{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Provides standardized instrumentation utilities for generative AI libraries, managing telemetry (spans, metrics, events) around LLM and embedding invocations via OpenTelemetry.","skillfed_tags":["observability","genai-instrumentation","opentelemetry"],"use_cases":["Add observability to applications calling OpenAI, Anthropic, or other LLM providers without writing custom instrumentation code.","Track token usage and latency across LLM invocations for cost monitoring and performance analysis.","Archive prompts and completions to cloud storage (GCS, S3, local filesystem) for audit, fine-tuning, or debugging.","Emit structured events with message content to a LoggerProvider for downstream processing or analysis.","Standardize telemetry across multiple GenAI libraries using OpenTelemetry semantic conventions."],"what_it_does":"OpenTelemetry Util for GenAI is a standardization layer for instrumenting generative AI libraries. It wraps LLM and embedding invocations to automatically generate spans, metrics, and events following OpenTelemetry semantic conventions. The package provides a TelemetryHandler that manages the lifecycle of AI operations, capturing request parameters, response metadata, token usage, and optionally message content (controlled via environment variables). It also supports uploading prompts and completions to external storage via fsspec-compatible paths.\n\nThe package is designed to reduce boilerplate when adding observability to GenAI applications. Instead of manually creating spans and recording metrics for each LLM call, developers use context managers or manual lifecycle methods provided by TelemetryHandler. It sets standard span attributes (operation name, provider, model, server details, token counts) and supports both chat and embedding operations. Message content capture is opt-in and configurable, and event emission can be controlled independently.","worth_installing":"Yes, if you are building observability into a GenAI application and want to follow OpenTelemetry standards. The package is actively maintained, has no known vulnerabilities, and low install friction. It is in beta status (1.0b0), so expect the API to stabilize; verify compatibility with your specific GenAI providers and exporters before production use."},"id":"opentelemetry-util-genai","links":{"html":"https://skillfed.io/packages/opentelemetry-util-genai","md":"https://skillfed.io/packages/opentelemetry-util-genai.md","pypi":"https://pypi.org/project/opentelemetry-util-genai/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-09","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"opentelemetry-util-genai","python_support":"supports_current","summary":"OpenTelemetry GenAI Utils"},"popularity":{"monthly_downloads":5541228,"position":2079,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.0b0"}