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.
日本語の概要は準備中です。原文の説明を表示しています。
Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.
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。
You MUST NOT install, upgrade, or modify packages on the user's behalf. Provide the exact command; the user runs it. No exceptions.
Forbidden: running pip install, uv pip install, uv add,
uv sync, conda install, apt install, or any package manager.
Instead: give the exact command and ask the user to run it. Explain why the package is needed.
When a package is needed:
Even if the user says "just install it", give the command and require them to execute it themselves.
Help users install Earth2Studio and its optional model dependencies correctly for their use case. This skill handles package installation, optional-extra selection, environment variable configuration, and install verification.
You are helping a user install Earth2Studio and its optional model dependencies. Your only job is to get the package installed correctly for their use case — do not write inference code, do not compose workflows.
Earth2Studio installation commands, version tags, and extra names change between releases. Before executing or recommending any install command, fetch the live installation docs:
https://nvidia.github.io/earth2studio/userguide/about/install.html
Parse the page for the current version tag, available extras, and any special build notes. The workflow below is structural guidance — the specific commands come from the live page.
Use WebFetch on the install URL above. Extract:
@0.14.0)--no-build-isolation for pip,
manual pre-installs)Keep this data in working memory for all subsequent steps.
Ask (cap at 3 questions, skip what the user already answered):
Provide commands from the live docs based on their answers:
After the user runs the install, verify:
import earth2studio
earth2studio.__version__
Present the available extras organized by use case. Ask what the user plans to do — don't dump all options unprompted. Categories from the docs:
| Category | Example extras |
|---|---|
| Prognostic (forecasting) | aifs, aurora, graphcast, pangu, sfno, stormcast, ... |
| Diagnostic (post-processing) | corrdiff, climatenet, precip-afno, ... |
| Data assimilation (beta) | da-healda, da-interp, da-stormcast |
| Submodules | data, perturbation, statistics |
The exact list comes from the live docs — cite those, not this table.
Ask:
--extra all)Provide the exact commands from the live docs for their selections. Key warnings to surface:
--no-build-isolation or pre-installing packages like earth2grid,
torch-harmonics, or makaniMention environment variables the user might want to set — only if relevant (e.g. limited disk, shared filesystem, CI environment):
| Variable | Purpose |
|---|---|
EARTH2STUDIO_CACHE | General cache directory |
EARTH2STUDIO_DATA_CACHE | Data source cache (overrides general) |
EARTH2STUDIO_MODEL_CACHE | Model checkpoint cache (overrides general) |
EARTH2STUDIO_PACKAGE_TIMEOUT | Max seconds for model downloads |
If installation fails, point the user to:
Common issues:
torch.cuda.is_available() firstsudo apt-get install libeccodes-dev (Debian/Ubuntu) or
conda install -c conda-forge eccodessudo apt-get install python3-devdata extra is out of scopeOwns: package installation, optional-extra selection, environment variable configuration, install verification.
Does not own: writing inference or training code, composing
Earth2Studio workflows, data source setup beyond the data extra,
model checkpoint downloads (those happen at runtime), troubleshooting
runtime errors unrelated to missing dependencies.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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'.
日本語の概要は準備中です。原文の説明を表示しています。
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`.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。