For some time I have been planning to do some type of proof of concept with the Workflow functionality, which, like so many other functionalities present in IRIS, tends to go quite unnoticed by our clients (and for which I say mea culpa). That's why I decided a few days ago to develop an example of how to configure and exploit this functionality by connecting it with a user interface developed in Angular.

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In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions.

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InterSystems FAQ rubric

After upgrading your system, you may receive the error below when you try to open the Management Portal:

ERROR #5001: Server version of object does not match version sent from the client: %ZEN.Component.vgroup

This error is caused by outdated information remaining in your browser's cache.

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In our previous article we presented the general concepts as well as the problem that we wanted to solve by using the task engine integrated in InterSystems IRIS, in today's article we will see how we configure an interoperability production to provide a solution.

Workflow Engine Configuration

First we are going to define the roles of the tasks that we are going to manage, in our example we are going to define two types:

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In the previous article, we saw in detail about Connectors, that let user upload their file and get it converted into embeddings and store it to IRIS DB. In this article, we'll explore different retrieval options that IRIS AI Studio offers - Semantic Search, Chat, Recommender and Similarity.

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ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.

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