Pre-pulling the base Docker image in the deploy script prevents
potential TLS certificate errors during the `docker build` process. This
ensures a smoother deployment by leveraging the cached image layer.
This commit introduces a new standalone FastAPI service for the NVIDIA
Canary ASR model.
Key changes include:
- A new `canary/` directory containing the service code.
- `Dockerfile`: Defines the Docker image for the Canary service.
- `docker-compose.yml`: Configures the Docker Compose setup for running
the service.
- `main.py`: Implements the FastAPI application, model loading, and
inference logic.
- `requirements.txt`: Lists the Python dependencies for the service.
- `CHUNKING.md`: Documents the long-form audio handling strategy for
Canary.
- `README.md`: Provides an overview of the service, API, and deployment
instructions.
- `deploy.sh`: A script for deploying the service to a remote host.
This service allows for independent evaluation and deployment of the
Canary ASR model, separate from the existing `doctate-whisper` service.
It utilizes a buffered inference approach for handling long audio files,
as detailed in `CHUNKING.md`.
Brummel