01. Prompt Engineers can define custom prompts through uploading txt files to a storage account.

02. Prompt configurations include placeholders for dynamic content binding.

03. The prompt engine generates descriptions based on the configured prompts.

04. When a specific prompt configuration is missing, the prompt engine defaults to a predefined fallback prompt.

05. Fallback prompts are designed to provide contextually relevant descriptions.

06. Liquid Templates (Scriban package) are seamlessly integrated into the prompt engine.

07. Prompt Engineers can bind prompt configurations to dynamic input data using Liquid Templates syntax.

08. The prompt engine is modular and designed for reuse across various endpoints within the OpenAI service.

09. Integration of the prompt engine across different endpoints demonstrates consistent behavior and configuration options.

10. Comprehensive documentation is provided on configuring prompts, using fallbacks, utilizing Liquid Templates, and handling multilingual prompts.

11. The prompt engine processes prompt configurations and generates descriptions efficiently, without noticeable delays.

12. The prompt engine operates reliably even when handling a substantial volume of prompt requests.