using  intersystemsdc/iris-ml-community:latest I failed with

Error: Invalid Community Edition license, may have exceeded core limit.
Shutting down the system : $zu(56,2)= 0Starting IRIS

What is the actual valid version with ML ??

Table of Contents

If you start with InterSystems ObjectScript, you will meet the XECUTE command.
And beginners may ask: Where and Why may I need to use this ?

The official documentation has a rich collection of code snippets. No practical case.
Just recently, I met a use case that I'd like to share with you.

The scenario:

When you build an IRIS container with Docker, then, in most cases,
you run the  initialization script  

iris session iris < iris.script 

Introduction

The article was motivated by the 2025 September Article Bounty
***************************************************************
The principle of Docker is just convincing to me.

• Get a sandbox where you play and try whatever you want/need to do
• Once done. You drop it without leaving traces in your working environment

This was the technical base for me to run about 700 reviews in OEX 
with almost no side effects  (except those caused by myself).

For beginners, I'll start with straight pure IRIS, no *health, *ML, *whatever

I was really surprised that such a flexible integration platform with a rich toolset specifically for app connections has no out-of-the-box Enterprise Service Bus solution. Like Apache ServiceMix, Mule ESB, SAP PI/PO, etc, what’s the reason? What do you think? Has this pattern lost its relevance completely nowadays? And everybody moved to message brokers, maybe?

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

If you want to find out what exact version your Docker image is (and since the latest image tagging scheme you cannot just rely on the image tag; and assuming you don't want to actually run it just in order to find out) you can run this docker command:

I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:

ollama-ai-iris/data/prompts/medical_progress_notes_prompt.txt at main · oliverwilms/ollama-ai-iris
 

I combined @Rodolfo Pscheidt Jr https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

I attempted to run

The 2025.1.1 maintenance releases of InterSystems IRIS^® data platform, InterSystems IRIS^® for Health^TM, and HealthShare^® Health Connect are now Generally Available (GA). Please share your feedback through the Developer Community so we can build a better product together.

Documentation

You can find the detailed change lists & upgrade checklists on these pages:

• InterSystems IRIS
• InterSystems IRIS for Health
• HealthShare Health Connect

Early Access Programs (EAPs)

There are many EAPs available now. Check out this page and register to those you are interested.

How to get the software?

At hackathons that InterSystems participated and I supported, many students were asking how all their teammates could use the same IRIS database that they spun up in a container. I suggested using ngrok to expose their localhost IRIS and realized we don't have documentation on that. Hence, I thought this would be great to let more people knwo about this powerful technique for enhancing collaboration during development and testing.

Step-by-Step Guide to Exposing InterSystems IRIS with ngrok

Introduction

InterSystems IRIS allows you to build REST APIs using ObjectScript classes and the %CSP.REST framework. This enables the development of modern services to expose data for web apps, mobile apps, or system integrations.

In this article, you'll learn how to create a basic REST API in InterSystems IRIS, including:

• A persistent data class
• A REST class with GET and POST methods
• A web application to expose the API
• A full demonstration using Docker

Step 1: Create the data class Demo.Producto

Description

This is a template for a Flask application that can be deployed in IRIS as an native Web Application.

Installation

1. Clone the repository
2. Create a virtual environment
3. Install the requirements
4. Run the docker-compose file

git clone
cd iris-flask-template
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
docker-compose up

Usage

The base URL is http://localhost:53795/flask/.

Endpoints

I have created a new docker stack with webgateway and IRIS for Health 2025.1. I have mapped the posts of wegateway like this:

• 8743:443
• 8780:80

I can access IRIS portal through 8743 without problems.

I also have created a FHIR repository, and I'm able to access it through 8743 port.

I have a web application, in another server with another domain, that connects to this FHIR repository. I have configured in FHIR endpoint the allowed origin to the domain of this application. But when I try to connect from this application to FHIR repository I have this error on Webgateway:

Hi Developers!

As you know the concept of ObjectScript Package Manager consists of ZPM client - client application for IRIS which helps you to install packages from the registry. And the code which works "on the other side" is  ZPM Registry - server which hosts packages and exposes API to submit, list and install it. Now when you install the ZPM client it installs packages from community package registry, which si hosted on pm.community.intersystems.com

Let me introduce you to FHIRCraft, a lightweight tool to generate synthetic FHIR resources.

