WingmanAI is a powerful tool for interacting with real-time transcription of both system and microphone audio. Powered by ChatGPT, this tool lets you interact in real-time with the transcripts as an extensive memory base for the bot, providing a unique communication platform.

As you can see, the bot can answer questions about past conversations when you load the transcripts for a designated person.

• Real-time Transcription: WingmanAI can transcribe both system output and microphone input audio, allowing you to view the live transcription in an easy-to-read format.

• ChatGPT Integration: You can chat with a ChatGPT powered bot that reads your transcripts in real-time.

• Efficient Memory Management: The bot maintains a record of the conversation but in a token-efficient manner, as only the current chunk of transcript is passed to the bot.

• Save and Load Transcripts: WingmanAI allows you to save transcripts for future use. You can load them up anytime later, and any query made to the bot will be cross-referenced with a vector database of the saved transcript, providing the bot with a richer context.

• Append Conversations: You can keep appending to the saved transcripts, building a vast database over time for the bot to pull from.

1. Clone the repository.
2. Install the requirements: pip install -r requirements.txt
3. If you wish to use CUDA for Whisper (which is highly recommended), uninstall (pip uninstall torch) torch and run: pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117

Note: This application is currently compatible only with Windows.

Ensure you have ffmpeg installed on your system. Have a working OpenAI API key. Works best using CUDA! CPU transcription is not real-time. The model currently being used is the "base" model - if your hardware can't run it, change it to "tiny". Language is currently set to English.

1. Add your OpenAI API key to the keys.env file.
2. Run main.py.

For any queries or issues, feel free to open a new issue in the repository.

Contributions are always welcomed to improve the project.

This project uses a modified version of SevaSk's "Ecoute" project for the transcriptions - check it out here!