retrieval-augmented-generation

A production-ready AI system combining Claude's conversational capabilities, LangChain's orchestration framework, and Pinecone's vector database to build retrieval-augmented generation applications that can answer questions using custom knowledge bases.

Describes the process of building and deploying a Retrieval Augmented Generation (RAG) system in a production environment, integrating vector databases with Large Language Models (LLMs) to enhance response accuracy and relevance.