howto – Winko Erades

Installation and configuration of ThunderAI on Ubuntu 24.04

ThunderAI is a powerful Thunderbird extension that leverages the advanced capabilities of AI to revolutionize email management. By integrating with ChatGPT, OpenAI and Ollama ThunderAI empowers users to:

Craft compelling emails: Define custom prompts to generate email drafts, refine existing messages, and ensure professional tone and style.
Gain deeper insights: Analyze emails using additional data provided by the user, such as context files or previous communications.
Enhance productivity: Automate tasks like email tagging and categorization, freeing up time for more important matters.
Improve communication quality: Leverage ChatGPT’s language expertise to identify and correct grammatical errors, enhance clarity, and optimize email content for maximum impact.

And of course, you want that AI running on your own computer. Luckily that is not that difficult… The installation and configuration of ThunderAI on Ubuntu 24.04 consists of 4 easy steps:

Install Ollama on Ubuntu
Configure Ollama service on Ubuntu
Install ThunderAI in Thunderbird
Configure ThunderAI in Thunderbird

Install Ollama on Ubuntu

Go to the Ollama website.
Follow the installation steps for Linux:
Open a terminal
Run the following command: curl -fsSL https://ollama.com/install.sh | sh
Download and run an LLM model.
For example by typing: ollama run zephyr:7b-beta-q8_0
After downloading the LMM it will start Ollama running the zephyr:7b-beta-q8_0 LLM.
You can exit Ollama by entering: /bye

Configure Ollama service on Ubuntu

Open a terminal and type: sudo nano /etc/systemd/system/ollama.service
In the file, you will see a line starting with Environment
Add the following sentence just beneath it: Environment="OLLAMA_ORIGINS=moz-extension://*"
Save and exit the file
Restart your computer

Install ThunderAI in Thunderbird

Open Thunderbird and go to Tools, Add-ons and Themes.
Search the ThunderAI extension by typing ThunderAI in Find more add-ons, and install it.

Configure ThunderAI in Thunderbird

Open Thunderbird and go to Tools, Add-ons and Themes.
Search the ThunderAI Extension.
Click the wrench Icon.
Select Ollama API (Local LLM) as the Connection Type.
Fill in http://127.0.0.1:11434/ as the Host Address.
Choose your favorite Ollama Model, and you can use AI in your favorite email client ;-).

Now you should be ready to run your own LLM as a useful assistant on your favorite email client.

Suggestions for improving this article are welcome, please let me know and drop me a line.

The easiest way to Install Joget on Ubuntu

Joget is a user-friendly open-source no-code / low-code application platform that empowers everyday people to build, deliver, monitor, and maintain business process management applications. It supports full-fledged agile development capabilities such as processes, forms, lists, CRUD, and UI. There are several ways of installing Joget, in this article I’ll show you how to set up your environment in just a few steps. You’ll be up and running in no-time. I’m going to do this by Installing Joget on Ubuntu using Docker compose.

How to install Wexflow server on Ubuntu 18.04 using Docker compose

Wexflow is an incredible free, open-source, high-performance, extensible, modular, and cross-platform workflow engine that is specially built for automation. It’s a tool that helps you to easily automate workflows with recurring tasks. You can read more about it here. In this “how-to” I’ll show you how you can install a Wexflow server on Ubuntu 18.04 using Docker compose.

How to install Form Tools on Ubuntu 18.04

Form Tools is a powerful, flexible, free, and open-source PHP/MySQL script you can install on your website for managing your forms and data. It is all about data management. This article takes you through an installation of Form Tools on Ubuntu server 18.04 for testing purposes.

Configure Raspberry Pi and Sense HAT for logging

Smart buildings are a really hot item right now, but how smart is your home? And how much do you know about what is going on in your home, when you are not there? What is a useful data-set to create? What data can you create? Luckily I got my hands on some Raspberry Pis with a Sense HAT Kit. Now I could try to answer these questions myself! I really wanted to figure out how the Raspberry Sense Hat kit worked. To my big surprise, it was rather easy to create a nice script that writes the Raspberry Pi SenseHat sensor data to a log file. This enabled me to analyze my data later-on by importing the log file into a spreadsheet program like Libre Office (or something similar). The spreadsheet enabled me to create nice graphs. As I’m always curious I tried this in a friendly environment at home, and in the harsh environment of my wife’s atelier where the environmental conditions are constantly changing caused by the warmth of the winter and heat produced by the glass kilns.