PostForge: A Unified, Locally Deployable Multimodal AI Platform for Social Media Content Generation

The exponential growth of social media platforms has created a demand for high-quality, optimized content that exceeds the capacity of manual creation methods. While Arti¬ficial Intelligence (AI) offers a solution, current tools are often fragmented, requiring users to navigate multiple applications for image generation, captioning, and hashtag optimization. Furthermore, reliance on third-party APIs raises concerns regarding cost, latency, and data privacy. This paper presents PostForge, a unified web application designed to streamline social media content creation by integrating specialized AI models. Unlike monolithic multimodal models, PostForge em-ploys a modular architecture leveraging distinct state-of-the-art models for specific tasks: Latent Diffusion Models for text-to-image generation, BLIP for image captioning, and transformer-based models for hashtag generation. The system is designed for local deployment, ensuring data sovereignty and reducing operational costs. Experimental evaluation demonstrates the system’s efficacy, achieving a ROUGE-L score of 0.457 and BLEU score of 0.041, validating the feasibility of a unified, privacy-centric approach to content automation.