Initial commit with app and dependencies

app.py

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+import os
+import streamlit as st
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+from sentence_transformers import SentenceTransformer, util
+import torch
+
+# Prevent parallelism warnings
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+# Load the models and tokenizer using Streamlit's updated caching method
+@st.cache_resource
+def load_models():
+    generation_model = T5ForConditionalGeneration.from_pretrained('t5-small')
+    generation_tokenizer = T5Tokenizer.from_pretrained('t5-small')
+    sentence_model = SentenceTransformer('all-MiniLM-L6-v2')
+    return generation_model, generation_tokenizer, sentence_model
+
+generation_model, generation_tokenizer, sentence_model = load_models()
+
+# Predefined meals with calorie information
+# Updated predefined meals with higher calorie options
+meals = {
+    "Breakfast": [
+        {"meal": "Oatmeal with fruits", "calories": 250},
+        {"meal": "Scrambled eggs with toast", "calories": 350},
+        {"meal": "Protein Smoothie", "calories": 300},
+        {"meal": "Avocado toast with poached egg", "calories": 320},
+        {"meal": "Greek yogurt with granola and berries", "calories": 280},
+        {"meal": "Pancakes with honey", "calories": 400},
+        {"meal": "Veggie omelette", "calories": 300},
+        {"meal": "Cereal with milk", "calories": 400}
+    ],
+    "Lunch": [
+        {"meal": "Grilled chicken salad", "calories": 400},
+        {"meal": "Vegetable stir-fry with tofu", "calories": 350},
+        {"meal": "Chicken wrap", "calories": 500},
+        {"meal": "Turkey sandwich on whole grain bread", "calories": 450},
+        {"meal": "Quinoa salad with mixed greens", "calories": 375},
+        {"meal": "Fish tacos", "calories": 480},
+        {"meal": "Lentil soup with a side salad", "calories": 420},  
+        {"meal": "Pasta Alfredo with garlic bread", "calories": 1100},  # High-calorie option
+        {"meal": "Buffalo wings with ranch dressing", "calories": 950}  # High-calorie option
+    ],
+    "Dinner": [
+        {"meal": "Salmon with steamed vegetables", "calories": 600},
+        {"meal": "Pasta with tomato sauce", "calories": 500},
+        {"meal": "Vegetarian chili", "calories": 450},
+        {"meal": "Beef stir-fry with bell peppers", "calories": 550},
+        {"meal": "Chicken curry with brown rice", "calories": 650},
+        {"meal": "Grilled shrimp with quinoa", "calories": 580},
+        {"meal": "Stuffed bell peppers with ground turkey", "calories": 525},
+        {"meal": "Ribeye steak with mashed potatoes", "calories": 1300},  # High-calorie option
+        {"meal": "BBQ pork ribs with cornbread", "calories": 1400},  # High-calorie option
+        {"meal": "Seafood platter with garlic butter", "calories": 1250}  # High-calorie option
+    ],
+    "Snacks": [
+        {"meal": "Apple with peanut butter", "calories": 200},
+        {"meal": "Greek yogurt with honey", "calories": 150},
+        {"meal": "Granola bar", "calories": 250},
+        {"meal": "Handful of almonds", "calories": 180},
+        {"meal": "Hummus with carrot sticks", "calories": 100},
+        {"meal": "Cheese and crackers", "calories": 200},
+        {"meal": "Protein shake", "calories": 220}
+    ]
+}
+
+
+# Function to suggest meals based on the target calorie goal
+def suggest_meals(target_calories):
+    suggestions = {}
+    total_calories = 0
+    remaining_calories = target_calories
+
+    # Prioritize essential meals
+    essential_meal_categories = ["Breakfast", "Lunch", "Dinner"]
+    snack_category = "Snacks"
+
+    for category in essential_meal_categories:
+        # Sort meals by calories in descending order to prioritize higher calorie meals
+        available_meals = sorted(meals[category], key=lambda x: -x["calories"])
+        selected_meal = None
+
+        for meal in available_meals:
+            if meal["calories"] <= remaining_calories:
+                selected_meal = meal
+                break
+
+        if selected_meal:
+            suggestions[category] = f"{selected_meal['meal']} containing {selected_meal['calories']} calories"
+            total_calories += selected_meal["calories"]
+            remaining_calories -= selected_meal["calories"]
+
+    # Add multiple snacks to use up the remaining calories efficiently
+    available_snacks = sorted(meals[snack_category], key=lambda x: -x["calories"])
+    snack_descriptions = []
+
+    for snack in available_snacks:
+        if snack["calories"] <= remaining_calories:
+            snack_descriptions.append(f"{snack['meal']} containing {snack['calories']} calories")
+            total_calories += snack["calories"]
+            remaining_calories -= snack["calories"]
+
+            if remaining_calories < 100:  # Stop adding snacks if the remaining calories are too low
+                break
+
+    return suggestions, snack_descriptions, total_calories
+
+# Streamlit interface
+st.title("Calorie-Based Meal Plan Bot")
+st.write("Enter your daily calorie goal, and I will suggest a balanced meal plan for the day. Minimum calorie goal is 800 kcal for a sustainable diet.")
+
+# Ensure the user inputs a calorie target without a default value
+target_calories = st.number_input("Enter your daily calorie target (in kcal):", min_value=800, max_value=4500, value=None)
+
+if target_calories:
+    suggested_meals, snack_descriptions, total_calories = suggest_meals(target_calories)
+    
+    st.subheader("Suggested Meals:")
+    for category, meal_description in suggested_meals.items():
+        st.write(f"{category}: {meal_description}")
+    
+    
+    if(len(snack_descriptions) == 0):
+        st.write("Snacks: Sorry. No snacks for you 🙁")
+    else:
+        st.write("Snacks:")
+        for snack in snack_descriptions:
+            st.write(f"- {snack}")
+    
+    st.write(f"Total Calories: {total_calories} calories")
+    
+    if total_calories < target_calories:
+        st.write("You can add more snacks or meals to meet your target!")
+    elif total_calories > target_calories:
+        st.write("Consider reducing meal portions to stay within your target!")

requirements.txt

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+streamlit
+transformers
+torch
+sentence-transformers