InterSystems FAQ rubric

If you want to run an OS executable file, command, or a program created within an InterSystems product when the InterSystems product starts, write the processing in the SYSTEM^%ZSTART routine. (The %ZSTART routine is created in the %SYS namespace).

Before you write any code in SYSTEM^%ZSTART, make sure that it works properly under all conditions.

Data Analysis

This is the sequel to Data Collection. If you have not had a chance to go through and install that you should first do that.

What is provided here is the analysis for the collection of that data that was collected earlier.

In much the same way as was done in that repository you will need to import the xml that makes up this repository.

Starting at the topmost level there is a task:

Data Collection

This is a step-by-step instruction guide for creating a task to collect data about the InterSystems database and globals therein (as seen in the associated Open Exchange App - find all the associated code there)

InterSystems FAQ rubric

The TIMESTAMP type corresponds to the %Library.TimeStamp data type (=%TimeStamp) in InterSystems products, and the format is YYYY-MM-DD HH:MM:SS.nnnnnnnnn.

If you want to change the precision after the decimal point, set it using the following method.

1) Set system-wide

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.

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.

Principle: After dividing the article uploaded by the user into sentences using Python, the embedded value is obtained and stored in the Iris database. Then, the similarity between sentences is compared through Iris vector search, and finally displayed on the front-end page.

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:

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.

The InterSystems IRIS has a series of facilitators to capture, persist, interoperate, and generate analytical information from data in XML format. This article will demonstrate how to do the following:

1. Capture XML (via a file in our example);
2. Process the data captured in interoperability;
3. Persist XML in persistent entities/tables;
4. Create analytical views for the captured XML data.

Capture XML data

The InterSystems IRIS has many built-in adapters to capture data, including the next ones:

InterSystems FAQ rubric

When you run a routine in the terminal and an error occurs in the program, if you have not set the error trap properly, the program will enter debug mode as shown below.

InterSystems FAQ rubric

The Web/CSP Gateway management page is typically configured so that it cannot be accessed from client machines.

To access from any client, do the following: