AX CLI

The AX CLI (ax) lets you manage your Arize AI platform resources — datasets, projects, spans, and configuration profiles — directly from your terminal. It’s useful for scripting workflows, automating data pipelines, and integrating Arize into CI/CD environments.

Getting Started

1. Install the CLI

Requires Python 3.11 or later.

pip install arize-ax-cli

Verify the installation:

ax --version

2. Create a configuration profile

ax profiles create

You’ll be prompted for your API key, region, and preferred output format. Choose Simple mode for most use cases, or Advanced mode for custom routing, transport tuning, and SSL settings.

ax profiles create is required before running any other commands. Without it, most commands will fail with: Error: Profile 'default' not found.

3. Verify your setup

ax profiles show    # Check your profile settings
ax projects list    # Run your first command

Shell Completion (optional)

Enable tab completion for your shell:

ax --install-completion

Supports bash, zsh, fish, and PowerShell. Restart your shell or source your profile to activate.

Configuration

Profiles store your API key, region, and output preferences so you don’t have to pass them on every command. Configuration files are stored at:

macOS/Linux: ~/.arize/profiles/<profile>.toml
Windows: %USERPROFILE%\.arize\profiles\<profile>.toml

The CLI automatically detects any ARIZE_* environment variables in your shell and offers to use them during ax profiles create. You can also reference environment variables in config files using ${VARIABLE_NAME} syntax.

Using a self-hosted, on-premise, or VPC deployment? You’ll need to configure custom endpoint routing in your profile. See Self-Hosted / On-Premise Configuration for setup instructions.

Managing Profiles

Here’s a full reference of profile commands:

ax profiles create                       # Create a new profile
ax profiles list                         # List all profiles (active profile is marked)
ax profiles show                         # Show active profile settings
ax profiles show myprofile               # Show a specific profile
ax profiles show --expand                # Resolve environment variable references
ax profiles show --all                   # Show all sections including defaults
ax profiles use <profile>                # Switch the active profile
ax profiles delete <profile>             # Delete a profile (cannot delete default or active)
ax profiles delete <profile> --force     # Delete without confirmation prompt

Working with Multiple Environments

Create separate profiles for production and staging, then switch between them as needed:

ax profiles create   # name it "production"
ax profiles create   # name it "staging"

# Switch the active profile
ax profiles use production

# Or override per-command with --profile
ax datasets list --profile staging --space sp_stg123

Options & Output

Top-Level Options

These options are available on the root ax command itself:

Option	Short	Description
`--version`		Show version and exit
`--install-completion`		Install shell completion
`--show-completion`		Show completion script for your shell
`--help`	`-h`	Show help

Subcommand Options

Most subcommands (e.g., ax datasets list, ax projects get) accept these options:

Option	Short	Description
`--profile <name>`	`-p`	Use a specific configuration profile instead of the active one
`--output <format\|path>`	`-o`	Set output format (`table`, `json`, `csv`, `parquet`) or write to a file path
`--verbose`	`-v`	Enable detailed logging
`--help`	`-h`	Show help for the command

--profile and --output are subcommand options, not top-level flags. Use them after the subcommand: ax datasets list --profile staging, not ax --profile staging datasets list.

Output Formats

The default output format is table. Use --output to change the format or write results directly to a file:

Format	Description
`table`	Human-readable default; formatted for the terminal
`json`	Machine-parseable JSON
`csv`	Spreadsheet-compatible format
`parquet`	Apache columnar format for large datasets

ax datasets list --output json                                 # Print as JSON
ax datasets list --output datasets.json                        # Write to a JSON file
ax datasets export <dataset-id> --stdout | jq '.' > out.json   # Pipe export to file

Cache

The CLI caches certain data locally at ~/.arize/cache/ to speed up repeated operations. To clear the cache:

ax cache clear

Resources

AI Integrations

Create and manage LLM provider integrations

Annotation Configs

Create and manage annotation schemas

API Keys

Create, refresh, and revoke API keys

Datasets

Create, list, and manage datasets

Evaluators

Create and manage LLM-as-judge evaluators

Experiments

Create, list, and manage experiments

Projects

Create, list, and manage projects

Prompts

Create and version prompt templates

Spaces

Create, list, and manage spaces

Spans

Export span data with filtering

Tasks

Create and manage evaluation tasks

Traces

List and export trace data

Users

Create, list, and manage users

Useful Links

PyPI Package

Install and version history

GitHub Repository

Source code and issues

Arize Community Slack

Get help from the community

Support

Contact the Arize support team

API reference

API clients

Getting Started

1. Install the CLI

2. Create a configuration profile

3. Verify your setup

Shell Completion (optional)

Configuration

Managing Profiles

Working with Multiple Environments

Options & Output

Top-Level Options

Subcommand Options

Output Formats

Cache

Resources

AI Integrations

Annotation Configs

API Keys

Datasets

Evaluators

Experiments

Projects

Prompts

Spaces

Spans

Tasks

Traces

Users

Useful Links

PyPI Package

GitHub Repository

Arize Community Slack

Support

​Getting Started

​1. Install the CLI

​2. Create a configuration profile

​3. Verify your setup

​Shell Completion (optional)

​Configuration

​Managing Profiles

​Working with Multiple Environments

​Options & Output

​Top-Level Options

​Subcommand Options

​Output Formats

​Cache

​Resources

AI Integrations

Annotation Configs

API Keys

Datasets

Evaluators

Experiments

Projects

Prompts

Spaces

Spans

Tasks

Traces

Users

​Useful Links

PyPI Package

GitHub Repository

Arize Community Slack

Support

Getting Started

1. Install the CLI

2. Create a configuration profile

3. Verify your setup

Shell Completion (optional)

Configuration

Managing Profiles

Working with Multiple Environments

Options & Output

Top-Level Options

Subcommand Options

Output Formats

Cache

Resources

Useful Links