As a developer, productivity is crucial in today's fast-paced tech industry. One effective way to boost your productivity and tackle challenges efficiently is by utilizing large language models (LLMs). Most developers are probably familiar with LLMs such as OpenAI's GPT-3.5 and GPT-4, however, other alternatives exist that are private (no more sending your data to OpenAI), open source, and free of cost! In this article, we will explore how to harness the power of these tools to enhance your daily tasks and problem-solving abilities.

Understanding the Tools: First, it's essential to familiarize yourself with Ollama, a lightweight service that can be easily installed on all platforms and makes getting up and running with local LLMs a breeze. With Ollama, developers can run, customize, and even create their own models. The Open Web UI interface is a progressive web application designed specifically for interacting with Ollama models in real time. You can think of the Open Web UI like the Chat-GPT interface for your local models. The Open Web UI Interface is an extensible, feature-rich, and user-friendly tool that makes interacting with LLMs effortless. Open Web UI allows you to engage in conversations with multiple models simultaneously, harnessing their unique strengths for optimal responses. They can also integrate OpenAI API for even more versatile conversations.

Setting up the Environment: To get started, install Ollama on your local machine or container using the install options for your platform of choice. Once Ollama is installed and running it's time to run the Open Web UI interface. There are many provided methods for installation, however, Docker is by far the easiest. Run the following command 👇 (assuming you already have Docker installed on your machine)

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

After installation, visit the Open Web UI interface by opening your web browser and navigating to http://localhost:8000.

Create a local admin user at the login screen by clicking sign up which will then allow you to log in to the interface.

Before you can begin chatting, you must first download your first model. Go to the settings popup and under models, you can enter any model name to download from the list of supported Ollama models (see screenshot)

Boosting Productivity: Now that you have your tools prepped and ready, it's time to leverage the power of LLMs to take your daily workflows to the next level! Here are some examples of how you can use Ollama + Open Web UI to be a more productive developer:

Coding Assistant: The most obvious way to use these tools is to use code models such as starcoder to help you with code suggestions, writing boilerplate or project organization tasks.

Brainstorming Assistant: Create a custom model in the Open Web UI with a specific prompt to be your Rubber Ducky to bounce ideas off of and help you debug those pesky bugs.

Feature Requirement Analyst: Use the Open Web UI documents feature to upload feature requirement documents such as CSV or PDF files and use them in your chat conversations to easily probe into and summarize deep topics that you will need to write your features.

Dev.to Article Assistant: Add a URL into your chat conversations to let the LLM assist you in parsing real-time website data to give you ideas on your next article (kind of like I did with this one 😉)

These are just some examples of how to use these tools to make your daily workflows more productive but the sky is the limit!

In conclusion, by incorporating Ollama's seamless local platform to run open-source large language models coupled with the feature-rich and user-friendly Open Web UI interface into your daily development tasks, you can significantly enhance your problem-solving abilities and increase your overall productivity. Give it a try today and join the growing community of developers who are already supercharging their coding experiences!