Article
· Oct 11, 2023 2m read
Reviews on Open Exchange - #34

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

I also placed a bunch of Pull Requests on GitHub when I found a problem I could fix.
Some were accepted and merged, and some were just ignored.
So if you did a major change and expect a changed review just let me know.

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When analyzing data, there is often a need to look at specific indicators more thoroughly and to highlight sections of information of particular interest to a user.

For instance, examining the data dynamics for specific regions or dates can help us uncover some hidden trends and patterns that will allow us to make an informed decision about our project in the future.

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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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Article
· Oct 6, 2023 2m read
Reviews on Open Exchange - #33

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

I also placed a bunch of Pull Requests on GitHub when I found a problem I could fix.
Some were accepted and merged, and some were just ignored.
So if you made a major change and expect a changed review just let me know.

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Hi Community,

This is my first post in the developer community - would appreciate any feedback!

For testing or demo purposes, you may want to send emails from your Interoperability Production. In this post then I will walk you through connecting an InterSystems IRIS Production to Gmail so you can use it to send emails alerts.

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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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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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If you work with Productions, highlighting connections between Business Hosts is a very convenient feature, allowing developers to get a visual representation of a data flow.

This feature works by default with all system Business Hosts. If a user writes their own Business Services, Processes, or Operations, they must implement the OnGetConnections method for this functionality to work with their custom Business Hosts (or use Ens.DataType.ConfigName properties for connections).
That said, the SMP shows only the first layer of connections of the selected Business Host. Sometimes, we need to get connections of connections recursively to build a complete data flow graph. Or we might need this connection information to check which downstream systems might be affected by a change upstream.

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Article
· Sep 26, 2023 1m read
Create JSON Objects and Arrays by SQL

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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Article
· Sep 24, 2023 2m read
Reviews on Open Exchange - #32

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

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Earlier this year I announced availability of a VS Code extension for coding in ObjectScript, Embedded Python or SQL using the notebook paradigm popularized by Jupyter. Today I published a maintenance release to correct a "getting started" problem.

Here's a video of the installation steps from the extension's README:

Why not try it for yourself?

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InterSystems FAQ rubric

The meaning of each timeout value is as follows.

1. [Server response timeout]

If IRIS/Caché processing (routine or query execution) does not finish within this set time, the browser will return an error.

For example, if this value is 60 seconds and it takes 90 seconds to execute a routine/method/query, an error will occur.

2. [Queued request timeout]

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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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Why to use it

This app offers an easy interface to analyze memory:

  • Filter by database (namespace), global name, used size, or allocated size;
  • View a sum of the used and allocated sizes for the filters applied;
  • Export the table to JSON, CSV, or XML.

How to use it

Follow the instructions on the README file from the GitHub repository, and configure the settings to connect to your instance.

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In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.

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image
Hello to all developers and IRIS users.
I am submitting to the competition a project for an alternative IRIS management portal that I have long wanted to create. The project was implemented on the Django framework and the intersystems_irispython-3.2.0-py3-none-any.whl library using native IRIS. The Django project is integrated with the telegram messenger and can be launched from a docker container or directly.

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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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Article
· Sep 18, 2023 7m read
Vectors support, well almost

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

  • Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
  • Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
  • Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

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