prompts.txt

A web-based code classification system leveraging AI models (specifically fine-tuned Transformer models based on replit/replit-code-v1_5-3b, WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-8B, and WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B) to analyze and categorize code snippets for cybersecurity and software engineering purposes. The system is trained on specialized datasets including Canstralian/Wordlists, Canstralian/CyberExploitDB, Canstralian/pentesting_dataset, and Canstralian/ShellCommands, under MIT license.  Core Features: - Code submission interface with syntax highlighting - AI-powered analysis and classification of submitted code - Results display showing classification categories and confidence scores - Historical record of analyzed code snippets  Visual References: Inspired by GitHub Copilot and OpenAI Playground interfaces, combining professional code presentation with intuitive analysis tools.  Style Guide: - Colors: Primary #2D333B (dark navy), Secondary #539BF5 (bright blue), Background #22272E (deep grey), Text #ADBAC7 (light grey), Accent #347D39 (success green) - Design: JetBrains Mono/Inter fonts, dark theme optimized for code display, syntax highlighting support, 16px padding, responsive layout with collapsible panels