RAG Development Timeline

From Lewis et al.’s original RAG proposal in 2020 to becoming the standard enterprise LLM architecture in 2024.

Core Components

Indexing

Document loading → Text splitting → Embedding → Storage

Retrieval

Query embedding → Similarity search → Top-K recall

Generation

Prompt assembly → LLM generation → Output

For practical implementation, see Building RAG Apps with LangChain and Vector Database: Pinecone vs Milvus.