#Open Exchange

Profiling CCD Documents with LEAD North’s CCD Data Profiler
Ever opened a CCD and been greeted by a wall of tangled XML? You’re not alone. Despite being a core format for clinical data exchange, CCD's are notoriously dense, verbose, and unfriendly to the human eye. For developers and analysts trying to validate their structure or extract meaningful insights, navigating these documents can feel more like archaeology than engineering.

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.

There are a lot of great community articles regarding "vector search on IRIS", and samples in OpenExchange. Everytime I see these, I'm so excited to know that so many developers already try vectors on IRIS!

But if you've not tried "Vector Search on IRIS" yet, please give me one minute 😄 I create one IRIS class - and with only one IRIS class you can see how you put vector data in your IRIS database and how you compare these in your application.

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

https://community.intersystems.

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.

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.

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?

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

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:

File "/irisdev/app/src/python/rag/app.py", line 28, in process_input agent_text = _service.ask(user_text, rag_enabled) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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 need to add an extra blank OBX segment after a segment containing text, Total Cost:

I get the OBX segment but it is in incorrect location.

It should be after the line containing Total Cost:

It needs to contain:

OBX|1|TX|2000.02^REASON FOR REQUEST^AS4|

code:

    //Do pOutput.SetValueAt(tOBXText_"~~","ORCgrp(1).OBRuniongrp.OBXgrp("_i_").OBX:5","set") //
         If (tOBXText[ "Total Cost:") {
             Set tSegmentOBX = ##class(EnsLib.HL7.Segment).%New()
             Set tSegmentOBX.SegType = "2.3:OBX"
             Set tSC = tSegmentOBX.SetValueAt("OBX", 0, "set")
             Set tSC = pOutput.

Hi Community,

I would like to present my last package OpenAPI-Suite, this is a set of tools to generate ObjectScript code from an OpenAPI specification version 3.0.  In short, these packages allow to: 

• Generate server-side class.  It’s pretty similar to the generated code by ^%REST but the added value is the version 3.0 support.
• Generate HTTP client classes.
• Generate client production (business services, business operation, business process, Ens.Request, Ens.Response) classes.
• A web interface to generate and download the code or generate and compile directly on the server.
• Convert specification from version 1.x, 2.x to version 3.0.

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 

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.

Prompt

Firstly, we need to understand what prompt words are and what their functions are.

Prompt Engineering

Hint word engineering is a method specifically designed for optimizing language models.
Its goal is to guide these models to generate more accurate and targeted output text by designing and adjusting the input prompt words.

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.

Hello there 🙋‍♂️,

I'm looking towards a functionality alike Python's difflib, but made with Intersystems products. I already know could embed Python code within IRIS but thought maybe there was a development already done for handling deltas, with a different approach or extra utils.

Even if I find such a library after comparing both might still go with difflib or any other more suitable. Intend to use it for a cross-environment checklist/check tool.

Please find below a sample of HTML rendering computed and made with difflib, with a few lines of code:

thanks ! best regards,  

By extending %XML.Adaptor, we can use

Parameter XMLIGNORENULL   

to handle empty tags in output xml file from %Persistent. But this parameter only applies to %String property. What if a class has other types of properties, like %Stream (for holding large chunk of data). What is the recommended handle if we cannot use XMLIGNORENULL here?

Context: In change control, exported .xml file is important to make diff between versions.

Hello!

This article is a small overview of a tool that helps to understand classes and their structure inside the InterSystems products: from IRIS to Caché, Ensemble, HealthShare.

In short, it visualizes a class or an entire package, shows the relations between classes and provides all the possible information to developers and team leads without making them go to Studio and examine the code there.

If you are learning InterSystems products, reviewing projects a lot or just interested in something new in InterSystems Technology solutions — you are more than welcome to read the overview of ObjectScript Class Explorer!

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:

It's been a while since I've posted about Embedded Git on the Developer Community, and I'd like to provide an update on the massive amount of work we've done this year and where we're going next.

Context

If you're building solutions on IRIS and want to use Git, that's great! Just use VSCode with a local git repo and push your changes out to the server - it's that easy.

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.

The latest "Bringing Ideas to Reality" InterSystems competition saw me trawling through the ideas portal for UI problems to have a go at. 

In principle I'm looking in forward direction.
Though from time to time it makes sense to turn back and see the full path taken.

• I started reporting my reviews almost 4 years ago. 
• I just reviewed packages that I could reproduce in my environment.
• Skipping items beyond my physical or mental capacities.
• So some great packages might not be present here
• But I added also 139 contributions of other reviewers
• It was anyhow a total of  769 reviews published
• Meeting over this time 191 different authors