{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Wraps OpenTelemetry with Phoenix-aware defaults and decorators to instrument AI applications for tracing, with automatic configuration from environment variables and support for GenAI patterns.","skillfed_tags":["llm-observability","opentelemetry","distributed-tracing"],"use_cases":["Enable automatic tracing of OpenAI, LangChain, or LlamaIndex calls in an LLM application with a single function call and environment variables.","Collect and export distributed traces from a multi-component AI system to a self-hosted or cloud Phoenix instance for debugging and monitoring.","Manually instrument custom AI workflows using decorators like @tracer.chain and @tracer.tool for GenAI-specific patterns.","Configure production-ready batching and authentication for trace export without writing custom OpenTelemetry span processor code.","Organize traces by project and environment using Phoenix project names and custom headers for multi-tenant or multi-environment deployments."],"what_it_does":"arize-phoenix-otel is a lightweight wrapper around OpenTelemetry that simplifies tracing setup for AI applications by providing Phoenix-aware defaults, automatic environment variable configuration, and drop-in replacements for standard OTel classes. It reads configuration from environment variables (PHOENIX_COLLECTOR_ENDPOINT, PHOENIX_API_KEY, PHOENIX_PROJECT_NAME, etc.) or a `.env.phoenix` file, with explicit arguments taking precedence.\n\nThe package's main value is reducing boilerplate: a single `register()` call with `auto_instrument=True` automatically instruments popular AI frameworks (OpenAI, LangChain, LlamaIndex) with zero code changes, batches spans for production use, and sends traces to a Phoenix instance over OTLP using OpenInference semantic conventions. It also provides tracing decorators for GenAI patterns and works with any recent Phoenix server version without version pairing.","worth_installing":"Yes. Active maintenance, no vulnerabilities, low install friction, and permissive license make it a safe choice. Install it if you need to trace AI applications and are already using or planning to adopt Phoenix for observability; the auto-instrumentation and environment-based configuration save significant boilerplate compared to raw OpenTelemetry setup."},"id":"arize-phoenix-otel","links":{"html":"https://skillfed.io/packages/arize-phoenix-otel","md":"https://skillfed.io/packages/arize-phoenix-otel.md","pypi":"https://pypi.org/project/arize-phoenix-otel/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"arize-phoenix-otel","python_support":"supports_current","summary":"LLM Observability"},"popularity":{"monthly_downloads":1990947,"position":3379,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.17.1"}