Skip to content

oconnoob/lemur-lecture-summarizer

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

LeMUR Lecture Summarizer

This application allows you to automatically summarize lectures and ask questions about the lesson material. Learn how to build this application in the associated blog.

The application was tested with Python 3.10.5

Prerequisites

You must have:

  1. Python installed
  2. pip installed
  3. An AssemblyAI account

Setup

  1. Clone this repository and cd into it

    git clone https://github.com/AssemblyAI-Examples/lemur-lecture-summarizer.git
    cd lemur-lecture-summarizer
  2. Create and activate a virtual environment (optional)

    MacOS/Linux:

    python -m venv venv  # you may need to use `python3` instead
    source ./venv/bin/activate

    Windows:

    python -m venv venv  # you may need to use `python3` instead
    .\venv\Scripts\activate.bat
  3. Install dependencies

    pip install -r requirements.txt
  4. Set your AssemblyAI API Key (optional)

    In the .env file, replace paste-your-key-here with your AssemblyAI API key, which you can copy from your Dashboard. If you do not do this, you will be required to enter your API key in the application.

    Note that you will need to have set up billing to use this application since it utilizes LeMUR.

Run the application

  1. Start the app
streamlit run app.py
  1. Open the app Click the link output in the terminal by the last command - the default is http://localhost:8501/

Use the application

  1. Enter your AssemblyAI API key if you did not follow step 4 in the Setup section

    Entering your API key

  2. Select the lecture file

    You can use either an audio or video file, and the file can be locally stored, remotely stored (and publicly accessibly), or on YouTube.

    You can optionally add Context to provide contextualizing information about the lecture.

    Selecting a lecture file

  3. View the results

    Click "Submit" and wait for the results.

    Processing time will depend on the length of the file - hour long lectures may take several minutes to process.

    Viewing the results

  4. Ask a question (optional)

    You can ask questions about the course content for further clarification

    Asking a question

About

Automatically summarize lectures and ask questions about the course material

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%