This cheat sheet provides a two-step guide for adding users to your watsonx project in IBM Cloud.
CheatSheet: How to add users to your watsonx project?
CheatSheet: Configure the Block Storage usage in Virtual Server Instances on IBM Cloud
This post introduces the use of Block Storage in Virtual Server Instances, particularly in relation to GPUs. It covers the process of mounting and configuring block storage, along with creating, formatting, and mounting the disk. It also provides steps for permanently mounting the storage and attaching existing block storage to a new virtual service instance machine.
CheatSheet: How to set up remote development with VS Code using SSH?
The blog post provides a short guide on accessing source code remotely with SSH using VS Code. It covers which of the Visual Studio Code extensions you should install, SSH configuration, connecting to the host, and using VS Code for remote development. The post also includes helpful tips and an example SSH configuration for a Raspberry Pi.
CheatSheet: How to ensure you use the right Python environment in VS Code interpreter settings?
This post covers to ensure you set the virtual environment for Python in VS Code using venv. It details creating and activating a Python venv, and ensuring it’s used in VS Code environments. The steps include opening the VS Code command palette, selecting an interpreter, and navigating to the pyvenv.cfg file.
Unleash your creativity and design a custom visualization for the Shelly 3EM device with Grafana
The blog post details an example implementation of a connection server using Shelly 3EM, IBM Cloud Cloudant, and Grafana. It aims to store historical data for visualizing electricity consumption. The project involves detailed architecture, environment setup, Python, FastAPI, Podman, and more usage. The setup covers Raspberry Pi, Podman Compose, and IBM Cloud Code Engine environments, with prerequisites and detailed configurations. The approach allows users to monitor and visualize power consumption efficiently and cost-effectively using Grafana.
CheatSheet: Run a PostgreSQL container with Podman and podman-compose
This brief article provides a step-by-step guide for setting up and running a PostgreSQL database container locally using Podman Desktop and podman-compose. It covers installation, configuration, and execution, along with additional notes on maintenance and troubleshooting.
How do you initially set up a Virtual Server Instance with a GPU in IBM Cloud?
Generative AI offers diverse business opportunities, often requiring GPU for intensive computing. IBM Cloud provides easy GPU instantiation with Virtual Server Instance (VSI) in a Virtual Private Cloud, available in minutes with pay-per-usage. This guide covers VPC configuration, VSI setup with GPU, SSH access, GPU accessibility in Ubuntu, and GPU verification in Python.
Writing an HTML-to-Text converter can be the first task in an AI pipeline with the JSOUP Java Library
This blog post is about the powerful JSOUP Java Library, which allows you to convert an HTML to plain formatted text based on your requirements by extracting and inspecting HTML elements in various ways. We check two methods to do this in this example.
How to define a custom Open API specification for a Watson Machine Learning deployment to integrate it into watsonx Assistant
This blog post is about how to define a custom Open API specification` for Watson Machine Learning - IBM Cloud deployment to integrate it into watsonx Assistant. The Watson Machine Learning deployments make it easy for data scientists to write AI Prototypes to be integrated into applications because they can use Jupyter Notebooks and Python they are used to without knowing how to write containers and set up runtimes; they can deploy, and the developers can consume the AI functionalities they have implemented via a REST API.
How to create a FastAPI server to use OpenAI models
Last time, I wrote a blog post about "IBM Watsonx.ai and a simple question-answering pipeline using Python and FastAPI", and I had an exchange with my family about an OpenAI sample for a FastAPI application, so I created a small FastAPI server to access OpenAI with Python.
Thomas Suedbroecker's Blog 