Phoenix is an open-source AI observability platform designed for experimentation, evaluation, and troubleshooting. It provides:

🔭 Tracing - Trace your LLM application's runtime using OpenTelemetry-based instrumentation.

🧠 Evaluation - Leverage LLMs to benchmark your application's performance using response and retrieval evals.

🗄️ Datasets - Create versioned datasets of examples for experimentation, evaluation, and fine-tuning.

🧪 Experiments - Track and evaluate changes to prompts, LLMs, and retrieval.

Phoenix is vendor and language agnostic with out-of-the-box support for popular frameworks (🦙LlamaIndex, 🦜⛓LangChain, Haystack, 🧩DSPy) and LLM providers (OpenAI, Bedrock, MistralAI, VertexAI, LiteLLM, and more). For details on auto-instrumentation, check out the OpenInference project.

Phoenix is built by Arize AI, the company behind the the industry-leading AI observability platform, and a set of core contributors.

Join our community to connect with thousands of AI builders.

Find us at:

https://github.com/Arize-ai/phoenix https://docs.arize.com/phoenix https://x.com/ArizePhoenix https://phoenix.arize.com

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