Retrieval-augmented generation (RAG) fundamentals
This section introduces the key components and principles behind developing RAG applications over unstructured data.
In particular:
- Data pipeline: Transforming unstructured documents, such as collections of PDFs, into a format suitable for retrieval using the RAG application’s data pipeline.
- Retrieval, Augmentation, and Generation (RAG chain): A series (or chain) of steps is called to:
- Understand the user’s question.
- Retrieve the supporting data.
- Call an LLM to generate a response based on the user’s question and supporting data.
- Evaluation: Assessing the RAG application to determine its quality, cost, and latency to ensure it meets your business requirements.
- Governance and LLMOps: Tracking and managing the lifecycle of each component, including data lineage and governance (access controls).