AI-Powered Meal Nutritional Analysis Workflow

This n8n workflow automates the process of analyzing meal images to extract detailed nutritional information. It starts with a webhook trigger that receives an image upload from a mobile app or website. The image is then sent to OpenAI’s Vision API via the ‘analyze_image’ node, which analyzes the meal content, identifies food items, estimates portion sizes, and computes various nutritional metrics. The raw results are processed through language models, including ‘extract_results’ and ‘Auto-fixing Output Parser’, which format the data into a structured JSON object containing details such as calories, proteins, carbs, fats, and a health score. Finally, the structured data is returned as a JSON response, enabling seamless integration with a calorie tracking or nutrition app. This workflow is ideal for fitness apps, diet planners, and nutrition tracking services aiming to provide instant, AI-driven nutritional feedback based on user-uploaded meal photos.