Container Resource Tuning Program
The following optimization strategies can be used for different deployment environments:
- memory limit: Add at startup
--memory=2g --memory-swap=3gParameters (4G or more recommended for Vincentian video scenes) - CPU allocation: Use
--cpus=2Limit the number of CPU cores, which can be temporarily raised during video generation - Data Volume Optimization: Will
./dataMount to SSD storage and clean it regularlytemp_filescatalogs - Model Loading on Demand: By
MODEL_PRELOADEnvironmental variables control the preloading model (e.g.-e MODEL_PRELOAD="gpt-4o,flux")
Recommended configuration for production environments:docker run --name genspark2api -d
--memory=4g --memory-swap=6g
--cpus=3
-v /mnt/ssd/genspark_data:/app/genspark2api/data
-e MODEL_PRELOAD="gpt-4o"
deanxv/genspark2api:latest
This answer comes from the articleGenspark2api (failed)The
May not be reproduced without permission:AI productivity tools " How to optimize the resource usage of genspark2api in Docker containers?
