How to build an interactive lecture summarization app

This tutorial demonstrates how to build a web application that transcribes audio files and summarizes the transcriptions using the Python SDK for AssemblyAI, an enterprise-grade AI platform with advanced capabilities in speech recognition, natural language processing (NLP), and machine learning. The final result is an interactive GUI that can transcribe, summarize, and answer questions about an uploaded lecture file or YouTube video. The application first prompts the user to enter their AssemblyAI API key or set it as an environment variable. It then presents a radio selector for selecting the file type: local file upload, remote file URL, or YouTube link. Based on this selection, users either upload a file or enter a URL. The user can also provide additional contextual information about the file to help LeMUR better understand its content. Once a file is selected and submitted, it is transcribed using AssemblyAI's Transcriber class methods, which transcribe audio files that are either stored locally on the client device or publicly available via a URL. If the supplied file is a YouTube video, get_transcript function first downloads the video to a temporary local file before transcribing it. After transcribing the file, its transcript is saved in the application's session state so that its value persists between re-renders of the app. Any temporary local files are also removed at this point. The AssemblyAI Python SDK makes it easy to generate summaries from the transcribed text using the lemur.summarize method. We specify an answer format as markdown and then pass in any additional contextual information provided by the user. Once a summary has been generated, it is saved to the session state. Finally, the application provides space for users to enter questions about the lecture content. The ask_question function uses the lemur.question method of the transcript object to generate answers to these questions in real-time. The resulting GUI displays a summary and allows users to ask and receive answers to their questions about the uploaded file or YouTube video.