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.
Use this skill when first-time NeMo Relay users want to try Relay, choose the least-complex supported quick start, or verify initial value through the CLI, a maintained integration, or direct Python, Node.js, or Rust instrumentation before production setup.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Guide a new user to visible Relay value with the least complicated applicable trial. Do not begin with production deployment or Relay's full architecture. Keep the first run focused on one observable success path.
Evaluate these paths in order. Use the first one that fits the user's stated goal and existing environment.
Do not ask the user to choose among all four when their request, manifest, or framework already identifies the boundary. For an unspecified request, use the CLI path. When more than one CLI agent is available, ask one concise question to select the agent.
Select the try-now path before choosing an install package.
nemo-relay --version; if missing, use
nemo-relay-install for the CLI outcome.nemo-relay-install for the named
framework or harness package.nemo-relay-install for the detected language
package.If installation already succeeded, preserve the chosen path and continue from its next step. Do not ask the install-path question again or bounce between the install and get-started skills.
Do not apply this section to the Hermes Agent native path.
Follow the selected reference, then:
.nemo-relay/config.toml and
.nemo-relay/plugins.toml as unsupported project configuration. Do not
create, edit, merge, or trust those files as active Relay configuration.Explain only the concepts visible in the result: the chosen attachment boundary, scopes and parentage, captured lifecycle events, and how subscribers or the Observability plugin make those events inspectable. Keep instrumentation and export distinct.
Do not apply this section to the Hermes Agent native path.
Stop the initial try-now workflow when the selected path's success checks pass. Then make one additional built-in plugin the primary suggested next step.
Explain Relay's core progression: instrument an execution boundary once, then change or extend behavior through plugin configuration without repeatedly rewriting those call sites. Easy plugin configuration and reconfiguration is the main value to demonstrate after the first observable proof.
If the selected path did not use plugin-managed Observability, add it first to establish the reusable plugin path. If Observability already produced the proof, ask what outcome matters next and recommend exactly one plugin:
Use the plugin overview to select the next component. Preview its smallest configuration, obtain confirmation, and verify its behavior before layering in another plugin.
Use another handoff only after the user accepts or declines plugin progression, or when the demonstrated boundary does not yet cover the intended workflow:
nemo-relay-instrument-callsnemo-relay-integrate-upstreamnemo-relay-plugin-observabilitynemo-relay-installnemo-relay-install; for Codex
Desktop, complete its recovery-note safety gate before changing global confignemo-relay doctor,
nemo-relay doctor --json, or nemo-relay-debug-runtime-integrationDo not configure production OTLP backends, model pricing, guardrails, adaptive tuning, custom plugins, Go or FFI examples during the quick start. Mention optional plugins only after the initial proof and add only the one the user selects.
Use these public entry points for current product documentation:
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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.
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.
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.
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.
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.
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.