Red Hat Trusted Application Pipeline for AI applications
Pubblicato il November 20, 2024
This interactive demo helps developers accelerate the creation and deployment of AI-powered applications using standardized templates. It walks through the full application development and MLOps workflow from initial setup to model serving.
Note: This demo may contain AI-generated content and/or media. All AI-generated content was reviewed or edited by a human before being made available to you.
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What you'll learn in this interactive demo
• Signing into Red Hat Developer Hub and creating an AI application from a template.
• Configuring a Large Language Model (LLM) and reviewing the application deployment pipeline with OpenShift GitOps.
• Monitoring model serving status and accessing a Jupyter Notebook workbench in Red Hat OpenShift AI.
• Modifying chatbot code in OpenShift DevSpaces with Quarkus live dev mode and committing changes.
• Running LLM response quality tests and an MLOps pipeline based on Kubeflow.
• Exploring data connections and object storage for models and pipeline artifacts in MinIO.
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