Hi,

It's me again😁, recently I am working on generating some fake patient data for testing purpose with the help of Chat-GPT by using Python. And, at the same time I would like to share my learning curve.😑

1st of all for building a custom REST api service is easy by extending the %CSP.REST

Creating a REST Service Manually

Let's Start !😂

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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ SMART on FHIR: Introduction & FHIR Server Setup

https://www.youtube.com/embed/OHaZ5qiyQ1c
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Hi Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Integrating DBT and Apache Airflow with InterSystems IRIS @ Global Summit 2024

https://www.youtube.com/embed/tFHSoqZpA88
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Hi Developers!

Here're the technology bonuses for the InterSystems AI Programming Contest: Vector Search, GenAI and AI Agents that will give you extra points in the voting:

  • Agent AI solution - 5
  • Vector Search usage - 4
  • Embedded Python - 3
  • LLM AI or LangChain usage: Chat GPT, Bard, and others - 3
  • IntegratedML usage - 3
  • Docker container usage - 2
  • ZPM Package deployment - 2
  • Online Demo - 2
  • Implement InterSystems Community Idea - 4
  • Find a bug in Vector Search, or Integrated ML, or Embedded Python - 2
  • First Article on Developer Community - 2
  • Second Article On DC - 1
  • First Time Contribution - 3
  • Video on YouTube - 3
  • Suggest a new idea - 1

See the details below.<--break->

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In the previous article, we saw how to build a customer service AI agent with smolagents and InterSystems IRIS, combining SQL, RAG with vector search, and interoperability.

In that case, we used cloud models (OpenAI) for the LLM and embeddings.

This time, we’ll take it one step further: running the same agent, but with local models thanks to Ollama.

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Dear Community members,

We are currently performing technical work, and during this time, you may experience issues with the Developer Community portal, Developer Community AI, and search functionality:

🔹 Ask DC AI is temporarily unavailable
🔹 Search may take longer than usual or may not return results
🔹 You may experience problems with logging into the Developer Community and Open Exchange

We’re working to restore full functionality as quickly as possible. Thank you for your patience and understanding.

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Article
· Oct 10, 2025 9m read
IRIS install automation using Ansible

Deploying new IRIS instances can be a time-consuming task, especially when setting up multiple environments with mirrored configurations.

I’ve encountered this issue many times and want to share my experience and recommendations for using Ansible to streamline the IRIS installation process. My approach also includes handling additional tasks typically performed before and after installing IRIS.

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A step by step implementation path to a cross regional stretched IrisCluster with Mirroring using the Intersystems Kubernetes Operator (IKO), Google Cloud Platform, and Tailscale.

I am giving this distraction the code name "Compliment Sandwich" for a reason yet to be realized, but I'd rather the community go right for the jugular shooting holes in a solution that implements wireguard based connectivity for our workloads in general, as I would like to refine it as a fall project leading up to KubeCon in Atlanta and if I miss the mark, Ill get it done before Amsterdam.

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Hi Community,

We're excited to share the new video in the "Rarified Air" series on our InterSystems Developers YouTube:

⏯ Leading with Empathy: The Human Side of Customer Centricity

https://www.youtube.com/embed/qIb43czL9LY
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img

This will be a short article about Python dunder methods, also known as magic methods.

What are Dunder Methods?

Dunder methods are special methods in Python that start and end with double underscores (__). They allow you to define the behavior of your objects for built-in operations, such as addition, subtraction, string representation, and more.

Some common dunder methods include:

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Hi Community!

Check out the new video on how to build the frontend UI by prompting it in lovable or (potentially) any spec first REST API in InterSystems IRIS:

📺 Prompt the frontend UI for InterSystems IRIS with Lovable

🗣 Presenter: @Evgeny Shvarov, Senior Manager of Developer and Startup Programs, InterSystems

https://www.youtube.com/embed/Oo4OBfTf4d4
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Hi Community!

Thank you to everyone who participated in the "Help Us Improve the DC Search" sweepstakes! Your feedback is invaluable in making the Developer Community better, and we will use it to improve our search. Now, it's time to announce the winner - watch the video to see the sweepstake drawing:

https://www.youtube.com/embed/SXS9F0McVsM
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In the previous article, we talked about ODBC and connecting from C#. And now, let's look at JDBC and Java. The InterSystems JDBC driver is the recommended, high-performance way to integrate your Java applications.

Here is a step-by-step guide to getting your Java application connected to an IRIS instance using the JDBC driver.

Step 1: Obtain and Include the InterSystems IRIS JDBC Driver

Unlike ODBC drivers, which are often installed system-wide, JDBC drivers are typically distributed as JAR files that must be included in your Java project's classpath.

If InterSystems IRIS is installed on your local machine or another you have access to, you can find the file in install-dir/dev/java/lib/ or similar, where install-dir is the installation directory for the instance. Conversely, you can download the jar file from Driver packages page.

Or as suggested by @Dmitry Maslennikov in the comments, use the maven central repository for Maven:

<dependency>
    <groupId>com.intersystems</groupId>
    <artifactId>intersystems-jdbc</artifactId>
    <version>3.10.5</version>
</dependency>

or for Gradle:

implementation("com.intersystems:intersystems-jdbc:3.10.5")

Include the jar file in Project:

  • Maven/Gradle: If you use a build tool, the simplest method is to add the InterSystems JDBC driver as a dependency in your pom.xml or build.gradle file. This automatically downloads and manages the JAR.
  • Manual: For simple projects, you must place the JAR file in a project directory (e.g., /lib) and explicitly add it to your classpath when compiling and running.

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Article
· Mar 31, 2025 2m read
Operate the database through dialogue

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.

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Modern SQL engines are enormously complex pieces of software. Even when they appear stable and mature, subtle bugs can hide in their optimizers, type systems, predicate evaluation, or execution layers. These bugs rarely announce themselves loudly. Instead, they quietly produce incorrect results, behave inconsistently, or fail abruptly under specific combinations of SQL constructs.

This is precisely why tools like SQLancer exist. SQLancer automatically generates SQL queries and uses logical “oracles” to detect when a database behaves incorrectly. It has revealed hundreds of real bugs in widely used systems such as MySQL, PostgreSQL, SQLite, and DuckDB.

With this in mind, I attempted to bring SQLancer to InterSystems IRIS, starting with the NOREC oracle — a powerful method for detecting optimizer correctness issues. The journey, however, uncovered not just potential SQL correctness problems, but also a surprising number of driver-level and server-level failures that prevented SQLancer from running at full strength.

This article summarizes why SQLancer is important, how the NOREC oracle works, and what unexpected findings appeared while testing IRIS.

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Hi,

Just thought I'd share quite a handy hook that has helped me out when developing on Health Connect Cloud with VS Code and GitBash. When developing on Health Connect Cloud, if changes are made directly on the server such as routing rules or component deployments, they aren't automatically included in source control, therefore you must export from the server into your local files and push to your remote repo. I'm sure there are easier methods to deal with that which I'm in the process of testing, but as a quick solution I thought it would be handy have a pre-commit hook which triggers a reminder in GitBash - see below.

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Question
· Sep 16, 2025
HL7 Pass-through interface

For historic reasons we've got a mix of ADT feeds coming out of our PAS (TrakCare) to a wide range of downstream systems. In particular, there are some that are direct from TrakCare to the downstream systems, and many more that pass through Ensemble as our integration engine.

This is complicating management of the integrations, and so we'd like everything to go through the integration engine. In other words move from the flow in the top of the diagram to the flow in the bottom of the diagram:

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