Now, you might be thinking:
“But wait — doesn’t Synthea already do that, and with tons of resources?”
Exactly — and that’s precisely why I created this app.

FHIRCraft is designed to generate simpler, smaller, and more focused FHIR resources. Unlike Synthea, it doesn’t aim to simulate entire patient histories or clinical workflows. Instead, it helps when you’re just getting started with FHIR — when you want to test things incrementally, or explore how specific resources behave in isolation.

Hello everyone,

I am attempting to implement continuous integration using Docker with Caché 2018.1, and I am in the process of creating an image for our client. I have already installed Caché 2018.1 on the RedHat server, but I am working on a script to create the database and namespace. For the database, I used the following code:

do ##class(SYS.Database).CreateDatabase("/usr/cachepoc/cache2018/mgr/poc/")

However, I have encountered some issues with this code. For instance, I am unable to view this local database in the portal's list:

Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals. Secure, responsive, and (unlike your last vendor) emotionally

I cloned @Yuri Marx's langchain-iris-tool repo and modified docker-compose yaml per this post:

https://community.intersystems.com/post/error-when-trying-langchain-iri…

Now I see this:

I combined @Rodolfo Pscheidt https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

My own project is https://github.com/oliverwilms/ollama-ai-iris

I can run load_data.py and it connects to IRIS (same container).

When I try to run query_data.py https://github.com/oliverwilms/ollama-ai-iris/blob/main/query_data.py , it cannot connect to ollama:

ConnectionError: Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible.

The 2024.1.4 and 2023.1.6 maintenance releases of InterSystems IRIS^® data platform, InterSystems IRIS^® for Health^TM, and HealthShare^® Health Connect are now Generally Available (GA). These releases include the fixes for the following alert recently issued - Alert: SQL Queries Returning Wrong Results | InterSystems. Please share your feedback through the Developer Community so we can build a better product together.

Documentation

You can find the detailed change lists & upgrade checklists on these pages:

• InterSystems IRIS
• InterSystems IRIS for Health
• HealthShare Health Connect

Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

I read the article by @Rodolfo Pscheidt:

https://community.intersystems.com/post/ollama-ai-iris

I forked his app and copied selected files from @Guillaume Rongier iris-rag-demo to make it containerized:

oliverwilms/ollama-ai-iris
 

I ran load_data.py and I got this output:

I cloned iris-rag-demo from Open Exchange and issued docker-compose up -d. I went to the front end and type in the chat message:

Who was the 46th President of United States of America?

I got a run time error:

RuntimeError: ERROR <Ens>ErrBPTerminated: Terminating BP ChatProcess # due to error: ERROR #5002: ObjectScript error: <PYTHON EXCEPTION> *<class 'RuntimeError'>: <PYTHON EXCEPTION> <class 'ValueError' > ERROR #5002: ObjectScript error: <PYTHON EXCEPTION> *<class 'RuntimeError'

Traceback:

I cloned @Yuri Marx's langchain-iris-tool repo and typed docker-compose up -d. I see error message:

Error response from daemon: could not select device driver "nvidia" with capabilities: [[gpu]]
 

I know that people who are completely new to VS Code, Git, Docker, FHIR, and other tools can sometimes struggle with setting up the environment. So I decided to write an article that walks through the entire setup process step by step to make it easier to get started.

I’d really appreciate it if you could leave a comment at the end - let me know if the instructions were clear, if anything was missing, or if there’s anything else you'd find helpful.

The setup includes:

Background

Embeddings is a new IRIS feature empowering the latest capability in AI semantic search.
This presents as a new kind of column on a table that holds vector data.
The embedding column supports search for another existing column of the same table.
As records are added or updated to the table, the supported column is passed through an AI model and the semantic signature is returned.
This signature information is stored as the vector for future search comparison.
Subsequently when search runs, a comparison of the stored signatures occurs without any further AI model processing overhead.

Hi all.

I'm trying to create an indexed table with an vector field so I can search by the vector value.
I've been investigating and found that to get the vector value based on the text (token), use a Python method like the following:

Hello,

i am building a new container with Docker-Compose with a --volume ./:/irisdev/app:rw to mount a host volume (UBUNTU).

If i try to create some data in /irisdev/app i have no write permission

If i open a bash host session i see all mounted files of my ./ directory. But with ls -l only UID 100 has write permission. The UID for "iris owner" is 52773.

Is there a way to set the UID and Group to "iris owner" ?

regards Matthias