{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/2"}],"enrichment":{"capability":"Extends OpenTelemetry's GenAI semantic conventions to capture telemetry from large language models, agents, tool calls, vector retrieval, and related operations, mapping them to standardized Span attributes, optional message content, and GenAI events.","skillfed_tags":["observability","genai-tracing","agent-instrumentation"],"use_cases":["Trace LLM API calls end-to-end with standardized span attributes, token counts, and model metadata for debugging and performance monitoring.","Monitor agent orchestration workflows by capturing agent creation, invocation, tool execution, and memory operations as linked spans.","Observe vector retrieval and reranking operations within RAG pipelines to identify latency and quality bottlenecks.","Correlate user sessions and requests across distributed AI services using Baggage-based span coloring at application entry points.","Audit LLM inputs and outputs by enabling structured event capture with full message content when compliance or debugging requires it.","Integrate GenAI telemetry into existing OpenTelemetry observability stacks (Jaeger, Datadog, Honeycomb, etc.) without custom instrumentation."],"what_it_does":"loongsuite-util-genai is an extension of OpenTelemetry's GenAI semantic conventions, designed to capture observability data from large language model calls, agent orchestration, vector retrieval, tool execution, and related AI workflows. It provides a unified telemetry handler that maps these operations into standardized OpenTelemetry Spans with semantic attributes, optional structured events, and configurable message content capture. The package imports as opentelemetry.util.genai but is distributed as loongsuite-util-genai to avoid conflicts with the upstream community package.\n\nThe handler supports LLM chat/completion calls with multimodal message handling, agent creation and invocation, embedding operations, tool execution with skill metadata, retrieval and reranking, memory operations, application entry points with session/user ID propagation via Baggage, and ReAct iteration tracking. Message content (prompts, responses) is not captured by default to protect sensitive data and reduce trace volume; it must be explicitly enabled via environment variables. The package integrates with OpenTelemetry's standard export pipeline and is designed to work with auto-instrumentation frameworks or direct SDK initialization.","worth_installing":"Yes, if you are building AI applications with OpenTelemetry and need standardized tracing for LLMs, agents, and retrieval workflows. The package is actively maintained, has low install friction, and is Apache-2.0 licensed. Install via LoongSuite's recommended instrumentation chain to avoid dependency conflicts with the upstream package. Be aware that message content capture requires explicit environment variable configuration and that the extended semantic model for some scenarios (Agent, ReAct, memory) may still be evolving."},"id":"loongsuite-util-genai","links":{"html":"https://skillfed.io/packages/loongsuite-util-genai","md":"https://skillfed.io/packages/loongsuite-util-genai.md","pypi":"https://pypi.org/project/loongsuite-util-genai/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-11","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"loongsuite-util-genai","python_support":"supports_current","summary":"LoongSuite GenAI Utils"},"popularity":{"monthly_downloads":4315183,"position":2331,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.5.0"}