How to Self Host LLMs with ORIV

With the growing popularity of large language models (LLMs), developers and businesses are increasingly looking for ways to host these powerful AI tools on their own servers. Self-hosting an LLM provides greater control over data privacy, customization, and performance, without relying on third-party platforms. Learn how to self host LLMS and deploy OpenWebUI and Ollama with ORIV or your own cloud servers.

Step 1: Create a Docker+ NGINX Server

First, you need to create a server to deploy any LLMs. Click on the ‘Add New Server’ button from the dashboard and enter all the credentials required to connect your server. You can deploy Ollama on your own server or on an ORIV server.

Next, enter a**‘Server Name’** and choose an ‘App Type’ from the dropdown menu. You will see all available application types here, including ‘OpenWebUI’ and ‘Ollama,’ which will provide the user with the necessary configuration settings.

Then choose a ‘Server Size’ and ‘Region’ of the server according to your preferences.

Then choose your preferred ‘Ubuntu Version’ of this server and enter the ‘Tags’ for this server.

Next, you can see the ‘Docker + NGINX’ stack is already selected, which is mandatory for deploying the LLM application.

Once the server is created, you will be able to deploy your OLLAMA Application to this server.

How to Install Ollama on a Cloud Server

Learn how to install Ollama on a cloud server. It walks you through creating a server, configuring the environment, and launching your Ollama application easily.

Step 2: Access the One Click Apps Dashboard

Begin by logging into your ORIV account. Once logged in, navigate to your dashboard and click on the ‘New Site’ button. Then choose your server and click on the ‘Next’ button to proceed.

This will take you to the site creation interface. From here, select your Server, then navigate to the One-Click Apps section. You will see two options: OpenWebUI and Ollama. Choose Ollama to proceed with the deployment of this application.

Step 3: Set Up the Ollama Application

In the site setup screen, you will be prompted to enter basic site information. Provide a ‘Site Title’ and add relevant ‘Tags’ to help organize your deployment.

At this point, you can choose between two deployment modes: ‘Go Live’ for a production-ready deployment or ‘Demo Site’ for testing purposes. Selecting ‘Go Live’ will immediately create a live environment, while choosing ‘Demo Site’ allows you to experiment in a staging environment before promoting it to production.

Step 4: Configure Domain Settings

If you select the ‘Demo Site’ option, ORIV will assign a temporary subdomain for your Ollama application. You can adjust the ‘Site User’ according to your preferences, or leave it as the default.

Step 4: Visit the Ollama Application

With Ollama set up with ORIV, you should be able to log in and confirm that it’s working. From the dashboard, click on the ‘Visit Site’ app.

Environment Editor for Ollama

The Environment section in ORIV allows you to customize configuration settings for your Ollama instance. Just go to the ‘Environment’ option from the sidebar and adjust as you need, then click on the ‘Save’ button.

Manage Ollama Models

Later, you can manage your Ollama application. Go to the ‘Ollama’ → ‘Management’. Next, click on the**‘Add New Model’** to install more AI models. Also, you can click on the ‘Delete Icon’ to delete the AI models of this application.

How to Install OpenWebUI on a Cloud Server

Learn how to set up OpenWebUI on a cloud server and get it running quickly. It covers server setup, application configuration, and accessing your deployed site, making it easy to get started regardless of your technical background.

Step 1: Access the One Click Apps Dashboard

Begin by logging into your ORIV account. Once logged in, navigate to your dashboard and click on the ‘New Site’ button. Then choose your server and click on the ‘Next’ button to proceed.

This will take you to the Site Creation Interface. From here, choose your Server, then go to the One-Click Apps section. You will see two options ‘OpenWebUI’ and ‘Ollama’. Choose ‘OpenWebUI’ to begin deploying the application.

Step 2: Set Up the OpenWebUI Application

In the site setup screen, you will be asked to enter basic site information. Provide a ‘Site Title’ and add relevant ‘Tags’ for your application.

