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pipeline-basics

pipeline-basics

Install/import OpenPrompt, inspect the public pipeline APIs, and build the minimal PromptDataLoader/PromptForClassification/PromptForGeneration flow.

Independent GitHub snapshot · Automated classification · Original documentation governs

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name: pipeline-basics description: "Install/import OpenPrompt, inspect the public pipeline APIs, and build the minimal PromptDataLoader/PromptForClassification/PromptForGeneration flow." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Pipeline Basics

Use this sub-skill for the OpenPrompt package-usage surface: install checks, public exports, InputExample / InputFeatures, PromptDataLoader, PromptForClassification, PromptForGeneration, and load_plm.

Start here:

  • references/api-reference.md for verified signatures and return contracts.
  • references/workflows.md for the minimal classification/generation quickstart and the no-download smoke.
  • references/troubleshooting.md for dependency and wrapper failures.
  • scripts/check_openprompt_install.py for the canonical import/API smoke.

Operating rules:

  1. Keep to the basic pipeline. Do not expand into prompt-template grammar, prompt-asset curation, dataset acquisition, or training-loop tuning.
  2. Prefer the smoke script before deeper debugging. It runs from a temporary working directory, imports the installed openprompt package, avoids downloads, and checks the fake-wrapper loader path.
  3. PromptDataLoader accepts either a ready wrapper object or a wrapper class plus tokenizer; the wrapper class must expose the constructor kwargs filtered by the loader.
  4. Route template/verbalizer design to ../template-verbalizer-design/, data/config work to ../data-and-config-workflows/, and training/runtime issues to ../training-and-generation/.
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