
如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具,协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题,请先让 AI 阅读并遵守轩辕镜像的规则文档。
只需在 AI 对话中先发送下面这句话即可:
请先完整阅读并严格遵守以下文档中的全部规则与要求:
https://xuanyuan.cloud/agents.md
在未充分阅读并理解该文档前,不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。查看 agents.md 用法指南与完整示范。国内用户首推 元宝 AI、DeepSeek 的深度思考模式,不推荐豆包 AI;Cursor 等编辑器可在对话 @ 该链接,或加入 User Rules。 若 AI 无法访问外链,可 打开说明文档 复制全文粘贴。文档会随站点更新,复制内容可能过期,建议定期检查。
The command line interface for the Digital Ocean API.
This image packages releases from https://github.com/digitalocean/doctl
Source location: https://github.com/boxcutter/oci/tree/main/doctl
Set up some environment variables that are commonly used by other tools:
You can generate a new token via https://cloud.digitalocean.com/account/api/tokens
SSH_KEY_IDS is the Digital Ocean API numeric identifier for each ssh key, not the friendly string name. You can get the numeric identifier with the following API call. It's the id field:
bashcurl -X GET https://api.digitalocean.com/v2/account/keys \ -H "Authorization: Bearer $DIGITALOCEAN_ACCESS_TOKEN"
Some commands require user input, for those to pass the --interactive and --tty flags as well:
bashdocker container run --rm --interactive --tty \ --env=DIGITALOCEAN_ACCESS_TOKEN \ docker.io/boxcutter/doctl account get
NOTE: Don't use the tty flag when you plan to pipe the output of docker to another program. It adds
extra newlines to the output: https://github.com/moby/moby/issues/8513
Listing public images
bash% docker container run --rm \ --env=DIGITALOCEAN_ACCESS_TOKEN \ docker.io/boxcutter/doctl doctl compute image list-distribution --public ID Name Type Distribution Slug Public Min Disk Created 135509519 9 x64 base Rocky Linux rockylinux-9-x64 true 10 2023-06-28T21:06:21Z 143033891 8 x64 base Rocky Linux rockylinux-8-x64 true 10 2023-10-25T11:45:21Z 159651797 22.04 (LTS) x64 base Ubuntu ubuntu-22-04-x64 true 7 2024-07-02T16:43:14Z 168639140 12 x64 base Debian debian-12-x64 true 7 2024-10-24T21:24:54Z 169810124 41 x64 base Fedora fedora-41-x64 true 15 2024-11-07T21:03:46Z 189723042 AMD AI/ML Ready base Ubuntu gpu-amd-base true 30 2025-06-09T21:24:11Z 191457505 NVIDIA AI/ML Ready base Ubuntu gpu-h100x1-base true 30 2025-06-26T17:14:44Z 191457541 NVIDIA AI/ML Ready with NVLink base Ubuntu gpu-h100x8-base true 30 2025-06-26T17:19:10Z 193655201 42 x64 base Fedora fedora-42-x64 true 15 2025-07-17T17:34:59Z 194271330 25.04 x64 base Ubuntu ubuntu-25-04-x64 true 7 2025-07-23T15:30:12Z 195932981 24.04 (LTS) x64 base Ubuntu ubuntu-24-04-x64 true 7 2025-08-08T15:11:27Z 196174368 AlmaLinux 9 base AlmaLinux almalinux-9-x64 true 10 2025-08-10T20:00:17Z 196493389 AlmaLinux 8 base AlmaLinux almalinux-8-x64 true 10 2025-08-13T21:35:16Z 197014428 AlmaLinux 10 base AlmaLinux almalinux-10-x64 true 10 2025-08-18T16:34:37Z 197131532 9 Stream x64 base CentOS centos-stream-9-x64 true 10 2025-08-19T23:52:30Z 197216326 10 x64 base Rocky Linux rockylinux-10-x64 true 10 2025-08-20T18:03:04Z
Listing regions
