I decided to write this down before time wiped out my memory It's a very personal story as a partner, as a competitor, as an employee, as a customer and finally as an external observer of InterSystems.
This guideline provides an overview of how to design and implement a REST API interface for querying patient demographic data from an Electronic Patient Record (EPR) system using HealthConnect. The process involves sending a query request with the patient's identification number, retrieving the response from the EPR system, extracting the required patient demographic data from the HL7 message, and sending it as a JSON response to the supplier. The high-level process diagram is shown below (Screenshot 1).
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.
# IRIS-Intelligent Butler IRIS Intelligent Butler is an AI intelligent butler system built on the InterSystems IRIS data platform, aimed at providing users with comprehensive intelligent life and work assistance through data intelligence, automated decision-making, and natural interaction. ## Application scenarios adding services, initializing configurations, etc. are currently being enriched ## Intelligent Butler
If you want to know if a class about a topic already exists asking a simple natural language question, it is possible now. Download and run the application https://openexchange.intersystems.com/package/langchain-iris-tool to know all about your project classes in a Chat.
As part of the development an API to know what is the instance of IRIS is connected, I've found some methods to know information about the server that can help you.
Get the server name: $SYSTEM.INetInfo.LocalHostName()
Get the server IP: $SYSTEM.INetInfo.HostNameToAddr($SYSTEM.INetInfo.LocalHostName())
I just realized I never finished this serie of articles!
In today's article, we'll take a look at the production process that extracts the ICD-10 diagnoses most similar to our text, so we can select the most appropriate option from our frontend.
Looking for diagnostic similarities:
From the screen that shows the diagnostic requests received in HL7 in our application, we can search for the ICD-10 diagnoses closest to the text entered by the professional.
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.
As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.
The complex record mapper can help you process text file data consisting of various types of records to persistent messages in IRIS. To gain a basic understanding of the complex record mapper and see an example implemented in the production, check out the learning services video below:
I'm very excited to share with you some highlights from yesterday, from UK&I Data Summit in Birmingham! There are exciting announcements, FREE tickets to the Summit and much more, so read on!
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.
A button on a web page can capture the users voice. IRIS integration could manipulate the recordings to extract semantic meaning that IRIS vector search can then offer for new types of AI solution opportunity.
As an IT and cloud team manager with 18 years of experience with InterSystems technologies, I recently led our team in the transformation of our traditional on-premises ERP system to a cloud-based solution. We embarked on deploying InterSystems IRIS within a Kubernetes environment on AWS EKS, aiming to achieve a scalable, performant, and secure system. Central to this endeavor was the utilization of the AWS Application Load Balancer (ALB) as our ingress controller.
Since the introduction of Embedded Python there has always been doubt about its performance compared to ObjectScript and on more than one occasion I have discussed this with
With the introduction of vector data types and the Vector Search functionality in IRIS, a whole world of possibilities opens up for the development of applications and an example of these applications is the one that I recently saw published in a public contest by the Ministry of Health from Valencia in which they requested a tool to assist in ICD-10 coding using AI models.
How could we implement an application similar to the one requested? Let's see what we would need:
In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.
This is a quickstart guide to IRIS for Linux systems administrators who need to be able to support the IRIS DB as well as other normal infrastructure tasks.
IRIS is a DB system from Intersystems. An IRIS DB can hold code (in the form of a Class) or data (in the form of Globals). IRIS DB are Linux files called IRIS.DAT.
The FHIR standard establishes a powerful but flexible data model that can smoothly adapt to the complexities of operational healthcare data management. This flexibility comes at the cost of a data model with many tables and relationships, even for simple data such as the patient's record of telephone numbers, addresses, and emails. It would easily require querying 4 different tables. However, FHIR SQL Builder eliminates this problem, allowing you to create visual projections (mappings) in web wizards.
The InterSystems IRIS data platform underlies all InterSystems applications, as well as thousands of customer and partner applications across Healthcare, Financial Services, Supply Chain, and other ecosystems. It is a converged platform, providing transactional-analytical data management, integrated interoperability, and data integration, as well as integrated analytics and AI. It supports the InterSystems Smart Data Fabric approach to managing diverse and distributed data.
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:
Have you ever been editing files in VS Code, but needed to check a global value or run a few ObjectScript commands? Now you can, with no setup required! If you have vscode-objectscript extension version 2.10.0 or later and are connected to InterSystems IRIS 2023.2 or later, you can now open a terminal connection to your server, regardless of where it's located.
For programmers new to ObjectScript, one question will inevitably arise: “What is the difference between methods and class methods?” A typical answer would be: “A class method applies to a class, but a method applies to an instance of that class.” While that answer is correct, it lacks important information on how these methods di
By update
Open Exchange app.png)
.png)
.png)
.png)
.png)
