Learn how to build a simple Retrieval-Augmented Generation (RAG) chatbot using Python, incorporating Pinecone for the vector database and OpenAI for the language model. This guide addresses the issue of chatbot hallucinations by enhancing the language model with external knowledge sources. Step-by-step instructions include setting up API keys, installing necessary packages, creating a Pinecone index, chunking and embedding documents, and querying Pinecone for accurate responses.
Table of contents
HallucinationsHow RAG works?PrerequisitesStore knowledge in PineconeCreate a server less index in Pinecone for storing the embeddings of your documentDivide the document into smaller chunksEmbed the chunksQuery Pinecone to view the chunksUse Chat botSort: