Prompt Genius is a comprehensive, multi-lingual website designed to help users discover, organize, and share effective prompts for AI language models. It targets individuals seeking to enhance productivity and quality across various tasks, from research and writing to coding and office productivity. The platform offers a hierarchical classification system, personalized collections, and a preview of AI responses to prompts.

How It Works

The website employs a hierarchical, tree-like structure for prompt classification, covering a wide array of use cases. Users can search by keywords within prompt categories and content. Prompts are displayed with category tags and author information, featuring a one-click copy function for easy integration with AI models. A key feature is the ability to preview how different AI models respond to specific prompts, aiding in prompt selection and refinement.

Quick Start & Requirements

• Install dependencies: pip install -r requirements.txt
• Start server (debug): export FLASK_APP=app, export FLASK_DEBUG=true, flask run --port 9000
• Start server (production): waitress-serve --port=8080 --call app:create_app
• Requires a app_config.json file in the /app directory with database URI and secret key.
• Data is stored in a SQLAlchemy-managed database (SQLite example provided).
• Project website: www.promptgenius.site or http://8.130.82.126:8080/

Highlighted Details

• Hierarchical classification system for prompts across 9 major categories and numerous sub-categories.
• Multi-language support (English, Chinese, Japanese, Korean, German).
• Responsive design for multi-device access (mobile, tablet, desktop).
• User accounts for personalized prompt collections and contributions.
• AI response preview feature for prompt validation.

Maintenance & Community

The project acknowledges contributions from several users, indicating community involvement. Further community channels or roadmap details are not explicitly provided in the README.

Licensing & Compatibility

The README does not specify a license. The technical stack (Flask, Bootstrap, jQuery) is generally compatible with commercial and closed-source applications.

Limitations & Caveats

The project is described as "开箱即用" (out-of-the-box ready), but requires manual creation of a configuration file (app_config.json) for setup. Specific details on database management beyond the SQLite example are not elaborated.