Metaflow Pipeline Setup for SAP AI Core
The Metaflow Library for SAP AI Core is an open-source Python library that allows developers to build and manage machine learning workflows on SAP AI Core. It provides a framework for defining ML pipelines as code, enabling developers to run and track data science workflows in a scalable and reproducible way on the SAP AI Core platform.
Tutorials that teach this
Prerequisites
- Concept Docker Image Build and Registry Management The provided sources do not contain enough information to define a specific SAP developer concept, as no concept name was supplied and the source snippets consist only of tutorial titles without substantive content. To generate an accurate, source-grounded definition, please provide a valid concept name and supporting source snippets that describe it.
- Concept Docker Image Build and Publish The provided sources do not contain sufficient information to write a grounded definition for an **undefined** concept. The sources cover a range of SAP BTP topics (HANA connection issues, Kyma runtime, AI Core, Cloud Foundry) but do not define or describe a specific named concept that can be documented here.
- Concept AWS service integration (Amazon S3 and Amazon Rekognition) The concept name was not provided, so a precise definition cannot be generated. The available source describes accessing data from Amazon S3 in SAP HANA Cloud, SAP HANA Database, but without a defined concept to document, no accurate or grounded prose definition can be written. Please supply the concept name so a correct definition can be produced.
- Concept Docker Container Packaging The concept name was not provided and the supplied sources do not contain enough information to produce a grounded, accurate definition. Please provide a valid concept name and relevant source snippets so a definition can be written.
- Concept SAP Python Packages The concept name provided is **undefined**, and the supplied sources do not contain sufficient detail to construct a grounded, accurate definition for a specific SAP developer concept. Without a valid concept name or supporting source content, no definition can be written that meets the requirement of being grounded exclusively in the provided snippets.
- Concept Python Virtual Environment Setup The provided sources do not contain sufficient information to write a grounded definition for an undefined concept. Please provide a valid concept name and relevant source snippets so that an accurate, source-grounded definition can be written.
- Concept Cloud Object Store Integration for ML Data The provided sources do not contain enough information to define a specific SAP developer concept, as no concept name was supplied and the source snippets consist only of tutorial titles without descriptive content. A meaningful, source-grounded definition cannot be written without at least a named concept or substantive excerpt from the referenced materials.
- Concept SAP AI Core Service Setup The concept name was not provided, so a precise definition cannot be constructed from the available sources. Based on the sources, these materials collectively cover building and integrating [Generative AI applications](https://architecture.learning.sap.com/docs/golden-path/ai-golden-path/2-build-and-deliver/3-genai-applications/readme) on SAP Business Technology Platform using SAP AI Core — a managed service that developers use to train models, run AI workloads, and connect to large language models via orchestration. Developers leverage it alongside [SAP BTP service instances and keys](https://help.sap.com/docs/btp/sap-business-technology-platform/5b35ee98403045309bb0f8c7f0c79365?locale=en-US&state=PRODUCTION&version=Cloud) to authenticate and consume AI capabilities such as prompt optimization, grounding, multimodal responses, and custom evaluation within their applications.