Create app.py

app.py

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+import streamlit as st
+import base64
+from huggingface_hub import InferenceClient
+import os
+
+# Initialize Hugging Face Inference client using token from environment variables
+client = InferenceClient(api_key=os.getenv("HF_API_TOKEN"))
+
+# 1. Function to identify dish from image
+def identify_dish(image_bytes):
+    encoded_image = base64.b64encode(image_bytes).decode("utf-8")
+    dish_name = ""
+
+    for message in client.chat_completion(
+        model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+        messages=[
+            {
+                "role": "You are a food identification expert who identifies dishes from images. Your task is to strictly return the names of the dishes present in the image. Only return the dish names if you have high Confidence Level and without additional explanation or description.",
+                "content": [
+                    {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}" }},
+                    {"type": "text", "text": "Identify the dishes in the image and return only the names of the dishes."},
+                ],
+            }
+        ],
+        max_tokens=70,
+        stream=True,
+    ):
+        if message.choices[0].delta.content:
+            dish_name += message.choices[0].delta.content
+
+    return dish_name.strip()
+
+# 2. Function to get user inputs and calculate daily caloric needs
+def calculate_metrics(age, gender, height_cm, weight_kg, weight_goal, activity_level, time_frame_months):
+    # Calculate BMI
+    bmi = weight_kg / ((height_cm / 100) ** 2)
+
+    # Calculate BMR using Mifflin-St Jeor formula
+    if gender == "male":
+        bmr = 10 * weight_kg + 6.25 * height_cm - 5 * age + 5
+    else:
+        bmr = 10 * weight_kg + 6.25 * height_cm - 5 * age - 161
+
+    # Calculate TDEE (Total Daily Energy Expenditure)
+    activity_multipliers = {
+        "sedentary": 1.2,
+        "light": 1.375,
+        "moderate": 1.55,
+        "active": 1.725,
+        "very active": 1.9
+    }
+    tdee = bmr * activity_multipliers[activity_level]
+
+    # Calculate Ideal Body Weight (IBW) using Hamwi method
+    if gender == "male":
+        ibw = 50 + (0.91 * (height_cm - 152.4))
+    else:
+        ibw = 45.5 + (0.91 * (height_cm - 152.4))
+
+    # Calculate Daily Caloric Needs
+    if weight_goal == "loss":
+        daily_caloric_needs = tdee - 500  # Deficit for weight loss
+    elif weight_goal == "gain":
+        daily_caloric_needs = tdee + 500  # Surplus for weight gain
+    else:
+        daily_caloric_needs = tdee
+
+    # Calculate macronutrient calories
+    protein_calories = daily_caloric_needs * 0.2
+    fat_calories = daily_caloric_needs * 0.25
+    carbohydrate_calories = daily_caloric_needs * 0.55
+
+    return {
+        "BMI": bmi,
+        "BMR": bmr,
+        "TDEE": tdee,
+        "IBW": ibw,
+        "Daily Caloric Needs": daily_caloric_needs,
+        "Protein Calories": protein_calories,
+        "Fat Calories": fat_calories,
+        "Carbohydrate Calories": carbohydrate_calories
+    }
+
+# 3. Function to generate diet plan
+def generate_diet_plan(dish_name, calorie_intake_per_day, goal):
+    user_input = f"""
+    You are a certified Dietitian with 20 years of experience. Based on the following input, create an Indian diet plan that fits within the calculated calorie intake and assesses if the given dish is suitable for the user's goal.
+
+    Input:
+    - Dish Name: {dish_name}
+    - Caloric Intake per Day: {calorie_intake_per_day} calories
+    - Goal: {goal}
+
+    """
+    # Request from the dietitian model
+    response = client.chat_completion(
+        model="meta-llama/Meta-Llama-3-8B-Instruct",
+        messages=[{"role": "You are a certified Dietitian with 20 years of Experience", "content": user_input}],
+        max_tokens=500
+    )
+
+    return response.choices[0].message.content
+
+# Streamlit Sidebar for user input
+st.sidebar.title("User Input")
+image_file = st.sidebar.file_uploader("Upload an image of the dish", type=["jpeg", "png"])
+age = st.sidebar.number_input("Enter your age", min_value=1)
+gender = st.sidebar.selectbox("Select your gender", ["male", "female"])
+height_cm = st.sidebar.number_input("Enter your height (cm)", min_value=1.0)
+weight_kg = st.sidebar.number_input("Enter your weight (kg)", min_value=1.0)
+weight_goal = st.sidebar.selectbox("Weight goal", ["loss", "gain", "maintain"])
+activity_level = st.sidebar.selectbox("Activity level", ["sedentary", "light", "moderate", "active", "very active"])
+time_frame = st.sidebar.number_input("Time frame to achieve goal (months)", min_value=1)
+
+# Process the image and calculate metrics
+if image_file:
+    st.write("### Results")
+    image_bytes = image_file.read()
+    
+    # Step 1: Identify the dish
+    dish_name = identify_dish(image_bytes)
+    st.success(f"Identified Dish: {dish_name}")
+    
+    # Step 2: Perform Calculations
+    metrics = calculate_metrics(age, gender, height_cm, weight_kg, weight_goal, activity_level, time_frame)
+    st.write(f"**Your BMI:** {metrics['BMI']:.2f}")
+    st.write(f"**Your BMR:** {metrics['BMR']:.2f} calories")
+    st.write(f"**Your TDEE:** {metrics['TDEE']:.2f} calories")
+    st.write(f"**Ideal Body Weight (IBW):** {metrics['IBW']:.2f} kg")
+    st.write(f"**Daily Caloric Needs:** {metrics['Daily Caloric Needs']:.2f} calories")
+    
+    # Step 3: Generate diet plan
+    diet_plan = generate_diet_plan(dish_name, metrics["Daily Caloric Needs"], weight_goal)
+    st.write(f"### Diet Plan\n {diet_plan}")
+
+# CSS for styling
+st.markdown("""
+    <style>
+    .stButton button { background-color: #4CAF50; color: white; }
+    .stContainer { border: 1px solid #ddd; padding: 20px; margin-bottom: 20px; }
+    </style>
+""", unsafe_allow_html=True)