Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace
In the previous article, we saw how to build a customer service AI agent with smolagents and InterSystems IRIS, combining SQL, RAG with vector search, and interoperability.
In that case, we used cloud models (OpenAI) for the LLM and embeddings.
This time, we’ll take it one step further: running the same agent, but with local models thanks to Ollama.
Customer support questions span structured data (orders, products 🗃️), unstructured knowledge (docs/FAQs 📚), and live systems (shipping updates 🚚). In this post we’ll ship a compact AI agent that handles all three—using:
🧠 Python + smolagents to orchestrate the agent’s “brain”
🧰 InterSystems IRIS for SQL, Vector Search (RAG), and Interoperability (a mock shipping status API)
I’ve been exploring options for connecting Google Cloud Pub/Sub with InterSystems IRIS/HealthShare, but I noticed that IRIS doesn’t seem to ship with any native inbound/outbound adapters for Pub/Sub. Out of the box, IRIS offers adapters for technologies like Kafka, HTTP, FTP, and JDBC, which are great for many use cases, but Pub/Sub appears to be missing from the list.
Interoperability on Python (IoP) is a proof-of-concept project designed to showcase the power of the InterSystems IRIS Interoperability Framework when combined with a Python-first approach.IoP leverages Embedded Python (a feature of InterSystems IRIS) to enable developers to write interoperability components in Python, which can seamlessly integrate with the robust IRIS platform. This guide has been crafted for beginners and provides a comprehensive introduction to IoP, its setup, and practical steps to create your first interoperability component. By the end of this article, you will get a clear understanding of how to use IoP to build scalable, Python-based interoperability solutions.
I have a custom Buffer class which is designed to capture written/printed statements to the device, to be able to transform the captured text to string or stream type. I have used this in ObjectScript to capture ObjectScript write statements and return a string. I would like to try to use this with a [ Language = python ] method as follows. This class will be called by a scheduled task.
This article will introduce you to the concept of virtual environments in Python, which are essential for managing dependencies and isolating project from the OS.
I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:
In this section, we will explore how to use Python as the primary language in IRIS, allowing you to write your application logic in Python while still leveraging the power of IRIS.
Sending emails is a common requirement in integration scenarios — whether for client reminders, automatic reports, or transaction confirmations. Static messages quickly become hard to maintain and personalize. This is where the templated_email module comes in, combining InterSystems IRIS Interoperability with the power of Jinja2 templates.
Why Jinja2 for Emails
Jinja2 is a popular templating engine from the Python ecosystem that enables fully dynamic content generation. It supports:
This will be a short article about Python dunder methods, also known as magic methods.
What are Dunder Methods?
Dunder methods are special methods in Python that start and end with double underscores (__). They allow you to define the behavior of your objects for built-in operations, such as addition, subtraction, string representation, and more.
Are you curious about how to run Python scripts directly in your InterSystems IRIS or Caché terminal? 🤔 Good news it's easy! 😆 IRIS supports Embedded Python, allowing you to use Python interactively within its terminal environment.
How to access the Python Shell?
To launch the Python shell from the IRIS terminal, simply run the following command:
This will be an introduction to Python programming in the context of IRIS.
Before anything I will cover an important topic: How python works, this will help you understand some issues and limitations you may encounter when working with Python in IRIS.
All the articles and examples can be found in this git repository: iris-python-article
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For my intern project, I am building a Flask REST API backend. My goal is to host it on InterSystems IRIS using the WSGI interface. This is a relatively new approach and is currently only being used in a handful of projects such as AskMe. To help others get started, I decided to write this article to simplify the process.
I'm trying to connect a Python backend application to an InterSystems IRIS Community Edition instance running in a Docker container on an AWS EC2 instance. I'm facing persistent connection issues and an SSL Error despite the Superserver apparently having SSL disabled. I'm hoping for some insight into what might be causing this contradictory behavior.
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.
I was wondering what best practice was for using macros in Embedded Python, i.e. iris.execute('$$$MACRO()') or something else. Does anyone have insight into this?
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