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phoenix

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Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

When to use

• Debugging LLM application issues with detailed traces
• Running systematic evaluations on datasets
• Monitoring production LLM systems in real-time
• Building experiment pipelines for prompt/model comparison
• Self-hosted observability without vendor lock-in
• **Tracing**: OpenTelemetry-based trace collection for any LLM framework
• **Evaluation**: LLM-as-judge evaluators for quality assessment
• **Datasets**: Versioned test sets for regression testing

When not to use

• Managed platform with LangChain-first integration
• Deep learning experiment tracking focus
• Managed Phoenix with enterprise features
• General ML lifecycle, model registry focus

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