技能库智客分类：运维与云 cuopt-install

Cuopt Install

通过 pip, conda 或 Docker 为 Python, C 或服务器安装 CuOpt; 验证安装. 关于从源头建造cuOpt,参见cuopt-developer.

2425 安装量

官方网址：skills.sh

技能介绍

先看中文介绍；官方 description 原文单独保留，不改写 SKILL.md。

做什么

通过 pip, conda 或 Docker 为 Python, C 或服务器安装 CuOpt; 验证安装. 关于从源头建造cuOpt,参见cuopt-developer.

何时用

官方 description 未单独写出 Use when。按规范，代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露：启动时只加载 name 与 description（约 100 token）；任务匹配后才读入整份 SKILL.md 正文；scripts/、references/、assets/ 仅在需要时再读。本文件正文结构：cuOpt Install (user)、System requirements、Required questions、Python API、pip、conda。

文件分析

文件分析：除 SKILL.md 外，正文引用了 references/verification_examples.md，属于带资源的技能包，这些文件按需再读。

官方 description（原文）

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.

cuOpt Install (user)System requirementsRequired questionsPython APIpipcondaVerifyC APIpipcondaVerifyServer (REST)

· 许可：Apache-2.0

来源分类：skills.sh agent-skill

来源与网址

市场来源：skills.sh

GitHub 完整包

开源榜 Skill 分类

SKILL.md 与 Agent 调用

官方规范 ↗

name: cuopt-install
description: Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
许可: Apache-2.0

发现技能客户端向 Agent 提供名称与描述目录。
匹配与调用用户指定或任务匹配后，载入 SKILL.md 指令。
按需加载按步骤读取参考文档、使用脚本与素材。

指令中引用的文件 · 1

references/verification_examples.md

以下路径提取自原文；文件是否齐全请以来源仓库中的完整目录为准。

具体调用语法与可用工具以目标 Agent 客户端为准。查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围，保留技能包的附属文件，安装后检查客户端能否发现该技能。

该技能引用了附属文件，请从来源获取完整目录；仅复制 SKILL.md 可能缺少依赖。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理，确认其中的目标目录与客户端匹配。

把 Agent Skill「cuopt-install」安装到我的项目：SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-9f75687563a10893-Cuopt-Install.html
请存为 .cursor/skills/cuopt-install/SKILL.md 或 .claude/skills/cuopt-install/SKILL.md，frontmatter 的 name 与 description 保持原样，不要改写。
该技能还带 scripts/、references/、assets/ 等文件，请从 https://github.com/nvidia/skills 取完整目录，不要只建一个 SKILL.md。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表，确认实际名称。

npx skills add 'https://github.com/nvidia/skills' --list

目标客户端安装范围

npx skills add 'https://github.com/nvidia/skills' --skill 'cuopt-install'

CLI 会交互选择目标 Agent，默认安装到项目；用户级安装使用 -g。先通过查看命令核对仓库内容，再用 npx skills list 检查已安装技能。

SKILL.md 原文可复制，不会改动源文件

---
name: cuopt-install
version: "26.10.00"
description: Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
license: Apache-2.0
metadata:
  author: NVIDIA cuOpt Team
  tags:
    - cuopt
    - install
    - deployment
    - python
    - server
---

# cuOpt Install (user)

Install cuOpt to *use* it from Python, C, or as a REST server. For building cuOpt from source to contribute or modify it, see `cuopt-developer`.

## System requirements

- **GPU**: NVIDIA Compute Capability ≥ 7.0 (Volta or newer). Examples: V100, A100, H100, RTX 20xx/30xx/40xx. Not supported: GTX 10xx (Pascal).
- **CUDA**: 12.x or 13.x. The package CUDA suffix must match the runtime CUDA (e.g. `cuopt-cu12` / `libcuopt-cu12` with CUDA 12).
- **Driver**: NVIDIA driver compatible with the CUDA version.
- `cuopt-cuXX` (Python) depends on `libcuopt-cuXX` (C), so installing the Python package also installs the C library and headers. Installing `libcuopt-cuXX` on its own does **not** install the Python API.

## Required questions

Ask these if not already clear:

1. **Interface** — Python, C, or REST server? Server can be called from any language via HTTP.
2. **CUDA version** — What is installed? Check with `nvcc --version` or `nvidia-smi`.
3. **Package manager** — pip, conda, or Docker preferred?
4. **Environment** — Local machine with GPU, cloud instance, Docker/Kubernetes, or remote/server (no local GPU)?

## Python API

**Choose one** — do not run both. The second install would override the first and can cause CUDA / package mismatch.

### pip

- **CUDA 13.x:**
  ```bash
  pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu13
  ```
- **CUDA 12.x:**
  ```bash
  pip install --extra-index-url=https://pypi.nvidia.com 'cuopt-cu12==26.2.*'
  ```

### conda

```bash
conda install -c rapidsai -c conda-forge -c nvidia cuopt
```

### Verify

```python
import cuopt
print(cuopt.__version__)
from cuopt import routing
dm = routing.DataModel(n_locations=3, n_fleet=1, n_orders=2)
```

## C API

The C API ships in `libcuopt-cuXX`, which is also pulled in as a dependency of `cuopt-cuXX` — so if you already installed the Python package, the C library and headers are already present. Install `libcuopt` standalone only when you want the C API without Python. **Choose one** of pip or conda — do not run both.

