Uplimit Project: Podcast Summarizer

In this project, an LLM app was built to summarize a podcast episode, identifies the podcast guests and attempts to retrieve the guest's public information from wikipedia, and identifies key highlights using OpenAI ChatGPT and prompting techniques. Cloud deployment provider Modal was used to convert the information extraction function into a cloud on demand service, while the front-end interface was deployed on Streamlit

The solution was developed in three parts:

Part 1: Use a large language model from OpenAI to build the information extraction functionality, paired with a speech-to-text model for transcribing the podcast.

Part 2: Use a simple cloud deployment provider to easily convert the information extraction function to run on demand – This would be the app backend.

Part 3: Use ChatGPT from OpenAI as your coding assistant to create and deploy a front-end that allows users to experience the end-to-end functionality.

Try it here

Getting started

Open Uplimit_Week1_Summarise_Podcast_GPT.ipynb on . The notebook consists of further technical details.