# Changelog

## Version 2.3.0 - Enhancement release - 2026-07-20

- Added supported Python versions: 3.13, 3.14

## [Version 2.2.1] - Run:ai Macro Managment Feature - 2026-07

### Changed
* **Run:ai Macro Workflow**: The Run:ai macro no longer updates Dataiku pod configuration directly. It now provides an optional admin interface to validate, create, and update Run:ai projects used for scheduler enforcement.
* **Run:ai Namespace Requirement**: NIM Service submissions that use Run:ai scheduling now require a Kubernetes namespace that is mapped to a Run:ai project namespace.
* **Run:ai create or update projects**: The Run:ai macro added a feature to create or update projects dedicated for Dataiku usage

## [Version 2.2.0] - NIM Cache & Enhanced Deployment - 2026-07

### New Features
* **NIM Cache Support**: Pre-download and cache model files for faster NIM Service deployments with add/inspect/remove macro actions
* **Startup Probe Configuration**: Configurable startup probe settings for models with long initialization times
* **NIM Operator Version Update**: Updated default NIM Operator version to v3.0.0

## [Version 2.1.0] - Run:ai Integration - 2026-04

### New Features
* **Run:ai Cluster Macro**: Deploy and manage Run:ai scheduler on Kubernetes clusters
* **Fractional GPU Support**: Deploy NIM Services with fractional GPU allocation using Run:ai scheduler
* **Optional GPU Operator Installation**: Made GPU Operator installation optional during NIM Operator deployment

## [Version 2.0.1] - Bug Fixes - 2026-03

### Bug Fixes
* **NGC SDK Version Lock**: Fixed NGC SDK version to avoid future version compatibility issues

## [Version 2.0.0] - NemoGuard Guardrails & Enhanced Storage - 2026-01

### New Features
* **NemoGuard NIMs Guardrails Support**: Added comprehensive guardrail capabilities powered by NVIDIA NemoGuard microservices
  - Topic Control: Ensure conversations stay on approved topics
  - Content Moderation: Detect inappropriate, harmful, or policy-violating content in user queries and model responses
  - Jailbreak Detection: Identify prompt injection attacks and attempts to bypass AI safety measures

### NIM Deploy Macro Updates
* **Volume Storage Type Configuration**: Added input option to configure volume storage type for NIM deployments.
* **NIM Model Selection**: Added support to select NIM models from a dropdown to deploy.

### Deprecations
* **Custom LLM Connection**: The custom LLM connection is deprecated. Dataiku 14.2 and later versions include a built-in NVIDIA NIM connection.

## [Version 1.0.0] - Host NIM Capability - 2025-06

* Added Capability to self host NIM Containers in Dataiku EC with autoscaling
* NIM Plugin - support added for Multimodal Chat, Multimodal Embedding, Streaming and Tool Calling.

## [Version 0.3.0] - Initial Release - 2024-07

* Custom LLM connection option for Nvidia NIM container LLMs deployed
* Connect to a deployed NVIDIA container chat completion endpoint to use in Dataiku Prompt Studios, LLM recipes, and via the LLM Mesh python APIs
* Connect to a deployed NVIDIA container embedding endpoint to use in Dataiku Embed recipe for Retrieval Augmented Generation (RAG)
