AI-Meal-Planner

This project implements an AI-powered meal planner that helps users create personalized meal plans based on their dietary preferences, restrictions, and caloric goals. It leverages Python, Groq for AI processing, and a Food API (you'll need to specify which one you use, e.g., Spoonacular, Edamam, etc.) for accessing a vast database of recipes and nutritional information. This version simplifies setup by using Docker.

Table of Contents

• Introduction
• Features
• Tech Stack
• Installation (Docker)
• Usage
• API Integration
• Groq Integration

Introduction

Planning meals can be a time-consuming and often frustrating task. This AI Meal Planner simplifies the process by using artificial intelligence to generate meal plans tailored to individual needs. Users can specify dietary restrictions (e.g., vegetarian, vegan, gluten-free), allergies, preferred cuisines, and even their daily calorie goals. The AI then uses this information, along with the Food API data, to create a diverse and balanced meal plan.

Features

• Personalized Meal Plans: Generates meal plans based on user preferences, dietary restrictions, and caloric goals.
• AI-Powered Recommendations: Uses Groq for intelligent meal suggestions and recipe matching.
• Food API Integration: Accesses a large database of recipes and nutritional information (e.g., Spoonacular, Edamam). (Specify which API you use)
• Flexible Customization: Allows users to customize generated meal plans, swap meals, and add their own recipes.
• Nutritional Information: Displays detailed nutritional information for each meal, including calories, macronutrients, and micronutrients.
• (Optional) Shopping List Generation:* Automatically creates a shopping list based on the generated meal plan.
• (Optional) User Authentication:* Allows users to save their preferences and meal plans.
• Dockerized: Easy setup and deployment using Docker.

Tech Stack

• Python: The primary programming language.
• Groq: Used for AI processing and meal planning logic.
• [Food API Name]: (e.g., Spoonacular, Edamam) Provides access to recipe data and nutritional information. (Specify which API you use)
• (Optional) Flask/Django: For creating a web interface.
• (Optional) Database (e.g., SQLite, PostgreSQL): For storing user data and meal plans.
• Docker: For containerization.

Installation (Docker)

1. Clone the repository:

   git clone [https://github.com/your-username/ai-meal-planner.git](https://www.google.com/search?q=https://github.com/your-username/ai-meal-planner.git)

Navigate to the project directory:

Bash

cd ai-meal-planner Create a .env file in the project root and add your API keys:

FOOD_API_KEY=[Your Food API Key] # Replace with your actual key GROQ_API_KEY=[Your Groq API Key] # Replace with your actual key

... other environment variables if needed

Build the Docker image:

Bash

docker build -t ai-meal-planner . Run the Docker container:

Bash

docker run -p 5000:5000 --env-file .env ai-meal-planner # Replace 5000 with your port This command maps port 5000 on your host machine to port 5000 in the container and uses the .env file to set the environment variables.

Usage Access the application through the web interface at http://localhost:5000 (or the port you specified).

Follow the prompts to input your dietary preferences, restrictions, and caloric goals.

The AI will generate a personalized meal plan.

API Integration This project integrates with the [Food API Name] API. (Provide more details about how the API is used, including specific endpoints and data retrieval methods.)

Groq Integration Groq is used to power the AI meal planning logic. (Explain how Groq is used in the project, including the prompts or models used and how the results are processed.)

Contributing Contributions are welcome! Please open an issue or submit a pull request.