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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.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.
Guides Holoscan SDK installation: inspects the host, assesses platform compatibility, recommends an install method, and delegates to the matching install skill.
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Trace and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
Use when running people attribute search (PAS) image augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: people attribute search, PAS, person augmentation, attribute search, person re-identification, clothing augmentation, person crop augmentation.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
基于 SOC 职业分类
| name | cuopt-server-api-python |
| version | 26.08.00 |
| description | cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API. |
| license | Apache-2.0 |
| metadata | {"author":"NVIDIA cuOpt Team","tags":["cuopt","server","rest-api","python","deployment"]} |
This skill covers starting the server and client examples (curl, Python). Server has no separate C API (clients can be any language).
| Problem type | Supported |
|---|---|
| Routing | ✓ |
| LP | ✓ |
| MILP | ✓ |
| QP | ✗ |
Ask these if not already clear:
# Development
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000
# Docker
docker run --gpus all -d -p 8000:8000 -e CUOPT_SERVER_PORT=8000 \
nvidia/cuopt:latest-cuda12.9-py3.13
curl http://localhost:8000/cuopt/health
/cuopt/request → get reqId/cuopt/solution/{reqId} until solution readyimport 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)
req_id = r.json()["reqId"]
# Poll: GET /cuopt/solution/{req_id}
| 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]].
Validation errors: Check field names against OpenAPI (/cuopt.yaml). Common mistakes: transit_time_matrix_data → travel_time_matrix_data; capacities per dimension [[50, 50]] not per vehicle [[50], [50]]. Capture reqId and response body for failed requests.
Run from each asset directory (server must be running; scripts exit 0 if server unreachable). All use Python requests:
See assets/README.md for overview.
For contribution or build-from-source, see the developer skill.