This project provides a metaframework for AI prompts, enabling developers to structure prompt engineering with file-based routing and data integration. It targets AI developers seeking organized, reproducible, and data-aware prompt workflows, offering a more robust alternative to ad-hoc prompt management.

How It Works

Dataprompt uses a .prompt file format, extending Handlebars, to define prompts, data sources (e.g., fetching from APIs or Firestore), and post-generation actions. It leverages Genkit for AI model integration and Zod for schema validation of prompt inputs and outputs, ensuring type safety and structured data. The framework exposes prompts as a JSON API, simplifying integration and testing.

Quick Start & Requirements

• Install via npm: npm i dataprompt genkit or use CLI: npx dataprompt create.
• Requires Node.js.
• Official docs: https://dataprompt.dev/

Highlighted Details

• Supports data fetching from URLs and Firestore.
• Enables post-generation actions like writing to Firestore or files.
• Includes scheduled task triggers via node-cron.
• Allows custom data sources, actions, and triggers via plugins.

Maintenance & Community

• Project status is Alpha.
• Community links are not explicitly mentioned in the README.

Licensing & Compatibility

• The license is not specified in the README.

Limitations & Caveats

• The project is in Alpha status, indicating potential instability and breaking changes.
• Firestore and Fetch plugins are marked as experimental and not recommended for production.
• Customization of fetchPlugin and schedulerPlugin requires explicit configuration in dataprompt.config.js.
• The fsPlugin requires careful configuration of sandboxDir for security.