ComfyUI to API issues
Hello! My team and I are moving to runpod and are preparing to scale big and I wanted to share what we are doing in hope that someone finds a better way to handle it.
We currently have one universal Dockerfile that prepares the folders, and creates symlinks to models and custom_nodes we have in an S3 volume which the serverless instances have access to.
This S3 volume has all the models and custom_nodes folders, and each GPU on boot installs all dependencies of custom_nodes.
Does all of this make sense or is there a better way to do it?
After spending the entire week building this I saw there is a "ComfyUI-to-API" tool but it prepares a dockerfile that makes each container on each GPU to download everything every time, which doesnt sound very interesting to reduce costs on amount of time spent...
Another big issue:
My workflows tend to make CPU AND GPU at 100%, and im pretty sure CPU being at 100% makes the images be generated with very weird looking artifacts, and the overall composition doesnt make sense, but running the same workflow locally on an even worse GPU works fine...
We currently have one universal Dockerfile that prepares the folders, and creates symlinks to models and custom_nodes we have in an S3 volume which the serverless instances have access to.
This S3 volume has all the models and custom_nodes folders, and each GPU on boot installs all dependencies of custom_nodes.
Does all of this make sense or is there a better way to do it?
After spending the entire week building this I saw there is a "ComfyUI-to-API" tool but it prepares a dockerfile that makes each container on each GPU to download everything every time, which doesnt sound very interesting to reduce costs on amount of time spent...
Another big issue:
My workflows tend to make CPU AND GPU at 100%, and im pretty sure CPU being at 100% makes the images be generated with very weird looking artifacts, and the overall composition doesnt make sense, but running the same workflow locally on an even worse GPU works fine...
