docs: update compose.yaml and Dockerfile to clarify GPU parameter usage and add libgl installation

docker/china/Dockerfile

 # Use the official sglang image
 FROM lmsysorg/sglang:v0.4.8.post1-cu126
 
-# install mineru latest
+# Install libgl for opencv support
+RUN apt-get update && apt-get install -y libgl1 && apt-get clean
+
+# Install mineru latest
 RUN python3 -m pip install -U 'mineru[core]' -i https://mirrors.aliyun.com/pypi/simple --break-system-packages
 
 # Download models and update the configuration file

docker/compose.yaml

@@ -14,9 +14,9 @@ services:
       --host 0.0.0.0
       --port 30000
       # --enable-torch-compile  # You can also enable torch.compile to accelerate inference speed by approximately 15%
-      # --dp 2  # If you have more than two GPUs with 24GB VRAM or above, you can use sglang's multi-GPU parallel mode to increase throughput  
-      # --tp 2  # If you have two GPUs with 12GB or 16GB VRAM, you can use the Tensor Parallel (TP) mode
-      # --mem-fraction-static 0.7  # If you have two GPUs with 11GB VRAM, in addition to Tensor Parallel mode, you need to reduce the KV cache size
+      # --dp-size 2  # If using multiple GPUs, increase throughput using sglang's multi-GPU parallel mode
+      # --tp-size 2  # If you have more than one GPU, you can expand available VRAM using tensor parallelism (TP) mode.
+      # --mem-fraction-static 0.5  # If running on a single GPU and encountering VRAM shortage, reduce the KV cache size by this parameter, If VRAM issues persist, try lowering it further to `0.4` or below.
     ulimits:
       memlock: -1
       stack: 67108864

docker/global/Dockerfile

 # Use the official sglang image
 FROM lmsysorg/sglang:v0.4.8.post1-cu126
 
-# install mineru latest
+# Install libgl for opencv support
+RUN apt-get update && apt-get install -y libgl1 && apt-get clean
+
+# Install mineru latest
 RUN python3 -m pip install -U 'mineru[core]' --break-system-packages
 
 # Download models and update the configuration file