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Podcast Summary App

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Overview

The Podcast Summary App is a web application that allows users to explore podcast details and summaries in an interactive and user-friendly way. The app provides a platform to view comprehensive information about podcast episodes, including summaries, guest details, highlights, and chapters.

The app is built using a combination of Google Colab, Modal Labs, and Streamlit. The language model for podcast processing was developed using Google Colab, and the backend is hosted on Modal Labs. Streamlit is used for the frontend interface.

To access the live app, visit https://podcastsummarizer-corise.streamlit.app/

Features

  • Podcast Exploration: Easily select from a list of available podcast feeds to view detailed information about episodes.
  • Add New Podcasts: Input a podcast RSS feed link to add and process new podcasts.
  • Dark Mode: The app is designed with a dark mode theme for a sleek and modern look.
  • Interactive: Users can quickly access episode summaries, guest details, highlights, and chapter information.

Setup

To set up the Podcast Summary App locally, follow these steps:

  1. Clone the repository: git clone https://github.com/GbotemiB/podcastSummarizer/

  2. Navigate to the project directory: cd podcastSummarizer

  3. Install the required dependencies: pip install -r requirements

  4. Run the app: streamlit run app.py

  5. Instructions on the process for the app are included in Podcast_Summarizer.ipynb

How to Use

  1. Launch the app by running the app.py script.
  2. Use the sidebar to select an available podcast feed from the dropdown list.
  3. View detailed information about the selected podcast, including episode summary, guest details, highlights, and chapters.
  4. To add a new podcast, input the RSS feed link in the sidebar and click "Process Podcast Feed."

Contact

Feel free to reach out if you have any questions or feedback:

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Acknowledgments

  • The language model for podcast processing was developed using Google Colab.
  • The backend is hosted on Modal Labs.
  • The frontend interface is built using Streamlit.

License

This project is licensed under the MIT License.

About

This is a podcast summarizer built with Open AI

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