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Ray 2.59 enables token authentication by default for local clusters, and Ray 2.61 extends it to all clusters. Read the rollout details

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Site Navigation

  • Get Started

  • Use Cases

  • Example Gallery

  • Library

    • Ray CoreScale general Python applications

    • Ray DataScale data ingest and preprocessing

    • Ray TrainScale machine learning training

    • Ray TuneScale hyperparameter tuning

    • Ray ServeScale model serving

    • Ray RLlibScale reinforcement learning

  • APIs

  • Resources

    • Discussion ForumGet your Ray questions answered

    • TrainingHands-on learning

    • BlogUpdates, best practices, user-stories

    • EventsWebinars, meetups, office hours

    • Success StoriesReal-world workload examples

    • EcosystemLibraries integrated with Ray

    • CommunityConnect with us

Try Managed Ray

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  • Ray APIs
  • Ray Serve API

Ray Serve API#

The Ray Serve API reference documents Serve’s public Python API, CLI, and REST API. Each page below covers one group of APIs.

  • Writing applications
    • Deployments and applications
    • Deployment decorators
  • Deployment handles
    • Handle and response classes
    • Get a handle
  • Running applications
  • Configuration
    • Options and policies
    • Configuration models
  • Runtime context
    • Replica and request context
    • gRPC context
  • Request router
  • Schemas
    • Status and details
    • Config schemas
    • Response schemas
  • Exceptions
  • Observability
    • Metrics
    • Logging and tracing
  • LLM API
    • Builders
    • Configs
    • Deployments
  • CLI
    • serve
  • REST API
    • PUT "/api/serve/applications/"
    • GET "/api/serve/applications/"
    • DELETE "/api/serve/applications/"

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Writing applications

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