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arize_toolkit

ML observability toolkit for Arize AI

PythonML ObservabilityArizeLLM
Arize Toolkit Logo

Tests Documentation PyPI Package Lint and Format Python Version uv Code style: black coverage CLI

📚 Documentation

Quick Links

Tools Documentation

Tool CategoryDescription
Project/Model ToolsAccess and manage projects/models, retrieve performance metrics and traces/inference volumes
Monitor ToolsCreate, copy, and manage monitors and alerting
Custom Metrics ToolsCreate and manage custom metrics
Language Model ToolsWork with prompts, annotations, evaluations, and LLM features
Space & Organization ToolsNavigate and manage spaces, organizations, and projects
Data Import ToolsImport data from cloud storage and databases
Trace ToolsQuery traces and spans, discover columns, and export trace data
Dashboard ToolsCreate and manage dashboards
Utility ToolsClient configuration and utility functions

Extensions

ExtensionDescription
Prompt OptimizationAutomated prompt improvement based on historical performance

Claude Code Plugin Marketplace

This repository is a Claude Code plugin marketplace with AI-assisted tools for the Arize platform.

# Add the marketplace
claude plugin marketplace add duncankmckinnon/arize_toolkit

# Install plugins
claude plugin install arize-toolkit@arize-toolkit
claude plugin install arize-toolkit-dev@arize-toolkit
PluginSkillsDescription
arize-toolkitarize-toolkit-cli, arize-tracesManage Arize resources via CLI, debug traces
arize-toolkit-devarize-graphql-analytics, new-query-workflowDeveloper workflows for adding new functionality

See the Plugin Marketplace docs for full details.

Arize Claude Code Tracing

For automatic tracing of Claude Code sessions to Arize AX or Phoenix, install the tracing plugin from the Arize Claude Code Plugin marketplace:

# Add the Arize plugin marketplace
claude plugin marketplace add Arize-ai/arize-claude-code-plugin

# Install the tracing plugin
claude plugin install claude-code-tracing@arize-claude-plugin
PluginSkillsDescription
claude-code-tracingsetup-claude-code-tracingAutomatic tracing of Claude Code sessions with OpenInference spans (9 lifecycle hooks)

For Developers

Disclaimer

Although this package is used for development work with and within the Arize platform, it is not an Arize product. It is a open source project developed and maintained by an Arize Engineer. Feel free to add issues or reach out for help in the Arize community Slack channel.

Overview

Arize Toolkit is a set of tools packaged as a Python client that lets you easily interact with Arize AI APIs. Here's a quick overview of the main features in the current release:

  • Access and manage models
  • Retrieve performance metrics over a time period
  • Retrieve inference volume over a time period
  • Create, copy, and manage custom metrics
  • Create, copy, and manage monitors and alerting
  • Work with LLM features like prompts and annotations
  • Import data from cloud storage (S3, GCS, Azure) and databases (BigQuery, Snowflake, Databricks)
  • Create, update, and delete data import jobs with full lifecycle management
  • Prompt Optimization Extension (optional): Automatically optimize prompts using meta-prompt techniques with feedback from evaluators
  • Trace Inspection: List traces, retrieve spans with full attributes, discover available columns, and export to DataFrames or CSV
  • Command-Line Interface (optional): Manage all Arize resources directly from the terminal with Rich table output and JSON mode

Installation

pip install arize_toolkit

Optional Dependencies

Command-Line Interface

To use the arize_toolkit CLI, install with the cli extras:

pip install arize_toolkit[cli]

Prompt Optimization Extension

For automated prompt optimization using meta-prompt techniques, install with the prompt_optimizer extras:

pip install arize_toolkit[prompt_optimizer]

Command-Line Interface

The CLI wraps all Client functionality so you can manage models, monitors, prompts, and more directly from the terminal.

Quick Start

# One-time setup — saves credentials to ~/.arize_toolkit/config.toml
arize_toolkit config init

# List models (Rich table output by default)
arize_toolkit models list

# Same thing, using the "projects" alias
arize_toolkit projects list

# JSON output, pipe to jq
arize_toolkit --json models list | jq '.[].name'

# Get monitor details for a specific model
arize_toolkit monitors get "accuracy-alert" --model "fraud-detection-v3"

# Create a performance monitor
arize_toolkit monitors create-performance "accuracy-alert" \
    --model "fraud-detection-v3" \
    --environment production \
    --performance-metric accuracy \
    --threshold 0.95

# Use a named profile for a different environment
arize_toolkit --profile staging spaces list

Global Options

FlagDescription
--versionShow the installed version
--profile NAMEUse a named configuration profile
--jsonOutput raw JSON instead of Rich tables
--api-key KEYOverride the API key
--org NAMEOverride the organization
--space NAMEOverride the space
--app-url URLOverride the Arize app URL

Command Groups

GroupDescription
configManage configuration profiles (init, list, show, use)
spacesList, create, and switch spaces or orgs
orgsList and create organizations
usersSearch users and manage space membership
models / projectsList models, check volume, pull performance metrics
monitorsCreate, list, copy, and delete monitors
promptsManage prompt templates and versions
custom-metricsCreate and manage custom metrics
evaluatorsManage LLM and code evaluators
dashboardsCreate and view dashboards
tracesList traces, get spans, and discover available columns
importsManage file and table import jobs

See the full CLI documentation for detailed usage and examples.

Client Setup

The Client class is the entrypoint for interacting with the toolkit. It provides maintains the connection information for making requests to the Arize APIs, and offers a wide range of operations for interacting with models, monitors, dashboards, and more.

API Key

To create a client, you need to provide your Arize API key. Use this reference to get your API key from the Arize UI.

Arize UI Path

Organization and Space

You will also need to provide an organization name and space name. To give some context, models are scoped to a space, and the space is scoped to an organization. These can be found by navigating to the Arize UI and looking at the upper left dropdown from the landing page. You will first select an organization from the dropdown and then pick the space from the available spaces in that organization.

For the example below, the organization is Demo Org and the space is Test Space.

Arize UI Path

For On Prem deployments

For SaaS users, the default API endpoint is always going to be https://api.arize.com. If you are using an on prem deployment of Arize, you will need to provide the api_url parameter. This parameters should just be the base url of your Arize instance.