YTAI - Your YouTube AI

Features ✨

YTAI summarizes YouTube videos and is not the first project to do that. However, it offers some features that other similar projects and AI summarizers on the internet don't:

• provide a custom prompt ✍️
  • you can tailor the response to your needs by providing a custom prompt or just use the default summarization
• automatically save summaries 📂
  • the summaries can be automatically saved in the directory where you run the app. The summaries will be available under <YT-channel-name>/<video-title>.md
• choose from different OpenAI models 🤖
  • currently available: gpt-3.5-turbo, gpt-4 (turbo), gpt-4o
  • by choosing a different model, you can summarize even longer videos and potentially get better responses
• experiment with settings ⚙️
  • adjust the temperature and top P of the model
• choose UI theme 🖌️
  • go to the three dots in the upper right corner, select settings and choose either light, dark or my aesthetic custom theme

Installation & usage

No matter how you choose to run the app, you will first need to get an OpenAI API-Key. This is very straightforward and free. Have a look at their instructions to get started.

build & run with Docker

# build locally
docker build --tag=ytai:latest .
# or pull from Docker Hub
docker pull sudoleg/ytai:latest
docker run -d -p 8501:8501 -v $(pwd):/app/responses -e OPENAI_API_KEY=<your-openai-api-key> --name yt-summarizer sudoleg/ytai:latest

development in virtual environment

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
export OPENAI_API_KEY=<your-openai-api-key>
streamlit run main.py

Contributing

Feedback and contributions are welcome! This is a small side-project and it's very easy to get started! Here’s the gist to get your changes rolling:

1. Fork & clone: Fork the repo and clone your fork to start.
2. Pick an issue or suggest One: Choose an open issue to work on, or suggest a new feature or bug fix by creating an issue for discussion.
3. Develop: Make your changes.
   • Ensure your code is clean and documented. Test the changes at least exploratively. Make sure to test 'edge cases'.
   • Commit your changes with clear, descriptive messages, preferably using conventional commits.
4. Stay updated: Keep your branch in sync with the main branch to avoid merge conflicts.
5. Pull Request: Push your changes to your fork and submit a pull request (PR) to the main repository. Describe your changes and any relevant details.
6. Engage: Respond to feedback on your PR to finalize your contribution.

Technologies used

The project is built using some amazing libraries:

• The project uses YouTube Transcript API for fetching transcripts.
• LangChain is used to create a prompt, submit it to an LLM and process it's response.
• The UI is built using Streamlit.

License

This project is licensed under the MIT License - see the LICENSE file for details.