Generative artificial intelligence is artificial intelligence capable of generating text, images or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics.

As you have seen in the latest community publications, InterSystems IRIS has included since version 2024.1 the possibility of including vector data types in its database and based on this type of data vector searches have been implemented. Well, these new features reminded me of the article I published a while ago that was based on facial recognition using Embedded Python.

We all know that having a set of proper test data before deploying an application to production is crucial for ensuring its reliability and performance. It allows to simulate real-world scenarios and identify potential issues or bugs before they impact end-users. Moreover, testing with representative data sets allows to optimize performance, identify bottlenecks, and fine-tune algorithms or processes as needed. Ultimately, having a comprehensive set of test data helps to deliver a higher quality product, reducing the likelihood of post-production issues and enhancing the overall user experience.

In this article, let's look at how one can use generative AI, namely Gemini by Google, to generate (hopefully) meaningful data for the properties of multiple objects. To do this, I will use the RESTful service to generate data in a JSON format and then use the received data to create objects.

Attempting to setup an outbound (I'm querying out, not querying the IRIS db) SQL connection. I am connecting to a PostgreSQL database, name "hl7interface".

I have setup the odbc.ini file at /usr/local/etc with the following contents:

[HL7Interface2]
Driver = PostgreSQL
Description = HL7 Interface DB
Servername = localhost
Port = 5432
Protocol = 7.4-1
#userName = postgres
#Password = <real pw here>
Database = hl7interface
ReadOnly = no
ServerType = Postgres

I have set the /etc/odbcinst.ini file with the location of the PostgreSQL driver:

Hey Developers,

Watch the latest video on InterSystems Developers YouTube:

⏯ What is the HL7 FHIR Specification

https://www.youtube.com/embed/LQ9_itHr_Pc
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Last year we introduced our new angular-based View page for CCR as part of the UI refresh for the application. This has been used very effectively by close to 1000 users around the world as the default UI for viewing CCR, and as a result we're getting ready to completely disable the "classic" View page.

Benefits of the new page include:

Hi Developers,

Join us at the upcoming Developer Roundtable on March 26th at 11 am ET | 4 pm CET. 📍
We will have 2 topics covered by the invited experts and open discussion as always!

Talks:

➡ Demo on Documenting and Testing REST Call's by generating documentation and making scenario's for integration tests - presented by @Danny Wijnschenk , Application Developer, Winfo.

Danny is an independent developer based in Belgium, specialized in InterSystems Caché and IRIS. He has customers in both the healthcare and non-healthcare sectors.

➡ Cypress for web application testing - presented by @Pravin Barton , Senior Applications Developer, InterSystems

▶ Update: watch the recording of the roundtable below.

https://www.youtube.com/embed/2NeWf-Y8Cuk
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Hello Community,

I'd like to share with you our article with @Regilo Regilio Guedes de Souza on AWS Amazon blog Automating application-consistent Amazon EBS Snapshots for InterSystems IRIS databases. Our team has created this step-by-step instruction to create application-consistent snapshots for InterSystems IRIS databases. In this article, we outline how to automate pre-scripts to pause I/O and flush buffer to disk and post-scripts to thaw I/O, as shown in the following figure:

I'd like to announce the release of something really rather interesting - revolutionary in fact. That may sound like hyperbole, but I don't think you'll have seen anything quite like this, or even thought it possible!

We've pushed out a new JavaScript/Node.js module named glsdb which you can read all about here in detail:

https://github.com/robtweed/glsdb

Using VECTOR_COSINE() in SQL query to perform a text similarity search on existing embeddings in a %VECTOR column.

Code is below.

Commented out sql query returns this error: SQLCODE: -29 Field 'NEW_EMBEDDING_STR' not found in the applicable tables^ SELECT TOP ? maxID , activity , outcome FROMMain .AITest ORDER BY VECTOR_COSINE ( new_embedding_str ,

Sql query as written returns ERROR #5002: ObjectScript error: <PYTHON EXCEPTION> *<class 'OSError'>: isc_stdout_write: PyArg_ParseTuple failed!

Hello everyone,

I am working with InterSystems IRIS and seeking guidance on how to perform specific tasks related to the FHIR SQL Builder using commands or code, rather than the graphical user interface (GUI). The specific tasks I am trying to accomplish are:

I have files of mixed types; e.g. a.pdf, b.pdf, c.txt.

I zipped them with gzip to make a.pdf.gz, b.pdf.gz, c.txt.gz.

I concatenated them into one file, all.gz.

I renamed all.gz to all.zip.

I emailed it but cannot extract in windows browser.

I have a week learning object script after 5 yrs as full stack developer, object script seems to be one of lauguage that has own syntax and new methods that I had to give my self more time to explore a lot. any suggestion about what is the best thing you you did figure out about IRIS to share ?

Hi community,

The aim of this article is to explain how to create messaging between IRIS and Microsoft Teams.

In my company, we wanted to monitor error messages, and we used the Ens.Alert class to redirect those error messages through a Business Operation that sent an email.
The problem was that we sent those error messages to a support account where there were many emails. We wanted something specific for a specific team.

So we investigated how to make these messages reach the development team directly and they could have, in real time, a notification of an error in our production.
In our company we use Microsoft Teams as a corporate tool, so we asked ourselves: How could we make these messages reach the IRIS development team?