Writing a Simple Ollama and OpenWebUI Guide for Local AI

PUBLIC ARCHIVE EDITION

Provenance

Provider: ChatGPT
Original title: Installing Local AI Simply
Conversation ID: 6a817107-88a4-83e8-ac76-20abbb3ec22d
Created: 2026-08-16T01:13:01-07:00
Updated: 2026-08-19T12:00:51-07:00
Models: gpt-5-6-thinking
Source archive SHA-256: 0f7aee663dace8d779cc4e6f229b4e22a8386f8075b81801a3c8c2b112e1bdd7
Source transcript SHA-256: a78bce37739af6c8d2284362a79be5ea29826af798cfe11aa5854b2c877f4dfb
Active-path treatment: active-current-node
Alternate messages preserved: 0
Attachment state: not-applicable
Privacy state: PRIVACY_VERIFIED
Publication state: public-archive
Record ID: chatgpt:6a817107-88a4-83e8-ac76-20abbb3ec22d
Source member: conversations-002.json
Source record SHA-256: 6dec6dfddc2cee12bd4c6ebbe9183cde9c13edcf1f1aa5a1f2608337edea6d11
Transcript verification status: canonical-verified; privacy-verified; source-order-preserved
Editorial changes: privacy-approved local edits preserved; approved editorial title applied
Publication/version history: public archive edition v1

Conversation

Darren — 2026-08-16T01:13:00-07:00

Well, let’s see. A small task for the website. From our previous conversations, what I want to do is what Taz asked for. In other words, how to build an OLLM in the most simple and easiest way for both Linux and Windows. If you want to access the latest installation information and then turn it into kindergarten speak with step-by-step for a human, number one. And then number two, is there a prompt that you could develop that would tell an AI all in one block exactly what we’re doing and the steps needed to take it and so forth.

ChatGPT — 2026-08-16T01:13:01-07:00 · gpt-5-6-thinking

I’ll turn this into two pieces you can drop onto the site: first, a “human-proof” install path for Windows and Linux; second, one AI prompt that can walk someone through the whole job interactively. I’m also going to keep it to the smallest working setup—no Docker, databases, or Ougway-style extras unless they’re actually needed.

ChatGPT — 2026-08-16T01:13:12-07:00 · gpt-5-6-thinking

The current Ollama setup is simpler than it was when we first talked about this. Windows now has a normal installer and desktop app, while Linux is still essentially one terminal command; Ollama’s own quick-start then lets you run a model directly without adding a web interface first.

For the “first model,” I’d make the website default Qwen 3.5 4B rather than throwing beginners into a giant model. Ollama currently offers a 4B Qwen 3.5 build around 3.4 GB, with smaller and larger versions available if the machine struggles or has more capacity.

ChatGPT — 2026-08-16T01:13:32-07:00 · gpt-5-6-thinking

Yes. And one distinction will make the page much easier for newcomers: we are not teaching them to build an LLM from scratch. We are teaching them to put a local LLM on their own computer. Ollama is the engine; the downloaded model is the AI.

The current official installation path really can be reduced to Ollama + one model. Windows 10 or later has a normal installer, Linux has the one-line official installer, and a public local model does not require signing into an Ollama account. [Citation reference unavailable in the original export.]

Here is how I would write the human-facing page.

:::writing{variant=”document” id=”47321″ title=”Put an AI on Your Own Computer — The Easy Way”}

Put an AI on Your Own Computer — The Easy Way

You do not need to be a programmer.

You do not need Docker.

You do not need Python.

You do not need to build an AI yourself.

We are going to do two things:

Install a small program called Ollama.
Give Ollama an AI model to run.

That’s it.

Think of it this way:

Ollama = the engine

The AI model = the brain

Once both are on your computer, you can talk to the AI locally.

For this example we will use:

Qwen 3.5 4B

It is small enough to be a reasonable first model while still being a useful general-purpose AI. The current Ollama version is about 3.4 GB for the common 4B build. [Citation reference unavailable in the original export.]

Windows

Step 1 — Install Ollama

Open your web browser and go to the official Ollama Download page.

Choose Windows and download the installer.

The file will be called something similar to:

OllamaSetup.exe

Double-click it.

Install Ollama just as you would install any other Windows program.

Ollama currently supports Windows 10 and newer, and its normal installer does not require Administrator privileges. [Citation reference unavailable in the original export.]

Step 2 — Open PowerShell

Click the Windows Start button.

Type:

PowerShell

Open Windows PowerShell.

You will see a window with text and a blinking cursor.

Don’t panic.

That blinking cursor is simply the computer waiting for you to tell it something.

Step 3 — Download and start your AI

Copy this line:

ollama run qwen3.5:4b

Paste it into PowerShell.

Press Enter.

The first time you do this, Ollama has to download the AI model.

Let it finish.

After the download, the model will start and you will be able to type to it.

Ollama’s official command for starting a model is ollama run MODELNAME. [Citation reference unavailable in the original export.]

Step 4 — Say hello

Try typing:

Hello. Tell me who you are in two sentences.

Press Enter.

If the AI answers you:

Congratulations. You now have an AI running on your own computer.

Step 5 — Leave the AI

When you are finished, type:

/bye

and press Enter. [Citation reference unavailable in the original export.]

Linux

The Linux version is actually even shorter.

Step 1 — Open Terminal

Open your Terminal program.

On many Linux desktops you can do this with:

Ctrl + Alt + T

You will see some text and a blinking cursor.

Again, the cursor is just waiting for instructions.

Step 2 — Install Ollama

Copy this entire line:

curl -fsSL https://ollama.com/install.sh | sh

Paste it into the Terminal.

Press Enter.

This is the current official Ollama Linux installation command. [Citation reference unavailable in the original export.]

Let it finish.

Step 3 — Download and start your AI

Now type:

ollama run qwen3.5:4b

Press Enter.

The first time you run it, Ollama will download the model.

After that, the AI will start.

Step 4 — Talk to it

Try:

Hello. Tell me who you are in two sentences.

If it answers:

You did it.

There is now a local large language model running on your Linux computer.

Step 5 — Leave

Type:

/bye

and press Enter.

What Just Happened?

You installed a program called Ollama.

Then you downloaded an AI model called Qwen 3.5 4B.

Ollama knows how to load that model and let your computer talk to it.

You did not create an account.

You did not rent a server.

You did not build a database.

You did not install a giant collection of development tools.

You simply installed the engine and downloaded a brain.

Ollama distinguishes between local models, which run on your hardware, and optional cloud models, which run through Ollama’s cloud service. Cloud models require an Ollama account; ordinary public local use does not. [Citation reference unavailable in the original export.]

If Your Computer Is Older or Slow

The 4b in:

qwen3.5:4b

refers roughly to the size of the model.

If the 4B model is too much for your computer, try a smaller one:

ollama run qwen3.5:2b

There is even a smaller 0.8B version.

If you have a stronger computer, larger models are available too. Ollama currently provides Qwen 3.5 in sizes ranging from 0.8B upward. [Citation reference unavailable in the original export.]

Small model = easier for the computer, but generally less capable.

Large model = more capable, but requires more memory and computing power.

Start small.

You can always download another model later.

If Linux Says It Cannot Reach Ollama

Normally the installer takes care of starting Ollama.

If it does not, open a Terminal and run:

ollama serve

Leave that Terminal open.

Open a second Terminal and try:

ollama run qwen3.5:4b

Ollama’s Linux documentation provides ollama serve as the command for starting the Ollama server manually. [Citation reference unavailable in the original export.]

That’s Really It

At this point you have the simplest useful local-AI system:

Your computer

↓

Ollama

↓

A local AI model

↓

You

Everything else—pretty web interfaces, memory systems, document libraries, web search, agents, tools and automation—can be added later.

But none of those things are required to begin.

Get the AI talking first.

