Article
· Jun 12, 2023 3m read
LangChain fixed the SQL for me

This article is a simple quick starter (what I did was) with SqlDatabaseChain.

Hope this ignites some interest.

Many thanks to:

sqlalchemy-iris author @Dmitry Maslennikov

Your project made this possible today.

The article script uses openai API so caution not to share table information and records externally, that you didn't intend to.

A local model could be plugged in , instead if needed.

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GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.

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Hi Developers, I'm currently doing a demo about building a front end UI doing data analytics and setup a performance test with large data objects, therefore using "Populate Utility" could help me auto generate some sample data that I can play with.

Within this post I would like to share my experience of using Populate Utility, including using POPSPEC Parameter.

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Article
· Jun 19, 2023 8m read
Open AI integration with IRIS

As you all know, the world of artificial intelligence is already here, and everyone wants to use it to their benefit.

There are many platforms that offer artificial intelligence services for free, by subscription or private ones. However, the one that stands out because of the amount of "noise" it made in the world of computing is Open AI, mainy thanks to its most renowned services: ChatGPT and DALL-E.

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It seems like yesterday when we did a small project in Java to test the performance of IRIS, PostgreSQL and MySQL (you can review the article we wrote back in June at the end of this article). If you remember, IRIS was superior to PostgreSQL and clearly superior to MySQL in insertions, with no big difference in queries.

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Intro

In a fast-paced digital era, effective communication is crucial. This article introduces a Java-based chat project, combining the strength of IRIS database and ChatGPT intelligence. Built on Java, it goes beyond real-time messaging, leveraging IRIS and ChatGPT for an enhanced chat experience. Also, the name of the project references the cultural classic - Star Wars.

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Article
· Feb 1 2m read
Mind map your FHIR patient data

According Wikipedia a mind map is a diagram used to visually organize information into a hierarchy, showing relationships among pieces of the whole. It is often created around a single concept, drawn as an image in the center of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those major ideas.

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Hi Community,

This is my first post in the developer community - would appreciate any feedback!

For testing or demo purposes, you may want to send emails from your Interoperability Production. In this post then I will walk you through connecting an InterSystems IRIS Production to Gmail so you can use it to send emails alerts.

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Introduction

Visual Studio Code (VS Code) is a free source code editor made by Microsoft for Windows, Linux, and macOS. It provides built-in support for JavaScript, TypeScript, and Node.js. You can add extensions to provide support for numerous other languages including ObjectScript.

The InterSystems extensions enable you to use VS Code to connect to an InterSystems IRIS server and develop code in ObjectScript. The Visual Studio Code Documentation is an excellent resource on VS Code, so it is a good idea to be familiar with it.

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For the upcoming Python contest, I would like to make a small demo, on how to create a simple REST application using Python, which will use IRIS as a database. Using this tools

  • FastAPI framework, high performance, easy to learn, fast to code, ready for production
  • SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL
  • Alembic is a lightweight database migration tool for usage with the SQLAlchemy Database Toolkit for Python.
  • Uvicorn is an ASGI web server implementation for Python.

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Article
· Aug 16, 2023 11m read
Http request response time monitoring

Hi developers!

Today I would like to address a subject that has given me a hard time. I am sure this must have been the case for quite a number of you already (so-called “the bottleneck”). Since this is a broad topic, this article will only focus on identifying incoming HTTP requests that could be causing slowness issues. I will also provide you with a small tool I have developed to help identify them.

Our software is becoming more and more complex, processing a large number of requests from different sources, be it front-end or third-party back-end applications. To ensure optimal performance, it is essential to have a logging system capable of taking a few key measurements, such as the response time, the number of global references and the number of lines of code executed for each HTTP response. As part of my work, I get involved in the development of EMR software as well as incident analysis. Since user load comes mostly from HTTP requests (REST API or CSP application), the need to have this type of measurement when generalized slowness issues occur has become obvious.

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Motivation

The motivation behind the InterLang project is rooted in the innovative integration of LangChain chatbot agents with the Fast Healthcare Interoperability Resources (FHIR) framework to revolutionize conversational social prescriptions in healthcare. This project aims to leverage the rich and standardized data available through FHIR, an emerging standard in healthcare data exchange, to inform and empower these advanced chatbot agents.

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Article
· Nov 27, 2023 2m read
Generative AI for image creation

Currently, many digital artists use generative AI technology as a support to accelerate the delivery of their work. Nowadays it is possible to generate a corresponding image from a text sentence. There are several market solutions for this, including some available to be used through APIs. See some at this link: https://www.analyticsvidhya.com/blog/2023/08/ai-image-generators/.

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In recent versions of IRIS, a powerful new data loading command has been introduced to SQL: LOAD DATA. This feature has been highly optimized to import data into IRIS extremely fast, allowing hundreds of gigabytes of data to be inserted in seconds instead of hours or days.

This is a very exciting improvement. However, a big problem in the data loading experience still exists. Namely, the time and hassle it takes to:

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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?

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As an example of an application on Java working with Hibernate dialect for IRIS, wanted to use RealWorld application, and found realization for Quarkus. RealWorld application is an example of an application close to some real one, with already prepared tests for the backend. Most of the examples of realizations can be found here

RealWorld Example App

The RealWorld example application is often referred to as the "Wikipedia for building full-stack applications." It serves as a standardized prototype that developers can use to create applications using various programming languages and frameworks. The application provides a real-world use case by mimicking a blogging platform, complete with features like user authentication, profile management, article posting, and comments. With a comprehensive set of specifications, including ready-made backend API documentation and frontend designs, it allows developers to see how the same functional requirements are implemented across different technology stacks. The RealWorld example is widely used as a learning tool and a benchmark for comparing various technologies.

Quarkus

Quarkus is an open-source, Kubernetes-native Java framework tailored for the GraalVM and HotSpot. Created with the aim to enhance the modern cloud-native environment, it significantly reduces the footprint and startup time of Java applications. Quarkus is known for its "container-first" philosophy, allowing developers to build lightweight, high-performing applications with a focus on microservices architecture. This flexibility has made it a popular choice for organizations looking to transition into serverless or cloud-based platforms, combining both imperative and reactive programming models. Whether it's a traditional web application or a complex system of microservices, Quarkus provides a robust platform for building scalable and maintainable software.

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As a former JAVA developer it has always been a challenge to decide which database was the most suitable for the project we were going to develop, one of the main criteria I used was their performance, as well as their HA configuration capabilities ( high availability). Well, now is the time to put IRIS to the test with respect to some of the most commonly used databases, so I've decided to create a small Java project based on SpringBoot that connects via JDBC with a MySQL database, another of PostgreSQL and finally with IRIS.

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