YouTubeGPT- Your YouTube AI

Features ✨

YouTubeGPT lets you summarize and chat (Q&A) with YouTube videos. Its features include:

provide a custom prompt for summaries ✍️ VIEW DEMO
- you can tailor the summary 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
get answers to questions about the video content ❓ VIEW DEMO
- part of the application is designed and optimized specifically for question answering tasks (Q&A)
create your own knowledge base 💾
- once a video is processed, you can chat with it at any time!
choose from different OpenAI models 🤖
- currently available: gpt-3.5-turbo, gpt-4 (turbo), gpt-4o (mini)
- 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 (or docker-compose)

make sure to provide an OpenAI API key (l. 43 in docker-compose.yml)
adjust the path to save the summaries (l. 39 in docker-compose.yml)
execute the following command:

# pull from docker hub
docker-compose up -d
# or build locally
docker-compose up --build -d

if you are only interested in summaries

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

ℹ️ For the best user-experience, you need to be in Tier 1 usage tier, which requires a one-time payment of 5$. However it's worth it, since then, you'll have access to all models and higher rate limits.

Contributing & Support 🤝

I’m working on adding more features and am open to feedback and contributions. Don't hesitate to create an issue or a pull request. Also, if you are enjoying the app or find it useful, please consider giving the repository a star ⭐

This is a small side-project and it's easy to get started! If you want to contribute, here’s the gist to get your changes rolling:

Fork & clone: Fork the repo and clone your fork to start.
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.
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, using conventional commits.
Stay updated: Keep your branch in sync with the main branch to avoid merge conflicts.
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.
Engage: Respond to feedback on your PR to finalize your contribution.

development in virtual environment

# create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate
# install requirements
pip install -r requirements.txt
# you'll need an API key
export OPENAI_API_KEY=<your-openai-api-key>
# run chromadb (necessary for chat)
docker-compose up -d chromadb
# run app
streamlit run main.py

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.
ChromaDB is used as a vector store for embeddings.

License

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

sudoleg/YouTubeGPT