bash% docker container run --rm \ --env=DIGITALOCEAN_ACCESS_TOKEN \ docker.io/boxcutter/doctl doctl compute region list Slug Name Available nyc1 New York 1 true sfo1 San Francisco 1 false nyc2 New York 2 true ams2 Amsterdam 2 false sgp1 Singapore 1 true lon1 London 1 true nyc3 New York 3 true ams3 Amsterdam 3 true fra1 Frankfurt 1 true tor1 Toronto 1 true sfo2 San Francisco 2 true blr1 Bangalore 1 true sfo3 San Francisco 3 true syd1 Sydney 1 true atl1 Atlanta 1 true
Listing image sizes/pricing
bash% docker container run --rm --interactive --tty \ --env=DIGITALOCEAN_ACCESS_TOKEN \ docker.io/boxcutter/doctl doctl compute size list Slug Description Memory VCPUs Disk Price Monthly Price Hourly s-1vcpu-512mb-10gb Basic 512 1 10 4.00 0.005950 s-1vcpu-1gb Basic 1024 1 25 6.00 0.008930 s-1vcpu-1gb-amd Basic AMD 1024 1 25 7.00 0.010420 s-1vcpu-1gb-intel Basic Intel 1024 1 25 7.00 0.010420 s-1vcpu-1gb-35gb-intel Basic Intel 1024 1 35 8.00 0.011900 s-1vcpu-2gb Basic 2048 1 50 12.00 0.017860 s-1vcpu-2gb-amd Basic AMD 2048 1 50 14.00 0.020830 s-1vcpu-2gb-intel Basic Intel 2048 1 50 14.00 0.020830 s-1vcpu-2gb-70gb-intel Basic Intel 2048 1 70 16.00 0.023810 s-2vcpu-2gb Basic 2048 2 60 18.00 0.026790 s-2vcpu-2gb-amd Basic AMD 2048 2 60 21.00 0.031250 s-2vcpu-2gb-intel Basic Intel 2048 2 60 21.00 0.031250 s-2vcpu-2gb-90gb-intel Basic Intel 2048 2 90 24.00 0.035710 s-2vcpu-4gb Basic 4096 2 80 24.00 0.035710 s-2vcpu-4gb-amd Basic AMD 4096 2 80 28.00 0.041670 s-2vcpu-4gb-intel Basic Intel 4096 2 80 28.00 0.041670 s-2vcpu-4gb-120gb-intel Basic Intel 4096 2 120 32.00 0.047620 s-2vcpu-8gb-amd Basic AMD 8192 2 100 42.00 0.062500 c-2 CPU-Optimized 4096 2 25 42.00 0.062500 c2-2vcpu-4gb CPU-Optimized 2x SSD 4096 2 50 47.00 0.069940 s-2vcpu-8gb-160gb-intel Basic Intel 8192 2 160 48.00 0.071430 s-4vcpu-8gb Basic 8192 4 160 48.00 0.071430 s-4vcpu-8gb-amd Basic AMD 8192 4 160 56.00 0.083330 s-4vcpu-8gb-intel Basic Intel 8192 4 160 56.00 0.083330 g-2vcpu-8gb General Purpose 8192 2 25 63.00 0.093750 s-4vcpu-8gb-240gb-intel Basic Intel 8192 4 240 64.00 0.095240 gd-2vcpu-8gb General Purpose 2x SSD 8192 2 50 68.00 0.101190 g-2vcpu-8gb-intel General Purpose — Premium Intel 8192 2 30 76.00 0.113100 gd-2vcpu-8gb-intel General Purpose — Premium Intel 2x SSD 8192 2 60 79.00 0.117560 s-4vcpu-16gb-amd Basic AMD 16384 4 200 84.00 0.125000 m-2vcpu-16gb Memory-Optimized 16384 2 50 84.00 0.125000 c-4 CPU-Optimized 8192 4 50 84.00 0.125000 c2-4vcpu-8gb CPU-Optimized 2x SSD 8192 4 100 94.00 0.139880 s-4vcpu-16gb-320gb-intel Basic Intel 16384 4 320 96.00 0.142860 s-8vcpu-16gb Basic 16384 8 320 96.00 0.142860 m-2vcpu-16gb-intel Premium Memory-Optimized 16384 2 50 99.00 0.147320 m3-2vcpu-16gb Memory-Optimized 3x SSD 16384 2 150 104.00 0.154760 c-4-intel Premium Intel 8192 4 50 109.00 0.162200 m3-2vcpu-16gb-intel Premium Memory-Optimized 3x SSD 16384 2 150 110.00 0.163690 s-8vcpu-16gb-amd Basic AMD 16384 8 320 112.00 0.166670 s-8vcpu-16gb-intel Basic Intel 16384 8 320 112.00 0.166670 c2-4vcpu-8gb-intel Premium Intel 8192 4 100 122.00 0.181550 g-4vcpu-16gb General Purpose 16384 4 50 126.00 0.187500 s-8vcpu-16gb-480gb-intel Basic Intel 16384 8 480 128.00 0.190480 so-2vcpu-16gb-intel