Then decide what you want it to become.
:::

There is one thing I particularly like about that version: it deliberately stops there. No OpenWebUI, no RAG, no embeddings, no CUDA lesson, no database. The beginner gets the psychological payoff of “Holy crap, the thing answered me” before we introduce another moving part. Ollama can expose a local API automatically at localhost:11434 later, so this tiny installation is already a foundation we can build on rather than a throwaway beginner setup. [Citation reference unavailable in the original export.]

And yes—the second part can be stronger than a static tutorial. We can give somebody one prompt, paste it into ChatGPT, Claude, Gemini, etc., and essentially say: “You are now my local-AI installation technician. Figure out what machine I’m sitting at and walk me through this without burying me.”

:::writing{variant=”document” id=”68145″ title=”AI Prompt — Help Me Install a Local LLM”}

Help Me Install a Local AI on My Computer

I want you to help me install and run a local Large Language Model (LLM) on this computer using Ollama.

The goal is the simplest possible working installation.

We are NOT trying to build an LLM from source.

We are NOT trying to install a complicated AI development environment.

We are NOT installing Docker, Python, OpenWebUI, databases, RAG systems, agents, memory systems, web-search tools, CUDA toolkits, or other optional components unless they become genuinely necessary to make the basic local AI work.

The immediate goal is simply:

Computer → Ollama → local AI model → working conversation

Act as my installation technician and teacher.

How I want you to work

Assume I may know very little about computers.

Use plain English.

Do not dump twenty commands on me at once.

Give me one small step at a time.

For every command:

Tell me exactly where to type it.
Show me the exact command in a code block.
Briefly explain what the command does.
Tell me what I should expect to see.
Let me report the result before moving to the next step.

If something goes wrong, diagnose the result I give you instead of restarting the entire procedure.

Do not make me reinstall something that is already working.

Do not make assumptions about my hardware when we can check it.

Do not change unrelated system settings.

Do not use sudo, Administrator privileges, destructive commands, disk formatting, deletion commands, firewall changes, BIOS changes, or driver replacements unless they are genuinely necessary. Explain why before using anything potentially consequential.

Step 1 — Identify my computer

First determine whether I am using:

Windows
Linux
or something else.

Then determine, as simply as possible:

operating-system version
CPU
amount of RAM
whether I have an NVIDIA, AMD, Intel, or no dedicated GPU
available disk space

If you need me to run commands to discover this information, give me the commands one at a time.

Do not require me to already know my hardware specifications.

Step 2 — Check current Ollama information

If you have Internet/web access, check the current official Ollama documentation before giving installation commands.

Prefer information from:

ollama.com
docs.ollama.com

Do not blindly reuse an old installation command if the official procedure has changed.

If you do not have web access, tell me that clearly and use the most reliable procedure you know.

Step 3 — Install Ollama

Use the easiest official installation method for my operating system.

For Windows, prefer the normal official Ollama Windows installer unless there is a reason not to.

For Linux, prefer Ollama’s current official installation method.

Do not introduce Docker merely to run Ollama.

After installation, verify that Ollama actually works before continuing.

A useful verification command may be:

ollama --version

but use the current appropriate method if that has changed.

Step 4 — Choose an appropriate LOCAL model

I want a model that runs on this computer, not a cloud-hosted model.

Do not choose a model with :cloud in its name.

Base the model choice on the hardware we discovered.

For an ordinary beginner machine, consider a relatively small model first rather than downloading a huge model.

At the time this prompt was written, Qwen 3.5 4B was a useful starting choice:

qwen3.5:4b

If my computer is too limited for that, choose a smaller local model such as a 2B-class or smaller model.

If my computer is substantially more powerful, you may suggest a larger model, but explain why.

If you have web access, verify that your recommended model and tag currently exist in the official Ollama model library before telling me to download them.

Tell me approximately how large the download will be before we begin it whenever that information is available.

Step 5 — Download and run the model

Once Ollama is working and we have chosen the model, help me run it.

For example, if Qwen 3.5 4B is appropriate, the command may be:

ollama run qwen3.5:4b

Explain that the first run may download the model and therefore take longer.

Do not mistake downloading time for a failed installation.

Step 6 — Prove that it works

Once the model starts, have me give it a very simple test such as:

Hello. Tell me who you are in two sentences.

If it answers normally, consider the basic local-AI installation successful.

Then show me how to exit the conversation.

Step 7 — Verify that it is actually local

Confirm that we selected a local model rather than an Ollama cloud model.

If useful, help me run:

ollama ps

and explain the result in plain English.

If the model is partly using the CPU instead of the GPU, that is not automatically an installation failure. Explain what is happening before recommending changes.

Step 8 — Stop

Once I have a working local conversation, STOP adding software.

Do not automatically install:

OpenWebUI
Python
Docker
databases
vector databases
embedding models
agents
memory systems
web search
development frameworks

Instead, tell me:

“Your basic local AI is working.”

Then briefly explain that those other features can be added later if I want them.

Most Important Rule

Our goal is not to build the fanciest AI system possible.

Our goal is to get the smallest, simplest, correctly working local AI running on this computer first.

Start by identifying what operating system and hardware I have.
:::

That second one is essentially Taz’s escape hatch: instead of us trying to document every possible NVIDIA driver, Windows oddity, Linux distribution, old laptop, insufficient RAM condition, and future change to Ollama, the page can say:

“Don’t want to follow the manual instructions? Copy this entire prompt into the AI you already use and let it walk you through the installation.”

And because the prompt explicitly tells that AI to check the current official Ollama documentation, the prompt should age substantially better than a frozen 2026 command list. [Citation reference unavailable in the original export.]

I think those are actually the two layers the AnyKey Cafe page needs: “Do it yourself in five minutes” followed by “Or give this to your AI and make it help you.” That keeps the entry point almost absurdly simple while leaving Little Ougway, OpenWebUI, memory, RAG and all the fun machinery for a completely separate “Okay, now what can I do with it?” page. [Memory reference belonged to the original ChatGPT session.]

Darren — 2026-08-16T01:17:51-07:00

A couple changes. One, what I’m really looking to do is include both pieces, so OpenWebUI on top of that. The other thing is for the computer side, I’m thinking more of recommending that if they already have ChatGPT or a Claude account, that they install Claude Desktop. And then all they merely have to do is sit there and OK permissions.

ChatGPT — 2026-08-16T01:17:52-07:00 · gpt-5-6-thinking

Yes — that changes the shape of the page quite a bit, and I think for the better.

The target becomes “build a complete local AI workstation”: Ollama underneath, OpenWebUI as the friendly interface, and an existing cloud AI—ideally Claude Desktop—as the installer/helper so the human mostly copies nothing and approves what the AI proposes. I’m checking the current capabilities because the important question is exactly how much Claude Desktop can actually do on Windows/Linux today versus merely telling the user what to type.

ChatGPT — 2026-08-16T01:18:11-07:00 · gpt-5-6-thinking

There’s one important wrinkle I found, and it actually gives us a cleaner page rather than breaking the idea.

Windows: your “sit there and approve permissions” idea is now very close to literal. Claude Desktop’s Cowork can directly operate desktop apps and asks permission as it encounters them. Linux: Claude Desktop now exists officially, but Anthropic says its computer-control feature is not yet available in the Linux beta. So on Linux we should not promise the same hands-off experience; Claude can still guide the installation, but direct clicking/typing needs a different route.

ChatGPT — 2026-08-16T01:18:31-07:00 · gpt-5-6-thinking

Yes. That makes the actual goal much clearer. We aren’t merely getting a model to answer in a terminal; we’re giving a nontechnical person something that looks and behaves like the AI they’re already accustomed to using:

AI helper → Ollama → local model → Open WebUI

And there’s a nice development since we last worked on this: Open WebUI now has a native desktop application for Windows and Linux, explicitly intended to avoid Docker and manual setup. The Open WebUI documentation describes the desktop version as running natively without Docker or manual installation. [Citation reference unavailable in the original export.]

So I would change our beginner installation philosophy to this:

Let an AI install your AI.

The human shouldn’t need to understand package managers, services, ports, Python environments, Docker containers, or model tags before they’ve even seen the thing work.

The path I’d use

1. Start with an AI you already know.

If the person already uses Claude, install Claude Desktop and sign in. Claude Desktop is now officially available for Windows and Linux. [Citation reference unavailable in the original export.]

If they’re a ChatGPT user but don’t have Claude, they can still use ChatGPT to walk them through the procedure; a ChatGPT account doesn’t sign them into Claude Desktop.

There is one qualification I would put right on the page: Claude Cowork requires a paid Claude plan. [Citation reference unavailable in the original export.]

2. Give the AI our installer prompt.

Instead of:

“Tell me how to install Ollama.”

we give it the complete mission:

Examine this computer, determine the OS and hardware, install Ollama, choose an appropriate local model, install Open WebUI, connect Open WebUI to Ollama, test the model, and stop when I have a working local AI. Explain anything that requires my permission before doing it.

3. Install Ollama.

Still the backend—the engine that actually runs the model.

4. Install a model appropriate to that particular computer.

The AI checks RAM/GPU first rather than us telling everybody to install the same model.

5. Install Open WebUI Desktop.

This is a big simplification. Open WebUI Desktop is cross-platform on Windows and Linux and is designed as a one-click desktop setup. [Citation reference unavailable in the original export.]

6. Connect Open WebUI to Ollama and test it.

At that point:

Computer → Ollama → local model → Open WebUI

Now the beginner has something resembling ChatGPT or Claude rather than a terminal prompt.

The Claude idea needs one OS-specific footnote.

On Windows, your concept is remarkably close to exactly what Anthropic now supports. Claude’s computer-use feature can interact directly with applications, clicking and typing, and it asks for permission when accessing applications. [Citation reference unavailable in the original export.] So our instructions can basically be:

Install Claude Desktop → select Cowork → paste our prompt → review the plan → approve actions as Claude works.

That’s wonderfully close to “sit there and hit OK.”

On Linux, however, Anthropic currently says computer use isn’t available in the Claude Desktop Linux beta. [Citation reference unavailable in the original export.]

But there’s an excellent alternative: Claude Code. It works directly in the terminal and its default permission model asks before commands that touch the machine. Anthropic specifically describes it as asking permission for shell commands and edits. [Citation reference unavailable in the original export.]

So our two paths can actually read:

Windows

Claude Desktop/Cowork does the installation; you approve its actions.

Linux

Claude Code does the installation in the terminal; you approve its commands.

That preserves your original concept almost perfectly on both platforms. The human does not need to understand the commands. They merely need to read what the AI says it’s about to do and approve it.

And I think the prompt should now be changed substantially from my first version. Rather than telling the AI how to instruct the human, we tell it to do as much of the work itself as its environment permits:

:::writing{variant=”document” id=”58217″ title=”Install My Local AI — Master Installation Prompt”}

Install a Complete Local AI on This Computer

I want you to help me create a complete, easy-to-use local AI system on this computer.

The finished system should consist of:

Ollama → local AI model → Open WebUI

I am not trying to develop an AI from scratch. I want an existing open model running locally on my own computer with Open WebUI providing a friendly ChatGPT-like interface.

Your Role

Act as my installation technician.

Do as much of the installation yourself as your permissions and tools allow.

If you can execute commands or operate applications directly, do so.

When an action requires my permission, stop and ask me to approve it.

If you cannot perform an action yourself, give me the smallest possible instruction necessary to perform it.

Do not make me manually perform something that you are capable of doing yourself.

Before Installing Anything

First inspect this computer and determine:

Operating system and version
CPU
Installed RAM
GPU manufacturer and model, if present
GPU memory, if available
Available disk space
Existing Ollama installation, if any
Existing Open WebUI installation, if any
Existing AI models, if any

Do not ask me for information that you can determine yourself.

Check Current Instructions

If you have Internet access, verify the current official installation instructions before installing software.

Prefer primary sources:

ollama.com
docs.ollama.com
docs.openwebui.com
the official Open WebUI GitHub repositories

Installation procedures change over time, so do not blindly follow old commands contained in this prompt if the official procedure has changed.

Install Ollama

Install the current official version of Ollama using the simplest appropriate method for this operating system.

