文件列表:

podcast-clockwise.json (28718, 2023-08-19)
podcast-future_of_everything.json (25777, 2023-08-19)
podcast-me_myself_AI.json (22701, 2023-08-19)
podcast-twinml_url.json (35722, 2023-08-19)
podcast_backend.py (6861, 2023-08-19)
podcast_frontend.py (5898, 2023-08-19)
requirements.txt (32, 2023-08-19)
styles.css (126, 2023-08-19)

# Podcast-Summarizer This project is part of the course [Building AI products with OpenAI](https://uplimit.com/course/building-ai-products-with-openai) taught by Sidharth Ramachandran. In this project, I built an LLM app that summarizes a podcast episode, identifies podcast guests, and key momments. You can view it at https://podcast-summarizer.streamlit.app/. ## Approach - Part 1: use a Large Language Model (LLM) from OpenAI to build the information extraction functionality paired with a Speech to Text model for transcribing the podcast. * I used [Whisper](https://github.com/openai/whisper) as the speech to text model. * I used the OpenAI `gpt-3.5-turbo-16k` model to generate the summary by passing in the generated transcript. - 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. See [Modal](https://modal.com/). - Part 3: use ChatGPT from OpenAI as coding assistant to create and deploy a front-end that allows users to experience the end to end functionality. See [streamlit.io](https://streamlit.io/).

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：