to generate transcriptions from audio (using the Whisper model) and to create
embeddings for text data, as well as to generate responses to user queries
(using GPT and chat completions). For more details, see
[openai.com](https://openai.com/product).

### Whisper

Whisper is an automatic speech recognition system developed by OpenAI, designed
to transcribe spoken language into text. In this application, Whisper is used to
transcribe the audio from YouTube videos into text, enabling further processing
and analysis of the video content. For more details, see [Introducing Whisper](https://openai.com/research/whisper).

### Embeddings

Embeddings are numerical representations of text or other data types, which
capture their meaning in a way that can be processed by machine learning
algorithms. In this application, embeddings are used to convert video
transcriptions into a vector format that can be queried and analyzed for
relevance to user input, facilitating efficient search and response generation
in the application. For more details, see OpenAI's
[Embeddings](https://platform.openai.com/docs/guides/embeddings) documentation.