Do not install Docker merely to run Ollama.

Verify that Ollama is actually running before continuing.

Choose a Local Model

Examine the hardware and choose a useful general-purpose LOCAL model that runs comfortably on this machine.

Do not choose an Ollama cloud model.

Prefer a smaller model that runs well over a larger model that barely runs.

Explain your model choice to me in one or two sentences.

Tell me approximately how much disk space the model requires before downloading it.

Then install the model.

Test Ollama

Run the model directly through Ollama once.

Give it a simple test prompt.

Confirm that it responds correctly before proceeding.

If GPU acceleration is available, determine whether Ollama is using it.

Do not treat CPU execution as an installation failure if the computer does not have a supported GPU.

Install Open WebUI

Install the current official Open WebUI Desktop application if it is appropriate and supported on this operating system.

Prefer the native desktop application over Docker or a manual Python installation for this beginner setup.

Only use Docker, Python, or another installation method if the current official Open WebUI documentation shows that the desktop application is unsuitable for this computer.

Connect Open WebUI to Ollama

Configure Open WebUI to use the local Ollama installation.

Confirm that the model installed earlier appears inside Open WebUI.

Open a new conversation in Open WebUI and test the model.

Verify That It Is Local

Confirm that:

The model is stored on this computer.
Ollama is running the model locally.
Open WebUI is communicating with the local Ollama service.
The selected model is not an Ollama cloud model.

If practical, perform a final test with Internet access disabled or explain how I can perform that test later.

Do Not Add Extra Complexity

For this installation, do NOT add:

Docker unless genuinely required
Kubernetes
databases
vector databases
RAG
MCP servers
agents
memory systems
web search
development frameworks
programming environments

Those can be added later.

The goal right now is simply:

My computer
↓
Ollama
↓
A useful local AI model
↓
Open WebUI
↓
A working conversation

Safety and Permissions

Do not disable security protections simply to make installation easier.

Do not use commands that delete unrelated files.

Do not reformat drives or partitions.

Do not change BIOS/UEFI settings unless absolutely necessary, and explain why first.

Before performing an unusual or potentially destructive action, explain what you intend to do and ask for permission.

Normal software installation, package installation, service startup, directory creation, and configuration necessary for Ollama and Open WebUI are part of the approved task.

Definition of Success

The job is complete when I can open Open WebUI, select my locally installed model, type:

Hello. Are you running locally on my computer?

and receive a normal response.

When that works, tell me:

“Your local AI is installed and working.”

Then stop.

Do not add more software unless I ask you to.

Begin by examining this computer.
:::

That is much closer to what I think Taz was asking for.

And there’s a lovely inversion here compared with the original tutorial: the long step-by-step instructions become the fallback, not the primary installation method.

The website could lead with something almost ridiculously simple:

Already have an AI? Let it build your local one.

Install Claude Desktop/Claude Code, paste the block below, approve the requested actions, and let it build Ollama + a local model + Open WebUI for you.

Then immediately underneath:

Prefer to do it yourself?

Windows instructions
Linux instructions

That ordering feels much more in keeping with what you’re trying to accomplish: make local AI accessible to someone who isn’t interested in becoming a Linux administrator first. [Memory reference belonged to the original ChatGPT session.]

Darren — 2026-08-16T01:24:27-07:00

Yes, and I see you covered like 90 million bases in the local AI helper script. My goodness, that’s amazing. And now while I’m complimenting you, I forgot what I was gonna ask. Um, let me look through it again. There is local, complexity… I think it requires a little bit of explanation in between the llama install and the OpenWebUI install for the humans that says, okay, so now what you’ve got is, basically, you need to run this in this terminal, and now you can ask it questions. Here’s your AI. But it’s not as pretty as you hoped for, is it? So to give it the interface you expected, this is what you do. Now, you’re gonna have to, of course, translate the hell out of the Darren in that. But I think you know what I mean. The other thing is, one of the things I ran into was that the tools function call was overtaking the general knowledge calls on certain prompts I was putting in. And we had figured out a way how to fix that, and for the most part, it did, from what I’ve tried. I haven’t tried it again today to triple-check it. But it looks like it’s answering normally now. So if you can recall that, I guess from a previous conversation as to what we did. I know it was a settings change, and we set something to native. What the hell was it? I can’t remember, but you’ll probably pick it out in the conversation. I think we should include that too.

