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LLM | ollama Part 2. Running in a local browser

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- ollama Part 1. Running locally in the terminal : Linux (wsl 2), MacOS 
? ollama Part 2. Running in a local browser: open-webui
- ollama Part 3. Running it in a browser online (with my own domain) :
- ollama Part 4. Applying RAG (Retrieval Augmented Generation)
- ollama Part 5. Applying image recognition 
- (Coming soon) ollama Part 6. Applying MOE (mixture of experts) approach

 

 

 

ollama local browser 

1. Running with a Docker image (Mac terminal environment, almost identical to Windows cmd)

1) Sign up for Docker, then log in 

2) Install Docker for your computer's OS 

 

Install Docker Engine

Learn how to choose the best method for you to install Docker Engine. This client-server application is available on Linux, Mac, Windows, and as a static binary.

docs.docker.com

3) Search for [Terminal] and run it

Searching for Terminal

  docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v ollama-webui:/app/backend/data --name ollama-webui --restart always ghcr.io/ollama-webui/ollama-webui:main  

When you enter the command above and press enter, you'll see the result below 

Result of building/running the image via Docker

4) Open a browser and access the Web UI 

 http://localhost:3000 

The ollama WebUI accessed via the browser

5) Sign up. (Local-only — no email verification)

Ollama signup

6) (After login) main screen

Ollama main screen

      Click (1) to select one of the models you've installed. 

      Click (2) to manage your own documents and prompts.

 

#Reference 1. Result of building the image with Docker

Click NAME to view console log, installed files, status, etc., and click the Port(s) item on the right to access the WebUI in the browser.
Code dev tab. For reference, you can use the pause/play button at the top right to manage the virtual server.
You can check the list of images created with Docker, the configuration status, and so on
The image layers that have been created
Check the list of installed volumes > click the blue link to view the database usage records
ollama.db detail

#Reference 2. Docker — ollama official page 

 

Docker

 

hub.docker.com

 

 

 

 

ollama local browser

2. Running by configuring FE/BE directly 

1) Search for [Terminal] and run it

Searching for Terminal


 2) Pull the basic code for building the WebUI from GitHub onto your computer (*Install in the folder you want. Remember the location, ha)
 git clone https://github.com/ollama-webui/ollama-webui.git 

3) Move into the installed folder 
 cd ollama-webui/ 

4) Copy the configuration file (*For reference, regardless of whether you do simple ollama hands-on practice or not ;; I strongly recommend learning about '.gitignore' and '.env' in advance — it's about your personal information.)
 cp -RPp example.env .env 

5) FE — front-end setup — The code pulled from GitHub above is the baseline. Install the libraries each piece of code depends on at the latest version, or at a version suitable for your hardware (* This is the section where unexplained errors happen — particularly the "why is it not working only for me?" or "why is mine different?" moments. If you encounter an error, googling is recommended)
 npm i     

6) Build to deploy the locally installed code 
 npm run build   

7) Move into the backend folder
  cd ./backend  

8) BE — back-end setup — The code pulled from GitHub above is the baseline. Install the libraries each piece of code depends on at the latest version, or at a version suitable for your hardware (* This is the section where unexplained errors happen — particularly the "why is it not working only for me?" or "why is mine different?" moments. If you encounter an error, googling is recommended)
 pip install -r requirements.txt -U  

9) Start the WebUI 
 sh start.sh 

Result of running directly from terminal

10) Access the WebUI (same as Docker)  

Result of accessing ollama at http://0.0.0.0:8080

 

 

 

 

 

 

 

 

Docker VS direct FE/BE setup

3. Difference between Docker and front-end/back-end direct setup 

About. Docker

Pros. A single line of code in the terminal and you're up and running. The frequency of errors during environment setup is very low. For mere experience or personal use, this is a very useful approach.  
Cons. When the container is removed, the data created inside it is also removed. Of course, you can spin up multiple containers and manage them with Kubernetes, but the complexity of continuous data management inevitably increases.

 

About. Front-end/back-end direct setup

Pros. When you run the code above, in some cases it might run in one go… but for most people, different errors will have appeared depending on the OS or the version. In this same way, beyond your personal computer, within an enterprise you can optimize on the infrastructure side or on the design-concept side. It is also a necessary process when adding granular features such as RAG.  
Cons. The example above was, in truth, a copy-paste of execution code for hands-on practice. In real-world work, hand-crafting? the detailed contents of that code can feel daunting if it's outside your domain or if you're a beginner.

This English version was translated by Claude.

친절한 찰쓰씨
Written by
친절한 찰쓰씨

Pleasant Charles — UI/UX researcher at AIT. Keeping notes on design, planning, and slow days here since 2010.

More on the author's page

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