pandasで扱う表データ処理をcuDFでGPUへ移す作業を支援します。結合・集計・CSVやParquet入出力から、結果の照合、メモリ対策、複数GPU利用まで扱います。
- 既存pandas処理を少ない変更で加速
- 結合や集計をGPUへ移したいとき
- 欠損値や並び順をpandasと照合
再利用できるHoloscanの外部モジュールを、ひな形作成から実装・テスト・配布用パッケージ作成まで進め、別環境への導入と動作も確認します。
Develop external Holoscan Modules with the Holoscan CLI and use them in Holoscan applications: scaffold, test, Python bindings, DEB/WHEEL packaging, and clean-consumer proof.
再利用可能なHoloscanの外部モジュールを、設計から配布物の検証まで進めます。Holoscan CLIでひな形を作成し、公開APIや処理部品を実装して、テストとデモを用意します。Pythonから使うための接続部分や、DEB・WHEEL形式のパッケージも対象にし、別のアプリケーションから利用できるか確認します。
複数のアプリで共有する処理を独立したモジュールにまとめたい開発者に向いています。開発環境で動くだけでなく、配布物だけを入れたクリーンな環境でも読み込みや実行が通ることを確かめたい場面に使えます。
対象は外部モジュールで、SDK内部のモジュール開発や通常のアプリ開発は範囲外です。Holoscan CLI 5.x、Python 3.12〜3.14に対応し、付属テンプレートにはHoloscan SDK 5.0.0以上が必要です。テンプレートが生成するDEBはC++のみで、WHEELにはモジュール側のビルド設定が必要です。ライセンスはApache-2.0です。
この紹介文は、公開されている SKILL.md をもとに AI(OpenAI Codex)が作成しました。正確な仕様は下の原文を確認してください。
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Take a reusable Holoscan Module from layout and API contract through producer,
consumer, and clean artifact-install proof. Use uv run holoscan in a
standalone module, or holoscan in its activated pip environment.
A Holoscan Module extends holoscan::core with operators, resources, and
helpers for a domain capability, plus examples and tests. Core modules ship
with the SDK; external modules live in their own repositories, and
applications, including those in nvidia-holoscan/holoscan-applications,
consume their installed packages. This skill covers external Holoscan Module
development and consumption. For SDK core-module implementation, follow the
selected SDK checkout’s modules/DEVELOPER.md and module-specific guide; do
not apply the external CLI template or packaging workflow to SDK core modules.
Required: the API contract, workspace, identities, SDK floor, license, maintainer, package formats, and acceptance checks, from the request or an authoritative repository source. Optional: a consuming application. If consequential release metadata remains unknown, stop before scaffolding or packaging rather than guessing.
First honor any request for planning only (for example, “do not run commands”);
preserve that restriction when routing. Check the session’s available skill
catalog for the destination skill. Route a concrete failing or wrong
holoscan command to holoscan-app-debug-build-run. If the matching skill is
unavailable, preserve the handoff context and name the skill to install
instead of broadening this workflow. An ordinary application without a
reusable module API is outside this skill; follow the target repository's own
guidance, such as README.md and CONTRIBUTING.md in holoscan-applications.
The module's own README.md, DEVELOPER.md, and AGENTS.md, a consuming
checkout's guidance, local help, schemas, templates, tutorials, and nearby
examples are the live technical authority where they do not conflict with
user, system, or safety constraints.
For a planning-only request, return the proposed workflow and proof requirements without executing commands or changing files. Otherwise continue below.
