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ChefAI India: Personalized Indian Cuisine Recipe Generation Using Generative AI
India's rich and diverse culinary heritage spans hundreds of regional cuisines, dietary traditions, and cooking styles. Despite significant advances in natural language processing and generative artificial intelligence, no comprehensive system exists that can generate contextually accurate, nutritionally aware, and regionally authentic Indian recipe recommendations tailored to individual user preferences. This paper presents ChefAI India, a generative AI-powered recipe generation system that leverages a fine-tuned GPT-2 medium transformer model augmented with an Indian cuisine knowledge base to produce personalised recipes across six major regional categories: North Indian, South Indian, Bengali, Gujarati, Rajasthani, and other regional cuisines. The model is trained on a curated dataset of 28,400 annotated recipe instances enriched with dietary tags, ingredient substitution mappings, and nutritional metadata. ChefAI India achieves a classification accuracy of 94.3%, precision of 93.1%, recall of 92.8%, and F1-score of 92.9%, outperforming state-of-the-art baselines including Seq2Seq, GPT-2 (vanilla fine-tuned), mBART, and BERT2BERT. User evaluation trials with 120 participants across three Indian cities recorded a satisfaction rating of 4.6/5.0. ChefAI India represents a scalable, culturally grounded solution for personalised Indian cuisine recommendation and recipe generation.
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