How to Q&A YouTube Data with LangChain
Did you know that we can work with retrieval models by taking into consideration as documents the YouTube videos?
In retrieval augmented generation (RAG), an LLM retrieves contextual documents from an external dataset as part of its execution, which enables us to ask questions about the context of the documents. These documents can be plain text files, PDFs, URLs and even videos, like YouTube videos.
In this tutorial, we will show you how to upload a YouTube using LangChain.
YouTube Video Loading with LangChain
The YouTube loader enables users to extract text from videos. It highlights the importance of this functionality for engaging with favorite videos or lectures. This loader incorporates components such as the YouTube audio loader and the OpenAI Whisper parser, facilitating the conversion of YouTube audio into text. The process involves specifying a URL, a directory for saving audio files, and then combining the YouTube audio loader with the OpenAI Whisper parser to create a generic loader. Upon loading the documents, users can view…