At any step, a failing effect-bearing CLI command ends this happy path; follow Troubleshooting with its exact context. Parse read-only diagnostic results and stop only when a failed capability is required by the module, consumer, packaging environment, or requested proof. For example, a failed Docker capability blocks a container build; an unavailable display need not block an explicitly headless consumer.
holoscan-<name> repository with
its own demo applications. holoscan-applications keeps applications only
and directs reusable operators and Modules to independent repositories.snake_case
module/namespace, holoscan-<kebab-case> repository/package, and
snake_case_op operator slug consistent.holoscan create command with explicit language (cpp, or cpp python to
add Python bindings) and agreed metadata. Always specify
--context holoscan_version=<agreed-sdk-floor> to override configured or
template defaults; the template requires 5.0.0 or later, and its preview
does not check that floor. Examples explicitly select 5.0.0; use the agreed
SDK floor for the actual module. No launcher or holoscan-applications
checkout is required. Preserve existing Git state;
reject populated destinations. Inspect generated files and Git status
before continuing.--language cpp or --language python when a project
declares both. The module's test runs its repository-wide suite; combine
it with focused pytest or CTest targets and report the scope.find_package(holoscan-<name> CONFIG REQUIRED) and
holoscan::<module_slug>. In holoscan-applications, a metadata dependency
alone neither fetches nor builds the module; follow the
application consumer procedure
and do not change the shared root CMake without maintainer agreement. For
Python bindings, import from the exact build tree or install the
holoscan-<name>-python component into a task-owned prefix; follow the
Python consumer cleanup procedure:
record the interpreter, build directory, prefix, and installed paths, always
remove the task-owned prefix after the consumer attempt, and verify it is
absent. The packaged template stages no editable-import hooks, so do not
substitute install --dev. If cleanup fails, stop using that environment
and report incomplete cleanup; a missing debugging skill does not permit
continuing to package or publish. Discard a task-owned disposable
environment only under existing cleanup authorization; a shared environment
needs the owner’s repair decision.pyproject.toml builds one. For
DEB, verify the declared holoscan Debian dependency in the consumer’s
package database: a successful Python import or C++ build is insufficient.
If it is absent, report DEB installation unverified and follow the
DEB prerequisite guidance;
do not force dependency checks or claim archive extraction proves installability.git diff --check, and final status. In a dirty checkout, restrict
auto-fixing lint to task paths; before a requested commit, validate the
exact candidate change with the full lint required by that repository's
guidance, in a clean disposable checkout. If the required commands cannot
be determined, report lint unverified. Confirm no generated artifacts or
install prefixes are staged. Do not commit, push, upload, publish, or
release unless requested.If a CLI command fails, stop the happy path and hand off its exact command,
revision, dirty state, inputs, and observed result to
holoscan-app-debug-build-run.
holoscan with sudo; obtain approval for holoscan setup,
host packages, host-local execution, root containers, devices/capabilities,
or permission changes.Return layout and identities, public API/demo, metadata and registrations, preview and real command results, honest test scope, consumer proof, artifact identity/contents/install results, licensing and publication limits, and final worktree state.
For a planning-only request, return the proposed order, authoritative metadata sources, approval boundaries, and proof requirements without claiming results.
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pandasで扱う表データ処理をcuDFでGPUへ移す作業を支援します。結合・集計・CSVやParquet入出力から、結果の照合、メモリ対策、複数GPU利用まで扱います。
NVIDIA Nemotron Voice Agentのサンプルを変更し、別のバックエンドを設けずに予約受付や患者情報の聞き取りを行う音声エージェントを作るスキル。
ライブカメラのRTSP映像をVIOSで録画し、AutoMagicCalibでカメラ校正を進めます。設定や位置合わせ資料の取り込み、進捗確認、結果取得まで扱います。
同梱の倉庫カメラ映像でAMCのカメラ校正を一通り実行し、正解データとの誤差を確認します。導入後の動作検証や、実データ投入前の確認に使えます。
録画済みの複数カメラ映像をAutoMagicCalibに送り、カメラの位置や向きを調整する処理を、プロジェクト作成から進捗確認・結果評価まで進めます。
AutoMagicCalibの自動キャリブレーション環境をDocker Composeで構築し、NGC認証からポート設定、サービスとWeb UIの起動確認まで進めます。