Arize Phoenix
AI Observability and Evaluation
Phoenix is an open-source observability library designed for experimentation, evaluation, and troubleshooting. It allows AI Engineers and Data Scientists to quickly visualize their data, evaluate performance, track down issues, and export data to improve. Phoenix is built by Arize AI, the company behind the the industry-leading AI observability platform, and a set of core contributors.
Install Phoenix
In your Jupyter or Colab environment, run the following command to install.
For full details on how to run phoenix in various environments such as Databricks, consult our environments guide.
Quickstarts
Running Phoenix for the first time? Select a quickstart below.
Demo
Next Steps
Check out a comprehensive list of example notebooks for LLM Traces, Evals, RAG Analysis, and more.
Join the Phoenix Slack community to ask questions, share findings, provide feedback, and connect with other developers.
Supported Eval Models
The phoenix library supports a set of foundation models for Evals:
Direct Integrations:
OpenAI
Vertex AI
Azure Open AI
Anthropic
Mixtral/Mistral
AWS Bedrock
Partner Integrations:
Llama
Falcon
Code Llama
Local Hosted Models
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