This is a fun app that let you turn your thoughts into tweets in a jiffy!
You simply talk to the mic and it records your voice, transcribes it and turn it into a tweet with a click of a button. You can run the ASR Whisper models either locally or via OpenAI API. By default it's using the API, but if you'd like to use the models locally, check audio_service_local.py
file. There are two different approaches to run the model locally using two different python libraries: fast-whisper
and insanely-fast-whisper
. Pick whichever that suits you or faster on your system, and update the FastAPI endpoint/path accordingly.
moments_demo.mp4
- Clone the repo:
git clone https://github.com/mallahyari/transonic.git
- To run the frontend, go to the
frontend
directory and run:
npm install
npm start
You can skip the authentication if you run it locally. Nevertheless, if you would like to set up authentication, you'll need to add your CLERK_PUBLISHABLE_KEY
to your .env
file in frontend
folder.
Additionally, if you tend to run FastAPI backend locally, make sure to update the BACKEND_URL
inside the frontend/src/config.ts
to the appropriate url, e.g. http://localhost:8000
.
- To run the backend, from
backend/app
folder run:
pip install -r requirements.txt
python main.py
If you plan to use OpenAI Whisper API, you will need to enter your OPENAI_API_KEY
. To do that, simply create a .env
file in the backend/app
directory with the following info:
OPENAI_API_KEY=
- App logic: React + ant design
- Authentication: Clerk
- Deployment: Vercel
- App logic: FastAPI
- Deployment: Fly.io
If you have any comment or feedback, please don't hesitate to reach out directly or use the Discussions section and open a new topic. You can also reach out directly via Linkedin or Twitter.