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Docker install instructions in the Readme are not working (improvement suggestion) #23
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This is actually more complex than is really needed, if you start with step 3 and complete the install as documented there, step 2 & 4 are not needed (nvidia will be the default and docker restarted at this step: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#configuring-docker). Step 1 & 5 are already documented. I get your point though, I don't really try to make it easy to get docker setup, I'll consider how to update the docs to make it simpler. People having trouble with nvidia+docker is a common problem for all the projects that prefer docker deployment, open-webui, litellm, etc. |
Perhaps consider adding a comment in the docker instructions to mention that an additional package may be necessary for GPU support in the docker container and to check the item number 4 at "Known Problems & Workarounds" for details. Because currently these steps are guaranteed to fail for everyone who does not have docker specific requirements preinstalled. There are may be other ways to describe requirements, this is just a example suggestion, but as long as sequence of installation steps is clear, any location in the readme is fine. If correct sequence of steps was there, it would have saved a lot of time when I was working on getting the docker up and running with GPU support. But like I said, it is just a suggestion, but please consider it, taking into account first time experience of users who did not use docker with GPU before. |
Latest code has some updates for 3.12 & docker. See a64740f |
OK, thanks. I see that you updated Readme as well, current instructions look good and make it clear that the Nvidia container toolkit is needed. I am going to test them by tomorrow (or maybe this evening, if I find the time) and report back to confirm if there are no issues (probably there will not be, assuming my original steps contained some unnecessary commands, as you have mentioned). |
OK, it mostly worked. The docker container itself got up and running, the docker GPU support is there and new Readme clearly mentions how to get it if not installed already. But to my surprise, I encountered the issue #19 even though it is solved long time ago. And it was in a repository that I cloned from scratch not that long ago when testing this again. Perhaps something just got cached, I do not know. The full error log:
As a workaround, I can run But it is a mystery to me why I get the old code in the docker container, even though the code in the repository is defenitely fresh and does not have this issue. It was non-trivial to figure out how to edit the docker container either. Since I already got manual installation method working, I do not really need the docker, so the only reason why test it is to contribute and help to discover issues, so other users in the future can get things working more reliably. In this case, there is maybe a misconfiguration on my end or something cached outside the repository related to docker, but I found no way to refresh the docker container to the up to date source code, except patching it manually. |
so weird... maybe it's github workers... I've had a bunch of trouble with them recently. pip not working, disk filling, etc. |
confirmed.... the latest image has old code !? |
I checked the logs and it even shows it pulled 0.39.1... and was tagged :latest... I have no idea, it maybe had some github / ghrc.io server issue? The latest image is confirmed correct, 0.39.2. |
to build the docker from source you can just:
Sometimes you may need to:
If you want to make sure to pull github repos, new pip version, etc, from inside the docker. |
When I tried installing openedai-vision in Docker container I encountered multiple issues (mentioned in #20) but in the end I was able to figure out minimal steps required to get it working on PC with Nvidia cards. Since Nvidia I think is the most common platform to use, and you already have Nvidia-specific information in the Readme, I think adding relevant steps to actually get the project working on of the most popular platform could be useful, and may help users on other platforms/distributions as well because they will have a clue what steps they need to follow.
Here are steps to get the docker container running on Linux with Nvidia GPUs:
cp vision.sample.env vision.env
and uncomment wanted model, optionally pointHF_HOME
to/home/username/.cache/huggingface/
if the model already downloaded therenvidia
indocker-compose.yml
nvidia-container-toolkit
using instructions from https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.htmlsudo service docker restart
docker compose up
For non-nvidia platforms steps 2 and 3 would be different. Note: old packages like "nvidia-container-runtime" are no longer needed and Nvidia officially marked them deprecated. Only
nvidia-container-toolkit
is needed to get things working. I hope this information helps to improve Readme. Please feel free to close this report, since Docker installation is something I already solved, so this issue report is just a possible suggestion to consider to improve the Readme instructions.The text was updated successfully, but these errors were encountered: