Overview - Phoenix

@arizeai/phoenix-evals provides evaluator building blocks for TypeScript workflows. It includes LLM-based evaluators, code-based evaluators, prompt templating helpers, and compatibility points for Phoenix experiments.

Install

@arizeai/phoenix-evals depends on model adapters from the AI SDK ecosystem. Install the package plus at least one provider adapter for the models you plan to use.

npm install @arizeai/phoenix-evals

Common Setups

npm install @arizeai/phoenix-evals @ai-sdk/openai

npm install @arizeai/phoenix-evals @ai-sdk/google

You can also pair it with Phoenix experiments:

npm install @arizeai/phoenix-evals @arizeai/phoenix-client @ai-sdk/openai

Runtime Expectations

Node.js 18+
an AI SDK provider package such as @ai-sdk/openai
credentials required by your chosen provider

Minimal Example

import { openai } from "@ai-sdk/openai";
import { createFaithfulnessEvaluator } from "@arizeai/phoenix-evals";

const faithfulness = createFaithfulnessEvaluator({
  model: openai("gpt-4o-mini"),
});

const result = await faithfulness.evaluate({
  input: "What is Phoenix?",
  context: "Phoenix is an open-source AI observability platform from Arize.",
  output: "Phoenix is an open-source AI observability platform from Arize.",
});

Docs And Source In `node_modules`

After install, a coding agent can inspect the installed package directly:

node_modules/@arizeai/phoenix-evals/docs/
node_modules/@arizeai/phoenix-evals/src/

The bundled docs cover evaluator creation, LLM evaluators, classification metrics, templates, classification, and Phoenix integration.

Where To Start

Create evaluator for custom and code-based evaluator flows
LLM evaluators and Classification for model-backed evaluation
Classification metrics for precision/recall/F-beta code evaluators
Templates and Phoenix integration for prompt helpers and experiment wiring

Source Layout

src/index.ts re-exports the package surface you usually import from @arizeai/phoenix-evals
src/llm/ contains classification helpers and built-in LLM evaluator factories
src/code/ contains deterministic classification-metric evaluators (precision, recall, F-beta)
src/helpers/ contains createEvaluator and evaluation-result helpers
src/template/ contains formatTemplate and getTemplateVariables
src/types/ contains shared evaluator and prompt types

Source Map

src/index.ts
src/llm/
src/code/
src/helpers/
src/template/
src/core/
src/types/

​Install

​Common Setups

​Runtime Expectations

​Minimal Example

​Docs And Source In node_modules

​Where To Start

​Source Layout

​Source Map