ChatGPT — 2026-08-16T01:24:28-07:00 · gpt-5-6-thinking

Yes — I know exactly the transition you mean. I’m going to pull the earlier OpenWebUI troubleshooting detail so I don’t reconstruct it from memory, and I’ll also verify what that setting is called in the current OpenWebUI docs before we bake it into the beginner page.

ChatGPT — 2026-08-16T01:24:41-07:00 · gpt-5-6-thinking

I found it. In the version you were using, the setting was Model Parameters → Function Calling → Native. You were seeing Default there; changing it to Native and then starting a fresh chat was the thing we tried. The current Open WebUI documentation still uses that exact Function Calling = Native setting, although the menus have moved around in newer builds.

There’s also a useful lesson from what happened to you: for a beginner installation, I think we should prove ordinary conversation works before enabling a bunch of tools. Then tools get added afterward, one at a time. That prevents “my AI has turned into a calendar/tool robot” from being somebody’s first experience.

ChatGPT — 2026-08-16T01:24:41-07:00 · gpt-5-6-thinking

Exactly. And I think your wording contains the right teaching moment: don’t rush from Ollama into Open WebUI without showing the human what they just accomplished.

They should actually meet their AI in the terminal first. That gives them the conceptual separation:

This is the AI.
Then: Open WebUI is just the nice room we’re going to put it in.

I’d insert something like this between the Ollama test and the Open WebUI installation:

:::writing{variant=”document” id=”39542″ title=”Website Section — Your AI Is Already Working”}

Stop for a Moment — You Already Have an AI

Before we install anything else, notice what just happened.

You typed something into the Terminal, and the computer answered you.

That is your local AI.

Ollama is running the model directly on your computer, and you can actually keep using it exactly like this if you want.

Try asking it something:

Why is the sky blue?

Or:

Write me a short story about a robot who discovers coffee.

It will answer right there in the Terminal.

So technically, we’re finished.

You have a working local AI.

It’s just…

Well…

It’s not exactly pretty, is it?

That black Terminal window probably isn’t what you pictured when somebody said, “You can have your own ChatGPT-like AI.”

That’s where Open WebUI comes in.

Open WebUI does not replace the AI you just installed.

Think of it as putting a friendly face on top of it.

Right now you have:

You → Terminal → Ollama → AI model

We’re going to turn that into:

You → Open WebUI → Ollama → AI model

Same AI.

Same model.

Same computer.

Just a much nicer place to talk to it.

Now let’s install the interface you were probably expecting in the first place.
:::

That solves something important pedagogically: Open WebUI stops looking like another mysterious piece required to make AI work. The human knows Ollama already works, and Open WebUI is an interface layer.

And yes, I recovered the setting from our earlier troubleshooting. In your Open WebUI version, the path we used was:

Settings → General → Model Parameters → Function Calling → Native

You had been seeing Default. We explicitly selected Native, saved it, and then started a new conversation. There was also some weirdness because Open WebUI has overlapping global, model, user/chat settings, so at one point one page appeared to save it while another still showed Default.

The current Open WebUI documentation still has Function Calling = Native, but newer versions expose it at several levels: globally/model-specific under the model settings, or for an individual chat under Chat Controls → Advanced Params. Native is now documented as the normal/default tool-calling mode. [Citation reference unavailable in the original export.]

One subtle point is worth explaining on the website: Native does not mean “turn tools off.” It means the model itself gets to decide when a tool is appropriate instead of having the older tool-handling mechanism steer the interaction. Open WebUI describes native function calling as letting the model autonomously decide when to invoke tools. [Citation reference unavailable in the original export.]

So I would make this a little troubleshooting/setup box:

:::writing{variant=”document” id=”72416″ title=”Website Section — One Open WebUI Setting Worth Checking”}

One Setting Worth Checking

Once Open WebUI is working, have a normal conversation with your AI before turning on every available tool.

