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```python
import openai
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "Create a weekly vegan meal plan."},
{"role": "user", "content": "Include breakfast, lunch, and dinner with nutritional balance."}
]
)
print(response) // Outputs AI generated meal plan details
```
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The app uses AI to analyze your food preferences, dietary requirements, and health goals, then offers customized meal ideas just for you. This means the meals are not random but are suggested based on what you like and what is healthy for you. The process is dynamic, so your options evolve as your tastes or needs change.
This feature automatically pulls ingredients from your planned meals and creates a consolidated shopping list. It eliminates the need for manual list-making by ensuring every recipe's ingredients are captured in one place. The AI can even help predict when you might need to restock based on your cooking habits.
The app provides an in-depth view of your meals by breaking down calorie counts and macronutrients such as carbohydrates, proteins, and fats. With this clear nutritional overview, you can easily track and manage your diet, ensuring that every meal aligns with your health objectives.
This feature integrates your meal plan with a calendar, allowing you to see what you're eating on any given day alongside your other commitments. It helps you plan ahead, ensuring that meal times fit smoothly into your busy schedule. The AI continuously updates your plan in real-time if you have schedule changes.
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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>AI Meal Planning App</title>
<style>
body { font-family: Arial, sans-serif; margin: 20px; }
.container { max-width: 600px; margin: auto; }
label { display: block; margin-top: 10px; }
input, textarea, button { width: 100%; padding: 8px; margin-top: 5px; }
</style>
</head>
<body>
<div class="container">
<h3>Enter Your Preferences</h3>
<form id="mealPlanForm">
<label for="diet">Dietary Preference (e.g., vegan, keto):</label>
<input type="text" id="diet" name="diet" required>
<label for="calories">Calorie Limit:</label>
<input type="number" id="calories" name="calories" required>
<label for="allergies">Any Allergies (comma separated):</label>
<input type="text" id="allergies" name="allergies">
<button type="submit">Generate Meal Plan</button>
</form>
<h3>Your Meal Plan</h3>
<div id="mealPlanResult"></div>
</div>
<script>
document.getElementById('mealPlanForm').addEventListener('submit', function(e) {
e.preventDefault();
// Gather form data
var diet = document.getElementById('diet').value;
var calories = document.getElementById('calories').value;
var allergies = document.getElementById('allergies').value;
// Prepare data to send to the backend
var data = { diet, calories, allergies };
// Call the backend API to generate meal plan
fetch('/generate-meal-plan', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(data)
})
.then(response => response.json())
.then(result => {
// Display the result in the mealPlanResult div
document.getElementById('mealPlanResult').innerHTML = '<pre>' + JSON.stringify(result, null, 2) + '</pre>';
})
.catch(error => {
console.error('Error:', error);
});
});
</script>
</body>
</html>
from flask import Flask, request, jsonify
import requests
app = Flask(__name__)
# Replace YOUR_API_KEY with your actual API key from the AI service.
API_KEY = 'YOUR_API_KEY'
AI_ENDPOINT = 'https://api.openai.com/v1/completions'
@app.route('/generate-meal-plan', methods=['POST'])
def generate_meal_plan():
# Get data from the POST request
data = request.get_json()
diet = data.get('diet', '')
calories = data.get('calories', '')
allergies = data.get('allergies', '')
# Construct the prompt for the AI
prompt = f"Generate a detailed 3-day meal plan for a {diet} diet with a daily calorie limit of {calories} calories"
if allergies:
prompt += f" while avoiding the following allergens: {allergies}."
else:
prompt += "."
# Prepare the payload for the AI API
payload = {
"model": "text-davinci-003", // Specify the AI model to use, such as GPT-3
"prompt": prompt,
"max_tokens": 500 // Set maximum response length from the AI
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}
# Call the AI API
response = requests.post(AI_ENDPOINT, json=payload, headers=headers)
ai_response = response.json()
# Extract text from the AI response
meal_plan = ai_response.get("choices", [{}])[0].get("text", "").strip()
return jsonify({"meal_plan": meal_plan})
if __name__ == '__main__':
app.run(debug=True)
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