Generate Vector Embeddings Using LangChain
Learn to generate vector embeddings from the PDF document and storing them using LangChain.
Introduction
Before creating the API endpoint, let's make a script ready that will load a PDF document and the script is able to answer the questions asked. We will be using a node package langchain
to implement the question-answer over document. LangChain is an open-source framework designed to simplify the creation of applications powered by LLMs like GPT-3 and others. As discussed, we will use Nvidia's freely available PDF document on transformers as our dataset.
Below is a simple flow to implement the script:
Let's discuss the above steps briefly:
Load the PDF document using LangChain's document loader.
Split the document using
RecursiveCharacterTextSplitter
into smaller chunks of text.Generate a vector store to store the documents as vector embeddings so that the text can become searchable. ...