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!

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.

Introduction

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.

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/.

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.

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.

TL;DR

This article introduces using the langchain framework supported by IRIS for implementing a Q&A chatbot, focusing on Retrieval Augmented Generation (RAG). It explores how IRIS Vector Search within langchain-iris facilitates storage, retrieval, and semantic search of data, enabling precise and up-to-date responses to user queries. Through seamless integration and processes like indexing and retrieval/generation, RAG applications powered by IRIS enable the capabilities of GenAI systems for InterSystems developers.

Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

​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.

What is Unstructured Data?
Unstructured data refers to information lacking a predefined data model or organization. In contrast to structured data found in databases with clear structures (e.g., tables and fields), unstructured data lacks a fixed schema. This type of data includes text, images, videos, audio files, social media posts, emails, and more.

In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions.

Artificial intelligence is not limited only to generating images through text with instructions or creating narratives with simple directions.

You can also make variations of a picture or include a special background to an already existing one.

Additionally, you can obtain the transcription of audio regardless of its language and the speed of the speaker.

So, let's analyze how the file management works.

Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

What if you could speak in a chat to check what happens in Interoperability, is there any errors, and even solve some types of issues.

With MCP server, you can connect any of your MCP Client, for instance Claude, to IRIS, and ask to check on Interoperability