Premium Storage-Optimized 16384 2 300 131.00 0.194940 so-2vcpu-16gb Storage-Optimized 16384 2 300 131.00 0.194940 m6-2vcpu-16gb Memory-Optimized 6x SSD 16384 2 300 131.00 0.194940 gd-4vcpu-16gb General Purpose 2x SSD 16384 4 100 136.00 0.202380 so1_5-2vcpu-16gb-intel Premium Storage-Optimized 1.5x SSD 16384 2 450 139.00 0.206850 g-4vcpu-16gb-intel General Purpose — Premium Intel 16384 4 60 151.00 0.224700 gd-4vcpu-16gb-intel General Purpose — Premium Intel 2x SSD 16384 4 120 158.00 0.235120 so1_5-2vcpu-16gb Storage-Optimized 1.5x SSD 16384 2 450 163.00 0.242560 s-8vcpu-32gb-amd Basic AMD 32768 8 400 168.00 0.250000 m-4vcpu-32gb Memory-Optimized 32768 4 100 168.00 0.250000 c-8 CPU-Optimized 16384 8 100 168.00 0.250000 c2-8vcpu-16gb CPU-Optimized 2x SSD 16384 8 200 188.00 0.279760 s-8vcpu-32gb-640gb-intel Basic Intel 32768 8 640 192.00 0.285710 m-4vcpu-32gb-intel Premium Memory-Optimized 32768 4 100 198.00 0.294640 m3-4vcpu-32gb Memory-Optimized 3x SSD 32768 4 300 208.00 0.309520 c-8-intel Premium Intel 16384 8 100 218.00 0.324400 m3-4vcpu-32gb-intel Premium Memory-Optimized 3x SSD 32768 4 300 220.00 0.327380 c2-8vcpu-16gb-intel Premium Intel 16384 8 200 244.00 0.363100 g-8vcpu-32gb General Purpose 32768 8 100 252.00 0.375000 so-4vcpu-32gb-intel Premium Storage-Optimized 32768 4 600 262.00 0.389880 so-4vcpu-32gb Storage-Optimized 32768 4 600 262.00 0.389880 m6-4vcpu-32gb Memory-Optimized 6x SSD 32768 4 600 262.00 0.389880 gd-8vcpu-32gb General Purpose 2x SSD 32768 8 200 272.00 0.404760 so1_5-4vcpu-32gb-intel Premium Storage-Optimized 1.5x SSD 32768 4 900 278.00 0.413690 g-8vcpu-32gb-intel General Purpose — Premium Intel 32768 8 120 302.00 0.449400 gd-8vcpu-32gb-intel General Purpose — Premium Intel 2x SSD 32768 8 240 317.00 0.471730 so1_5-4vcpu-32gb Storage-Optimized 1.5x SSD 32768 4 900 326.00 0.485120 m-8vcpu-64gb Memory-Optimized 65536 8 200 336.00 0.500000 c-16 CPU-Optimized 32768 16 200 336.00 0.500000 c2-16vcpu-32gb CPU-Optimized 2x SSD 32768 16 400 376.00 0.559520 m-8vcpu-64gb-intel Premium Memory-Optimized 65536 8 200 396.00 0.589290 m3-8vcpu-64gb Memory-Optimized 3x SSD 65536 8 600 416.00 0.619050 c-16-intel Premium Intel 32768 16 200 437.00 0.650300 m3-8vcpu-64gb-intel Premium Memory-Optimized 3x SSD 65536 8 600 440.00 0.654760 c2-16vcpu-32gb-intel Premium Intel 32768 16 400 489.00 0.727680 g-16vcpu-64gb General Purpose 65536 16 200 504.00 0.750000 so-8vcpu-64gb-intel Premium Storage-Optimized 65536 8 1200 524.00 0.779760 so-8vcpu-64gb Storage-Optimized 65536 8 1200 524.00 0.779760 m6-8vcpu-64gb Memory-Optimized 6x SSD 65536 8 1200 524.00 0.779760 gd-16vcpu-64gb General Purpose 2x SSD 65536 16 400 544.00 0.809520 so1_5-8vcpu-64gb-intel Premium Storage-Optimized 1.5x SSD 65536 8 1800 556.00 0.827380 gpu-4000adax1-20gb RTX 4000 Ada GPU Droplet - 1X 32768 8 500 565.44 0.760000 g-16vcpu-64gb-intel General Purpose — Premium Intel 65536 16 240 605.00 0.900300 gd-16vcpu-64gb-intel General Purpose — Premium Intel 2x SSD 65536 16 480 634.00 0.943450 so1_5-8vcpu-64gb Storage-Optimized 1.5x SSD 65536 8 1800 652.00 0.970240 m-16vcpu-128gb