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.
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Create, refine, or fix NVIDIA voice agents (Cascaded or Omni) with Pipecat or LiveKit. Use when building, scaffolding, or iterating on a real-time voice-agent pipeline, including speech (ASR/TTS) customization and cloud or local deployment. Not for offline/batch speech-to-text, text-only chat or RAG, or generic Docker or CUDA work unrelated to a voice agent.
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Creates a working NVIDIA voice agent or updates an existing project:
Use this skill when the user wants to build, scaffold, configure, refine, or fix an NVIDIA voice agent — a real-time speech pipeline with audio input and spoken output — on Pipecat or LiveKit. This covers Cascaded (ASR → LLM → TTS) and Omni (audio-in LLM + TTS) pipelines, speech customization (ASR word boosting, TTS pronunciation), multilingual routing, and cloud or local deployment (NIM, vLLM, NeMo-Speech.cpp) on workstations, DGX Spark, or Jetson Thor.
Do not use this skill for text-only chatbots or RAG, standalone batch speech-to-text transcription, generic Docker or infrastructure help, or unrelated CUDA or model work that has no voice-agent pipeline.
Classify the starting state before following the phases:
references/operations/iterate.md first, and then route only the references needed for the requested change.references/operations/troubleshoot.md first. After restoring the baseline, continue with references/operations/iterate.md.For an empty project, follow these phases in order:
| Phase | Read |
|---|---|
| 1. Intake | references/intake.md resolves pipeline and framework first, then routes preflight, models, language, and domain files |
| 2. Build | references/platforms/readiness.md if self-hosted → exact profile or quantization variant in the routed model file → references/output-contract.md → routed deployment path → references/operations/observability.md → selected framework files |
| 3. Hand over | references/operations/run.md gates the client on the generated scripts/smoke.sh, then references/operations/troubleshoot.md if the spoken exchange fails |
| 4. Iterate | references/operations/iterate.md for changes to a working agent |
Wait for approval before writing files.
references/preflight.md §4 probes the host and selects the deployment path. The routed
platform file owns that path from there.
Also read references/networking/remote-webrtc.md when Pipecat WebRTC crosses hosts or
networks.
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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.
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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.
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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'.
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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`.
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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.
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