TunaCode is designed to streamline the entire software development lifecycle by translating plain-English project descriptions into production-ready code. Leveraging advanced machine learning algorithms trained on millions of code repositories, TunaCode supports popular frameworks such as React, Vue, Express, and Django. It can generate UI components with responsive layouts, define RESTful APIs, configure database models for SQL or NoSQL stores, and scaffold automated unit tests. A built-in real-time editor allows users to refine generated code snippets instantly, while version control integration ensures seamless collaboration. Additionally, TunaCode can produce detailed documentation and deployment scripts for cloud platforms like AWS, Azure, or Heroku. This comprehensive AI agent eliminates repetitive boilerplate tasks and empowers developers to focus on innovation and complex problem-solving.

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.

SDLC Copilot is an AI-powered agent designed to streamline SDLC phases: from requirement gathering to deployment. It processes user inputs or imported project specifications, then leverages natural language processing to break down requirements into actionable tasks. It generates UML class and sequence diagrams, proposes architecture plans, scaffolds code modules in multiple languages, drafts API documentation, and auto-generates unit and integration test cases. It integrates with Git-based workflows, issue trackers, and CI/CD pipelines to continuously analyze changes, suggest improvements, and enforce coding standards. Developers can interact through a chat UI or CLI to refine outputs, ask for refactoring suggestions, or request performance optimization tips, making SDLC Copilot a central hub for project management and code quality assurance.