Cuopt Server API Python
NVIDIAOfficialCreated by NVIDIA cuOpt Team
- Skill
- Tool integration
- Software development
- Apache-2.0
- Medium risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides instructions for deploying the cuOpt REST server and integrating it into applications using Python or curl. It covers server startup procedures for local and Docker environments, the asynchronous request-polling pattern required for job submission, and guidance on mapping problem data to REST API endpoints. It also includes troubleshooting steps for common payload and deployment issues.
What it does
- Provides commands to start the cuOpt REST server locally or via Docker.
- Explains the asynchronous request-polling workflow for job submission and solution retrieval.
- Maps Python API concepts to REST API field names and structures.
- Offers troubleshooting guidance for common HTTP errors and payload formatting issues.
- Provides examples for routing, LP, and MILP problem types.
- Outlines security considerations for the unauthenticated REST interface.
When to use it
- When deploying the cuOpt server in a production or development environment.
- When building a client application to interface with cuOpt via HTTP.
- When debugging rejected payloads or 422 errors during API interaction.
- When transitioning from the Python library to a REST-based architecture.
Advantages
- Language-agnostic API allows integration with any service capable of making HTTP requests.
- Standardized polling pattern for handling long-running optimization tasks.
- Clear mapping between Python API and REST schema reduces implementation friction.
- Comprehensive troubleshooting table addresses common deployment and payload errors.
Usage examples
- “How do I start the cuOpt server using Docker?”
- The agent provides the docker run command with the necessary GPU flags and port mappings, including advice on using specific version tags.
- “I am getting a 422 error when sending fleet data to the cuOpt API.”
- The agent explains the correct nesting for capacity dimensions and provides a corrected JSON structure example.
- “How do I retrieve a solution after posting a request to the cuOpt server?”
- The agent outlines the polling loop pattern, showing how to use the reqId to query the /cuopt/solution endpoint until the task is complete.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/nvidia/cuopt-server-api-python/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip cuopt-server-api-python.zip -d .agents/skills
Documentation by NVIDIA cuOpt Team
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 allfor Docker).cuopt-serverinstalled, 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:
Problem type — Routing or LP/MILP? (QP not available via REST.)
Deployment — Local, Docker, Kubernetes, or cloud?
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-cu13Use latest-cu12 or latest-cu13 to match your driver's CUDA major version (latest-cu13-ubi10 for a UBI10 base).
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>-cu<cuda-major>) or an immutable digest (nvidia/cuopt@sha256:<digest>). Check the nvidia/cuopt registry for available tags.
Verify
Confirm the server is up by requesting GET /cuopt/health on the local port (e.g. http://localhost:8000/cuopt/health) — a healthy server returns HTTP 200.
Instructions
POST to
/cuopt/request→ getreqIdPoll
/cuopt/solution/{reqId}until solution readyParse response
Treat reqId as untrusted input: validate it (e.g. re.fullmatch(r"[A-Za-z0-9_-]{1,64}", req_id)) 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 |
| set_order_time_windows() | task_time_windows |
| service_times | service_times |
Use travel_time_matrix_data (not transit_time_matrix_data). Capacities: [[50, 50]] not [[50], [50]].
Troubleshooting
| Error | Cause | Solution |
|---|---|---|
422 Unprocessable Content | Field name not in the schema | Check names against the OpenAPI spec at /cuopt.yaml. Most common: transit_time_matrix_data → travel_time_matrix_data |
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 solver_config.time_limit 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/vrp_simple/ — Basic VRP (no time windows)
assets/vrp_basic/ — VRP with time windows
assets/pdp_basic/ — Pickup and delivery
assets/lp_basic/ — LP via REST (CSR format)
assets/milp_basic/ — MILP via REST
See assets/README.md for overview.
Escalate
For contribution or build-from-source, see the developer skill.
