rhoai

The AI Accelerator is a template project for setting up Red Hat OpenShift AI using GitOps

Data science pipelines and model serving using Red Hat OpenShift Data Science

Non-destructive GPU based idle-culler for RHOAI/Kubeflow workloads

Production-pattern Red Hat OpenShift AI 3.4.0 platform with bare-metal ESXi, GPU passthrough, KServe RawDeployment, DeepSeek R1 inference at 12–17 tok/s

Biologically-grounded runtime for autonomous agent collectives under bounded agency — one codebase runs on a laptop, at the edge, and on OpenShift AI. Three-tier governance, persistent episodic memory, cross-collective delegation, and homeostatic rogue detection.

Red Hat OpenShift AI Model Registry Deployment and Automated Model Ingestion

MLOps and compute acceleration with Openshift AI

Red Hat OpenShift AI integration with Nvidia NIM

A Deployment agent for Model Serving runtimes Component in RHOAI

Benchmark study: NVIDIA L4 + Llama 3.1 8B FP8 on Red Hat OpenShift AI. Concurrent load benchmarks, quality evaluation, and deployment advisor grounded in real measured data.

Simple AI Chat browser interface to test with LLM's. Streaming, markdown response format.

Evaluate, annotate, and gate AI agents you didn't build — conversational AgentOps on MLflow + MCP for OpenShift AI

Cloud-Native 5G ISAC ML Inference dApp, FAPI UL Indication Signal Processing, Range-Doppler Heatmaps, and AI Telemetry

Quick Instructions to add user for RHO-AI. If you need to access the "settings" sidebar.

End-to-end Bielik model implementation on RHOAI with llm-d

Charter, guidelines, and plugin catalog for the Red Hat AI Community Plugins initiative

AWS 에 OpenShift 를 IPI 로 설치하고 agent OSS 스택과 Red Hat OpenShift AI 를 올려 GPU 서빙·LoRA 튜닝까지 해 본 뒤 깨끗하게 지우는 실습 레포

Models-as-a-Service Openshift AI Workshop Module