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/.

I created a new application to use in IRIS taking advantage of one of these APIs.I chose the Imagine API.

Hey Community,

Click play and immerse yourself in our fresh video on InterSystems Developers YouTube:

⏯ Adaptive Analytics in Action - Two Customer Use Cases @ Global Summit 2023

A "big" or "small" ask for ChatGPT?

I tried OpenAI GPT's coding model a couple of weeks ago, to see whether it can do e.g. some message transformations between healthcare protocols. It surely "can", to a seemingly fair degree. 
It has been nearly 3 weeks, and it's a long, long time for ChatGPT, so I am wondering how quickly it grows up by now, and whether it could do some of integration engineer jobs for us, e.g. can it create an InterSystems COS DTL tool to turn the HL7 into FHIR message? 

Immediately I got some quick answers, in less than one minute or two.

Test

First I want to test I am talking

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.

Creating a new virtual environment

python -m venv .

Hello Community,

Let us invite you to watch the recording of the webinar: 

👉 Developing an AI Powered IRIS Application, in Python 👈

Hi folks

I want to tell you how you can make your own assistant based on IRIS and OpenAI (perhaps you can then move to your own AI models)

iris-recorder-helper

This is the first time I have fully tried developing an application for IRIS and I want to point out steps that may also be useful to you

1. Deploy to google cloud via github workflows (One container with an IRIS database and a web server in Python (flask)) and placing secrets inside the application not through an environment variable
2. Record audio from the browser and send to the server
3. Launching cron jobs via the ZPM module
4. Integration

Yet another example of applying LangChain to give some inspiration for new community Grand Prix contest.

I was initially looking to build a chain to achieve dynamic search of html of documentation site, but in the end it was simpler to borg the static PDFs instead.

Create new virtual environment

mkdir chainpdf

cd chainpdf

python -m venv .

scripts\activate 

pip install openai
pip install langchain
pip install wget
pip install lancedb
pip install tiktoken
pip install pypdf

set OPENAI_API_KEY=[ Your OpenAI Key ]

python

Prepare the docs

import glob
import wget;

Hi Community
In this article, I will introduce my application IRIS-GenLab.
IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.

Application Features

• User registration and authentication
• Chatbot functionality with the help of Torch (python machine learning library)
• Named entity recognition (NER), natural language processing (NLP) method for text information extraction
• Sentim

The latest Node.js Weekly newsletter included a link to this article:

https://thecodebarbarian.com/getting-started-with-vector-databases-in-n…

I'm wondering if anyone has been considering or actually using IRIS as a vector database for this kind of AI/ChatGPT work?

FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

Introducing the FHIR - AI and OpenAPI Chain application, a solution that allows users to interact with FHIR APIs using natural language queries. Built with OpenAI,

Our next Developer Meetup will take place on July 26, 17:30 pm at the CIC Venture Café in Cambridge.

Join us to learn Generative AI Use Cases + Reference Architecture in Healthcare, witness the demo of LLMs in Healthcare and share your thoughts on the topic.

RSVP here

As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:

• Users prompts
• Execution errors

In order to extract useful data to apply analytics, we used the iknowpy library - an opensource library for Natural Language Processing based in the iKnow for IRIS Data Platform. It makes possible identifies entities (phrases) and their semantic context in natural language text in several languages.

Here it's used to extract concepts from data of

Previous post - Using AI to Simplify Clinical Documents Storage, Retrieval and Search

This post explores the potential of OpenAI's advanced language models to revolutionize healthcare through AI-powered transcription and summarization. We will delve into the process of leveraging OpenAI's cutting-edge APIs to convert audio recordings into written transcripts and employ natural language processing algorithms to extract crucial insights for generating concise summaries.

While existing solutions like Amazon Medical Transcribe and MedVoice offer similar capabilities, the focus of this post will be

The continuing convergence of AI technologies and healthcare systems has brought forward many compelling advancements. Let's set the scene. If you have interacted with dynamic models like ChatGPT, you might have, like many of us, begun to envision its application using your unique datasets. Suppose in the healthcare sector you wish to link this technology with Electronic Health Records (EHR) or Electronic Medical Records (EMR), or perhaps you aim for heightened interoperability using FHIR's resources.  It all boils down to how we transfer/receive contextual-data to/from LLMs available in

This project is an experiment to use OpenAI API to answer to user prompts in the healthcare domain using FHIR resources and Python code.

<iframe width="560" height="315" src="https://www.youtube.com/embed/WDTG5_SVvTg" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>

Project idea

Generative AIs, like the LLM models available on OpenAI, has been demonstrated remarkable power to understand and answer high level questions.

Hi colleagues!

InterSystems Grand Prix 2023 unites all the key features of InterSystems IRIS Data Platform!

Thus we invite you to use the following features and collect additional technical bonuses that will help you to win the prize!

Here we go!

