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pipelines-and-applications

pipelines-and-applications

Routes CogDL pipeline apps, embedding generation, recommendation, and OAG-BERT workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

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name: pipelines-and-applications description: "Routes CogDL pipeline apps, embedding generation, recommendation, and OAG-BERT workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

CogDL Pipelines and Applications

Use this sub-skill when the user wants a named CogDL application rather than a raw model or training loop.

Typical triggers:

  • "Show me CogDL dataset stats for a graph dataset"
  • "How do I generate embeddings with CogDL?"
  • "How do I use CogDL recommendation or OAG-BERT pipelines?"
  • "Why did the OAG archive or cache step fail?"

Read references/pipeline-recipes.md for the supported app names, the main input/output shapes, and the safe no-network examples. Read references/oagbert.md for OAG-BERT variants, paper/entity input fields, and the optional cache/network boundary. Read references/troubleshooting.md for unknown apps, PNG output, generate- emb feature requirements, recommendation data layout, and OAG cache issues.

Run scripts/pipeline_smoke.py to inspect the app registry and optionally run a tiny no-download generate-emb smoke on a small edge list.

Route these elsewhere:

  • ../experiments-and-cli/SKILL.md for experiment(...), CLI flags, and AutoML orchestration.
  • ../graph-data-and-datasets/SKILL.md for graph schemas, masks, and custom fixture creation.
  • ../models-layers-and-operators/SKILL.md for model/layer code and sparse operator details.
  • ../training-wrappers-and-customization/SKILL.md for wrappers and trainer settings used by the pipelines.

What this sub-skill covers

  • pipeline(app: str, **kwargs) and the SUPPORTED_APPS registry.
  • Dataset stats and dataset-visual apps.
  • Embedding generation apps, including the no-download ProNE smoke path.
  • Recommendation pipelines and their data-shape expectations.
  • OAG-BERT loading, model variants, and paper/entity input helpers.

Decision rules

  • If the user just needs a quick app name, use the registry and keep the answer brief.
  • If the app is dataset-related, make the cache/download behavior explicit.
  • If the app is OAG-BERT-related, label the model archive as optional and network/cache-dependent.
  • Keep runnable helpers safe by default; no helper in this sub-skill should download a dataset unless the user explicitly asks for that side effect.
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