https://github.com/ridwansharkar/the-nutrimancers-codex

AI-assisted Bioessence Extractor - Vol. II
https://github.com/ridwansharkar/the-nutrimancers-codex

cosine-similiarity gemini-api golang gsap llm machine-learning nlp nutritionix-api

Last synced: 4 months ago
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AI-assisted Bioessence Extractor - Vol. II

• Host: GitHub
• URL: https://github.com/ridwansharkar/the-nutrimancers-codex
• Owner: RidwanSharkar
• Created: 2024-10-05T20:29:22.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-12-29T06:01:14.000Z (6 months ago)
• Last Synced: 2025-01-16T08:16:50.423Z (5 months ago)
• Topics: cosine-similiarity, gemini-api, golang, gsap, llm, machine-learning, nlp, nutritionix-api
• Language: Go
• Homepage:
• Size: 145 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# The Nutrimancer's Codex - Vol. II

An AI-powered application that analyzes food descriptions to extract ingredients, compute nutrient deficiencies, and recommend foods to balance your diet.

## Overview:

The Nutrimancer's Codex is a full-stack application that leverages AI and machine learning to help users understand their nutrient intake and make informed dietary choices. By inputting a food description, users receive an analysis of nutrient content, identify deficiencies, and get personalized food recommendations.

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## Features:

• Ingredient Extraction: utilizes the Gemini Language Model to parse natural language food descriptions.


• Nutrient Analysis: calculates nutrient percentages based on recommended daily allowances using data from Nutritionix and USDA. 


• Deficiency Detection: identifies low or missing essential nutrients in the user's diet. 


• Recommendation: cosine similarity algorithm is applied across dataset to display the foods most capable of alleviating the current active deficiencies. 

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## Vol. II:


![Vol  II](https://github.com/user-attachments/assets/23c0f1a1-51d3-4898-b564-c90495477d4b)

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## Vol. I:


![Vol  I](https://github.com/user-attachments/assets/af91009a-d7f3-4c40-94fc-d8ace8988c8d)

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## Tech Stack:

• **Frontend:** React (TypeScript), GSAP, Tailwind (CSS), Axios

• **Backend:** Go (GoLang), net/http, CORS, JSON processing 

• **Dataset & APIs:** USDA FoodData Central, Google Generative Language, Nutritionix

• **Natural Language Processing:** Gemini Flash 1.5

• **Machine Learning:** Cosine Similarity (GoLang)

• **Deployment:** AWS Amplify, AWS Elastic Beanstack via EC2, Nginx