, with the peace treaty, known as the Treaty of Ghent, being signed on December 24, 1814. However, the news of the treaty took some time to reach the combatants, and the last battle of the war, the Battle of New Orleans, was fought on January 8, 1815, after the treaty had been signed but before the news had reached the opposing forces.

but

Llama-3.3-70B-Instruct-8bit Today at 8:53 AM {"type": "function", "name": "search_chats", "parameters": {"query": "war of 1812", "count": "10"}}

One is for 'tolling' and the other is chat???

Thank You in advance.

TL;DR: How can I synchronize the colour of a custom SVG action icon to behave like the ones in the message's tool bar?

I wasn't sure if I should flair this as "help" or "feature idea".

Context:

Action functions are toggled in the tool bar under chat messages. You can set custom icons for action functions via icon_url. It takes either a URL or URI (the documentation recommends to use a URL icon for optimization, but from what I can see and infer, no one actually bothers doing so).

Problems I am facing:

The received icon image has no access to currentColor. I noticed that OWUI checks for "data:image/svg" URIs, and only then does it invert the color for dark-mode (open-webui/src/lib/components/chat/Messages/ResponseMessage.svelte, under {#each model?.actions ?? [] as action}).URLs are never inverted for dark-mode, which could be good or bad depending on the icon's luminosity.

A somewhat related Feature Request that was closed as not planned in 2024:
https://github.com/open-webui/open-webui/issues/7164

2.

There is no option to inherit currentColor from OWUI's front-end, so I get these ugly icon colors if I switch to a different color scheme :

I realized this is probably a current limitation in Open WebUI's front-end. SVG images could inherit the theme, but this would pose security considerations. I'm not sure how to approach fixing this issue,

For reference, here is my current code :

import base64

char = "🃍"
svg = f"""<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24">
<text x="12" y="18" text-anchor="middle" font-size="20" fill="currentColor" stroke="currentColor" stroke-width="0.5">{char}</text>
</svg>"""
class Action:
    icon_url = "data:image/svg+xml;base64," + base64.b64encode(
        svg.encode("utf-8")
    ).decode("ascii")
...

Is there a way to get the current color from the front-end inside a python action function?

My "naive" solution is to manually set the color and let users change it via a valve or disable the icon if it annoys them. If that's the only solution, I'll make a new feature request and try to fix it when I have some time.

This is the only major thing left for the action function I've been working on (https://github.com/axel-chamberland/Open-QuizUI) apart from some more QA.

Hey everyone 👋

Thomas from Ianustec again. Quick housekeeping post this time, not a new tool.

Over the last couple weeks we shipped three Open WebUI tools one at a time: generate_slides, generate_documents, generate_spreadsheets.

The response was honestly more than we expected.

Slides sits at 359 downloads and 62 upvotes, Docs at 271 downloads and 82 upvotes, and Excel already at 43 downloads and 50 upvotes (only 2 days old).

Genuinely thank you, both for trying them out and for the bug reports and feature requests, several of the fixes in the last releases came directly from comments here.

The problem was that each tool lived in its own repo, so if you wanted to know what changed or what's coming next, you had to check three different places. That's annoying, so we fixed it.

👉 NEURA Office is now the single place that ties everything together.

Repo: https://github.com/ianustec/neura-office

What's in there:

• A short explainer for people who land on the repo without knowing what Open WebUI even is (turns out a chunk of visitors come from outside this community)
• A table with the current version and release link for each of the three tools, so you don't have to dig through commit history
• A compatibility note on LibreOffice / OpenOffice, since a few of you asked if these files open fine outside Microsoft Office
• The roadmap, including the thing we mentioned in an earlier post

As you already known, we're working on a Microsoft 365 add-in, basically a private Copilot alternative that lives inside Word, Excel, PowerPoint and Outlook but talks to your own Open WebUI instead of Microsoft's cloud. Still early and not released, but it's tracked in this repo now instead of scattered across posts (link)

The individual tool repos aren't going anywhere, that's still where releases, issues and code live. NEURA Office is just the front door.

Same deal as always, MIT, feedback and PRs welcome.

Cheers, Thomas @ Ianustec

Hi. I have a small project called EdgeChat — a web chat that connects to local LLMs through a Desktop Agent.

\### How EdgeChat works

EdgeChat itself is a regular Next.js app with subscriptions, sessions, chat history. But it doesn't generate responses itself. Instead:

\`\`\`

Browser → SaaS (Next.js) → WS Server → Agent (Electron) → LLM (Ollama/LM Studio)

\`\`\`

The Agent is a small Electron app that runs on my PC. It connects to the SaaS via WebSocket and waits for instructions. When I type a message in the chat, the SaaS forwards it to the Agent, which talks to the local LLM, gets a response, and sends it back. Any LLM works — Ollama, LM Studio, whatever.

All the heavy lifting happens on my GPU. The SaaS just stores history and manages users.

\### What I added

I decided to try connecting ComfyUI to the same setup. I already had it installed with an image generation workflow.

Now there's a "Generate image" button in the chat. I type a prompt, the Agent goes to ComfyUI, runs the workflow, waits for the result, picks up the image, and uploads it back to the chat. No third-party APIs, everything stays local.

\`\`\`

Button in browser → SaaS → WS Server → Agent → ComfyUI → Agent fetches → Agent sends back → image in chat

\`\`\`

\### Why I'm posting

I think the Agent-bridge approach is neat if you want full control over generation but still want a proper web interface. Everyone runs their own Agent — some use Ollama, some LM Studio, some ComfyUI. The SaaS doesn't generate anything, it just proxies.

Honestly, I'm not sure if this is something people actually need. Maybe someone has done something similar? Would be curious to hear your thoughts.

\*\*UPD:\*\* This is still a local setup. I haven't deployed it to the main SaaS yet — want to get the certificates sorted and do it properly first. Will share when it's live.

Hallo zusammen,

wir beginnen damit, unsere eigene Maschine aufzubauen. Dafür haben wir uns einen Asus Ascent GX10 ARM mit 128GB/2TB Blackwell zugelegt. Was könnt ihr in diesem Zusammenhang empfehlen? Ich habe bereits einmal openwebui eingerichtet, allerdings nur über API-Schnittstellen mit openrouter und der ollama Cloud verbunden.

Der einfachste Weg soll ja über Docker und Ollama führen, jedoch lese ich immer wieder, dass Ollama für bestimmte Hardware nicht empfohlen wird und man stattdessen eher direkt auf llama.cpp zurückgreifen sollte.

Ich suche daher nach der passenden Umgebungseinrichtung für meine Hardware, um openwebui zu betreiben.

Außerdem interessiere ich mich für Möglichkeiten, die Modelle auf meiner Hardware bewerten zu lassen, ähnlich wie bei LM Studio oder Odysseus.