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).

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 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 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:

✅ VS Code – Code editor
✅ Git – Version control system
✅ Docker – Runs an instance of IRIS for Health Community
✅ VS Code REST Client Extension – For running FHIR API queries
✅ Python – For writing FHIR-based scripts
✅ Jupyter Notebooks – For AI and FHIR assignments

Before you begin: Ensure you have administrator privileges on your system.

In addition to reading the guide, you can also follow the steps in the videos:

For Windows

https://www.youtube.com/embed/IyvuHbxCwCY
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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:

In this article I'll show you how to set up in your laptop, very quickly, a cluster of IRIS nodes in sharding. It's not the goal of this article neither to talk about sharding in detail nor define a deployment of a production ready architecture, but to show how to set up quickly, in your own machine, a cluster of IRIS instances configured as shard nodes, with which you'll able to play and test this functionality. If you're insterested in knowing more about sharding in IRIS, take a look at the documentation clicking here.

First and foremost, I want to remark that IRIS sharding will allow us 2 things:

• Define, load and query shard tables, which data will be distributed transparently between the cluster's nodes
• Define federated tables, which offer a global and composed view of data belonging to different tables that will be physically stored in different distributed nodes

So, as I said, we let for other article playing with shard or federated tables, and just focus now in the previous step, that is, setting up the cluster of shard nodes.

I have a flask application, its working locally. I also have a iris for health 2024.3 docker container front-ended with the iris nginx container.

Hello,

When setting up a new web app in iris (iris is in a container) iris complains that a WSGI framework is not installed. I have installed python into the container as well as both flask and django via the python virtual environment (see second screenshot) and the python language server is running

Is this the wrong way to install flask? How do I get the container version to recoginize that flask is installed?

Hi! I've extended my demo repository, andreas5588/demo-dbs-iris, to make it easy to test the FOREIGN SERVER and FOREIGN TABLE features in IRIS.

To achieve this, I created a namespace called FEDERATION. The idea is as follows:

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:

Hi fellow developers in InterSystems IRIS!

I'm often being asked, especially related to technical bonuses we encourage for every Open Exchange contest why do we constantly give bonuses for Docker, IPM and ObjectScript Quality pass.

In fact, this is very easy to answer.

Monitor incremental changes in the database through scheduled tasks, display change trends through charts, set alarm thresholds, and write information to messages.log

How to use it

You can install it through Docker or ZPM

Deploying with Docker Prerequisites

Make sure you have git and Docker desktop installed.

Hello,

The title says it all. I’m building an IRIS image with docker-compose using a separate Dockerfile. Pretty straightforward procedure: I import a Installer script inside the container containing a Installer Manifest I defined. Within the manifest, I create a namespace with code and data databases in separate locations. My intention is to keep the code database inside the container, so whenever I build the container, the imported code is replaced. The data, however, should be persistent.

iris-docker-multi-stage-script

A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !

TL;DR

Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final

ADD --chown=${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} https://github.com/grongierisc/iris-docker-multi-stage-script/releases/latest/download/copy-data.py /irisdev/app/copy-data.py

RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/copy-data.py -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!