AI-Powered Food Nutrition Analysis from Images
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Automate detailed nutritional analysis of meals from images using OpenAI Vision and Langchain. This workflow extracts meal name, calories, macronutrients, and health scores, outputting structured JSON.
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About This Workflow
Overview
This n8n workflow automates the process of analyzing food images to extract detailed nutritional information. It leverages the OpenAI Vision API to identify food items, estimate portion sizes, and calculate various nutritional values. The results are then processed by Langchain nodes to format the output into a structured JSON object, suitable for integration with applications like a calorie tracking app. This workflow solves the problem of manual food logging and provides an AI-driven solution for quick and accurate nutritional assessment.
Key Features
- Analyzes food images to identify meal components.
- Estimates portion sizes and calculates key nutritional data (calories, protein, carbs, fat, fiber, sugar, sodium).
- Provides a confidence score for the analysis accuracy.
- Assesses the overall healthiness of the meal with a health score.
- Outputs structured JSON for easy application integration.
How To Use
- Set up the
meal_image_webhoookto receive image data via HTTP POST requests. - Configure the
analyze_imagenode with your OpenAI API key and provide the detailed prompt for food analysis. - Connect the output of
analyze_imageto theextract_resultsnode (using Langchain's Chain LLM) to format the initial AI response. - Utilize the
Structured Output ParserorAuto-fixing Output Parserto ensure the extracted data conforms to the expected JSON schema. - Configure the
respond_to_webhooknode to return the structured nutritional data back to the calling application.
Apps Used
Workflow JSON
{
"id": "be8266a3-8a03-4645-b841-d8d161e200d6",
"name": "AI-Powered Food Nutrition Analysis from Images",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: be8266a3-8a03...
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