In this blog post, we will introduce you to a powerful, user-friendly solution for transcribing YouTube videos: a Flask web app utilizing OpenAI's cutting-edge Whisper API for speech-to-text conversion. We'll walk you through the entire process, from setting up the app to integrating Pytube for downloading YouTube videos and OpenAI's Whisper API for transcription. By the end of this post, you'll have a functional web application that allows users to transcribe YouTube videos with just a few clicks. So, let's dive in and explore the world of automated YouTube video transcription! The app created in this guide is a user-friendly web application that allows users to transcribe YouTube videos effortlessly.

OpenAI, the company behind ChatGPT and DALL-E 2, announced several significant changes today. It also changed its terms of service to let developers opt out of using their data for improvements while adding a 30-day data retention policy. The new ChatGPT API will use the same AI model ("gpt-3.5-turbo") Snap's My AI is an early example, along with a new virtual tutor feature for the online study tool Quizlet and an upcoming Ask Instacart tool in the popular local-shopping app. However, the API won't be limited to brand-specific bots mimicking ChatGPT; it can also power "non-chat" software experiences that could benefit from AI brains. The ChatGPT API is priced at $0.002 per 1,000 tokens (about 750 words).

We tested it and got impressed! We took the latest RealPython episode for 1h 10 minutes. It took us 56 minutes with a basic CPU to convert the audio file into almost perfect text transcription with the smallest Whisper model. Next, we show in steps using Whisper in practice with just a few lines of Python code. This tutorial explains with single code a way to use the Whisper model both on your local machine and in a cloud environment.