#Open Exchange

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.

In this article I will be discussing the use of an alternative LLM for generative IA. OpenIA is commonly used, in this article I will show you how to use it and the advantages of using Ollama

In the generative AI usage model that we are used to, we have the following flow:

In this article, we’ll dive into the inner workings of the database management tool, exploring the architecture and technologies that power it. Understanding how the application functions behind the scenes will give you insight into its design, how it manages databases, tables, and how the API interacts with data.

If one of your packages on OEX receives a review you get notified by OEX only own YOUR 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.

The latest "Bringing Ideas to Reality" InterSystems competition saw me trawling through the ideas portal for UI problems to have a go at.

https://www.youtube.com/embed/zw51X1JQhQ0
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I produce my monthly Review Report on OEX packages now for 18 months.
These are a view figures and some comments:

If one of your packages on OEX receives a review you get notified by OEX only own YOUR 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.

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.

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.

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.

Hi Community,

In this article, I will introduce my application iris-AgenticAI .

The rise of agentic AI marks a transformative leap in how artificial intelligence interacts with the world—moving beyond static responses to dynamic, goal-driven problem-solving. Powered by OpenAI’s Agentic SDK , The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm.
This application showcases the next generation of autonomous AI systems capable of reasoning, collaborating, and executing complex tasks with human-like adaptability.

Application Features

• Agent Loop 🔄 A built-in loop that autonomously manages tool execution, sends results back to the LLM, and iterates until task completion.
• Python-First 🐍 Leverage native Python syntax (decorators, generators, etc.) to orchestrate and chain agents without external DSLs.
• Handoffs 🤝 Seamlessly coordinate multi-agent workflows by delegating tasks between specialized agents.
• Function Tools ⚒️ Decorate any Python function with @tool to instantly integrate it into the agent’s toolkit.
• Vector Search (RAG) 🧠 Native integration of vector store (IRIS) for RAG retrieval.
• Tracing 🔍 Built-in tracing to visualize, debug, and monitor agent workflows in real time (think LangSmith alternatives).
• MCP Servers 🌐 Support for Model Context Protocol (MCP) via stdio and HTTP, enabling cross-process agent communication.
• Chainlit UI 🖥️ Integrated Chainlit framework for building interactive chat interfaces with minimal code.
• Stateful Memory 🧠 Preserve chat history, context, and agent state across sessions for continuity and long-running tasks.

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.

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.

In principle I'm looking in forward direction.
Though from time to time it makes sense to turn back and see the full path taken.

• I started reporting my reviews almost 4 years ago.
• I just reviewed packages that I could reproduce in my environment.
• Skipping items beyond my physical or mental capacities.
• So some great packages might not be present here
• But I added also 139 contributions of other reviewers
• It was anyhow a total of 769 reviews published
• Meeting over this time 191 different authors