AI-based content generation has become increasingly important across various industries, en-abling users to create textual and visual content efficiently using artificial intelligence. This project presents the design and development of a unified AI-powered content generation platform implemented without relying on external APIs. The proposed system utilizes LLaMA-based large language models for text generation and diffusion models for image generation, deployed locally to ensure greater control, data privacy, and reduced dependency on third-party services. The system allows users to generate articles, blogs, sum-maries, and AI-generated images through a single web-based interface. User inputs are processed by the in-tegrated language and image generation models, and the generated outputs are delivered in real time. The system architecture is designed to efficiently manage model inference, content generation workflows, and user interactions. This project demonstrates the feasibility of building a standalone AI content generation system using open-source models and highlights its applicability in domains such as education, digital content creation, and media automation.