Files
- ATTRIBUTION.mdAdded by AutoGineer938 B
- BENCHMARK.md8.8 KiB
- LICENSELicence file added by AutoGineer11.2 KiB
- SKILL.md5.8 KiB
- assets/README.md608 B
- assets/lp_basic/README.md368 B
- assets/lp_basic/client.pyScript2.9 KiB
- assets/milp_basic/README.md360 B
- assets/milp_basic/client.pyScript2.8 KiB
- assets/pdp_basic/README.md287 B
- assets/pdp_basic/client.pyScript3.3 KiB
- assets/vrp_basic/README.md376 B
- assets/vrp_basic/client.pyScript3.5 KiB
- assets/vrp_simple/README.md254 B
- assets/vrp_simple/client.pyScript3.2 KiB
- evals/evals.json8.5 KiB
- skill-card.md4.2 KiB
- skill.oms.sig7.0 KiB
assets/vrp_simple/client.py
# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
"""
REST client: Basic VRP (no time windows). 4 locations, 3 tasks, 2 vehicles.
Requires cuOpt server running. Exits 0 if server unreachable.
"""
import argparse
import re
import sys
import time
import requests
DEFAULT_SERVER = "http://localhost:8000"
HEADERS = {"Content-Type": "application/json", "CLIENT-VERSION": "custom"}
REQUEST_TIMEOUT = 30
REQ_ID_PATTERN = re.compile(r"[A-Za-z0-9_-]{1,64}")
def parse_args():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--server",
default=DEFAULT_SERVER,
help=f"cuOpt server base URL (default: {DEFAULT_SERVER})",
)
return parser.parse_args()
def server_ok(server):
try:
r = requests.get(f"{server}/cuopt/health", timeout=2)
return r.status_code == 200
except Exception:
return False
def main():
server = parse_args().server
if not server_ok(server):
print(
"Server not running, skipping. Start with: python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000"
)
sys.exit(0)
payload = {
"cost_matrix_data": {
"data": {
"0": [
[0, 10, 15, 20],
[10, 0, 12, 18],
[15, 12, 0, 10],
[20, 18, 10, 0],
]
}
},
"travel_time_matrix_data": {
"data": {
"0": [
[0, 10, 15, 20],
[10, 0, 12, 18],
[15, 12, 0, 10],
[20, 18, 10, 0],
]
}
},
"task_data": {
"task_locations": [1, 2, 3],
"demand": [[10, 15, 20]],
"service_times": [5, 5, 5],
},
"fleet_data": {
"vehicle_locations": [[0, 0], [0, 0]],
"capacities": [[50, 50]],
},
"solver_config": {"time_limit": 5},
}
response = requests.post(
f"{server}/cuopt/request",
json=payload,
headers=HEADERS,
timeout=REQUEST_TIMEOUT,
)
response.raise_for_status()
req_id = response.json()["reqId"]
if not REQ_ID_PATTERN.fullmatch(req_id):
print(f"Unexpected reqId from server: {req_id!r}")
sys.exit(1)
print(f"Submitted: {req_id}")
for _ in range(30):
response = requests.get(
f"{server}/cuopt/solution/{req_id}",
headers=HEADERS,
timeout=REQUEST_TIMEOUT,
)
result = response.json()
if "response" in result:
solver_response = result["response"].get("solver_response", {})
print(f"Status: {solver_response.get('status')}")
print(f"Cost: {solver_response.get('solution_cost')}")
if "vehicle_data" in solver_response:
for vid, vdata in solver_response["vehicle_data"].items():
print(f"Vehicle {vid}: {vdata.get('route', [])}")
return
time.sleep(1)
print("Timeout waiting for solution")
sys.exit(1)
if __name__ == "__main__":
main()
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs network access, Needs an API key, Needs a command-line tool, Needs Python
Security
What our scanner noticed· Medium risk
- Large base64-encoded blobs
- Instructions that use the network
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- NVIDIA cuOpt Team
- Publisher
- NVIDIA (Official)
- Source
- NVIDIA/skills · skills/cuopt-server-api-python · commit fce3cca
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE-APACHE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by NVIDIA cuOpt Team or NVIDIA.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download cuopt-server-api-python.zip