| name | managed-model-endpoints |
| description | Register a model service in the managed family — a local model server container the daemon starts/stops on demand, or a remote upstream model API (https). Read the runbook, allocate a port (local only), compose idempotent start/stop scripts (local only), register once. Load when the user wants a model service available for inference, or when list_compute shows managed endpoints. |
| license | Apache-2.0 |
Managed model endpoints
A managed model endpoint is a model service the daemon owns: you
register it once, then every compute_provider cell against it just
works — the daemon swaps the resident model off the device (one model at a
time, via the resident's own approved stop), runs your approved start
script, waits for the readiness route, then runs your cell, streaming its
lifecycle progress into the cell as it goes. You never run the container
runtime yourself, never poll readiness in cells, and never see the
credential value. Two verbs: register() (asks the user once) and ordinary
inference cells.
Container specifics — image, registry login, internal port, cache mount
target, readiness route — come from the model's own runbook skill; this
skill is the translation contract.
Calling a registered endpoint — inference cells
Calling a registered endpoint — use the using-model-endpoint skill
(this skill is the REGISTRATION contract; that one documents the call
side in full).
The ONLY dispatch form is the compute_provider tool with the endpoint's
registered name (list_compute shows them):
compute_provider(provider="boltz2-service", code="""
import requests
r = requests.post(BASE_URL + "/v1/infer", json=payload)
""")