### pip

- **CUDA 13.x:**
  ```bash
  pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu13
  ```
- **CUDA 12.x:**
  ```bash
  pip install --extra-index-url=https://pypi.nvidia.com 'libcuopt-cu12==26.2.*'
  ```

### conda

```bash
conda install -c rapidsai -c conda-forge -c nvidia libcuopt
```

### Verify

See [`references/verification_examples.md`](references/verification_examples.md)
for the canonical C-API header/library `find` commands (conda and pip/venv variants).

## Server (REST)

### pip

```bash
pip install --extra-index-url=https://pypi.nvidia.com cuopt-server-cu12 cuopt-sh-client
```

### conda

```bash
conda install -c rapidsai -c conda-forge -c nvidia cuopt-server cuopt-sh-client
```

### Docker

```bash
docker pull nvidia/cuopt:latest-cuda12.9-py3.13
docker run --gpus all -it --rm -p 8000:8000 nvidia/cuopt:latest-cuda12.9-py3.13
```

### Verify

```bash
python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000 &
sleep 5
curl -s http://localhost:8000/cuopt/health | jq .
```

## Common Issues

- `No module named 'cuopt'` → check `pip list | grep cuopt`, `which python`, reinstall with the correct extra-index-url.
- CUDA not available → run `nvidia-smi` and `nvcc --version`; ensure the package CUDA suffix (`cu12` vs `cu13`) matches the installed CUDA.
- Python vs C → `cuopt-cuXX` pulls in `libcuopt-cuXX` as a transitive dependency, so the C library (`libcuopt.so`) and headers (`cuopt_c.h`) are already available after installing the Python package. The reverse is **not** true: `libcuopt-cuXX` alone does not install the Python bindings.

## See also

- [verification_examples.md](references/verification_examples.md) — full verification recipes for Python, C, server, and Docker.
- `cuopt-developer` — build cuOpt from source and contribute to the codebase.

阅读排版

name: cuopt-install version: "26.10.00" description: Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer. license: Apache-2.0 metadata: author: NVIDIA cuOpt Team tags: - cuopt - install - deployment - python - server

cuOpt Install (user)

Install cuOpt to use it from Python, C, or as a REST server. For building cuOpt from source to contribute or modify it, see cuopt-developer.

System requirements

GPU: NVIDIA Compute Capability ≥ 7.0 (Volta or newer). Examples: V100, A100, H100, RTX 20xx/30xx/40xx. Not supported: GTX 10xx (Pascal).
CUDA: 12.x or 13.x. The package CUDA suffix must match the runtime CUDA (e.g. cuopt-cu12 / libcuopt-cu12 with CUDA 12).
Driver: NVIDIA driver compatible with the CUDA version.
cuopt-cuXX (Python) depends on libcuopt-cuXX (C), so installing the Python package also installs the C library and headers. Installing libcuopt-cuXX on its own does not install the Python API.

Required questions

Ask these if not already clear:

Interface — Python, C, or REST server? Server can be called from any language via HTTP.
CUDA version — What is installed? Check with nvcc --version or nvidia-smi.
Package manager — pip, conda, or Docker preferred?
Environment — Local machine with GPU, cloud instance, Docker/Kubernetes, or remote/server (no local GPU)?

Python API

Choose one — do not run both. The second install would override the first and can cause CUDA / package mismatch.

pip

CUDA 13.x:

pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu13

CUDA 12.x:

pip install --extra-index-url=https://pypi.nvidia.com 'cuopt-cu12==26.2.*'

conda

conda install -c rapidsai -c conda-forge -c nvidia cuopt

Verify

import cuopt
print(cuopt.__version__)
from cuopt import routing
dm = routing.DataModel(n_locations=3, n_fleet=1, n_orders=2)

C API

The C API ships in libcuopt-cuXX, which is also pulled in as a dependency of cuopt-cuXX — so if you already installed the Python package, the C library and headers are already present. Install libcuopt standalone only when you want the C API without Python. Choose one of pip or conda — do not run both.

pip

CUDA 13.x:

pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu13

CUDA 12.x:

pip install --extra-index-url=https://pypi.nvidia.com 'libcuopt-cu12==26.2.*'

conda

conda install -c rapidsai -c conda-forge -c nvidia libcuopt

Verify

See references/verification_examples.md for the canonical C-API header/library find commands (conda and pip/venv variants).

Server (REST)

pip

pip install --extra-index-url=https://pypi.nvidia.com cuopt-server-cu12 cuopt-sh-client

conda

conda install -c rapidsai -c conda-forge -c nvidia cuopt-server cuopt-sh-client

Docker

docker pull nvidia/cuopt:latest-cuda12.9-py3.13
docker run --gpus all -it --rm -p 8000:8000 nvidia/cuopt:latest-cuda12.9-py3.13

Verify

python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000 &
sleep 5
curl -s http://localhost:8000/cuopt/health | jq .

Common Issues

No module named 'cuopt' → check pip list | grep cuopt, which python, reinstall with the correct extra-index-url.
CUDA not available → run nvidia-smi and nvcc --version; ensure the package CUDA suffix (cu12 vs cu13) matches the installed CUDA.
Python vs C → cuopt-cuXX pulls in libcuopt-cuXX as a transitive dependency, so the C library (libcuopt.so) and headers (cuopt_c.h) are already available after installing the Python package. The reverse is not true: libcuopt-cuXX alone does not install the Python bindings.

Cuopt Install

技能介绍

做什么

何时用

代理如何加载

文件分析

SKILL.md 与 Agent 调用

安装这个技能

cuOpt Install (user)

System requirements

Required questions

Python API

pip

conda

Verify

C API

pip

conda

Verify

Server (REST)

pip

conda

Docker

Verify

Common Issues

See also

相关技能

Docker Essentials

Find Skills

Azure Diagnostics

Azure Prepare