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Generative artificial intelligence is artificial intelligence capable of generating text, images or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics.

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· Mar 25 7m read
Introduction to Kubernetes

In this article, we will cover below topics:

  • What is Kubernetes?
  • Main Kubernetes (K8s) Components


What is Kubernetes?

Kubernetes is an open-source container orchestration framework developed by Google. In essence, it controls container speed and helps you manage applications consisting of multiple containers. Additionally, it allows you to operate them in different environments, e.g., physical machines, virtual machines, Cloud environments, or even hybrid deployment environments.

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Hi Community!

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 we need to build a custom ChatGPT AI by using LangChain Framework:

Below are the steps to build a custom ChatGPT:

  • Step 1: Load the document

  • Step 2: Splitting the document into chunks

  • Step 3: Use Embedding against Chunks Data and convert to vectors

  • Step 4: Save data to the Vector database

  • Step 5: Take data (question) from the user and get the embedding

  • Step 6: Connect to VectorDB and do a semantic search

  • Step 7: Retrieve relevant responses based on user queries and send them to LLM(ChatGPT)

  • Step 8: Get an answer from LLM and send it back to the user

For more details, please Read this article

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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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Sometimes we need to convert FHIR message to HL7 V2, e.g. to register a patient to the PACS system.
In this article, I will explain the steps to achieve the desired by using IRIS FHIR Server production.

Below are the steps we need to follow:

  1. Make sure FHIRServer production is started.
  2. Register Business Service with FHIRServer endpoint.
  3. Define Business Processes to convert FHIR message to SDA and then Convert SDA to HL7 v2.
  4. Post JSON resource to FHIRServer endpoint and get HL7 V2 response.

Let's review the steps in detail.

Step 1. Make sure FHIRServer production is started

Open the production page and make sure Production is started. In the next step, we need to make sure business service HS.FHIRServer.Interop.Service is registered with FHIRServer

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In the context of HL7 FHIR (Fast Healthcare Interoperability Resources), the terms "id" and "identifier" refer to specific elements used for identifying resources within the FHIR data model. For a newbie, these terms can be confusingly similar, but they serve distinct purposes.

Look at the below Patient resource for August T. Faulkner:

The resource has an id of “1” — generated by the FHIR server when the resource was created.
Patient August T. Faulkner also has a identifier (Medical Record Number) — possibly provided by the hospital — of 78510398960

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Hi, Community!

Since this article is an overview of Flask Login, let's begin with Flask Introduction!

What is Flask?

In the realm of web development, Python has emerged as a formidable force, offering its versatility and robustness to create dynamic and scalable applications. For that reason, tools and services compatible with this language are in demand these days. Flask is a lightweight and easy-to-use web framework for Python. It stands out as a lightweight and user-friendly option. Its simplicity and flexibility have made it a popular choice for developers, particularly for creating smaller-scale applications. It is based on the Werkzeug toolkit and provides a simple but powerful API for building web applications.
Unlike its full-stack counterparts, Flask provides a core set of features, focusing on URL routing, template rendering, and request handling. This minimalist approach makes Flask lightweight and easy to learn, allowing developers to build web applications quickly and without the burden of unnecessary complexity.

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Hi, Community!

This article is an overview of SQLAlchemy, so let's begin!

SQLAlchemy is the Python SQL toolkit that serves as a bridge between your Python code and the relational database system of your choice. Created by Michael Bayer, it is currently available as an open-source library under the MIT License. SQLAlchemy supports a wide range of database systems, including PostgreSQL, MySQL, SQLite, Oracle, and Microsoft SQL Server, making it versatile and adaptable to different project requirements.

The SQLAlchemy SQL Toolkit and Object Relational Mapper from a comprehensive set of tools for working with databases and Python. It has several distinct areas of functionality which you can use individually or in various combinations. The major components are illustrated below, with component dependencies organized into layers:

_images/sqla_arch_small.png

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image

Hi Community,
In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • Step1: Install required libraries

  • Step2: Create patterns and responses file

  • Step3: Train the Model

  • Step4: Create ChatBot Application based on the trained model

So Let us start.

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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.

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Hi Community,

In my previous article, we learned topics listed below:

  1. What is Docker?
  2. Some of the Docker benefits
  3. How does Docker work?
  4. Docker Image
  5. Docker Container
  6. Docker Image repository
  7. InterSystems's Docker image repository
  8. Docker Installation
  9. Docker Basic Commands
  10. Running IRIS community edition by using Docker
  11. Docker Desktop GUI

In this article, we will cover the following topics:

  1. Use of Docker Compose file (a YAML file)
  2. Use of Docker file (employed to build a Docker image)
  3. Use of Docker volume

So let's begin.

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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:

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image

Hi Community

In this article, I will introduce my application irisChatGPT which is built on LangChain Framework.

First of all, let us have a brief overview of the framework.

The entire world is talking about ChatGPT and how Large Language Models(LLMs) have become so powerful and has been performing beyond expectations, giving human-like conversations. This is just the beginning of how this can be applied to every enterprise and every domain!

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