At this point, you can choose between two deployment modes: ‘Go Live’ for a production-ready deployment or ‘Demo Site’ for testing purposes. Selecting ‘Go Live’ will immediately create a live environment, while choosing ‘Demo Site’ allows you to experiment in a staging environment before promoting to production.

Step 3: Configure Domain Settings

If you select the ‘Demo Site’ option, ORIV will assign a temporary subdomain for your OpenWebUI application. Adjust the Site User according to your preferences, or leave it as the default.

Step 4: Install Ollama Application

If you want to install Ollama, toggle on the installation option and choose a model from the dropdown menu. Then, click ‘Next’ to proceed with the installation.

Step 5: Visit the OpenWebUI Application

Once OpenWebUI is set up on ORIV, you can log in to confirm that it’s working. From the dashboard, click on ‘Visit Site’.

Environment Editor for OpenWebUI

The Environment section in ORIV allows you to customize configuration settings for your OpenWebUI instance. Just go to the ‘Environment’ option from the sidebar and adjust as you need, then click on the ‘Save’ button.

Manage AI Models

Later, you can manage your OpenWebUI application. Go to the ‘OpenWebUI’ → ‘Management’. Next, click on the ‘Add New Model’ to install more AI models. Also, you can click on the ‘Delete Icon’ to delete the AI models of this application.

Self-hosting LLMs with ORIV empowers developers and businesses to take full control of their AI deployments, ensuring data privacy, customization, and optimized performance. By following the instructions for setting up Docker + NGINX servers, deploying Ollama, and configuring OpenWebUI, you can quickly get your AI models up and running on a cloud environment tailored to your needs. With ORIV’s One Click Apps, Environment Editor, and model management tools, maintaining and scaling your LLM deployments becomes straightforward and efficient Still stuck? Contact our support teamfor any of your queries.

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How to Self Host LLMs with ORIV

Step 1: Create a Docker+ NGINX Server

How to Install Ollama on a Cloud Server

Step 2: Access the One Click Apps Dashboard

Step 3: Set Up the Ollama Application

Step 4: Configure Domain Settings

Step 4: Visit the Ollama Application

Environment Editor for Ollama

Manage Ollama Models

How to Install OpenWebUI on a Cloud Server

Step 1: Access the One Click Apps Dashboard

Step 2: Set Up the OpenWebUI Application

Step 3: Configure Domain Settings

Step 4: Install Ollama Application

Step 5: Visit the OpenWebUI Application

Environment Editor for OpenWebUI

Manage AI Models

​Step 1: Create a Docker+ NGINX Server

​How to Install Ollama on a Cloud Server

​Step 2: Access the One Click Apps Dashboard

​Step 3: Set Up the Ollama Application

​Step 4: Configure Domain Settings

​Step 4: Visit the Ollama Application

​Environment Editor for Ollama

​Manage Ollama Models

​How to Install OpenWebUI on a Cloud Server

​Step 1: Access the One Click Apps Dashboard

​Step 2: Set Up the OpenWebUI Application

​Step 3: Configure Domain Settings

​Step 4: Install Ollama Application

​Step 5: Visit the OpenWebUI Application

​Environment Editor for OpenWebUI

​Manage AI Models

Step 1: Create a Docker+ NGINX Server

How to Install Ollama on a Cloud Server

Step 2: Access the One Click Apps Dashboard

Step 3: Set Up the Ollama Application

Step 4: Configure Domain Settings

Step 4: Visit the Ollama Application

Environment Editor for Ollama

Manage Ollama Models

How to Install OpenWebUI on a Cloud Server

Step 1: Access the One Click Apps Dashboard

Step 2: Set Up the OpenWebUI Application

Step 3: Configure Domain Settings

Step 4: Install Ollama Application

Step 5: Visit the OpenWebUI Application

Environment Editor for OpenWebUI

Manage AI Models