Intermediate · Systems

Retrieval Pipeline

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A sequence of steps and components used to efficiently retrieve relevant information from a knowledge source, often for RAG systems.

Technical Definition

A sequence of steps and components used to efficiently retrieve relevant information from a knowledge source, often for RAG systems.

How it works

A retrieval pipeline typically involves processes like document indexing, embedding generation for query and documents, similarity search in a vector database, and potentially re-ranking retrieved results. This structured approach ensures that RAG systems can quickly and accurately fetch the most pertinent information to augment LLM generation, enhancing factual accuracy and relevance.

Related Concepts

• Retrieval-Augmented Generation (RAG) — A technique that enhances LLM responses by retrieving relevant documents from an external knowledge base before generating an answer.
• Vector Database — A specialized database optimized for storing, indexing, and querying high-dimensional embedding vectors using similarity search.
• Similarity Search — Finding the items in a dataset most similar to a given query, usually by vector distance.
• Embeddings — Dense vector representations of discrete items, capturing their semantic relationships and meanings.