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
Artificial Intelligence applications are increasingly built around Retrieval-Augmented Generation (RAG), semantic search, and AI agents. As these applications move into production, choosing the right persistence layer becomes just as important as selecting the LLM.
Today, I'm excited to announce the InterSystems IRIS Document Store for Haystack, a new open-source integration that enables developers to use InterSystems IRIS as a native Document Store within the Haystack AI framework.
It all started on a train ride to visit my parents, while I was chatting with a neighbor in my compartment. As it usually goes, the talk turned to technology, and she threw out a highly specific question: *Could ChatGPT be used to analyze the human genome?* I was highly skeptical that it could pull off something that complex. But the question lingered, burrowing into my mind. By the time I walked through my front door, my skepticism had transformed into a challenge. I didn't have a genome sequencing dataset on hand, but I did want to see if standard ChatGPT could build a functional Interoperability Production from scratch using the PyProd package. Besides, that would give me the chance to participate in the 1st round of the Community Bounty Program "Idea to Application" implementing the third idea.
One of the most visible additions in 4.0.0 is PollingBusinessService.
Before this release, creating a scheduled Python business service meant dealing
directly with the low-level inbound adapter pattern. In 4.0.0, a scheduled
Python entry point can be written directly as a PollingBusinessService and
the framework uses the default IRIS inbound adapter behind the scenes.
Hi Community,
Enjoy the new video on InterSystems Developers YouTube:
📺 Python Meet InterSystems: Native Tools for a Modern Ecosystem