• LLM AI or LangChain usage: Chat GPT, Bard and others - 6
• InterSystems FHIR SQL Builder- 5
• InterSystems FHIR - 3
• IntegratedML - 4
• Native API - 3
• Embedded Python - 4
• Interoperability - 3
• Production EXtension(PEX) - 2
• Adaptive Analytics (AtScale) Cubes usage - 3
• Tableau, PowerBI, Logi usage - 3
• InterSystems IRIS BI - 3 
• Columnar Index Usage - 1
• Docker container usage - 2 
• ZPM Package deployment - 2
• Online Demo - 2
• Unit Testing - 2
• Implement InterSystems Community Idea - 4
• First Article on Developer Community - 2
• Second Article On DC - 1
• Code Quality pass - 1
• First Time Contribution - 3
• Video on YouTube - 3

Problem

In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.

Motivation

AI has made document search remarkably powerful. Question and answering over docs has never been easier with open-source tools like Chroma and Langchain to store and use vector embeddings to query across Generative AI APIs.

As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:

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.

What is Open AI?

Open AI is a non-profit AI research laboratory launched in 2015 by Sam Altman, Ilya Sutskever, Greg Brockman, Wojciech Zaremba, Elon Musk, John Schulman and Andrej Karpathy with

Demonstration example for the current Grand Prix contest for use of a more complex Parameter template to test the AI.

Interview Questions

There is documentation. A recruitment consultant wants to quickly challenge candidates with some relevant technical questions to a role.

Can they automate making a list of questions and answers from the available documentation?

Interview Answers and Learning

One of the most effective ways to cement new facts into accessible long term memory is with phased recall.

In essence you take a block of text information, reorganize it into a series of self-contained

Hi Community, 

We invite you to join our next Developer Meetup in Boston: What happens next? Demos of the Latest Predictive Analytics technology.

Date: Monday, June 26, 2023 at 5:30 PM - 7:30 PM
Location: Venture Café Cambridge

>> RSVP here <<

Posing a question to consider during the current Grand Prix competition.

I wanted to share an observation about using PDFs with LangChain.

When loading the text out of a PDF, I noticed there was an artifact of gaps within some of the words extracted.

For example (highlighted in red)

Hi Community!

Just want to share with you an exercise I made to create "my own" chat with GPT in Telegram.

It became possible because of two components on Open Exchange: Telegram Adapter by @Nikolay Solovyev and IRIS Open-AI by  @Kurro Lopez 

So with this example you can setup your own chat with ChatGPT in Telegram. 

Let's see how to make it work!

On this GitHub you can find all the information on how to use a HuggingFace machine learning / AI model on the IRIS Framework using python.

1. iris-huggingface

Usage of Machine Learning models in IRIS using Python; For text-to-text, text-to-image or image-to-image models.

Here, models as example :

• https://huggingface.co/gpt2

• https://huggingface.co/Jean-Baptiste/camembert-ner

• https://huggingface.co/bert-base-uncased

• https://huggingface.co/facebook/detr-resnet-50

• https://huggingface.co/facebook/detr-resnet-50-panoptic

• 1. iris-huggingface

• 2. Installation

  • 2.1. Starting the Production
  • 2.

Hi Community!

Please welcome a new video on InterSystems Developers YouTube Channel:

Getting Sharded with InterSystems IRIS

Here're the technology bonuses for the InterSystems IRIS Cloud SQL and IntegratedML Contest 2023 that will give you extra points in the voting:

• IntegratedML usage
• Online Demo
• Article on Developer Community
• The second article on Developer Community
• Video on YouTube
• First Time Contribution
• Community Idea Implementation
• IRIS Cloud SQL Survey

See the details below.

Hey Developers,

We'd like to invite you to join our next contest dedicated to creating AI/ML solutions that use Cloud SQL to work with data: 

🏆 InterSystems IRIS Cloud SQL and IntegratedML Contest 🏆

Duration: April 3 - April 23, 2023

Prize pool: $13,500

​Keywords: ChatGPT, COS, Lookup Table, IRIS, AI 

Purpose

Here is another quick note before we move on to GPT-4 assisted automation journey. Below are some "little" helps ChatGPT had already been offering,  here and there, during daily works. 

And what could be the perceived gaps, risks and traps to LLMs assisted automation, if you happen to explore this path too. I'd also love to hear anyone's use cases and experiences on this front too. 

Lookup tables

One of the simplest tasks could be Lookup tables.

Fun or No Fun - how serious is it?

Large language models are stirring up some phenomena in recent months. So inevitably I was playing ChatGPT too over last weekend, to probe whether it would be a complimentary to some BERT based "traditional" AI chatbots I was knocking up, or rather would it simply sweep them away. 
A thought comes to mind while playing.By going slightly theoretical or philosophical, eventually interoperability standards such as HL7 and FHIR etc are kind of "languages", right?HL7 has its own grammar, rules, vocabulary and even dialects - every system speaks its own tone.

Morning all,

I got access to the new Bing this morning and thought I would try out some things on it. Below are a series of screenshots of what I searched and the results.
Please share your experiences here too.

   Searching for help with arrays:

  A search for a Python related topic: