Meal Planner AI Recommender
Meal Planner AI Recommender is a lightweight AI meal recommendation system that generates personalized meal suggestions based on user preferences such as diet, budget, allergies, cuisine, cooking time, and nutrition goals.
This model uses a content-based recommendation approach with TF-IDF vectorization and cosine similarity.
Model Overview
This project is not a large language model. It is a lightweight recommendation engine designed to be used as the model core for a meal planner application.
The model recommends meals based on:
- Diet preference
- Allergy restrictions
- Budget level
- Cuisine preference
- Meal type
- Cooking time
- Nutrition goals
- Difficulty level
Files
| File | Description |
|---|---|
vectorizer.pkl |
Trained TF-IDF vectorizer |
meals_database.pkl |
Processed meal database |
inference.py |
Example inference script |
week_plan.json |
Example generated 7-day meal plan |
shopping_list.json |
Example generated shopping list |
requirements.txt |
Python dependencies |
Dataset Columns
The meal database contains these fields:
id
name
meal_type
calories
protein
carbs
fat
ingredients
diet_tags
allergen_tags
budget_level
cooking_time
cuisine
difficulty
features