Definition
The retrieval phase of a RAG pipeline where a system identifies and extracts the most relevant information from a corpus to provide factual context for an LLM. It focuses on maximizing the 'Top-K' relevance to ensure the model stays grounded and avoids hallucinations.
In RAG, this refers to semantic retrieval via embeddings rather than simple CTRL+F keyword matching.
"A robotic warehouse picker retrieving specific storage bins containing relevant parts to fulfill a complex assembly order."
- Vector Database(Component)
- Chunking(Prerequisite)
- Top-K Retrieval(Component)
- Hybrid Search(Optimization)
Conceptual Overview
The retrieval phase of a RAG pipeline where a system identifies and extracts the most relevant information from a corpus to provide factual context for an LLM. It focuses on maximizing the 'Top-K' relevance to ensure the model stays grounded and avoids hallucinations.
Disambiguation
In RAG, this refers to semantic retrieval via embeddings rather than simple CTRL+F keyword matching.
Visual Analog
A robotic warehouse picker retrieving specific storage bins containing relevant parts to fulfill a complex assembly order.