phoenix

varize-phoenix-evals-v3.1.1 scope: arize-phoenix-evals Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 13d Tracing

✓ No known CVEs patched

✓ No known CVEs patched in this version

Topics

agents ai-monitoring ai-observability aiengineering anthropic datasets

+10 more

evals langchain llamaindex llm-eval llm-evaluation llmops llms openai prompt-engineering smolagents

Summary

AI summary

Fixed evals bugs: correct per‑class weighted F‑score, count executor timeouts toward retry limit, and conditionally enable 0/1 label detection.

Type	Severity	Summary	CVE
Bugfix
Bugfix	Medium	Counts AsyncExecutor timeouts against max_retries in evals. Counts AsyncExecutor timeouts against max_retries in evals. Source: llm_adapter@2026-07-14 Confidence: high	—
Bugfix	Medium	Gates 0/1 positive_label auto-detection on default macro average in evals. Gates 0/1 positive_label auto-detection on default macro average in evals. Source: llm_adapter@2026-07-14 Confidence: high	—
Bugfix	Medium	Computes macro/weighted F-score per class to match sklearn semantics in evals. Computes macro/weighted F-score per class to match sklearn semantics in evals. Source: llm_adapter@2026-07-14 Confidence: high	—

Full changelog

evals: compute macro/weighted F-score per class to match sklearn semantics (#13740) (c0f6267)
evals: count AsyncExecutor timeouts against max_retries (#14361) (90eee08)
evals: gate 0/1 positive_label auto-detection on default macro average (#14012) (f96dbd9)

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About phoenix

AI Observability & Evaluation

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