format: jb-book
root: index
parts:
  - caption: Overview
    chapters:
      - file: ray-overview/index
      - file: ray-overview/installation
      - file: ray-overview/learn-more
      - file: ray-overview/ray-libraries

  - caption: Ray ML
    chapters:
      - file: data/dataset
        title: Ray Data
        sections:
          - file: data/getting-started
          - file: data/user-guide
          - file: data/key-concepts
          - file: data/examples/big_data_ingestion

      - file: train/train
        title: Ray Train
        sections:
          - file: train/user_guide
          - file: train/examples
          - file: train/architecture
          - file: train/migration-guide
          - file: raysgd/raysgd
            title: "RaySGD v1: Distributed Training Wrappers"
      - file: tune/index
        title: Ray Tune
        sections:
          - file: tune/getting-started
          - file: tune/key-concepts
          - file: tune/tutorials/overview
            sections:
              - file: tune/tutorials/tune-sklearn
              - file: tune/tutorials/tune-pytorch-cifar
              - file: tune/tutorials/tune-pytorch-lightning
              - file: tune/tutorials/tune-serve-integration-mnist
              - file: tune/tutorials/tune-xgboost
              - file: tune/tutorials/tune-wandb
              - file: tune/tutorials/tune-mlflow
              - file: tune/tutorials/tune-comet
              - file: tune/tutorials/tune-stopping
              - file: tune/tutorials/tune-metrics
              - file: tune/tutorials/tune-output
              - file: tune/tutorials/tune-resources
              - file: tune/tutorials/tune-checkpoints
              - file: tune/tutorials/tune-lifecycle
              - file: tune/tutorials/tune-advanced-tutorial
              - file: tune/tutorials/tune-distributed
          - file: tune/examples/index
          - file: tune/faq
          - file: tune/api_docs/overview.rst
      - file: serve/index
        title: Ray Serve
        sections:
          - file: serve/end_to_end_tutorial
          - file: serve/core-apis
          - file: serve/http-servehandle
          - file: serve/deployment
          - file: serve/ml-models
          - file: serve/pipeline
          - file: serve/performance
          - file: serve/architecture
          - file: serve/tutorials/index
          - file: serve/faq
      - file: rllib/index
        title: Ray RLlib
        sections:
          - file: rllib/rllib-toc
          - file: rllib/core-concepts
          - file: rllib/rllib-training
          - file: rllib/rllib-env
          - file: rllib/rllib-models
          - file: rllib/rllib-algorithms
          - file: rllib/rllib-sample-collection
          - file: rllib/rllib-offline
          - file: rllib/rllib-concepts
          - file: rllib/rllib-examples
          - file: rllib/rllib-dev
      - file: workflows/concepts
        title: Ray Workflows
        sections:
          - file: workflows/basics
          - file: workflows/management
          - file: workflows/actors
          - file: workflows/metadata
          - file: workflows/events
          - file: workflows/comparison
          - file: workflows/advanced
      - file: ray-more-libs/index
        title: More Ray ML Libraries

  - caption: Ray Core
    chapters:
      - file: ray-core/walkthrough
        title: Getting Started
      - file: ray-core/using-ray
        title: "User Guide"
      - file: ray-core/examples/overview
        title: "Tutorials and Examples"

  - caption: Ray Clusters
    chapters:
      - file: cluster/quickstart
      - file: cluster/user-guide
      - file: cluster/cloud
      - file: cluster/deploy

  - caption: References
    chapters:
      - file: ray-references/api

  - caption: Developer Guides
    chapters:
      - file: ray-contribute/getting-involved
        sections:
          - file: ray-contribute/development
          - file: ray-contribute/fake-autoscaler
      - file: ray-core/configure
      - file: ray-observability/index
      - file: ray-design-patterns/index
      - file: ray-contribute/whitepaper

# TODO: Add examples section