Lecture Summarizer

Description

Tkinter application to record text with openai-whisper, extract keywords from transcription with sklearn's TF-IDF and generate notes with gguf llm model

Requirements

Python 3.10.12 pip 24.0

Installation

Running Locally

Clone the repository:

git clone https://github.com/JRoshthen1/LectureSummarizer.git

Navigate to the project directory:

cd LectureSummarizer/

Install dependencies:

pip install tkinter sounddevice soundfile numpy openai-whisper torch scikit-learn nltk llama-cpp-python

Usage

1. Create recordings directory in the root of the application (./recordings/)

2. Download a gguf model for text generation, examples

3. Run the app

python3 main.py

Contributing

• Start by forking the repository.
• Create a branch in your fork for your contributions.
• Commit your changes with clear commit messages.
• Push your branch to your fork on GitHub and submit a pull request to the main project.

License

Lecture Summary Bot Copyright (C) 2024 Martin Jaros

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.