AI Prompt Resource Bundle

A AI Prompt Resource Bundle is a software resource bundle that packages AI prompts with associated metadata, configurations, and dependencys for distribution.

• AKA: Prompt Resource Package, AI Prompt Bundle, Prompt Asset Bundle, Prompt Distribution Package.
• Context:
  • It can typically contain Static AI Prompts with version information and usage documentation.
  • It can typically include Prompt Metadata such as author information, license terms, and compatibility requirements.
  • It can typically provide Prompt Configuration Files for runtime parameters and environment settings.
  • It can typically bundle Prompt Test Suites with validation scripts and example usage.
  • It can typically incorporate Prompt Dependency Manifests listing required librarys and external resources.
  • It can often support Multi-Language Prompts through localization files and translation mappings.
  • It can often enable Prompt Template Variables via placeholder definitions and substitution rules.
  • It can often implement Bundle Integrity Checks using checksums and digital signatures.
  • It can range from being a Minimal AI Prompt Resource Bundle to being a Comprehensive AI Prompt Resource Bundle, depending on its content scope.
  • It can range from being a Single-Prompt Bundle to being a Multi-Prompt Bundle, depending on its prompt count.
  • It can range from being a Platform-Specific AI Prompt Resource Bundle to being a Cross-Platform AI Prompt Resource Bundle, depending on its compatibility range.
  • It can range from being a Compressed AI Prompt Resource Bundle to being an Uncompressed AI Prompt Resource Bundle, depending on its packaging format.
  • ...
• Examples:
  • Archive-based Prompt Bundles, such as:
    • ZIP Prompt Archive with directory structure.
    • TAR.GZ Prompt Package with compression.
    • Python Wheel Bundle with metadata specification.
  • Repository-based Prompt Bundles, such as:
    • Git Repository Bundle with submodules.
    • NPM Package Bundle with package.json manifest.
    • Docker Image Bundle with layered structure.
  • Framework-Specific Prompt Bundles, such as:
    • LangChain Prompt Collection Bundle with chain templates.
    • Hugging Face Dataset Bundle with prompt examples.
    • OpenAI Function Bundle with tool definitions.
  • ...
• Counter-Examples:
  • Single Prompt File, which lacks bundling structure and associated metadata.
  • Inline Prompt Definition, which embeds prompts directly in source code without separate packaging.
  • Runtime-Generated Prompt, which creates prompts dynamically rather than packaging them statically.
• See: Software Resource Bundle, Static AI Prompt, Prompt-as-Code Practice, Python Prompt Package System, Versioned AI Prompt Repository, Prompt Organization System, Prompt Versioning Process, Resource Packaging, Distribution Package, Software Bundle, Package Metadata, Dependency Management.

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