Creating a Chatbot with IRIS and Python

In this article I'm going to show how to integrate the InterSystems IRIS Database with Python to serve a Machine Learning Model of Natural Language Processing (NLP).

Why Python?

With a large adoption and use in the world, Python have a great community and a lot of accelerators | libraries to deploy any kind of application. If you are curious (https://www.python.org/about/apps/).

Iris Globals

As I start to learn about ^globals they became familiar to use as a fast way to ingest data in a out-of-box data model.

Hey Developers,

You're very welcome to join the upcoming InterSystems webinar called "InterSystems IRIS Tech Talk: Python"! 

Date: Wednesday, June 08, 2022
Time: 11:00 AM EDT 

In this tech talk, we’ll go into detail about the breadth of support Python developers have using the InterSystems IRIS data platform, including:

This is the third post of a series explaining how to create an end-to-end Machine Learning system.

Training a Machine Learning Model

When you work with machine learning is common to hear this work: training. Do you what training mean in a ML Pipeline? Training could mean all the development process of a machine learning model OR the specific point in all development process that uses training data and results in a machine learning model.

Source

So Machine Learning Models are not equal Common Applications?

In the very last point it looks like a normal application.

Continuing to  observe the possibilities of Django, and usage with IRIS. The first we have looked how to define models and connect to tables already existing in IRIS, than we extended embedded Django Administration portal, with an ability to see what data we have in that models, with filters, editing and even pagination.

Time to go to real action, now we a going to create some REST API, on Django, based on the same data, we used before from the package posts-and-tags.

To do so, we will use Django REST Framework

Django REST framework is a powerful and flexible toolkit for building Web APIs.

Some reasons you might want to use REST framework:

• The Web browsable API is a huge usability win for your developers.
• Authentication policies including packages for OAuth1a and OAuth2.
• Serialization that supports both ORM and non-ORM data sources.
• Customizable all the way down - just use regular function-based views if you don't need the more powerful features.
• Extensive documentation, and great community support.
• Used and trusted by internationally recognised companies including Mozilla, Red Hat, Heroku, and Eventbrite.

I am documenting a demo of InterSystems IRIS featuring Embedded Python and Jupyter Notebook deployed on the same container, and an Embedded Python application developed on that Jupyter Notebook IDE.

I have used the Docker container created by @Bob Kuszewski as a development environment to demonstrate how Embedded Python app can be developed in such a setting to push and retrieve data to and from InterSystems IRIS. The benefit of using this container as the development environment is that it is a virtual environment with Jupyter IDE and IRIS connected and running side by side.

As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:

Voting time! 

Let's cast your votes for the best applications in the InterSystems Python Contest:

🔥 Vote for your favorites 🔥

How to vote? Details below.

Hello everyone, this is with great pleasure that I announce the V2 of my application 'Contest-FHIR'.

In this new version, I used new tools and techniques I discovered at the EUROPEAN HEALTHCARE HACKATHON in which I was invited by InterSystems as a guest and as a mentor to display the multiple projects I did in my intership back in April 2022.

Today I present to you the V2 of my application, it can now transform CSV to FHIR to SQL to JUPYTER notebook.

This is for me a really huge step in InterSystems technologies and I think this tool will be used for many other purpuse and cases.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 1 - SQL Gateway

Hello

In this article we will look at the use of SQL Gateway in Iris. SQL Gateway allows Iris to have access to tables from other (external) database via ODBC or JDBC. We can access Tables or Views from various databases, such as Oracle, PostgreSQL, SQL Server, MySQL and others.

Our objective

In the last article, we talked about a few starters for Django. We learned how to begin the project, ensure we have all the requisites, and make a CRUD. However, today we are going a little further. 
Sometimes we need to access more complex methods, so today, we will connect IRIS to a Python environment, build a few functions and display them on a webpage. It will be similar to the last discussion, but further enough for you to make something new, even though not enough to feel lost.

Making a blog using Python + IRIS Globals

Since I started to use internet (late 90's), I always had a CMS (content management system) present to make easier post any information in a blog, social media or even an enterprise page. And later years putting all my code into github I used to document it on a markdown file. Observing how easy could be persisting data into Intersystems IRIS with the Native API I decided to make this application and force myself to forget a little of SQL and stay open to key-value database model.

What is a blog?

I am writing this post primarily to gather an informal consensus on how developers are using Python in conjunction with IRIS, so please respond to the poll at the end of this article! In the body of the article, I'll give some background on each choice provided, as well as the advantages for each, but feel free to skim over it and just respond to the poll.

As most of you are probably aware, Python is currently the most popular programming language among developers around the world - and for good reason.

Hi Community,

This post is a introduction of my openexchange iris-python-apps application. Build by using Embedded Python and Python Flask Web Framework. 
Application also demonstrates some of the Python functionalities like Data Science, Data Plotting, Data Visualization and QR Code generation.

 Features

•  Responsive bootstrap IRIS Dashboard

•  View dashboard details along with interoperability events log and messages.

•  Use of Python plotting from IRIS

•  Use of Jupyter Notebook

•  Introduction to Data Science, Data Plotting and Data Visualization.

•  QR Code generator from python.

Hello,

I became aware of Python in the early 2000s when I started automating tasks. Some of our processes utilized python scripts. I never figured it out very well, and we decided to do away with Python because nobody on our team was familiar with it.

Along the way, I heard a lot about Python. My interest was renewed when InterSystems offered bonus points for using Python in contests.

The things I like the most about Python so far is how easy it is to find the mean of the ages of all Titanic passengers. For my test-data app I wanted to find the largest value in the ‘Qty’ column in a CSV file.

Hi Community!

