A Python API that exposes LLM backends, via FastAPI and gRPC, in the OpenAI API specification.

See instructions to get the API up and running. Then, go to http://localhost:8080/docs for the Swagger documentation on API usage.

The instructions in this section assume the following:

1. Properly installed and configured Python 3.11.x, to include its development tools
2. The config.yaml is created based on the config-example.yaml
3. You have chosen a LeapfrogAI model backend and have that running. Some examples of existing backends:

• https://github.com/defenseunicorns/leapfrogai-backend-ctransformers
• https://github.com/defenseunicorns/leapfrogai-backend-whisper

For cloning a model locally and running the development backend.

# Setup Python Virtual Environment
make create-venv
make activate-venv
make requirements-dev

# Start Model Backend
make dev

For local image building and running.

# Build the docker image
docker build -t ghcr.io/defenseunicorns/leapfrogai/leapfrogai-api:latest .

# Run the docker container
docker run -p 8080:8080 -v ./config.yaml:/leapfrogai/config.yaml ghcr.io/defenseunicorns/leapfrogai/leapfrogai-api:latest