One of the challenges of creating a DICOM message is how to implement putting data in the correct place. Part of it is by inserting the data in the specific DICOM tags, while the other is to insert binary data such as a picture - In this article I will explain both.

To create a DICOM message, you can either use the EnsLib.DICOM.File class (to create a DICOM file) or the EnsLib.DICOM.Document class (to create a message that can be sent to PACS directly). In either case, the SetValueAt method will allow you to add your data to the DICOM tags.

gj :: configExplorer is a new VS Code extension integrating with Server Manager and leveraging Structurizr to produce configuration diagrams of your servers.

Here's a short introductory video.

https://www.youtube.com/embed/WHkoZsg6P-A
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Hi Community,

In this article, I will introduce my application iris-AgenticAI .

The rise of agentic AI marks a transformative leap in how artificial intelligence interacts with the world—moving beyond static responses to dynamic, goal-driven problem-solving. Powered by OpenAI’s Agentic SDK , The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm.
This application showcases the next generation of autonomous AI systems capable of reasoning, collaborating, and executing complex tasks with human-like adaptability.

Application Features

• Agent Loop 🔄 A built-in loop that autonomously manages tool execution, sends results back to the LLM, and iterates until task completion.
• Python-First 🐍 Leverage native Python syntax (decorators, generators, etc.) to orchestrate and chain agents without external DSLs.
• Handoffs 🤝 Seamlessly coordinate multi-agent workflows by delegating tasks between specialized agents.
• Function Tools ⚒️ Decorate any Python function with @tool to instantly integrate it into the agent’s toolkit.
• Vector Search (RAG) 🧠 Native integration of vector store (IRIS) for RAG retrieval.
• Tracing 🔍 Built-in tracing to visualize, debug, and monitor agent workflows in real time (think LangSmith alternatives).
• MCP Servers 🌐 Support for Model Context Protocol (MCP) via stdio and HTTP, enabling cross-process agent communication.
• Chainlit UI 🖥️ Integrated Chainlit framework for building interactive chat interfaces with minimal code.
• Stateful Memory 🧠 Preserve chat history, context, and agent state across sessions for continuity and long-running tasks.

InterSystems OMOP, The Cloud Service (Troy)

The August Article Bounty on the Global Masters article caught my attention, and one of the proposed topics sounded quite interesting in regard to its future use in my teaching. So, here's what I'd like to tell my students about tables in IRIS and how they correlate with the object model.

First of all, InterSystems IRIS boasts a unified data model. This means that when you work with data, you are not locked into a single paradigm. The same data can be accessed and manipulated as a traditional SQL table, as a native object, or even as a multidimensional array (a global). It means that when you create an SQL table, IRIS automatically creates a corresponding object class. When you define an object class, IRIS automatically makes it available as an SQL table. The data itself is stored only once in IRIS's efficient multidimensional storage engine. The SQL engine and the object engine are simply different "lenses" to view and work with the same data.

First, let's look at the correlation between the relational model and the object model:

It's not always a 1:1 correlation, as you may have several tables represent one class, for example. But it's a general rule of thumb.

Hello everybody,

I would like to export project contents using Visual Studio Code, as well as I do with InterSystems Studio.

However, while attempting the export through the InterSystems extension I get the following error:

- There are no folders in the current workspace that code can be exported to.

These are the step to reproduce my error:

Every thriving technical community has individuals whose curiosity, perseverance, and generosity help shape its collective knowledge. In the InterSystems Developer Community, one such contributor is @Scott Roth, who has been an inspiring presence for nearly a decade.

👏 Let’s take a closer look at Scott's remarkable journey and his impact on the InterSystems ecosystem.

Migrating from Oracle, MSSQL, or other purely relational database systems to a multimodel InterSystems IRIS is a strategic decision that requires careful planning and execution. While this transition offers significant benefits, including enhanced performance, scalability, and support for modern architectures, it also comes with challenges. In this article I will highlight some of the considerations connected to coding to ensure a successful migration. I will leave everything connected to an actual migration of structures and data outside the scope of this article.

First, when you're considering migrating to a different database system, you need to understand your business logic, whether it's on the side of the application (application server) or the database server. Basically, where do you have your SQL statements that you will need to potentially rewrite?

Hi devs!

What is the best way to return JSON in IRIS for a GET request in a REST app?

This is how I do it now:

Introduction

In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.

Hey folks! Having recently onboarded to InterSystems, I realized that despite having a totally free and awesome Community Edition, it's not super clear how to get it. I decided to write up a guide highlighting all the different ways you can access the Community Edition of InterSystems IRIS:

Get InterSystems IRIS Community Edition as a Container

Working with a containerized instance of the Community Edition is the recommended approach for folks who are new to developing on InterSystems IRIS, and in my opinion it's the most straightforward. InterSystems IRIS Community Edition can be found on DockerHub; if you have an InterSystems SSO account, you can also find it in the InterSystems Container Registry.

In either case, you'll want to pull the image you want using the docker CLI:

docker pull intersystems/iris-community:latest-em
// or
docker pull containers.intersystems.com/intersystems/iris-community:latest-em

Next, you'll need to start the container: In order to interact with IRIS from outside the container (for example, to use the management portal) you'll need to publish some ports. The following command will run the IRIS Community Edition container with the superserver and web server ports published; note that you can't have anything else running that depends on ports 1972 or 52773!

docker run --name iris -d --publish 1972:1972 --publish 52773:52773 intersystems/iris-community:latest-em

Are you planning to attend InterSystems READY 2025 (June 22–25), this year's global summit?

I have see this discussed on the community but I'm not quite finding an answer.

Migrating InterSystems IRIS and InterSystems IRIS for Health from on-premises to the cloud offers many advantages for Application Providers and Solution Providers. These advantages include simplified operations, access to flexible resources, and enhanced resilience. Companies no longer need to worry about the physical constraints and expenses associated with maintaining on-prem infrastructure, such as power and space requirements and expensive computer hardware.

One of the most compelling benefits is the ability to accelerate speed to market. By removing the burden of infrastructure maintenance, cloud environments enable faster development and deployment cycles, allowing businesses to respond quickly to market demands and opportunities. Operational costs are also lowered, because companies can scale resources up or down based on actual needs, leading to more efficient use of capital. Moreover, migrating to the cloud can contribute to a reduced carbon footprint by optimizing energy usage through shared cloud infrastructure.

Transitioning to the cloud may involve significant changes. Companies may benefit from a more operational focus, managing and optimizing cloud resources continuously. This shift may require changes to business models, reconsideration of margins, and strategies for scaling operations up or out. While requiring more investment, embracing these changes can lead to improved agility and competitive advantage in the marketplace.