Python Prompt Package System

A Python Prompt Package System is a package management system that handles AI prompt resources within Python packages.

• AKA: Python Prompt Packager, PyPI Prompt System, Python Prompt Distribution, Pip-based Prompt Manager, Python Package Prompt Management System.
• Context:
  • It can typically package Static AI Prompts as Python modules using setuptools or poetry.
  • It can typically distribute Prompt Collections via PyPI repositorys with pip installation.
  • It can typically manage Prompt Dependencys through requirements.txt and pyproject.toml.
  • It can typically load Prompt Resources using pkg_resources or importlib.resources.
  • It can typically version Prompt Packages with semantic versioning and version specifiers.
  • It can often support Namespace Packages for prompt organization across multiple distributions.
  • It can often implement Prompt Discovery Protocols via entry points and plugin systems.
  • It can often provide Development Mode Installations through editable installs for local development.
  • It can range from being a Simple Python Prompt Package System to being a Complex Python Prompt Package System, depending on its feature sophistication.
  • It can range from being a Single-Package Python Prompt System to being a Multi-Package Python Prompt System, depending on its distribution scope.
  • It can range from being a Standalone Python Prompt System to being an Integrated Python Prompt System, depending on its framework coupling.
  • It can range from being a Public Python Prompt System to being a Private Python Prompt System, depending on its repository visibility.
  • ...
• Examples:
  • Framework-Integrated Python Prompt Packages, such as:
    • LangChain Python Prompt Templates with chain integration.
    • Guidance Python Prompt Library with template syntax.
    • DSPy Python Prompt Modules with signature system.
  • Standalone Python Prompt Packages, such as:
    • Prompttools Python Library for prompt testing.
    • Promptify Python Package for NLP task prompts.
    • Prompt-Engine Python Module for prompt generation.
  • Enterprise Python Prompt Distributions, such as:
    • Private PyPI Prompt Repository with corporate registry.
    • Artifactory Python Prompt Management with artifact control.
    • Azure Artifacts Prompt Distribution with feed management.
  • ...
• Counter-Examples:
  • JavaScript NPM Prompt Package, which uses Node.js ecosystem rather than Python.
  • Manual Prompt File Management, which lacks package management infrastructure.
  • Container-based Prompt Distribution, which uses Docker images rather than Python packages.
• See: Package Management System, Python Package, Static AI Prompt, Prompt-as-Code Practice, AI Prompt Resource Bundle, Versioned AI Prompt Repository, Prompt Organization System, Prompt Loading Mechanism, Python Library, PyPI, Pip, Python Module System.

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