AutoML-Studio/nacos/automl-config.yaml at dev · AI-change-the-world/AutoML-Studio · GitHub

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# Auto ML Platform Configuration

db:
  host: ${MYSQL_HOST}
  port: ${MYSQL_PORT}
  username: ${MYSQL_USER}
  password: ${MYSQL_PASSWORD}
  database: ${MYSQL_DATABASE}


local-s3-config:
  access_key: ${ACCESS_KEY}
  secret_key: ${SECRET_KEY}
  endpoint: ${MINIO_ENDPOINT}
  region: us-east-1
  bucket_name: auto-ml-datasets
  datasets_bucket_name: auto-ml-datasets
  models_bucket_name: auto-ml-models
  annotations_bucket_name: auto-ml-annotations

rabbitmq:
  host: ${RABBITMQ_HOST}
  port: ${RABBITMQ_PORT}
  username: ${RABBITMQ_USER}
  password: ${RABBITMQ_PASSWORD}
  virtual_host: ${RABBITMQ_VHOST}
  exchange_name: ${RABBITMQ_EXCHANGE}
  exchange_type: ${RABBITMQ_EXCHANGE_TYPE}
  queues:
    task_status: auto_ml.task.status
    task_log: auto_ml.task.log
    model_registered: auto_ml.model.registered
    model_deployed: auto_ml.model.deployed
    model_undeployed: auto_ml.model.undeployed
    trainer_task: trainer.task.queue
    training_code_execute: training.code.execute
    assist_rpc: auto_ml.assist.rpc
    pipeline_batch_execute: auto_ml.pipeline.batch.execute
    pipeline_batch_progress: auto_ml.pipeline.batch.progress
    pipeline_batch_result: auto_ml.pipeline.batch.result
  routing_keys:
    task_status: task.status.update
    task_log: task.log
    model_registered: model.registered
    model_deployed: model.deployed
    model_undeployed: model.undeployed
    trainer_task: trainer.task.submit
    training_code_execute: training.code.execute
    assist_rpc: assist.rpc.request
    pipeline_batch_execute: pipeline.batch.execute
    pipeline_batch_progress: pipeline.batch.progress
    pipeline_batch_result: pipeline.batch.result

model-trainer:
  base_url: ${MODEL_TRAINER_URL}
  timeout: 30
  default_device: cpu
  max_concurrent_tasks: 1
  temp_dir: /app/runs

model-deploy:
  base_url: ${MODEL_DEPLOY_URL}
  timeout: 60
  runtime_base_port: 9001
  runtime_max_port: 9100
  health_check_interval: 30

ai-pipeline-runtime:
  base_url: ${AI_PIPELINE_RUNTIME_URL}
  timeout: 120
  default_profile: assist_default

# Experimental only. Edit this block in Nacos to opt in; it is not part of
# the default Compose deployment and never dispatches production trainer tasks.
model-training-runtime:
  enabled: false
  base_url: ""
  timeout: 120
  token: ""
  allow_script_managed_data: false
  execution:
    enabled: false
    runtime_ids:
      - ultralytics-8.3.0-pytorch-2.5-cu124
      - pytorch-2.5-cu124

task_stale_timeout_seconds: ${TASK_STALE_TIMEOUT_SECONDS}

logging:
  level: INFO
  path: /app/logs

ai-pipeline-batch:
  secret_key: erwQngaQgmx96Ym8r2QBwMtQOWCHR3EjtQit04jD-Y8=

assistant:
  secret_key: erwQngaQgmx96Ym8r2QBwMtQOWCHR3EjtQit04jD-Y8=

ai-pipeline-sandbox:
  rabbitmq:
    host: rabbitmq
  storage:
    endpoint: http://minio:9000
  timeout_seconds: 300
  max_output_bytes: 2097152
  memory_bytes: 1073741824
  cpu_seconds: 300
  max_processes: 32
  script_runtime:
    venv_root: /app/runtime-data/venvs
    pip_cache_dir: /app/runtime-data/pip-cache
    pip_index_url: https://mirrors.aliyun.com/pypi/simple
    pip_trusted_host: mirrors.aliyun.com
    idle_timeout_seconds: 180
    bootstrap_max_processes: 128
    process_fsize_bytes: 52428800
    process_nofile: 512