# Deployment Files Perform the following steps to deploy On-premises files. 1. docker-compose.yml ```javascript version: "3" services: nginx: image: qureai/nginx:qureapp container_name: qureapp_nginx command: "/start.sh" env_file: hct_api.env restart: always ports: - "2001:80" qure-api: image: qureai/qure_platform_api:3.1.5.release.1f19fbb container_name: qureapi command: startgunicorn restart: always volumes: - qureapi-data:/srv/data - ./default_run_config.json:/srv/default_run_config.json ports: - "8080:8080" env_file: hct_api.env postgres: image: postgres container_name: psql_new command: "postgres -N 1000" restart: unless-stopped volumes: - qureapi-db:/var/lib/postgresql/data environment: - POSTGRES_HOST_AUTH_METHOD=trust - POSTGRES_USER=qure_user - POSTGRES_DB=qure_app ports: - "5432:5432" qure-api-worker-1: image: qureai/qure_platform_api:3.1.5.release.1f19fbb container_name: qureapiworker-1 command: run_workers_threaded --num_workers=4 env_file: hct_api.env volumes: - qureapi-data:/srv/data - qer-checkpoints:/srv/qer_checkpoints - qxr-checkpoints:/srv/cxr_checkpoints - qxr-blaze-checkpoints:/srv/qxr_blaze_checkpoints - qct-checkpoints:/srv/qct_checkpoints:ro restart: always logging: driver: "json-file" options: max-size: "1m" deploy: resources: reservations: devices: - driver: nvidia count: 1 capabilities: [gpu] qure-api-notebook: image: qureai/qure_platform_api:3.1.5.release.1f19fbb container_name: qureapi-notebook command: shell_plus --notebook -- --allow-root --ip 0.0.0.0 --NotebookApp.password=sha1:e9c30f3ff952:f15a3ef7d43f87f98048d9503149cb81b49cd539 restart: always volumes: - qureapi-data:/srv/data - notebooks:/app/services/qure_platform_api/qure_platform_api_image.binary.runfiles/qureai/notebooks/ ports: - "5888:8888" env_file: hct_api.env qer_checkpoints: image: qureai/hct_checkpoints:v3_ncct_cta_integration container_name: qer_checkpoints command: "tail -f /dev/null" restart: unless-stopped volumes: - qer-checkpoints:/checkpoints qct_checkpoints: image: qureai/qct_checkpoints:v1.3 container_name: qct_checkpoints command: "tail -f /dev/null" restart: unless-stopped volumes: - qct-checkpoints:/qct_checkpoints:ro cxr_checkpoints: image: qureai/qxr_checkpoints:4.0.3_ts_models_unencrypted container_name: cxr_checkpoints command: "tail -f /dev/null" restart: unless-stopped volumes: - qxr-checkpoints:/cxr_checkpoints:ro blaze_checkpoints: image: qureai/qxr_checkpoints:blaze_3.1 container_name: blaze_checkpoints command: "tail -f /dev/null" restart: unless-stopped volumes: - qxr-blaze-checkpoints:/qxr_blaze_checkpoints volumes: qureapi-data: qer-checkpoints: qxr-checkpoints: qxr-blaze-checkpoints: qct-checkpoints: qureapi-db: django_channel_data: ``` 2. hct\_api.env ```javascript HCT_API_DEBUG=True HCT_API_ALLOWED_HOSTS=* HCT_API_DATABASE_NAME=qure_app HCT_API_DATABASE_USER=qure_user HCT_API_DATABASE_HOST=postgres HCT_API_NGINX_SERVERNAME=~. HCT_API_NGINX_PRIVATE_SERVERNAME=~. NGINX_SERVER_NAME=~. NGINX_PRIVATE_SERVER_NAME=~. HCT_SOPCLASSUIDS=1.2.840.10008.5.1.4.1.1.2,1.2.840.10008.5.1.4.1.1.2.1,1.2.840.10008.5.1.4.1.1.2.2 IS_ON_PREMISE=True IMAGE_STORAGE_PROVIDER=FS FS_IMAGE_MANAGE_PATH=/srv/data/hct FS_SERVER_PATH=http://nginx/files STATIC_URL_PREFIX=/srv/data/hct FS_IMAGE_NGINX_PREFIX=/srv/data/hct ON_PREMISE=True #ZIP_TEMP_DIR=/srv/data/zip CLEAN_UP_AFTER_PROCESSING=True MAX_TASK_PER_WORKER=-1 CLEAN_UP_DELAY=3600 AUTH_OIDC_PROVIDER=https://accounts.qure.ai/auth KEYCLOAK_REALM=accounts AUTH_OIDC_CLIENT_ID=onpremise KEYCLOAK_CLIENT_SECRET=QP1eQQdJ7uCO77mDvVAZ8hZFfbxD8Lxx AUTH_FORCE_HTTPS=False POPULATE_DEFAULTS=True QER_CHECKPOINTS_PATH=/srv/qer_checkpoints/checkpoints CXR_CHECKPOINTS_PATH=/srv/cxr_checkpoints QCT_CHECKPOINTS_PATH=/srv/qct_checkpoints QXR_BLAZE_CHECKPOINTS_PATH=/srv/qxr_blaze_checkpoints WORKER_ID=MAIN-API1 MACHINE_ID=machine1 SC_GENERATOR_MOUNT_PATH=/srv/data/sc_generation_mount_path SC_GENERATION_PORT=8080 SC_GENERATION_HOST=sc_generation_api LD_LIBRARY_PATH=/app/services/qure_platform_api/qure_platform_api_image.binary.runfiles/python_deps_nvidia_cudnn_cu11/site-packages/nvidia/cudnn/lib:/app/services/qure_platform_api/qure_platform_api_image.binary.runfiles/python_deps_nvidia_cublas_cu11/site-packages/nvidia/cublas/lib:/app/python_deps_nvidia_cuda_nvrtc_cu11/site-packages/nvidia/cuda_nvrtc/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 DEFAULT_RUN_CONFIG_PATH=/srv/default_run_config.json ``` 3. default\_run\_config.json ```javascript { "qer":{}, "qct":{}, "qxr":{}, "qmsk":{}, "portal":{"enabled": true} }#contact qure support for changing this config ``` ## Log in to the docker-compose. ```javascript docker login - u prsjn dckr_pat_6bQdystrTNrhIDs - BHtBVqzS9lc ``` {% hint style="info" %} **Attention:** If the server does not have internet access, use the following command to transfer Docker images from one system to another. ```javascript #Taking #qureai/nginx:qureapp image as example #run this on system #1 docker save -o sample1.tar nginx:qureapp #tranfer the file to system #2 #run this on system #2 docker load -i sample1.tar #now you should be able to see your nginx:qureapp image in the system #2 ``` {% endhint %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://documentation.qure.ai/api/platform-api/on-premises-deployment-specifications/deployment-files.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.