Feat: provide constructs to simplify genAI patterns implementation

The most common patterns for GenAI applications are RAG and LLM fine-tuning/training. DSF can bring some GenAI constructs to accelerate the implementation of these patterns. In details we have identified 3 constructs that could help:

* The RAG pipeline to ingest data into vector databases and provide semantic context to GenAI applications
* The Data API pipeline to expose data to GenAI application and provide situational context to GenAI applications
* The data preparation pipeline to prepare data for model training or fine-tuning

The issue names no files, tests, or entry points. Begin by surveying existing DSF constructs and defining acceptance criteria for the RAG, Data API, and data preparation pipelines; the work is done when those three constructs have an agreed design and implementation scope.

Written by the indexing model from the issue text.