I want to share my experience in the cloud, AI, and agents development areas.
The post discusses automating local testing of IBM watsonx Orchestrate with Ollama models using a Bash script. The script simplifies the setup process, ensuring proper connections and configurations. It initiates services, confirms model accessibility, reducing typical setup errors.
The this post describes a Bash automation script for setting up the IBM watsonx Orchestrate Development Edition. The script automates tasks like resetting the environment, starting the server, and configuring credentials, allowing for a more efficient workflow. It addresses common setup issues, ensuring a repeatable and successful process.
This blog post outlines a bash automation for setting up and testing Text Generation Inference (TGI) using a container. It provides instructions for creating a Python test client, starting the TGI server, and troubleshooting common issues. The post emphasizes the benefits of using containers and references the Hugging Face and Nvidia technologies.
This blog post is a CheatSheet about how to loop an endpoint of an application running on IBM Cloud Code Engine with a bash automation.
This extract is from a bash automation script in the question-answering GitHub project. The bash script automates the deployment to IBM Cloud Code Engine. The extraction is about the building and pushing a container to the IBM Cloud Container Registry.
These are the standard config files that save PATH settings for shell scripting. There is an appropriate Stackoverflow entry: What's the difference between .bashrc, .bash_profile, and .environment?
The objective of this project is to deploy the Reranker to a Kubernetes cluster in a VPC on IBM Cloud and access the REST API of the Reranker. The Reranker is a component of PrimeQA.
This blog post is about to run Watson NLP for Embed example in a KServe ModelMesh Serving environment on an IBM Cloud Kubernetes cluster in a Virtual Private Cloud environment and reuses parts of the IBM Watson Libraries for Embed documentation.
This blog post is about to deploy the IBM Watson Natural Language Processing Library for Embed to an IBM Cloud Kubernetes cluster in a Virtual Private Cloud (VPC) environment and is related to my blog post Run Watson NLP for Embed on IBM Cloud Code Engine. IBM Cloud Kubernetes cluster is a “certified, managed Kubernetes solution, built for creating a cluster of compute hosts to deploy and manage containerized apps on IBM Cloud“.
In this blog post we use an existing template file, that we created for a custom resource to insert the needed value for an URL to point to a container image in a container registry, to create custom resource yaml file we use to deploy that custom resource . The template file contains a string which we will replace with the content of URL to the container image. We haven't used helm, kustomize to do that in this situation.
Thomas Suedbroecker's Blog 