67 lines
1.7 KiB
Markdown
67 lines
1.7 KiB
Markdown
# Lecture Summarizer
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## Description
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Tkinter application to record text with openai-whisper, extract keywords from transcription with sklearn's TF-IDF and generate notes with gguf llm model
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## Requirements
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Python 3.10.12
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pip 24.0
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## Installation
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### Running Locally
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Clone the repository:
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```bash
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git clone https://github.com/JRoshthen1/LectureSummarizer.git
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```
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Navigate to the project directory:
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```bash
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cd LectureSummarizer/
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```
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Install dependencies:
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```bash
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pip install tkinter sounddevice soundfile numpy openai-whisper torch scikit-learn nltk llama-cpp-python
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```
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## Usage
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1. Create `recordings` directory in the root of the application (./recordings/)
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2. Download a gguf model for text generation, [examples](https://huggingface.co/models?library=gguf)
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3. Run the app
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```bash
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python3 main.py
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```
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## Contributing
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- Start by forking the repository.
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- Create a branch in your fork for your contributions.
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- Commit your changes with clear commit messages.
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- Push your branch to your fork on GitHub and submit a pull request to the main project.
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## License
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Lecture Summary Bot
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Copyright (C) 2024 Martin Jaros
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <https://www.gnu.org/licenses/>.
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