worker_id: "local-worker"
base_path: "data/dev/experiments"
train_script: "train.py"

redis_url: "redis://localhost:6379/0"

local_mode: true

prewarm_enabled: false

max_workers: 2
poll_interval_seconds: 2

auto_fetch_data: false

data_manager_path: "./data_manager"
dataset_cache_ttl: "30m"

data_dir: "data/dev/active"

snapshot_store:
  enabled: false

podman_image: "python:3.9-slim"
container_workspace: "/workspace"
container_results: "/results"
gpu_devices: []
gpu_vendor: "apple"
gpu_visible_devices: []

# Apple M-series GPU configuration
apple_gpu:
  enabled: true
  metal_device: "/dev/metal"
  mps_runtime: "/dev/mps"

resources:
  max_workers: 2
  desired_rps_per_worker: 2
  podman_cpus: "2"
  podman_memory: "4Gi"

metrics:
  enabled: false

queue:
  type: "native"
  native:
    data_dir: "data/dev/queue"

# Plugin Configuration (for local development)
plugins:
  # Jupyter Notebook/Lab Service
  jupyter:
    enabled: true
    image: "quay.io/jupyter/base-notebook:latest"
    default_port: 8888
    mode: "lab"
    # Security settings
    security:
      trusted_channels:
        - "conda-forge"
        - "defaults"
      blocked_packages: []  # Less restrictive for local dev
      require_password: false  # No password for local dev
    # Resource limits
    max_gpu_per_instance: 1
    max_memory_per_instance: "4Gi"
  
  # vLLM Inference Service
  vllm:
    enabled: true
    image: "vllm/vllm-openai:latest"
    default_port: 8000
    # Model cache location
    model_cache: "data/dev/models"
    # Supported quantization methods: awq, gptq, fp8, squeezellm
    default_quantization: ""  # No quantization for dev (better quality)
    # Resource limits
    max_gpu_per_instance: 1
    max_model_len: 2048
    tensor_parallel_size: 1

task_lease_duration: "30m"
heartbeat_interval: "1m"
max_retries: 3
graceful_timeout: "5m"