Ask it ordinary questions.

For example:

Why do leaves change color?

Explain gravity to a ten-year-old.

Give me three ideas for dinner.

The AI should simply answer you.

If Your AI Starts Acting Like a Tool Instead of an AI

Open WebUI can give models extra abilities called tools.

Tools can let an AI search the web, work with files, call outside services, perform calculations, and do other useful things.

They’re great.

But occasionally a model—especially a smaller local model—can become a little too enthusiastic about them.

Instead of answering an ordinary question, it may start trying to call a tool for everything.

If that happens, check:

Function Calling → Native

Depending on your version of Open WebUI, this may be under the model’s Model Parameters / Advanced Parameters, or inside the current chat under Chat Controls → Advanced Params.

Set:

Function Calling: Native

Save the setting.

Then start a new conversation and test a normal question again.

Don’t Turn Everything On at Once

For your first setup, keep things simple.

First make sure:

Open WebUI → Ollama → your model

works normally.

Then add tools one at a time.

Turn on one feature.

Try it.

Make sure ordinary conversation still works.

Then add the next one.

If something suddenly behaves strangely, you will know which change caused it.

That’s much easier than turning on twelve new abilities and then trying to figure out which one confused the AI.
:::

And I would also put that logic into our monster installer prompt, because that’s exactly where it belongs. The assisting AI should not merely install Open WebUI and declare victory. It should test the finished system for the failure you actually encountered.

This could replace the current Open WebUI testing portion:

:::writing{variant=”document” id=”84631″ title=”Master Installer Prompt — Open WebUI Verification Addition”}

Explain the Transition to Me

After Ollama and the local model are working, stop briefly before installing Open WebUI.

Explain to me that the AI is already functional.

Tell me that I can continue talking to it directly through the Terminal and that Open WebUI is not the AI itself—it is a friendlier interface placed on top of Ollama.

Let me ask the model at least one ordinary question directly through Ollama and confirm that it responds normally.

Only then continue with Open WebUI.

Install and Test Open WebUI

Install the current appropriate Open WebUI version and connect it to the local Ollama service.

Confirm that the model we installed appears in Open WebUI.

Start a new conversation and test several ordinary general-knowledge prompts that should not require tools.

For example:

Why is the sky blue?

or:

Explain photosynthesis simply.

The model should answer normally.

Check Function Calling

Locate the Open WebUI Function Calling model parameter.

Prefer:

Function Calling: Native

If the current Open WebUI documentation has changed the location or terminology of this setting, follow the current official documentation.

Be aware that Open WebUI may have:

Global model settings
Individual model settings
Per-chat settings

A more specific setting may override a global setting.

If you change Function Calling, start a fresh conversation before testing again.

Prevent Tool Takeover

Do not enable every available Open WebUI tool during the initial installation.

First establish that ordinary conversation works correctly without unnecessary tools.

If the model attempts to invoke tools for simple general-knowledge questions, diagnose the tool/function-calling configuration before continuing.

Do not assume that the local model itself is defective.

After normal conversation is confirmed, optional tools can be enabled one at a time and tested individually.

Final Verification

The basic installation is successful only when all three layers have been demonstrated separately:

Ollama runs the local model directly.
The model answers an ordinary question directly through Ollama.
Open WebUI connects to that same model and ordinary conversation works normally.

Only after those tests succeed should optional tools or additional features be introduced.
:::

That last addition is especially valuable because we’re now building the tutorial around failure isolation without ever using that phrase with the beginner.

First:

Does Ollama work? Yes.

Then:

Does the model work? Yes.

Then:

Does Open WebUI work? Yes.

Then:

Let’s turn on a tool. Still work? Yes.

That means if something goes sideways, even somebody with very little computer experience can say, “It worked until I did this.” And their AI helper has an enormously smaller problem to diagnose.

Which, amusingly enough, is basically the scientific method sneaking into a kindergarten-level AI installation tutorial. ^_^ [Memory reference belonged to the original ChatGPT session.]