We’re excited to announce the launch of a new, hands-on training program:

 🧑‍💻 Developing FHIR Applications Using Python 🧑‍💻

This cohort-based course takes developers from FHIR fundamentals to advanced, real-world healthcare interoperability solutions, with deeper, more practical coverage than typical industry offerings and a strong focus on production-ready skills using InterSystems technology.

Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article.  Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory.  For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.

In the preceding section, we explored the installation process and initiated the writing of the IRIS in native Python. We will now proceed to examine global traversal and engage with IRIS class objects.

 get: this function is used to get values from the traversal node.

def traversal_firstlevel_subscript():
    """
    ^mygbl(235)="test66,62" and ^mygbl(912)="test118,78"
    """
    for  i in irispy.node('^mygbl'):
        print(i, gbl_node.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 2 – Python and Vector Search

Since we have access to the data from our external table, we can use everything that Iris has to offer with this data. Let's, for example, read the data from our external table and generate a polynomial regression with it.

For more information on using python with Iris, see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=AFL_epython

Let's now consume the data from the external database to calculate a polynomial regression. To do this, we will use a python code to run a SQL that will read our MySQL table and turn it into a pandas dataframe:

In 2017, Forbes published an article talking about API Economy (see: https://www.forbes.com/sites/louiscolumbus/2017/01/29/2017-is-quickly-becoming-the-year-of-the-api-economy/). This article was the trigger to popularize the use of API and API Management by large companies. The article published a maturity model. My understanding is that Intersystems IRIS allows you to reach the top of the pyramid with your current technologies. See the figure above.
For this it is important to combine % CSP.

Hi Community,

See how the new embedded Python feature enables you to write user-defined SQL functions and stored procedures in Python:

⏯ Embedding Python in SQL: Write Your Stored Procedures in Python

Hello interface engineers and app developers,     

Did you know that you can use Python in productions or integrations?

The production configuration user interface is low-code, but in many projects, you may reach a point where you need to write some code. As discussed in the Integration Architecture course, business processes are full of places for inserting code, specifically the BPL editor (for BPL business processes) and the DTL editor (for data transformations).

😯 As of InterSystems IRIS 2025.1, both Python and InterSystems ObjectScript are supported in the BPL and DTL editors.

🛠️ Managing InterSystems InterSystems API Manager (IAM = Kong Gateway) configurations in CI/CD

🔍 Context: InterSystems IAM configurations 

As part of integrating InterSystems IRIS into a secure and controlled environment, InterSystems IAM relies on Kong Gateway to manage exposed APIs.
Kong acts as a modern API Gateway, capable of handling authentication, security, traffic management, plugins, and more.

However, maintaining consistent Kong configurations (routes, services, plugins, etc.) across different environments (development, testing, production) is a major challenge.

This series of articles would cover Python Gateway for InterSystems Data Platforms. Execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:

• Execute arbitrary Python code
• Seamlessly transfer data from InterSystems IRIS into Python
• Build intelligent Interoperability business processes with Python Interoperability Adapter
• Save, examine, modify and restore Python context from InterSystems IRIS

Other articles

The plan for the series so far (subject to change).

• Part I: Overview, Landscape, and Introduction
• Part II: Installation and Troubleshooting
• Part III: Basic functionality
• Part IV: Interoperability Adapter
• Part V: Execute function
• Part VI: Jupyter Notebook <-- you're here
• Part VII: Dynamic Gateway
• Part VIII: Proxy Gateway
• Part IX: Use cases and ML Toolkit

Intro

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

This extension allows you to browse and edit InterSystems IRIS BPL processes as jupyter notebooks.

Hi Community,

Find out how you can use the open-source iKnow engine in Python within InterSystems IRIS.

⏯ Using the InterSystems iKnow Engine in Python

Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

I received some really excellent feedback from a community member on my submission to the Python 2024 contest. I hope its okay if I repost it here:

you build a container more than 5 times the size of pure IRIS

and this takes time

container start is also slow but completes

backend is accessible as described

a production is hanging around

frontend reacts

I fail to understand what is intended to show

the explanation is meant for experts other than me

The submission is here: https://openexchange.intersystems.

Keywords:  Anaconda, Jupyter Notebook, Tensorflow GPU, Deep Learning,  Python 3 and HealthShare    

1. Purpose and Objectives

This "Part I" is a quick record on how to set up a "simple" but popular deep learning demo environment step-by-step with a Python 3 binding to a HealthShare 2017.2.1 instance .  I used a Win10 laptop at hand, but the approach works the same on MacOS and Linux.

Last week it was noticed that Python overtook Java by becoming the most popular language in PYPL Index  Tensorflow is a powerful computation engine, very popular in research and academic worlds too.

Hi, Community!
In this article, I will introduce Python Streamlit Web Framework.
Below, you can find the topics we will cover:

• 1-Introduction to Streamlit Web Framework
• 2-Installation of Streamlit module
• 3-Running Streamlit Application
• 4-Streamlit Basic commands
• 5-Display multimedia 
• 6-Input widgets
• 7-Display progress and status
• 8-Sidebar and container
• 9-Data Visualization
• 10-Display a DataFrame

So, let's start with the first topic.

The preview release of InterSystems IRIS 2019.2 is now  available - give it a try!

Container images are available via the WRC's preview download site.

The build number for these releases is 2019.2.0.100.0.

InterSystems IRIS Data Platform 2019.2  is the first CD (continuous delivery) release of InterSystems IRIS.  It has many new capabilities including:

• Addition of the IRIS Native API for Python and Node.js and relational access for Node.

Hey Developers,

Watch this video to learn how to use Embedded Python using applications from the Open Exchange app gallery:

⏯ Embedded Python Use Cases @ Global Summit 2023