Observability and Evaluation · Public

phoenix

Observability and evaluation project for turning logs, quality metrics, drift, or experiment results into reviewable signals.

ObservabilityEvaluationQuality metricsData driftExperiment tracking

Best fitDevelopers who need reviewable observability or evaluation workflows for AI apps, data pipelines, or experiments.

Check whether this project matches your task before installing it.

What it can doObservability setup paths, metric boundaries, sample-data redaction, evaluation checks, and failure triage

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot10k stars

934 forks · 188 contributors

Doramagic.ai Last verification date: 2026-07-09 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-07-09

What is phoenix?

phoenix helps developers observe, evaluate, or monitor AI/data application behavior and quality.
Best fit: Developers who need reviewable observability or evaluation workflows for AI apps, data pipelines, or experiments.
Not for: Not for users without logs/sample data, privacy boundaries, or those who only need a chat UI.
Capability added to an AI workflow: Observability setup paths, metric boundaries, sample-data redaction, evaluation checks, and failure triage
First safe verification step: Verify collection, metric interpretation, export, and deletion paths with redacted sample data first.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/Arize-ai/phoenix, https://github.com/Arize-ai/phoenix#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers who need reviewable observability or evaluation workflows for AI apps, data pipelines, or experiments.

Match the project to your task before installing it.

CapabilityObservability setup paths, metric boundaries, sample-data redaction, evaluation checks, and failure triage

Observability and evaluation project for turning logs, quality metrics, drift, or experiment results into reviewable signals.

RepositoryArize-ai/phoenix

10k stars · 934 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Platform Overview and Architecture

Related topics: Tracing, Spans, and Observability, Datasets, Experiments, and Evaluation, PXI Agent, CLI, and MCP Extensibility

Sources: [js/packages/phoenix-evals/src/__generated__/default_templates/index.ts:1-9](), [js/packages/phoenix-evals/src/__generated__/default_templates/CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.ts:1-5](), [js/packages/phoenix-evals/src/__generated__/default_templates/TOOL_INVOCATION_CLASSIFICATION_EVALUATOR_CONFIG.ts:1-5]().

Tracing, Spans, and Observability

Related topics: Platform Overview and Architecture, Datasets, Experiments, and Evaluation

Source: https://github.com/Arize-ai/phoenix / Human Manual

Datasets, Experiments, and Evaluation

Related topics: Tracing, Spans, and Observability, PXI Agent, CLI, and MCP Extensibility

Source: https://github.com/Arize-ai/phoenix / Human Manual

PXI Agent, CLI, and MCP Extensibility

Related topics: Platform Overview and Architecture, Datasets, Experiments, and Evaluation

Source: https://github.com/Arize-ai/phoenix / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/Arize-ai/phoenix, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars10k stars

Forks934 forks

Contributors188 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using phoenix with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
[bug][agents] Inconsistent /clear invocation
github / github_issue
02
[ENHANCEMENT]: Support custom span costs independent of LLM token pricin
github / github_issue
03
[agents] backend bash emulator / FS access
github / github_issue
04
[BUG]: ROLE_ATTRIBUTE_PATH unconditionally overwrites manually set roles
github / github_issue
05
arize-phoenix: v17.9.0
github / github_release
06
arize-phoenix: v17.8.1
github / github_release
07
arize-phoenix: v17.8.0
github / github_release
08
arize-phoenix: v17.7.0
github / github_release
09
arize-phoenix: v17.6.0
github / github_release
10
arize-phoenix: v17.5.0
github / github_release
11
arize-phoenix-client: v2.9.0
github / github_release
12
arize-phoenix: v17.4.0
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install arize-phoenix

Official start command · https://github.com/Arize-ai/phoenix#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

phoenix Manual

AI Observability & Evaluation

Open the full manual

https://github.com/Arize-ai/phoenix Project Manual
Table of Contents
Platform Overview and Architecture
Related Pages
High-Level Architecture
Core Subsystems
Tracing and Observability
Evaluation Framework

Platform Overview and Architecture

Related topics: Tracing, Spans, and Observability, Datasets, Experiments, and Evaluation, PXI Agent, CLI, and MCP Extensibility

Sources: [js/packages/phoenix-evals/src/__generated__/default_templates/index.ts:1-9](), [js/packages/phoenix-evals/src/__generated__/default_templates/CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.ts:1-5](), [js/packages/phoenix-evals/src/__generated__/default_templates/TOOL_INVOCATION_CLASSIFICATION_EVALUATOR_CONFIG.ts:1-5]().

Tracing, Spans, and Observability

Related topics: Platform Overview and Architecture, Datasets, Experiments, and Evaluation

Source: https://github.com/Arize-ai/phoenix / Human Manual

Datasets, Experiments, and Evaluation

Related topics: Tracing, Spans, and Observability, PXI Agent, CLI, and MCP Extensibility

Source: https://github.com/Arize-ai/phoenix / Human Manual

PXI Agent, CLI, and MCP Extensibility

Related topics: Platform Overview and Architecture, Datasets, Experiments, and Evaluation

Source: https://github.com/Arize-ai/phoenix / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

high

Runtime risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Configuration risk requires verification

Developers may misconfigure credentials, environment, or host setup: [BUG]: ROLE_ATTRIBUTE_PATH unconditionally overwrites manually set roles on every OIDC login - manual UI overrides should persist

medium

Configuration risk requires verification

Upgrade or migration may change expected behavior: arize-phoenix-client: v2.8.0

medium

Capability evidence risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Maintenance risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.