The RAG-Llama3 Multi-AGI Django Website Code Generator is a specialized AI framework that combines retrieval-augmented generation techniques with multiple Llama3-based agents. It processes user-defined requirements and external documentation to retrieve relevant code snippets, orchestrates several AI agents to collaboratively draft Django model definitions, view logic, templates, URL routing, and project settings. This iterative approach ensures that generated code aligns with user expectations and best practices. Users start by seeding a knowledge base of documentation or code samples, then prompt the agent for specific features. The system returns a complete Django project scaffold, complete with modular apps, REST API endpoints, and customizable templates. The modular nature allows developers to integrate custom business logic and deploy directly to production environments.

Django Helper is a Visual Studio Code extension designed to assist Django developers directly in their code editor. By integrating with GitHub Copilot, it allows users to ask questions using the '@django' prefix and get real-time responses. Additionally, it offers GPT-4o-powered responses based on Django documentation, ensuring developers have quick access to the information they need without leaving their editor. This tool enhances productivity and simplifies the learning curve for Django, making it easier to solve issues and implement features efficiently.