Lightning AI Deployments

A Deployment runs a container (or an auto-built vLLM server for a HuggingFace model) behind an HTTPS endpoint with autoscaling. Sources are mutually exclusive: --image (Docker), --model (HuggingFace id, GPU required), or --studio (deploy a Studio's environment).

Setup & auth

# Use the Lightning AI CLI from the current env; install or upgrade it there if it's missing or older than 2026.9.18
v=$(lightning --version 2>/dev/null | sed -n 's/^Lightning CLI version //p')
[ -n "$v" ] && [ "$(printf '%s\n' 2026.9.18 "$v" | sort -V | head -1)" = 2026.9.18 ] \
  || uv pip install -U lightning-sdk || python3 -m pip install -U lightning-sdk
lightning --version   # must print "Lightning CLI version …"; if not, see the table below
lightning login                     # browser flow; or headless:
export LIGHTNING_API_KEY=... LIGHTNING_USER_ID=...   # USER_ID optional: with it Basic auth, without it the key is a Bearer token

This uses, and if needed installs into, the agent's current environment (project venv, conda env, …); then call plain lightning … everywhere. If setup doesn't go cleanly: