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Merge pull request #73 from devsapp/add-model-download
fix: nasAuto mountDir
2 parents 48884e0 + c23c3f2 commit 671cf89

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6 files changed

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‎example/s-pipeline.yaml‎

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edition: 3.0.0
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name: ai-model-app
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access: quanxi
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resources:
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modelDemo:
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component: fc3
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props:
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region: cn-shanghai
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runtime: custom-container
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functionName: ${env('fc_component_function_name', 'ai-model-test-qwen-pipeline')}
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description: model service from functionai test
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logConfig: auto
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vpcConfig: auto
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nasConfig: auto
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instanceConcurrency: 20
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cpu: 8
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memorySize: 65536
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diskSize: 10240
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timeout: 300
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gpuConfig:
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gpuMemorySize: 49152
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gpuType: fc.gpu.ada.1
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customContainerConfig:
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image: >-
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serverless-registry.cn-hangzhou.cr.aliyuncs.com/functionai/modelscope:ubuntu22.04-cuda12.1.0-py311-torch2.3.1-tf2.16.1-1.26.0
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port: 9000
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entrypoint:
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- sh
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- '-c'
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- >-
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mkdir -p /.function_model && curl -fL --retry 3 -o
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/.function_model/server.py
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https://images.devsapp.cn/modelscope/server.py && MODEL_ID="${env('MODEL_ID', 'iic/SenseVoiceSmall')}" MODEL_VERSION="${env('MODEL_VERSION', 'master')}" MODEL_PATH="/mnt/${env('fc_component_function_name', 'ai-model-test-qwen-pipeline')} /${env('MODEL_ID', 'iic/SenseVoiceSmall')}" TASK="${env('TASK')}" python3 -u /.function_model/server.py
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triggers: # 默认，用户可能关注的是开启 authType 是 bear token
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- triggerConfig:
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methods:
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- GET
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- POST
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- PUT
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- DELETE
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authType: anonymous
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disableURLInternet: false
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triggerName: httpTrigger
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description: ''
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qualifier: LATEST
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triggerType: http
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provisionConfig:
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target: 1
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alwaysAllocateCPU: false
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alwaysAllocateGPU: false
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mode: sync
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supplement:
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modelConfig:
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source: modelscope
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id: ${env('MODEL_ID', 'iic/SenseVoiceSmall')}
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# id: Qwen/Qwen3-14B
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storage: nas
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role: acs:ram::${config('AccountID')}:role/aliyundevsdefaultrole
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‎example/s.yaml‎

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@@ -4,7 +4,7 @@ access: quanxi
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resources:
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modelDemo:
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component: fc3@dev
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component: fc3
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props:
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region: cn-shanghai
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runtime: custom-container

example/test_models.sh renamed to example/test_models_VLLM.sh

File renamed without changes.

‎example/test_models_pipeline.sh‎

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#!/bin/bash
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# 定义日志文件
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LOG_FILE="test_models.log"
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# 清空或创建日志文件
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> "$LOG_FILE"
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# 日志记录函数
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log() {
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echo "$(date '+%Y-%m-%d %H:%M:%S') - $1" | tee -a "$LOG_FILE"
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}
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# 定义模型列表 (每个元素包含model_version, model_id, task)
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MODEL_LIST=(
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'{"model_version": "v2.4.0", "model_id": "iic/cv_convnextTiny_ocr-recognition-general_damo", "task": "ocr-recognition", "input":{"image":"http://modelscope.oss-cn-beijing.aliyuncs.com/demo/images/image_ocr_recognition.jpg"}'
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'{"model_version": "master", "model_id": "iic/SenseVoiceSmall", "task": "auto-speech-recognition", "input": "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"}'
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)
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# 检查yaml文件是否存在
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YAML_FILE="s.yaml"
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if [ ! -f "$YAML_FILE" ]; then
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log "Error: $YAML_FILE not found!"
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exit 1
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fi
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# 遍历每个model_id
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for MODEL_INFO in "${MODEL_LIST[@]}"; do
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log "========================================"
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log "Testing model: $MODEL_INFO"
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log "========================================"
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# 从JSON对象中提取字段 (使用 jq)
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export MODEL_VERSION=$(echo "$MODEL_INFO" | grep -o '"model_version": *"[^"]*' | awk -F'"' '{print $4}')
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export MODEL_ID=$(echo "$MODEL_INFO" | grep -o '"model_id": *"[^"]*' | awk -F'"' '{print $4}')
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export TASK=$(echo "$MODEL_INFO" | grep -o '"task": *"[^"]*' | awk -F'"' '{print $4}')
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INPUT=$(echo "$MODEL_INFO" | grep -o '"input": *"[^"]*' | awk -F'"' '{print $4}')
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# 生成随机函数名
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RANDOM_STRING=$(openssl rand -hex 10)
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export fc_component_function_name=ai-model-qwen-$RANDOM_STRING
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export NEW_MODEL_SERVICE_CLIENT_CONNECT_TIMEOUT=10000
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# 下载模型
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log "Downloading model..."
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DOWNLOAD_OUTPUT=$(s model download -t s-pipeline.yaml 2>&1)
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echo "$DOWNLOAD_OUTPUT" >> "$LOG_FILE"
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echo "$DOWNLOAD_OUTPUT"
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if echo "$DOWNLOAD_OUTPUT" | grep -q "Error"; then
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log "Failed to download model: $MODEL_ID"
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continue
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fi
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# 部署服务
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log "Deploying..."
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DEPLOY_OUTPUT=$(s deploy -t s-pipeline.yaml -y 2>&1)
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echo "$DEPLOY_OUTPUT" >> "$LOG_FILE"
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echo "$DEPLOY_OUTPUT"
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# 检查部署是否成功
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if echo "$DEPLOY_OUTPUT" | grep -q "state:.*Active"; then
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log "Deployment successful for model: $MODEL_ID"
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else
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log "Deployment failed for model: $MODEL_ID"
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# 清理资源
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REMOVE_OUTPUT=$(s model remove -t s-pipeline.yaml -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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REMOVE_OUTPUT=$(s remove -t s-pipeline.yaml -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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continue
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fi
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# 提取system_url
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SYSTEM_URL=$(echo "$DEPLOY_OUTPUT" | grep "system_url:" | sed 's/.*system_url: *//' | tr -d ' "[:cntrl:]')
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if [ -z $SYSTEM_URL ]; then
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log "Failed to extract system_url for model: $MODEL_ID"
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# 清理资源
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REMOVE_OUTPUT=$(s model remove -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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REMOVE_OUTPUT=$(s remove -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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continue
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fi
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log "Extracted system_url: $SYSTEM_URL"
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# 发送测试请求
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log "Sending test request..."
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CURL_OUTPUT=$(curl -v -d '{"input":$INPUT}' $SYSTEM_URL 2>&1)
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echo "$CURL_OUTPUT" >> "$LOG_FILE"
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echo "$CURL_OUTPUT"
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# 检查curl请求是否成功
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if echo "$CURL_OUTPUT" | grep -q '"object":"chat.completion"'; then
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log "Model test successful for: $MODEL_ID"
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# 提取并显示模型回复内容
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RESPONSE_CONTENT=$(echo "$CURL_OUTPUT" | sed -n 's/.*"text":"\([^"]*\)".*/\1/p' | sed 's/\\n/\n/g' | sed 's/\\t/\t/g')
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log "Model response: $RESPONSE_CONTENT"
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else
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log "Model test failed for: $MODEL_ID"
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fi
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# 清理资源
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log "Removing resources..."
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REMOVE_OUTPUT=$(s model remove -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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REMOVE_OUTPUT=$(s remove -y 2>&1)
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echo "$REMOVE_OUTPUT" >> "$LOG_FILE"
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echo "$REMOVE_OUTPUT"
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log ""
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log "Finished testing model: $MODEL_ID"
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log ""
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done
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log "All models tested."

‎src/subCommands/deploy/impl/function.ts‎

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@@ -402,7 +402,7 @@ nasConfig:
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userId: 0
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mountPoints:
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- serverAddr: ${mountTargetDomain}:/${functionName}${isEmpty(modelConfig) ? '' : '/' + modelConfig.id}
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mountDir: /mnt/${functionName}${isEmpty(modelConfig) ? '' : '/' + modelConfig.id}
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mountDir: /mnt/${functionName}
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enableTLS: false\n`),
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);
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this.createResource.nas = { mountTargetDomain, fileSystemId };
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mountPoints: [
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{
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serverAddr: `${mountTargetDomain}:/${functionName}${isEmpty(modelConfig) ? '' : '/' + modelConfig.id}`,
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mountDir: `/mnt/${functionName}${isEmpty(modelConfig) ? '' : '/' + modelConfig.id}`,
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mountDir: `/mnt/${functionName}`,
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enableTLS: false,
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},
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],

‎src/subCommands/model/index.ts‎

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import { sleep } from '../../utils';
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export const NEW_MODEL_SERVICE_CLIENT_CONNECT_TIMEOUT: number =
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parseInt(process.env.NEW_MODEL_SERVICE_CLIENT_CONNECT_TIMEOUT as string, 10) || 5 * 1000;
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parseInt(process.env.NEW_MODEL_SERVICE_CLIENT_CONNECT_TIMEOUT as string, 10) || 10 * 1000;
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export const NEW_MODEL_SERVICE_CLIENT_READ_TIMEOUT: number =
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parseInt(process.env.NEW_MODEL_SERVICE_CLIENT_READ_TIMEOUT as string, 10) || 86400 * 1000;
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export const MODEL_DOWNLOAD_TIMEOUT: number =
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userId: 0
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mountPoints:
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- serverAddr: ${mountTargetDomain}:/${functionName}/${supplement.modelConfig.id}
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mountDir: /mnt/${functionName}/${supplement.modelConfig.id}
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mountDir: /mnt/${functionName}
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enableTLS: false\n`),
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);
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this.createResource.nas = { mountTargetDomain, fileSystemId };
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mountPoints: [
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{
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serverAddr: `${mountTargetDomain}:/${functionName}/${supplement.modelConfig.id}`,
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mountDir: `/mnt/${functionName}/${supplement.modelConfig.id}`,
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mountDir: `/mnt/${functionName}`,
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enableTLS: false,
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},
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],

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