Highlighter Documentation

CLI Resource Management

Perform headless management of your Highlighter environment using the CLI.

Overview

The Highlighter CLI (hl) has been expanded to support lifecycle management of core system resources. This allows for "headless" operation, automation scripts, and cleanup tasks without needing to access the web interface.

You can now manage the following entities directly from your terminal:

  • Cases: hl case
  • Entities: hl entity
  • Workflows: hl workflow & hl workflow-order
  • Experiments & Training: hl experiment, hl evaluation, hl training-run
  • Pipelines: hl pipeline-instance

Common Operations

Most resource command groups support a delete operation for cleanup. Use the --help flag with any command to see available options.

hl case --help
hl evaluation --help

Cases

Manage the cases (tasks) within your workflows.

# Create a new case
hl case create --workflow-order-id <ORDER_ID> --name "My Case"

# Delete a specific case
hl case delete --id <CASE_ID>

# Add a message to a case
hl case message create --case-id <CASE_ID> --content "Please review this."

Workflows & Orders

Manage the structure of your projects.

# Delete a workflow
hl workflow delete --id <WORKFLOW_ID>

# Delete a workflow order
hl workflow-order delete --id <ORDER_ID>

Experiments & Research

Manage your model development lifecycle.

Experiments

# Read experiment details to a markdown file
hl experiment read --id <EXPERIMENT_ID> --save-dir ./output

# Delete an experiment
hl experiment delete --id <EXPERIMENT_ID>

Evaluations

Evaluations support a rich set of commands for managing metrics and results.

# List all evaluations
hl evaluation list

# Read a specific evaluation
hl evaluation read --id <EVALUATION_ID>

# Create a new evaluation
hl evaluation create --title "Model v2 Benchmark" --assigned-to-id <USER_ID>

# Manage metrics within an evaluation
hl evaluation metric list --evaluation-id <EVALUATION_ID>
hl evaluation metric create --evaluation-id <EVALUATION_ID> --code Accuracy --name "Test Accuracy"

# Record evaluation results
hl evaluation result create --metric-id <METRIC_ID> --value 0.95

# Delete an evaluation
hl evaluation delete --id <EVALUATION_ID>

Training Runs

# Create a training run
hl training-run create --evaluation-id <EVAL_ID> --experiment-id <EXP_ID> --capability-id <MODEL_ID> --workflow-id <WORKFLOW_ID> --name "Run v1"

# Read training run configuration
hl training-run read --id <RUN_ID> --output config.yaml

# Delete a training run
hl training-run delete --id <RUN_ID>

# Download a training run artefact
hl training-run artefact read --id <RUN_ID> --artefact-type OnnxOpset14 --save-path ./model.onnx

Entities & Pipelines

Manage other core resources.

# Delete an entity
hl entity delete --id <ENTITY_ID>

# Delete a pipeline instance
hl pipeline-instance delete --id <INSTANCE_ID>