# Search Recipes — How to discover PhysicsNeMo artifacts live Concrete Glob / Grep / Read patterns the skill should use to discover what's actually in the repo, instead of relying on a static inventory. All paths are relative to the resolved repo root. ## Guiding rule If you are about to name a class, file, or example, **run at least one search below first** to confirm it exists and capture its current description. --- ## 1. Confirm the repo root ``` Read /pyproject.toml # check name == "nvidia-physicsnemo" Glob /physicsnemo/__init__.py # must exist Glob /examples/README.md # usually exists ``` If any of these fail, ask the user to confirm the path. --- ## 2. Find examples for a domain ``` # 2a. Enumerate examples in the target domain Glob examples//**/README.md # 2b. Read each README's top (title + first paragraph) to match user intent Read examples///README.md # limit=30 # 2c. When READMEs are ambiguous, inspect the training script imports to see # which models / datapipes the example actually uses Grep "from physicsnemo" examples/// --type py -n --head_limit 20 ``` If the user's domain keyword doesn't map cleanly to a folder name: ``` # 2d. Broad search for concept across all examples Grep -l "" examples/ --type md Grep -l "" examples/ --type py ``` --- ## 3. List currently-exported models across ALL families matching a data shape The skill's output surfaces a *menu* of candidate families, not a single pick. Enumerate every family the taxonomy's data-shape row lists — not just the first one that looks plausible. ``` # 3a. Top-level model registry exports — the full top-level menu Read physicsnemo/models/__init__.py # 3b. Per-family loop — for EACH candidate family from the taxonomy data-shape row, # confirm the subdir exists and read its exports. Do not stop after one match. Glob physicsnemo/models//__init__.py Read physicsnemo/models//__init__.py # repeat for every candidate family in the data-shape row # 3c. Extract purpose from a specific model's docstring (after 3b has surfaced the family) Grep -n "^class " physicsnemo/models//.py Read physicsnemo/models//.py # limit ~80 lines around the class # 3d. Cross-reuse: find which examples instantiate each candidate family. # This feeds the "Instantiated by: " annotation in the output skeleton. Grep -rn "from physicsnemo.models." examples/ --type py -l ``` For experimental models: ``` Glob physicsnemo/experimental/models/**/__init__.py Read physicsnemo/experimental/models//__init__.py ``` Always flag experimental matches as *"API may change"*. --- ## 4. List currently-exported datapipes for a format ``` # 4a. Top-level datapipes exports Read physicsnemo/datapipes/__init__.py # 4b. Subpackage exports — enumerate live rather than assuming names Glob physicsnemo/datapipes/*/__init__.py Read physicsnemo/datapipes//__init__.py # 4c. Base classes for custom data # See TAXONOMY.md § Data format → how to find a datapipe for the # full file paths + confirmation steps. Commands below are quick # reference. Grep -n "^class " physicsnemo/datapipes/readers/base.py Grep -n "^class " physicsnemo/datapipes/datapipe.py Grep -n "^class " physicsnemo/datapipes/transforms/base.py ``` For format-specific discovery: ``` Grep -l "" physicsnemo/datapipes/ --type py ``` --- ## 5. List currently-exported core utilities ``` # 5a. For a known module (distributed, utils, metrics, mesh, diffusion, etc.) Read physicsnemo//__init__.py # 5b. If the init is thin, list the files and sample headers Glob physicsnemo//*.py Grep -n "^(class|def) " physicsnemo//.py --head_limit 20 ``` For submodules (e.g. `utils/logging/`, `utils/profiling/`, `metrics/climate/`): ``` Glob physicsnemo//*/__init__.py Read physicsnemo///__init__.py ``` --- ## 6. Find documentation pages ``` # 6a. Top-level doc indexes Read docs/index.rst Read docs/api_index.rst Read docs/examples_index.rst # 6b. Domain example indexes Glob docs/examples_*.rst Read docs/examples_.rst # 6c. API doc for a specific module Glob docs/api/**/*.rst Read docs/api/.rst # 6d. Broad search Grep -l "" docs/ --glob "*.rst" ``` --- ## 7. Confirm a specific class / function exists ``` # 7a. Search by class name across physicsnemo Grep -n "^class " physicsnemo/ --type py # 7b. Search by function name Grep -n "^def " physicsnemo/ --type py # 7c. If not found where expected — check compat layer for renames Read physicsnemo/compat/__init__.py ``` If a name isn't found anywhere, it may have been renamed. Do not emit it. --- ## 8. Check scale / distribution patterns used in an example ``` # Does this example use DDP, FSDP, domain parallelism? Grep -n "DistributedManager\|FSDP\|ShardTensor\|torch.distributed" examples/// -l Grep -n "DistributedManager\|FSDP\|ShardTensor\|torch.distributed" examples/// --type py ``` --- ## 9. Decide between similar examples When the user's description matches multiple examples, compare by: ``` # 9a. README purpose statements (first 20 lines) Read examples///README.md # limit 20 Read examples///README.md # limit 20 # 9b. Data format used (training script imports + file globs) Grep -n "h5py\|zarr\|xarray\|pyvista\|tfrecord\|numpy.load" examples/// --type py Glob examples///**/*.yaml # Hydra configs often hint at scale + data ``` Pick the example whose README *purpose statement* and *data format* match the user's situation most closely. --- ## 10. Fallback: pure keyword search If the user's phrasing doesn't map to any taxonomy entry: ``` Grep -l "" examples/ --type md Grep -l "" physicsnemo/ --type py Grep -l "" docs/ --glob "*.rst" ``` --- ## 11. Check shared datapipe across examples See TAXONOMY.md § Cross-example reuse patterns for the rationale and known reuse cases (Darcy2D, ERA5, VTK). The recipe below is the mechanical step: grep the datapipe class across `examples/` and surface confirmed reuse in the output. ``` # 11a. Which examples import a given datapipe class? Grep -rn "" examples/ --type py -l # 11b. Which models do those examples pair the datapipe with? # Run for each example surfaced by 11a. Grep -n "from physicsnemo.models" examples/// --type py ``` Use the result to annotate the "Datapipe(s) for your data format" section with *"Reused by: <examples>"* and to pick reference examples that span ≥2 model families on the same data. --- ## Output discipline Every pointer you emit must be traceable to a tool result in the current turn. If you cannot show where you just read it, don't emit it. This is how the skill stays honest as the repo evolves.