Memory-Optimized 131072 16 400 672.00 1.000000 c-32 CPU-Optimized 65536 32 400 672.00 1.000000 c2-32vcpu-64gb CPU-Optimized 2x SSD 65536 32 800 752.00 1.119050 m-16vcpu-128gb-intel Premium Memory-Optimized 131072 16 400 792.00 1.178570 m3-16vcpu-128gb Memory-Optimized 3x SSD 131072 16 1200 832.00 1.238100 c-32-intel Premium Intel 65536 32 400 874.00 1.300600 m3-16vcpu-128gb-intel Premium Memory-Optimized 3x SSD 131072 16 1200 880.00 1.309520 c2-32vcpu-64gb-intel Premium Intel 65536 32 800 978.00 1.455360 c-48 CPU-Optimized 98304 48 600 1008.00 1.500000 m-24vcpu-192gb Memory-Optimized 196608 24 600 1008.00 1.500000 g-32vcpu-128gb General Purpose 131072 32 400 1008.00 1.500000 so-16vcpu-128gb-intel Premium Storage-Optimized 131072 16 2400 1048.00 1.559520 so-16vcpu-128gb Storage-Optimized 131072 16 2400 1048.00 1.559520 m6-16vcpu-128gb Memory-Optimized 6x SSD 131072 16 2400 1048.00 1.559520 gd-32vcpu-128gb General Purpose 2x SSD 131072 32 800 1088.00 1.619050 so1_5-16vcpu-128gb-intel Premium Storage-Optimized 1.5x SSD 131072 16 3600 1112.00 1.654760 c2-48vcpu-96gb CPU-Optimized 2x SSD 98304 48 1200 1128.00 1.678570 gpu-l40sx1-48gb L40S GPU Droplet - 1X 65536 8 500 1168.08 1.570000 gpu-6000adax1-48gb RTX 6000 Ada GPU Droplet - 1X 65536 8 500 1168.08 1.570000 m-24vcpu-192gb-intel Premium Memory-Optimized 196608 24 600 1188.00 1.767860 g-32vcpu-128gb-intel General Purpose — Premium Intel 131072 32 480 1210.00 1.800600 m3-24vcpu-192gb Memory-Optimized 3x SSD 196608 24 1800 1248.00 1.857140 g-40vcpu-160gb General Purpose 163840 40 500 1260.00 1.875000 gd-32vcpu-128gb-intel General Purpose — Premium Intel 2x SSD 131072 32 960 1268.00 1.886900 so1_5-16vcpu-128gb Storage-Optimized 1.5x SSD 131072 16 3600 1304.00 1.940480 c-48-intel Premium Intel 98304 48 600 1310.00 1.949400 m3-24vcpu-192gb-intel Premium Memory-Optimized 3x SSD 196608 24 1800 1320.00 1.964290 m-32vcpu-256gb Memory-Optimized 262144 32 800 1344.00 2.000000 gd-40vcpu-160gb General Purpose 2x SSD 163840 40 1000 1360.00 2.023810 c2-48vcpu-96gb-intel Premium Intel 98304 48 1200 1466.00 2.181550 gpu-mi300x1-192gb AMD MI300X - 1X 245760 20 720 1480.56 1.990000 so-24vcpu-192gb-intel Premium Storage-Optimized 196608 24 3600 1572.00 2.339290 so-24vcpu-192gb Storage-Optimized 196608 24 3600 1572.00 2.339290 m6-24vcpu-192gb Memory-Optimized 6x SSD 196608 24 3600 1572.00 2.339290 m-32vcpu-256gb-intel Premium Memory-Optimized 262144 32 800 1584.00 2.357140 c-60-intel Premium Intel 122880 60 750 1639.00 2.438990 m3-32vcpu-256gb Memory-Optimized 3x SSD 262144 32 2400 1664.00 2.476190 so1_5-24vcpu-192gb-intel Premium Storage-Optimized 1.5x SSD 196608 24 5400 1668.00 2.482140 m3-32vcpu-256gb-intel Premium Memory-Optimized 3x SSD 262144 32 2400 1760.00 2.619050 g-48vcpu-192gb-intel General Purpose — Premium Intel 196608 48 720 1814.00 2.699400 c2-60vcpu-120gb-intel Premium Intel 122880 60 1500 1834.00 2.729170 gd-48vcpu-192gb-intel General Purpose — Premium Intel 2x SSD 196608 48 1440 1901.00 2.828870 so1_5-24vcpu-192gb Storage-Optimized 1.5x SSD 196608 24 5400 1956.00 2.910710 so-32vcpu-256gb-intel Premium