There are many applications for working with HL7 V2 messages, but the tools for working with XML in IRIS Management Portal and Cache Studio are limited.

IrisFirebase - FCM

Hi Community,

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

Iris-RAG-Gen is a generative AI Retrieval-Augmented Generation (RAG) application that leverages the functionality of IRIS Vector Search to personalize ChatGPT with the help of the Streamlit web framework, LangChain, and OpenAI. The application uses IRIS as a vector store.

Application Features

• Ingest Documents (PDF or TXT) into IRIS
• Chat with the selected Ingested document
• Delete Ingested Documents
• OpenAI ChatGPT

Hey Community,

More than 1000 applications are already available for everyone to download on the InterSystems Open Exchange.

And now it's time to announce the best developers and the most downloaded apps of 2024!

Let's take a closer look at our heroes and their apps:

Hi Community,

In this article, I will introduce my application iris-HL7v2Gen .

IRIS-HL7v2Gen is a CSP application that facilitates the dynamic generation of HL7 test messages. This process is essential for testing, debugging, and integrating healthcare data systems. The application allows users to generate a wide variety of HL7 message types, validate their structure against HL7 specifications, explore the message hierarchy, and transmit messages over TCP/IP to production systems. These features are particularly useful in settings where compliance with HL7 standards is mandatory for interoperability between different healthcare organizations or systems.

Application Features

• Dynamic HL7 Message Generation: Instantly create HL7 messages for a range of message types, facilitating comprehensive testing.
• Message Structure Exploration: Visualize the structure of generated messages based on HL7 specifications.
• Value Set Visualization View predefined sets of allowable coded values for specific fields.
• Message Validation: Validate messages against HL7 standards to ensure compliance.
• TCP/IP Communication: Easily transmit messages to production using TCP/IP settings.
• Broad Message Type Support: Supports 184 different HL7 message types, ensuring versatility for various healthcare integration needs.
• ClassMethod: Generate a Test Message by Invoking a Class Method
• Version Support: Currently Supports HL7 Version 2.5

Hi Community,

Traditional keyword-based search struggles with nuanced, domain-specific queries. Vector search, however, leverages semantic understanding, enabling AI agents to retrieve and generate responses based on context—not just keywords.

This article provides a step-by-step guide to creating an Agentic AI RAG (Retrieval-Augmented Generation) application.

Implementation Steps:

1. Create Agent Tools
   • Add Ingest functionality: Automatically ingests and index documents (e.g., InterSystems IRIS 2025.1 Release Notes).
   • Implement Vector Search Functionality
2. Create Vector Search Agent
3. Handoff to Triage (Main Agent)
4. Run The Agent

In this article I will be discussing the use of an alternative LLM for generative IA. OpenIA is commonly used, in this article I will show you how to use it and the advantages of using Ollama

In the generative AI usage model that we are used to, we have the following flow:

In this article, we’ll dive into the inner workings of the database management tool, exploring the architecture and technologies that power it. Understanding how the application functions behind the scenes will give you insight into its design, how it manages databases, tables, and how the API interacts with data.

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.

What is the reason for

RUN apt-get update && apt-get install -y \
git \
nano \
python3-opencv \
sudo && \
/bin/echo -e ${ISC_PACKAGE_MGRUSER}\\tALL=\(ALL\)\\tNOPASSWD: ALL >> /etc/sudoers && \
sudo -u ${ISC_PACKAGE_MGRUSER} sudo echo enabled passwordless sudo-ing for ${ISC_PACKAGE_MGRUSER}

I think I get error because I do not have sudo privilege in the environment where I use podman to build the image

podman build --tag oliver3 .

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-iris...

Now I see this:

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

I also placed a bunch of Pull Requests on GitHub when I found a problem I could fix.
Some were accepted and merged, and some were just ignored.
So if you made a major change and expect a changed review just let me know.

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

I also placed a bunch of Pull Requests on GitHub when I found a problem I could fix.
Some were accepted and merged, and some were just ignored.
So if you made a major change and expect a changed review just let me know.