The blog post shows integrating watsonx Assistant and watsonx.ai to create a full-screen user interface for interacting with a large language model (LLM) using minimal coding. It outlines the motivation, architecture, setup process, and specific actions necessary to deploy the integration on IBM Cloud Code Engine.
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.
