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Valohai documentation
  • Tutorials
    • Learning paths
      • Valohai fundamentals
        • Setting up
        • Getting started
        • Upload output data
        • Use parameters
        • Download input data
        • Collect and view metrics
        • Define your steps in Python
        • Recap
      • Valohai pipelines
        • Getting started
        • Defining a pipeline in the valohai.yaml
        • Running a pipeline
        • Creating a pipeline with valohai-utils
        • Advanced pipeline features
        • Recap
    • Valohai 101
      • Creating a pipeline
      • Deployments
        • Deploying a model for online inference
        • Batch inference on CSVs
        • Batch inference on images
    • Jupyter Notebooks
    • Valohai APIs
      • Valohai API basics
      • Fetching failed executions
      • Downloading metadata of a single execution
      • Triggering an execution after a push to a code repository
    • Valohai command-line client valohai-cli
      • Using the valohai-cli
      • Choosing environment though valohai-cli
      • Using data inputs with valohai-cli
    • Example projects
      • Keras example project
      • R example project
      • TensorFlow example project
      • Valohai API tutorial
  • How-to guides
    • Connect to a Git repository
      • Integrating with GitHub
      • Integrating with Bitbucket
      • Integrating with GitLab
      • Integrating with Azure DevOps
      • Access multiple Git repositories in a project
        • Clone a repository during an execution
    • Work with data
      • Add a cloud data store
        • Add Azure Blob Storage
        • Add Google Cloud Storage
        • Add AWS S3
        • Add OpenStack Swift
      • Save files from trainings
      • Attach tags and metadata to your files
      • Data aliases
      • Datum adoption
      • Upload data to Valohai
      • Mounting a network file system (NFS)
      • Access Redshift from an execution
      • Access BigQuery from an execution
    • Bring your existing projects to Valohai
      • Add a valohai.yaml configuration file
      • Input and output data
      • Define Valohai parameters
      • Collect metadata
    • Docker images
      • Access a private Docker repository
      • Popular Docker images for notebook executions
      • Build your own Docker image
    • Compare executions
    • Save graphs from executions
    • Tasks
      • Running a grid search
      • Using the Bayesian optimizer
    • Notifications
      • Email notifications
      • Webhooks
    • Pipelines
      • Schedule pipelines
      • Run a task inside a pipeline
      • Create pipelines with valohai-utils
    • Remote access (SSH)
      • Debug from VSCode
      • Debug from PyCharm
    • Organization settings
      • Environments
        • Configure environments and scaling rules
        • Change your organizations default environment
        • Manage team quotas for environments
        • Choose which environments are available
      • Users and teams
        • Add users to your organization
        • Create teams in your organization
      • Billing & credit card
      • Integrating with Azure Active Directory
    • Deployments
      • Testing your deployment endpoints
      • Reading deployment version metadata
      • Using environment variables to configure endpoint behavior
      • Monitoring your deployment endpoints
      • Debugging failing deployments
    • Using with Airflow Pipelines
    • Deploy Valohai in your environment
      • Deploy to AWS
        • Deploy to AWS manually
        • Frequently Asked Questions
        • Deployment Cluster on AWS
          • Setting up HTTPS on a deployment cluster
      • Deploy to GCP
        • Deploy to GCP manually
        • Frequently Asked Questions
      • Deploy to Azure
        • Frequently Asked Questions
      • Deploy on-premise
      • Deploy a self-hosted Valohai
      • Setting up a shared cache for Valohai workers
  • Topic guides
    • Core concepts
      • Projects
      • Valohai YAML
      • Step
      • Executions
      • Parameters
      • Data stores
      • Tasks
      • Pipelines
      • Deployments
      • Notebooks
    • Workload management
      • Creating executions
      • Placeholder-based configuration
      • File-based configuration
      • Variable-based configuration
      • Real-time logging
      • Creating visualizations
      • Downloading files to executions
      • Uploading files from executions
      • Live outputs
    • Architecture overview
    • Reproducibility and lineage
    • valohai-utils Toolkit
      • valohai.prepare()
      • valohai.parameters()
      • valohai.inputs()
      • valohai.outputs()
      • valohai.metadata.logger()
  • Reference guides
    • valohai.yaml config file
      • step
      • step.name
      • step.image
      • step.command
      • step.parameters
      • step.inputs
      • step.environment
      • step.environment-variables
      • Special environment variables
      • pipeline
      • pipeline.nodes
      • pipeline.edges
      • endpoint
      • endpoint from a command
      • endpoint from a WSGI definition
      • Examples
    • valohai-cli command-line
      • vh environments
      • vh execution
      • vh init
      • vh lint
      • vh login
      • vh logout
      • vh parcel
      • vh project
      • vh update-check
    • Valohai API
    • Valohai API documentation

Reference guides¶

Reference guides contain technical reference for APIs and other aspects of Valohai They describe how it works and how to use it but assume that you have a basic understanding of key concepts.

  • valohai.yaml config file
  • valohai-cli command-line
  • Valohai API
  • Valohai API documentation
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valohai.yaml config file
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