본문으로 건너뛰기
cccskills
무료GitHub에 공개

nemo-relay-debug-runtime-integration

Use this skill when NeMo Relay is installed or imported but application-side runtime behavior is missing or incorrect, including load failures, inactive scopes, missing events, and plugin or adaptive wiring problems.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(5)

  • SKILL.md4.0 KB
  • BENCHMARK.md4.7 KB
  • evals/evals.json5.0 KB
  • skill-card.md4.0 KB
  • skill.oms.sig4.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Debug Runtime Integration

Use this skill when NeMo Relay is present in the application but something is not working. Start by proving which runtime layer is failing before changing configuration.

First Checks

  • Can the binding or native artifact load?
  • Is there an active scope when the failing call runs?
  • Is the work happening on the expected scope stack?
  • Is the subscriber/exporter/plugin configuration actually active?
  • Did the app choose the right public API layer: managed execute vs manual lifecycle vs typed wrappers vs adaptive/plugins?

Common Failure Classes

  • Python native extension missing
  • Go dynamic library not on the loader path
  • Node native addon not built or not loading
  • Execute call outside a scope
  • Missing events because registration never happened
  • Concurrency causing the wrong scope stack to be active
  • Adaptive component never initialized or config validation ignored

Embedded Troubleshooting Matrix

  • Rust build failure: run the narrowest core build first, then expand to the affected binding or workspace command.
  • Python import failure: rebuild the virtual environment and native extension with uv sync, then run a small Python test or import check from the same environment as the application.
  • Node.js addon failure: reinstall and rebuild the native addon from the Node binding package before debugging application code.
  • Go loader failure: build the release FFI shared library and point both the linker and runtime loader at the release output directory; use the macOS dynamic-library path variable (DYLD_LIBRARY_PATH) on macOS.
  • Scope stack empty: the work is outside an active scope or crossed a thread, task, goroutine, or worker boundary without the intended stack.
  • Work leaks across requests: separate requests are sharing one scope stack; create a fresh stack per independent request or agent.
  • Middleware missing or ordered incorrectly: check global vs scope-local registration, active scope ancestry, names, and priority values.
  • Subscriber missing events: register before the events are emitted; for scope-local subscribers, ensure the current scope is the owner or descendant.
  • Event fields missing: managed helpers populate semantic fields; manual lifecycle calls require explicit params for input, output, model names, and tool call IDs.
  • ATIF empty or mixed: register before work starts, use one exporter per run or clear between runs, and separate concurrent agents by root scope.
  • Provider payload conversion failure: convert non-JSON provider objects, SDK handles, callbacks, streams, or class instances with explicit codecs.
  • Plugin validation failure: validate config independently from runtime registration and check required fields, value types, defaults, and config source.
  • Adaptive behavior unchanged: confirm instrumentation emits events, the adaptive component is enabled, policy allows the behavior, and the call path reaches the configured component.
  • OpenTelemetry or OpenInference export failure: first identify the Relay version. For 0.6, check the separate exporter, http_binary versus grpc, endpoint, headers, target support, and an active Tokio runtime for native gRPC. For 0.7, check the typed projection, endpoint, headers, TLS, and target support; the subscriber owns the native gRPC runtime.
  • Callback succeeded but no lifecycle events appear: confirm the integration uses managed execute helpers or balanced manual start/end APIs, not only the underlying business callback.

Related Skills

  • nemo-relay-get-started
  • nemo-relay-instrument-context-isolation
  • nemo-relay-plugin-adaptive-tuning
  • nemo-relay-plugin-build

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA/skills3.6천2026년 10월 18일 업데이트

NVIDIA의 스킬 모두 보기

이 스킬의 문제 신고