1.2.2 – New Way To Add LLMs Lesson

Lesson Overview

Expanding your chatbot’s capabilities depends on how easily you can add and switch between large language models. Older methods required you to copy a command from sites like ollama.com and paste it into a terminal—an approach that, while effective, demanded more technical comfort and extra steps. Now, the web UI has been updated to let you search for and add models directly within the app’s settings menu, streamlining the process.

This lesson guides you through using the settings panel to import new models by entering their names and selecting them from a list. You’ll also learn to troubleshoot minor errors that can occur (such as error messages that do not prevent installation) and how to delete outdated or unused models. Whether you are testing different LLMs for conversation quality, updating your system with the latest models, or simply looking for a more user-friendly way to manage models, this lesson helps you work quickly and efficiently. Real-world uses include personal chatbot customization, classroom tool improvements, and business automation, all relying on flexible and straightforward model management.

Who This Is For

If you want more control over your AI chatbot’s capabilities—without using the command line—this lesson is built for you. It is particularly helpful if you are:

• Educators wishing to experiment with different language models
• Business teams deploying chatbots for customer or internal use
• Creators looking to easily test new models for quality or features
• Anyone managing private AI tools for personal productivity
• Users who prefer not to use terminal commands or manual installation

Where This Fits in a Workflow

Adding and removing large language models is a key part of maintaining or upgrading your AI chatbot. After initial setup, you’ll often want to try new models as they appear or respond to feedback by bringing in alternatives. With the web UI update covered in this lesson, you can now adjust your chatbot’s underlying intelligence on the fly—no need to break workflow momentum or troubleshoot terminal errors.

For example: you might read about a model on ollama.com that promises better general knowledge, or you might need to remove an older model to free up resources. This lesson gives you simple tools to make those changes directly from your browser. This is essential for anyone running ongoing upgrades or regular testing of chatbot quality in practical work or learning environments.

Technical & Workflow Benefits

Previously, adding a new language model required leaving the app: you’d copy commands from ollama.com and use the terminal, which could be slow and error-prone for many users. The new model management feature in the web UI speeds up the entire process—just copy, paste, and install right in your browser.

This change reduces setup time, decreases reliance on technical skills, and lowers the risk of mistakes from mistyping commands. For users who regularly switch models or support multiple chatbot applications, the ability to manage models in one place leads to better organization and faster experimentation. If an error appears during installation, the UI makes it easy to check if the new model was still added correctly, giving more transparency and confidence during each update.

Practice Exercise

Try out importing a language model yourself:

1. Open your chatbot’s web interface and go to the settings menu.
2. Click on the models tab. Locate a language model on ollama.com you haven’t tried yet and copy the model name.
3. Paste or type the model name into the model input field, submit it, and watch the installation process. If you get an error, check your installed models list—did your new model appear?

Question: How does using the web UI for adding models compare to your experience with the terminal? Were you able to locate, add, and remove models without leaving the interface?

Course Context Recap

This lesson builds directly on your initial setup by giving you a faster, less technical way to keep your chatbot’s language models up to date. You’ve moved from manual installation toward a more streamlined, browser-based method. Up next, you’ll learn more about managing and using these models, including how to activate, test, or switch between them in real time. Keep going to unlock the full potential of your private AI chatbot—explore the rest of the course for deeper customization and management skills.