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.

In this article we are going to see how we can use the WhatsApp instant messaging service from InterSystems IRIS to send messages to different recipients. To do this we must create and configure an account in Meta and configure a Business Operation to send the messages we want.

Let's look at each of these steps in more detail.

Setting up an account on Meta

This is possibly the most complicated point of the entire configuration, since we will have to configure a series of accounts until we can have the messaging functionality.

Hi everyone.

This is a full example how to use a %ScrollableResultSet for results pagination using %DynamicQuery:SQL and build a JSON response including page details.

Feel free to use, share, comment or improve it.

Kind Regards

JSON is a lightweight data interchange format for representing and exchanging data between a server and a web application. Its popularity has led to its widespread use in applications based on InterSystems technology, as well as demand for a converter that transforms globals to JSON and back. Therefore, @Evgeny Shvarov suggested developing Global->JSON->Global converter. Implementing such a converter is important to ensure interoperability, simplify data exchange, support web services, and provide a standardized approach to data representation across different software ecosystems. This article, the second in the "Implemented Ideas" series, focuses on several projects created by the legend of InterSystems Developer Community @Robert Cemper that deal with this task:

• GlobalToJSON-Compact
• GlobalToJSON-Efficient
• GlobalToJSON-Academic
• GlobalToJSON-embeddedPython
• GlobalToJSON-ePython-pure
• GlobalToJSON-XLA
• JSONfile-to-Global.

There is an interesting new feature in the recently announced 2024.1 preview, JSON_TABLE. JSON_TABLE is one of a family of functions introduced by the 2016 version of the SQL Standard (ISO Standard, published in early 2017). It allows for JSON values to be mapped to columns and queried using SQL. JSON_TABLE is valid in the FROM clause of some SQL statements.

The syntax of JSON_TABLE is quite large, allowing for exceptional conditions where the provided JSON values don't match expectations, nested structures and so on.

An App that converts HL7 messages to JSON objects. About a year ago I started a GitHub repo for collecting stuff related to HL7. Recently my team added an HL7 interface to our Interoperability Production and we were asked to persist HL7 messages. We created a Kafka topic to receive HL7 messages. We use Kafka Bridges to send messages to Kafka topics. Kafka messages are sent to the Kafka Bridge in JSON format.

Overview

In our previous post, we discussed the motivation for developing a chatbot agent with access to FHIR resources. In this post, we will dive into the high-level design aspects of integrating a Streamlit-based chat interface with a Java SpringBoot backend, and enabling a LangChain agent with access to FHIR (Fast Healthcare Interoperability Resources) via APIs.

Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.

Thus, at this point there are basically 3 main classes to work with JSON:

• %Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class like

set obj = ##class(%Library.DynamicObject).%New()

it is possible to use the following syntax

set obj = {}

• %Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the class

set array = ##class(%DynamicArray).%New()

set array = []

The related package avoids adding %JSONAdaptor to each class but uses instead
SQL functions JSON_OBJECT() to create my JSON objects. With this approach, you can
add JSON to any class - even deployed ones - without any need for change or recompiling.

The trigger was the Export of M:N relationships as JSON objects or arrays.

The JSON is a data document free of types and validation rules. However, in some scenarios it is important that the JSON document has type and business rules validation, especially in interoperability scenarios. This article demonstrates how you can leverage a market-defined JSONSchema technology that is open for everyone to use and do advanced validations.

Programming and languages

Being a programmer nowadays is basically the geek version of being a polyglot. Of course, most of us here, in the InterSystems Community, “speak ObjectScript”. Howeever, I believe this wasn’t the first language for many people. For instance, I had never heard about it prior to getting the appropriate training at Innovatium.

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.

Setting the Scene

Suppose you have the following 2 persistent classes that are both JSON-enabled (i.e. extends %JSON.Adaptor or %pkg.isc.rest.model.adaptor)