Application Programming Interface (API) is a set of subroutine definitions, protocols, and tools for building application software. In general terms, it is a set of clearly defined methods of communication between various software components.
One of the most common kinds of integration we are asked to do is emailing. One of the most typical email services our customers use is Microsoft’s Office 365. After setting up the right configuration on the Microsoft side, we can email from IRIS with two HTTP requests.
I would like to share with you a little trick to customize how messages are displayed in the Message Viewer. In particular, how you can display messages as JSON (instead of the default XML representation).
The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently.
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.
I have been using embedded python for more than 2 years now on a daily basis.
May be it's time to share some feedback about this journey.
Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.
So far, we have covered how to use ObjectScript to manage users, roles, resources, and applications. There are a few other classes in this package that work similarly to the ones mentioned above. However, these four classes are the ones everyone will have to use to manage their application security.
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.
Based on the successful solution for my 2nd contribution to the Contest I used an adapted version for this package. And have some findings I'd like to share.
Multiple communication steps over CPIPE may take time. You won't recognize it on a fast machine. But a slower box with Windows + Docker Desktop + your browser (and more) is neither "Speedy Gonzales" nor a "Road Runner". 🙂
There are situations when your only access to a server is using a web browser, and there is just no chance of a Terminal or Console access. The Online Demo Server is such a case.
So you have WebTerminal. That's fine for ObjectScript and Embedded Python.
In my previous articles, I described my Command Line Extension to NativeAPI. Of course, this is also available for any other NativeAPI package. So I created this example as a demo for the actual Java Contest. The package contains also an IRIS server in Docker for the demo It is evident that it also works with any remote IRIS server. You just have to provide it with my NativeAPI CommandLine Extension.
In my previous articles, I described my Command Line Extension to NativeAPI. Of course, this is also available for any other NativeAPI package. So I created this example in Python as a demo.
Using the Config.Configuration class and SYS.Database class methods, you can create and register a namespace database from the terminal.
Below is a series of execution examples that create database file /CacheDB/AAA/cache.dat and register database AAA and namespace AAA in the configuration file (cache.cpf). * Execute in the %SYS namespace. *
* Make sure that this script runs as the user that is used for all IRIS processes to ensure that the directory has appropriate ownership and permissions *
Hello everyone, I’m a French student that just arrived in Prague for an academical exchange for my fifth year of engineering school and here is my participation in the interop contest.
I hadn’t much time to code since I was moving from France to Prague and I’m participating alone, so I decided to make a project that’s more like a template rather than an application.
Being interoperable is more and more important nowadays. InterSystems IRIS 2022.1 comes with a new messaging API to communicate with event streaming platforms like Kafka, AWS SQS/SNS, JMS and RabbitMQ.
This article shows how you can connect to Kafka and AWS SQS easily. We start with a brief discussion of the basic concepts and terms of event streaming platforms.
This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.
What about having your IRIS REST APIs scanned every push you did and being reported on possible vulnerabilities? This is what I am going to show you in this article.
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Open Exchange app
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