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.
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.
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.
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.
We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.
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 *
Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.
As you might have heard, we just introduced the InterSystems API Manager (IAM); a new feature of the InterSystems IRIS Data Platform™, enabling you to monitor, control and govern traffic to and from web-based APIs within your IT infrastructure. In case you missed it, here is the link to the announcement.
In this article, I will show you how to set up IAM and highlight some of the many capabilities IAM allows you to leverage.
The following steps show you how to display a sample list of metrics available from the /api/monitor service.
In the last post, I gave an overview of the service that exposes IRIS metrics in Prometheus format. The post shows how to set up and run IRIS preview release 2019.4 in a container and then list the metrics.
This post assumes you have Docker installed. If not, go and do that now for your platform :)
By update
Open Exchange app
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