Storage-Optimized 262144 32 4800 2096.00 3.119050 so-32vcpu-256gb Storage-Optimized 262144 32 4800 2096.00 3.119050 m6-32vcpu-256gb Memory-Optimized 6x SSD 262144 32 4800 2096.00 3.119050 so1_5-32vcpu-256gb-intel Premium Storage-Optimized 1.5x SSD 262144 32 7200 2224.00 3.309520 g-60vcpu-240gb-intel General Purpose — Premium Intel 245760 60 900 2269.00 3.376490 m-48vcpu-384gb-intel Premium Memory-Optimized 393216 48 1200 2376.00 3.535710 gd-60vcpu-240gb-intel General Purpose — Premium Intel 2x SSD 245760 60 1800 2378.00 3.538690 gpu-h100x1-80gb H100 GPU - 1X 245760 20 720 2522.16 3.390000 gpu-h200x1-141gb Nvidia H200 - 1X 245760 24 720 2559.36 3.440000 so1_5-32vcpu-256gb Storage-Optimized 1.5x SSD 262144 32 7200 2608.00 3.880950 m3-48vcpu-384gb-intel Premium Memory-Optimized 3x SSD 393216 48 3600 2640.00 3.928570 so-48vcpu-384gb-intel Premium Storage-Optimized 393216 48 7000 3144.00 4.678570 gpu-mi300x8-1536gb AMD MI300X - 8X 1966080 160 2046 11844.48 15.920000 gpu-h100x8-640gb H100 GPU - 8X 1966080 160 2046 17796.48 23.920000 gpu-h200x8-1128gb Nvidia H200 - 8X 1966080 192 2046 20474.88 27.520000
Creating a Droplet
bashdocker container run --rm \ --env=DIGITALOCEAN_ACCESS_TOKEN \ --env=DIGITALOCEAN_SSH_KEY_IDS \ --env=DIGITALOCEAN_REGION \ docker.io/boxcutter/doctl doctl compute droplet create ubuntu22-04 \ --ssh-keys $DIGITALOCEAN_SSH_KEY_IDS \ --size s-1vcpu-1gb \ --image ubuntu-24-04-x64 \ --region $DIGITALOCEAN_REGION \ --enable-ipv6 \ --enable-monitoring
Listing current droplets
bashdocker container run --rm \ --env=DIGITALOCEAN_ACCESS_TOKEN \ docker.io/boxcutter/doctl doctl compute droplet list
SSH into a running instance
You can use two methods:
It is recommended that you use the ssh-agent and use SSH forwarding as it is slightly more secure.
Mounting private key in the container
# Mounting private key into container docker container run --rm --interactive --tty \ --env=DIGITALOCEAN_ACCESS_TOKEN \ --mount type=bind,source="$HOME/.ssh/id_ed25519",target="/root/.ssh/id_ed25519",readonly \ docker.io/boxcutter/doctl doctl compute ssh <DROPLET_ID>
Using SSH forwarding to get the private key into the container environment
# Using SSH forwarding ssh-add -l # Check if keys are cached ssh-add # If not add identities docker container run --rm --interactive --tty \ --env=DIGITALOCEAN_ACCESS_TOKEN \ --env=SSH_AUTH_SOCK \ --mount type=***d,source=$SSH_AUTH_SOCK,target=$SSH_AUTH_SOCK,readonly \ docker.io/boxcutter/doctl doctl compute ssh <DROPLET_ID> # Using SSH forwarding with Docker Desktop for Mac # Seems like you need to use a magic path to forward SSH_AUTH_SOCK into the VM running the Linux instancea ssh-add -l # Check if keys are cached ssh-add # If not add identities docker container run --rm --interactive --tty \ --env=DIGITALOCEAN_ACCESS_TOKEN \ --env=SSH_AUTH_SOCK=/run/host-services/ssh-auth.sock \ --mount type=***d,source=/run/host-services/ssh-auth.sock,target=/run/host-services/ssh-auth.sock,readonly \ docker.io/boxcutter
您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本,请访问 标签列表页面。
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