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docker-compose.yml
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docker-compose.yml
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version: '3.8'
services:
cratedb:
image: crate:latest
container_name: crate-db
ports:
- "4200:4200"
networks:
- data_network
- dp_network
- m_network
- ls_network
- deploy_network
volumes:
- ${DB_DATA_PATH}:/data
- ${DB_DATA_PATH}/repos:/repos
command: [ "crate", "-Cnetwork.host=_site_" , "-Cpath.repo=/repos"]
deploy:
replicas: 1
restart_policy:
condition: on-failure
environment:
- CRATE_HEAP_SIZE=2g
ls_web:
profiles:
- label
- dev
restart: on-failure
image: heartexlabs/label-studio:latest
container_name: label-studio-web
ports:
- "8080:8080"
networks:
- ls_network
volumes:
- ./label-studio/config:/config
- ${LS_DATA_PATH}:/label-studio/data
- ${LS_TASKS_PATH}:/tasks
- ${LS_ANNOTATIONS_PATH}:/annotations
environment:
- LABEL_STUDIO_LOCAL_FILES_SERVING_ENABLED=true
- LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOT=/label-studio/files
command: [ "label-studio", "start" ]
ls:
profiles:
- label
- dev
restart: on-failure
image: nullberry/adapt-ml-ls:latest
container_name: label-studio-dev
networks:
- ls_network
volumes:
- ./label-studio/ls:/code/ls
- ${LS_DATA_PATH}:/label-studio/data
- ${LS_TASKS_PATH}:/tasks
- ${LS_ANNOTATIONS_PATH}:/annotations
- ./test:/test
environment:
- DATABASE_IP=${DATABASE_IP}
stdin_open: true
tty: true
dp_db:
profiles:
- data_programming
- dev
restart: on-failure
image: mysql/mysql-server:8.0.26
container_name: dp-mlflow-db
expose:
- 3306
networks:
- dp_network
volumes:
- ${DP_DATA_PATH}/dbdata:/var/lib/mysql
environment:
- MYSQL_DATABASE=${DP_MYSQL_DATABASE}
- MYSQL_USER=${DP_MYSQL_USER}
- MYSQL_PASSWORD=${DP_MYSQL_PASSWORD}
- MYSQL_ROOT_PASSWORD=${DP_MYSQL_ROOT_PASSWORD}
dp_web:
profiles:
- dev
restart: on-failure
image: nullberry/adapt-ml-mlflow-server:latest
container_name: dp-mlflow-server
ports:
- "5000:5000"
networks:
- dp_network
depends_on:
- dp_db
volumes:
- ${DP_DATA_PATH}/mlruns:/mlflow/mlruns
environment:
- MLFLOW_TRACKING_URI=${DP_MLFLOW_TRACKING_URI}
command: [ "mlflow",
"server",
"--backend-store-uri=$DP_MLFLOW_TRACKING_URI",
"--default-artifact-root=./mlruns",
"--host=0.0.0.0"]
dp:
profiles:
- data_programming
- dev
image: nullberry/adapt-ml-dp:dev
container_name: dp-mlflow
networks:
- dp_network
depends_on:
- dp_db
volumes:
- ${LS_ANNOTATIONS_PATH}:/annotations
- ${DP_DATA_PATH}/mlruns:/code/mlruns
- ${DP_DATA_PATH}/unlabeled_data:/unlabeled_data
- ${DP_DATA_PATH}/tmp_artifacts:/tmp_artifacts
- ${EMBEDDINGS_PATH}:/embeddings
- ./data-programming/label:/code/label
- ./data-programming/MLproject:/code/MLproject
- ./data-programming/conda.yaml:/code/conda.yaml
- ./test:/test
environment:
- MLFLOW_TRACKING_URI=${DP_MLFLOW_TRACKING_URI}
- DATABASE_IP=${DATABASE_IP}
stdin_open: true
tty: true
deploy:
resources:
reservations:
devices:
- capabilities: [ "gpu" ]
m_db:
profiles:
- modelling
- deploy
- dev
restart: on-failure
image: mysql/mysql-server:8.0.26
container_name: modelling-mlflow-db
expose:
- 3306
networks:
- m_network
volumes:
- ${MODELLING_DATA_PATH}/dbdata:/var/lib/mysql
environment:
- MYSQL_DATABASE=${MODELLING_MYSQL_DATABASE}
- MYSQL_USER=${MODELLING_MYSQL_USER}
- MYSQL_PASSWORD=${MODELLING_MYSQL_PASSWORD}
- MYSQL_ROOT_PASSWORD=${MODELLING_MYSQL_ROOT_PASSWORD}
m_web:
profiles:
- dev
restart: on-failure
image: nullberry/adapt-ml-mlflow-server:latest
container_name: modelling-mlflow-server
ports:
- "5001:5000"
networks:
- m_network
depends_on:
- m_db
volumes:
- ${MODELLING_DATA_PATH}/mlruns:/mlflow/mlruns
environment:
- MLFLOW_TRACKING_URI=${MODELLING_MLFLOW_TRACKING_URI}
command: [ "mlflow",
"server",
"--backend-store-uri=$MODELLING_MLFLOW_TRACKING_URI",
"--default-artifact-root=./mlruns",
"--host=0.0.0.0" ]
m:
profiles:
- modelling
- deploy
- dev
image: nullberry/adapt-ml-m:latest
container_name: modelling-mlflow
networks:
- m_network
depends_on:
- m_db
volumes:
- ${MODELLING_DATA_PATH}/mlruns:/code/mlruns
- ${DP_DATA_PATH}/mlruns:/dp_mlruns
- ${MODELLING_DATA_PATH}/tmp_artifacts:/tmp_artifacts
# - ${EMBEDDINGS_PATH}:/embeddings
- ./modelling/model:/code/model
- ./modelling/model_objs.py:/code/model_objs.py
- ./modelling/MLproject:/code/MLproject
- ./modelling/conda.yaml:/code/conda.yaml
- ./test:/test
environment:
- MLFLOW_TRACKING_URI=${MODELLING_MLFLOW_TRACKING_URI}
- DATABASE_IP=${DATABASE_IP}
stdin_open: true
tty: true
m_deploy:
profiles:
- deploy
- dev
image: nullberry/adapt-ml-m-deploy:latest
container_name: modelling-mlflow-deploy
ports:
- "80:80"
networks:
- deploy_network
volumes:
- ${MODELLING_DATA_PATH}/mlruns:/mlruns
# - ${EMBEDDINGS_PATH}:/embeddings
- ./modelling/app:/app
- ./modelling/model_objs.py:/app/model_objs.py
environment:
- DATABASE_IP=${DATABASE_IP}
- MULTICLASS_EXAMPLE_MODEL_PATH=${MULTICLASS_EXAMPLE_MODEL_PATH}
- MULTILABEL_EXAMPLE_MODEL_PATH=${MULTILABEL_EXAMPLE_MODEL_PATH}
- CLIMATE_FRAMES_MODEL_PATH=${CLIMATE_FRAMES_MODEL_PATH}
data:
profiles:
- dev
image: nullberry/framing-data:latest
container_name: framing-data-processing
networks:
- data_network
volumes:
- ${EMBEDDINGS_PATH}:/embeddings
- ${TWEETS_PATH}:/tweets
- ./figures:/figures
- ./framing-data:/code
stdin_open: true
tty: true
deploy:
resources:
reservations:
devices:
- capabilities: [ "gpu" ]
networks:
data_network:
driver: bridge
ls_network:
driver: bridge
dp_network:
driver: bridge
m_network:
driver: bridge
deploy_network:
driver: bridge