refactor: Optimize the way to obtain GPU computing power.

scripts/get_cuda_capability.py

@@ -0,0 +1,20 @@
+import pycuda.driver as cuda
+import pycuda.autoinit
+import sys  # 导入sys模块来读取命令行参数
+
+def get_cuda_device_major_minor(device_id=0):
+    cuda.init()
+    device = cuda.Device(device_id)
+    attributes = device.get_attributes()
+    major = attributes[cuda.device_attribute.COMPUTE_CAPABILITY_MAJOR]
+    minor = attributes[cuda.device_attribute.COMPUTE_CAPABILITY_MINOR]
+    cmp_ver = f"{major}.{minor}"
+    return cmp_ver
+
+# 从命令行参数获取设备号
+device_id = 0  # 默认设备号
+if len(sys.argv) > 1:
+    device_id = int(sys.argv[1])  # 将传入的参数转换为整数
+
+cmp_ver = get_cuda_device_major_minor(device_id)
+print(cmp_ver)  # 打印结果以便在Shell中捕获

scripts/run_for_cloud_option.sh

@@ -123,10 +123,12 @@ echo "GPU ID: $gpu_id1, $gpu_id2"
 # 判断硬件条件与启动参数是否匹配
 # 获取显卡型号
 gpu_model=$(nvidia-smi --query-gpu=gpu_name --format=csv,noheader,nounits -i $gpu_id1)
-compute_capability=$(jq -r ".[\"$gpu_model\"]" /workspace/qanything_local/scripts/gpu_capabilities.json)
-# 如果compute_capability为空，则说明显卡型号不在gpu_capabilities.json中
-if [ -z "$compute_capability" ]; then
-    echo "您的显卡型号 $gpu_model 不在支持列表中，请联系技术支持。"
+# compute_capability=$(jq -r ".[\"$gpu_model\"]" /workspace/qanything_local/scripts/gpu_capabilities.json)
+# 执行Python脚本，传入设备号，并捕获输出
+compute_capability=$(python3 get_cuda_capability.py $gpu_id1)
+status=$?  # 获取Python脚本的退出状态码
+if [ $status -ne 0 ]; then
+    echo "您的显卡型号 $gpu_model 获取算力时出错，请联系技术支持。"
     exit 1
 fi
 echo "GPU1 Model: $gpu_model"

scripts/run_for_local_option.sh

@@ -150,14 +150,16 @@ gpu_model=$(nvidia-smi --query-gpu=gpu_name --format=csv,noheader,nounits -i $gp
 base_gpu_model=$(echo $gpu_model | grep -o '^[^-]*')
 # nvidia RTX 30系列或40系列或A系列，比如A10，A30，A30，A100，A800
 gpu_series=$(echo $gpu_model | grep -oP '(RTX\s*(30|40)|A(10|30|40|100|800))')
-if ! command -v jq &> /dev/null; then
-    echo "Error: jq 命令不存在，请使用 sudo apt update && sudo apt-get install jq 安装，再重新启动。"
-    exit 1
-fi
-compute_capability=$(jq -r ".[\"$base_gpu_model\"]" /workspace/qanything_local/scripts/gpu_capabilities.json)
-# 如果compute_capability为空，则说明显卡型号不在gpu_capabilities.json中
-if [ "$compute_capability" == "null" ]; then
-    echo "您的显卡型号 $gpu_model 不在支持列表中，请联系技术支持。"
+#if ! command -v jq &> /dev/null; then
+#    echo "Error: jq 命令不存在，请使用 sudo apt update && sudo apt-get install jq 安装，再重新启动。"
+#    exit 1
+#fi
+# compute_capability=$(jq -r ".[\"$base_gpu_model\"]" /workspace/qanything_local/scripts/gpu_capabilities.json)
+# 执行Python脚本，传入设备号，并捕获输出
+compute_capability=$(python3 get_cuda_capability.py $gpu_id1)
+status=$?  # 获取Python脚本的退出状态码
+if [ $status -ne 0 ]; then
+    echo "您的显卡型号 $gpu_model 获取算力时出错，请联系技术支持。"
     exit 1
 fi
 echo "GPU1 Model: $gpu_model"
@@ -376,9 +378,6 @@ CUDA_VISIBLE_DEVICES=$gpu_id2 nohup python3 -u qanything_kernel/dependent_server
 echo "The ocr service is ready! (3/8)"
 echo "OCR服务已就绪! (3/8)"
 
-pip install third_party/es/whl/elastic_transport-8.12.0-py3-none-any.whl
-pip install third_party/es/whl/elasticsearch-8.12.1-py3-none-any.whl
-
 nohup python3 -u qanything_kernel/qanything_server/sanic_api.py --mode "local" > /workspace/qanything_local/logs/debug_logs/sanic_api.log 2>&1 &
 
 # 监听后端服务启动