nvidia/skills · Official

cuopt-server-api-python

cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.

All-time #6078 First seen May 15, 2026
8-week activity · all time api

Installation

$ npx skills add nvidia/skills --skill cuopt-server-api-python

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Repository health

Stars 3.2K
License LICENSE-APACHE
Default branch main
Open issues 5
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version26.10.00
LicenseApache-2.0
More metadata
author
NVIDIA cuOpt Team
tags
["cuopt","server","rest-api","python","deployment"]

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,045 B
  • docs SUMMARY.md 162 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2,039 installs

SKILL.md

cuOpt Server — Deploy and client (Python/curl)

This skill covers starting the server and client examples (curl, Python). Server has no separate C API (clients can be any language).

Purpose

Use this skill when the user is deploying the cuOpt REST server or writing a client against it — choosing a deployment target, mapping a problem onto the HTTP endpoints, translating between Python-API and REST field names, or debugging a rejected payload.

Prerequisites

  • An NVIDIA GPU with a working CUDA driver (the server requires one; --gpus all for Docker).
  • cuopt-server installed, or Docker with the NVIDIA Container Toolkit. See the install skill.
  • Python clients need requests. No API key or auth token is required by the server itself.

Problem types supported

Problem type Supported
Routing
LP
MILP
QP

Required questions

Ask these if not already clear:

  1. Problem type — Routing or LP/MILP? (QP not available via REST.)
  2. Deployment — Local, Docker, Kubernetes, or cloud?
  3. Client — Which language or tool will call the API (e.g. Python, curl, another service)?

Start server

# Development
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000

# Docker — pick the tag matching your CUDA major version
docker run --gpus all -d -p 8000:8000 -e CUOPT_SERVER_PORT=8000 \
  nvidia/cuopt:latest-cu13

Use latest-cu12 or latest-cu13 to match your driver's CUDA major version (latest-cu13-ubi10 for a UBI10 base). Prefer these over the CUDA+Python-specific tags such as latest-cuda12.9-py3.13 — those track a single Python line and go stale when it stops receiving builds.

For production, pin rather than float: latest-* tags are mutable and can silently move to a different image. Use a full release tag (nvidia/cuopt:<release>-cuda<cuda>-py<python>) or an immutable digest (nvidia/cuopt@sha256:<digest>). Check the nvidia/cuopt registry for available tags.

Verify

curl http://localhost:8000/cuopt/health

Instructions

  1. POST to /cuopt/request → get reqId
  2. Poll /cuopt/solution/{reqId} until solution ready
  3. Parse response

Treat reqId as untrusted input: validate it (e.g. re.fullmatch(r"[A-Za-z0-9-]{1,64}", reqid)) before interpolating it into the polling URL, and set an explicit timeout on every request.

Examples

import requests, time
SERVER = "http://localhost:8000"
HEADERS = {"Content-Type": "application/json", "CLIENT-VERSION": "custom"}
payload = {
    "cost_matrix_data": {"data": {"0": [[0,10,15],[10,0,12],[15,12,0]]}},
    "travel_time_matrix_data": {"data": {"0": [[0,10,15],[10,0,12],[15,12,0]]}},
    "task_data": {"task_locations": [1, 2], "demand": [[10, 20]], "task_time_windows": [[0,100],[0,100]], "service_times": [5, 5]},
    "fleet_data": {"vehicle_locations": [[0, 0]], "capacities": [[50]], "vehicle_time_windows": [[0, 200]]},
    "solver_config": {"time_limit": 5}
}
r = requests.post(f"{SERVER}/cuopt/request", json=payload, headers=HEADERS, timeout=30)
req_id = r.json()["reqId"]
# Poll: GET /cuopt/solution/{req_id}

Terminology: REST vs Python API

Python API REST
order_locations task_locations
setordertime_windows() tasktimewindows
service_times service_times

Use traveltimematrixdata (not transittimematrixdata). Capacities: [[50, 50]] not [[50], [50]].

Troubleshooting

Error Cause Solution
422 Unprocessable Entity Field name not in the schema Check names against the OpenAPI spec at /cuopt.yaml. Most common: transittimematrixdatatraveltimematrixdata
422 on fleet_data Capacities nested per vehicle instead of per dimension Use [[50, 50]] (one inner list per capacity dimension), not [[50], [50]]
Connection refused Server not up, or bound to a different interface/port curl http://localhost:8000/cuopt/health; start with --ip 0.0.0.0 --port 8000
Docker container exits immediately No GPU visible to the container Run with --gpus all and confirm the NVIDIA Container Toolkit is installed
Polling never returns a solution Solve exceeds the client's poll budget Raise solverconfig.timelimit and the poll loop count together

Capture the reqId and the full response body for any failed request — both are needed to diagnose server-side rejections.

Limitations

  • QP is not exposed over REST. Use the Python or C API for quadratic objectives.
  • The server ships no authentication or TLS. Anything that can reach the port can submit jobs. Put it behind a gateway and treat --server/base URLs as trusted-network endpoints only.
  • Solutions are retrieved by polling; there is no push/webhook delivery.
  • One request is solved at a time per server process; concurrency requires multiple replicas.

Runnable assets

Run from each asset directory (server must be running; scripts exit 0 if server unreachable). All use Python requests and accept --server (default http://localhost:8000):

  • [assets/vrpsimple/](assets/vrpsimple/) — Basic VRP (no time windows)
  • [assets/vrpbasic/](assets/vrpbasic/) — VRP with time windows
  • [assets/pdpbasic/](assets/pdpbasic/) — Pickup and delivery
  • [assets/lpbasic/](assets/lpbasic/) — LP via REST (CSR format)
  • [assets/milpbasic/](assets/milpbasic/) — MILP via REST

See [assets/README.md](assets/README.md) for overview.

Escalate

For contribution or build-from-source, see the developer skill.