The motivation behind the InterLang project is rooted in the innovative integration of LangChain chatbot agents with the Fast Healthcare Interoperability Resources (FHIR) framework to revolutionize conversational social prescriptions in healthcare. This project aims to leverage the rich and standardized data available through FHIR, an emerging standard in healthcare data exchange, to inform and empower these advanced chatbot agents.

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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.

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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.

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According to Databricks Apache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. Apache Parquet is designed to be a common interchange format for both batch and interactive workloads. It is similar to other columnar-storage file formats available in Hadoop, namely RCFile and ORC. (source:

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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:

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How can IRIS productions be deployed more quickly and with greater peace of mind?

The aim of interoperability productions is to enable you to connect systems in order to transform and route messages between them. To connect systems, you develop, configure, deploy and manage productions that integrate several software systems.

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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". 🙂

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In the world of Big Data, selecting the right file format is crucial for efficient data storage, processing, and analysis. With the massive amount of data generated every day, choosing the appropriate format can greatly impact the speed, cost, and accuracy of data processing tasks. There are several file formats available, each with its own set of advantages and disadvantages, making the decision of which one to use complex. Some of the popular Big Data file formats include CSV, JSON, Avro, ORC, and Parquet.

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InterSystems FAQ rubric

You can set the maximum size of the IRISTemp database at IRIS startup by setting a configuration parameter called MaxIRISTempSizeAtStart.

After setting, the system will truncate IRISTemp to the set value (MB) at the next IRIS startup. If the current size is less than the specified MaxIRISTempSizeAtStart, no truncation will occur. Also, if 0 is specified, truncation will not be performed, so the size will start without changing. (Default) Settings are made from the menu below.

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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.

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InterSystems would like to optimize IRIS to take advantage of modern CPU instruction set extensions. That’s great for product performance, but how do you know if your CPU will still be supported for new IRIS builds? Here’s how to know your CPU’s microarchitecture family as well as how to find out your CPU’s specific instruction set extensions.

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InterSystems FAQ rubric

For routines (*.mac)

You can hide the source by exporting/importing only the *.obj that is generated after compiling the source program.

The command execution example specifies EX1Sample.obj and EX2Sample.obj, which are generated by compiling EX1Sample.mac and EX2Sample.mac, as export targets and exports them to the second argument file.

After moving to another namespace, I am using the exported XML file to perform the import.

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This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.

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We resume our series of articles on the FHIR Adapter tool available to HealthShare HealthConnect and InterSystems IRIS users.

In the previous articles we have presented the small application on which we set up our workshop and showed the architecture deployed in our IRIS instance after installing the FHIR Adapter. In today's article we will see an example of how we can perform one of the most common CRUD (Create - Read - Update - Delete) operations, the reading operation, and we will do it by recovering a Resource.

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InterSystems FAQ rubric

ObjectScript allows you to pass any number of arguments using arrays. Do it by adding ... after the argument name.

An example is as follows. In the example statement, the argument information is set in a global variable (a variable stored in the database) so that it can be easily checked after the method is executed.

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We return with our example of using the FHIR Adapter, in this article we are going to review how we can configure it in our IRIS instances and what the result of the installation is.

The steps taken to configure the project are the same as indicated in the official documentation, you can review them directly here. Well, let's get to work!

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Surely you have all heard about FHIR as the panacea and solution to all interoperability and compatibility problems between systems. Right here we can see one of his classic defenders holding a FHIR resource in his hand and enjoying it immensely:

But for the rest of us mortals we are going to make a small introduction.

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InterSystems FAQ rubric

In the sample below, an image file is encoded into a Base64 string in a class property, saved, decoded again with Base64, and restored to another file.

【Usage class】

Class User.test Extends %Persistent
Property pics As %GlobalBinaryStream;

【When importing】

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Are you preparing to use VS code for the first time? Just make sure you have enough privileges.

Have you defined your Iris server in your VS Code settings, and still get the following error?

VS Code accesses Iris/HealthConnect using the web application /api/atelier. If you do not have permission (i.e. you are using an LDAP user to connect and the web application is not configured to support LDAP), this is the reason why you couldn't connect.

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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.

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