Hi Community,

In this article, I will introduce my application iris-fhir-bridge

IRIS-FHIR-Bridge is a robust interoperability engine built on InterSystems IRIS for Health, designed to transform healthcare data across multiple formats into FHIR and vice versa. It leverages the InterSystems FHIR Object Model (HS.FHIRModel.R4.*) to enable smooth data standardization and exchange across modern and legacy healthcare systems.

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Article
· May 20 3m read
A knockout of weight

image

Just like a knockout punch, without giving the opponent a chance, Kubernetes, as an open source platform, has a universe of opportunities due to its availability (i.e., the ease of finding support, services and tools). It is a platform that can manage jobs and services in containers, which greatly simplifies the configuration and automation of these processes.

But let's justify the title image and give the tool in question the “correct” name: InterSystems Kubernetes Operator.

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Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?

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Prefer not to read? Check out the demo video I created:

https://www.youtube.com/embed/-OwOAHC5b3s
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Hi Community!

It's time to celebrate our 25 fellow members who took part in the latest InterSystems Technical Article Contest and wrote

🌟 38 AMAZING ARTICLES 🌟

The competition was filled with outstanding articles, each showcasing innovation and expertise. With so many high-quality submissions, selecting the best was no easy task for the judges.

Let's meet the winners and look at their articles:

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Introduction

As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.

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Hey Community,

It's time for the first programming contest of the year, and there's a surprise so read on! Please welcome:

🏆 InterSystems AI Programming Contest: Vector Search, GenAI, and AI Agents 🏆

Duration: March 17 - April 6, 2025

Prize pool: $12,000 + a chance to be invited to the Global Summit 2025!

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Hi Developers!

Here're the technology bonuses for the InterSystems AI Programming Contest: Vector Search, GenAI and AI Agents that will give you extra points in the voting:

  • Agent AI solution - 5
  • Vector Search usage - 4
  • Embedded Python - 3
  • LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
  • IntegratedML usage - 3
  • Docker container usage - 2
  • ZPM Package deployment - 2
  • Online Demo - 2
  • Implement InterSystems Community Idea - 4
  • Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
  • First Article on Developer Community - 2
  • Second Article On DC - 1
  • First Time Contribution - 3
  • Video on YouTube - 3
  • Suggest a new idea - 1

See the details below.<--break->

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Hi Community!

We are excited to announce the first French technical article writing contest!

✍️ Technical Article Contest ✍️

This is the perfect opportunity for all InterSystems technology enthusiasts to share their knowledge and showcase their writing skills. No matter your experience level, everyone is welcome to participate. Articles can cover a wide range of technical topics related to InterSystems products or services. So, let your creativity and expertise run wild!

📅 Contest period: September 2-29, 2024

🎁 Gifts for all: a special gift is prepared for each participant!

🏅 Prizes for the authors of the best articles

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After so many years of waiting, we finally got an official driver available on Pypi

Additionally, found JDBC driver finally available on Maven already for 3 months, and .Net driver on Nuget more than a month.

As an author of so many implementations of IRIS support for various Python libraries, I wanted to check it. Implementation of DB-API means that it should be replaceable and at least functions defined in the standard. The only difference should be in SQL.

And the beauty of using already existing libraries, that they already implemented other databases by using DB-API standard, and these libraries already expect how driver should work.

I decided to test InterSystems official driver by implementing its support in SQLAlchemy-iris library.

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Unlike the movie mentioned in the image (for those who don't know, Matrix, 1999), the choice between Dynamic SQL and Embedded SQL is not a choice between truth and fantasy, but it is still a decision to be made. Below, I will try to make your choice easier.

If your need is interactions between the client and the application (and consequently the database), Dynamic SQL may be more appropriate, as it "adapts" very easily to these query changes. However, this dynamism has a cost: with each new query, it is remodeled, which can have a higher cost to execute. Below is a simple example of a Python code snippet.

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Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 3 – REST and Interoperability

Now that we have finished the configuration of the SQL Gateway and we have been able to access the data from the external database via python, and we have set up our vectorized base, we can perform some queries. For this in this part of the article we will use an application developed with CSP, HTML and Javascript that will access an integration in Iris, which then performs the search for data similarity, sends it to LLM and finally returns the generated SQL. The CSP page calls an API in Iris that receives the data to be used in the query, calling the integration. For more information about REST in the Iris see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls...

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REST API with Swagger in InterSystems IRIS

Hello

The HTTP protocol allows you to obtain resources, such as HTML documents. It is the basis of any data exchange on the Web and a client-server protocol, meaning that requests are initiated by the recipient, usually a Web browser.

REST APIs take advantage of this protocol to exchange messages between client and server. This makes REST APIs fast, lightweight, and flexible. REST APIs use the HTTP verbs GET, POST, PUT, DELETE, and others to indicate the actions they want to perform.

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Article
· Feb 14 5m read
HTTP and HTTPS with REST API

HTTP and HTTPS with REST API

Hello

The HTTP protocol allows you to obtain resources, such as HTML documents. It is the basis of any data exchange on the Web and a client-server protocol, meaning that requests are initiated by the recipient, usually a Web browser.

REST APIs take advantage of this protocol to exchange messages between client and server. This makes REST APIs fast, lightweight, and flexible. REST APIs use the HTTP verbs GET, POST, PUT, DELETE, and others to indicate the actions they want to perform.

When we make a call to a RESt API, what actually happens is an HTTP call. The API receives this call and according to the requested verb and path, the API performs the desired action. In the case of the Iris implementation we can see this clearly in the URLMap definition area:

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Using Flask, REST API, and IAM with InterSystems IRIS

Part 2 – Flask App

Flask is a web development microframework written in Python. It is known for being simple, flexible, and enabling rapid application development.

Installing Flask is very simple. Once you have python installed correctly on your operating system, we need to install the flask library with the pip command. For REST API consumption, it is advisable to use the requests library. The following link provides a guide to installing flask: https://flask.palletsprojects.com/en/stable/installation/

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Using Flask, REST API, and IAM with InterSystems IRIS

Part 1 - REST API

Hello

In this article we will see the implementation of a REST API to perform the maintenance of a CRUD, using Flask and IAM.

In this first part of the article we will see the construction and publication of the REST API in Iris.

First, let's create our persistent class to store the data. To do this, we go to Iris and create our class:

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