This app exposes the Whisper model via a simple HTTP server, thanks to Replicate Cog. Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container. When you're up and running, you can trascribe audio using the /predictions endpoint.

Create a deploy the app in one single command:

fly launch --from https://github.com/fly-apps/cog-whisper --no-public-ips

Assign a Flycast IP to the app:

fly ips allocate-v6 --private

That's it! You can now access the app at http://<APP_NAME>.flycast/predictions

curl -X PUT \
     -H "Content-Type: application/json" \
     -d '{
           "input": {
             "audio": "https://fly.storage.tigris.dev/cogs/bun_on_fly.mp3"
           }
         }' \
     http://cog-whisper.flycast/predictions/test | jq

1. Clone the cog-whisper repository from GitHub:

   git clone [email protected]:fly-apps/cog-whisper.git

2. Navigate into the cloned directory:

   cd cog-whisper

3. Run locally. First, run get_weights.sh from the project root to download pre-trained weights, then build a container and run predictions:

   ./scripts/get_weights.sh:

   cog predict -i audio="<path/to/your/audio/file>"

4. Build the Docker image using cog:

   cog build -t whisper

Create an issue or ask a question here: https://community.fly.io/