Arize Phoenix

Arize Phoenix is an open-source AI observability and evaluation platform for tracing and testing LLM applications.

Arize Phoenix is an AI observability and evaluation platform designed for developers building large language model applications. It provides tracing capabilities to inspect application execution and performance. Users can run pre-built or custom LLM-based evaluations, integrate tools like Ragas, Deepeval, or Cleanlab, and collect human annotations in the user interface. The platform includes a prompt playground for versioning, storing, and deploying prompts, as well as span replay for debugging. Additionally, users can create datasets, run experiments, and test applications at scale.

Arize Phoenix at a glance

Best for: Software engineer
Runs on: self-hosted, open source, API
Pricing: Free
Released: November 2022
Category: AI coding tool
Website: arize.com

Key features

Tracing for LLM applications
Pre-built and custom evaluations
Evaluator integrations with Ragas, Deepeval, and Cleanlab
Human annotations for ground truth labels
Prompt management and versioning
Prompt playground for side-by-side experiments
Span replay for debugging
Dataset creation and experiment tracking

Use it for

Debug LLM application traces and spans
Run automated evaluations on datasets
Version and deploy prompts across environments
Compare different versions of an application

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