Update app.py

app.py

@@ -3,48 +3,35 @@ import base64
 from huggingface_hub import InferenceClient
 import os
 
-# Initialize Hugging Face Inference client using tokens from environment variables
+# Initialize Hugging Face Inference client using token from environment variables
 client = InferenceClient(api_key=os.getenv("HF_API_TOKEN_DISH"))
 client1 = InferenceClient(api_key=os.getenv("HF_API_TOKEN_DIET"))
 
 # 1. Function to identify dish from image
 def identify_dish(image_bytes):
-    try:
-        # Attempt to encode the image to check for format issues
-        encoded_image = base64.b64encode(image_bytes).decode("utf-8")
-    except Exception:
-        st.error("Invalid image format. Please upload a valid JPEG, PNG, or GIF image.")
-        return None  # Early exit if image encoding fails
-
+  try 
+    encoded_image = base64.b64encode(image_bytes).decode("utf-8")
     dish_name = ""
-    try:
-        for message in client.chat_completion(
-            model="meta-llama/Llama-3.2-11B-Vision-Instruct",
-            messages=[
-                {
-                    "role": "You are a highly specialized food identification AI with extensive knowledge of global cuisines. "
-                            "Your sole task is to accurately identify dishes from images. Adhere strictly to these guidelines:\n"
-                            "1. Analyze the image thoroughly, focusing on ingredients, presentation, and cultural context.\n"
-                            "2. Provide ONLY the name of the main dish or dishes visible. Do not list individual ingredients or components.\n"
-                            "3. Use the most specific and widely recognized name for the dish.\n"
-                            "4. If multiple distinct dishes are present, list them separated by commas.\n"
-                            "5. If you cannot identify a dish with high confidence (>75%), respond with 'Unidentified dish'.\n"
-                            "6. Do not provide any explanations, descriptions, or additional commentary.\n"
-                            "7. Respond in a concise, list-like format.",
-                    "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
-    except Exception:
-        st.error("Error identifying the dish. Please try uploading a different image.")
-        return None  # Early exit if the API call fails
+  except Exception:
+        st.error("Invalid image format. Please upload a valid JPEG, PNG, or GIF image.")
+        return None
+
+    for message in client.chat_completion(
+        model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+        messages=[
+            {
+                "role": "You are a highly specialized food identification AI with extensive knowledge of global cuisines. Your sole task is to accurately identify dishes from images. Adhere strictly to these guidelines:\n1. Analyze the image thoroughly, focusing on ingredients, presentation, and cultural context.\n2. Provide ONLY the name of the main dish or dishes visible. Do not list individual ingredients or components.\n3. Use the most specific and widely recognized name for the dish.\n4. If multiple distinct dishes are present, list them separated by commas.\n5. If you cannot identify a dish with high confidence (>90%), respond with 'Unidentified dish'.\n6. Do not provide any explanations, descriptions, or additional commentary.\n7. Respond in a concise, list-like format.\nYour response should contain nothing but the dish name(s) or 'Unidentified dish'.",
+                "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()
 
@@ -105,7 +92,7 @@ def generate_diet_plan(dish_name, calorie_intake_per_day, goal):
 
     Provide the response in the following format:
     1. Dish assessment (e.g., "The dish {dish_name} is suitable for your goal" or "The dish {dish_name} is not suitable for your goal, as it is too high in calories for weight goal").
-    2. Suggest an Indian diet plan that stays near to the {calorie_intake_per_day}. For each meal (morning, lunch, evening), list the dish name, calorie count, and ingredients required to make it.
+    2. Suggest an Indian diet plan that stays near to the {calorie_intake_per_day}. For each meal (morning, lunch, evening), list the dish name, calorie count, and ingredients required to make it.And Make it with in 700 Tokens.
     """
     response = client1.chat_completion(
         model="meta-llama/Meta-Llama-3-8B-Instruct",
@@ -121,6 +108,7 @@ st.title("AI Diet Planner")
 # Sidebar navigation to switch between the app and the user guide
 menu = st.sidebar.selectbox("Menu", ["App", "User Guide"])
 
+# If the user selects the app, show the existing app
 if menu == "App":
     # Sidebar for user input
     st.sidebar.title("User Input")
@@ -133,22 +121,48 @@ if menu == "App":
     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)
 
-    if st.sidebar.button("Submit"):
+    # Submit button
+    submit = st.sidebar.button("Submit")
+
+    # Process the image and calculate metrics upon submission
+    if submit:
         if image_file:
             st.write("### Results")
             image_bytes = image_file.read()
 
+            # Step 1: Identify the dish
             dish_name = identify_dish(image_bytes)
-            if dish_name:
-                st.write(f"**Dish Name Identified:** {dish_name}")
-                metrics = calculate_metrics(age, gender, height_cm, weight_kg, weight_goal, activity_level, time_frame)
-                st.write("**Metrics Calculated:**", metrics)
-                diet_plan = generate_diet_plan(dish_name, metrics["Daily Caloric Needs"], weight_goal)
-                st.write("**Diet Plan:**", diet_plan)
+            st.markdown("<hr>", unsafe_allow_html=True)
+            st.write("#### Dish Name Identified:")
+            st.markdown(f"<div style='background-color: #d4edda; color: #155724; padding: 10px; border-radius: 10px;'>{dish_name}</div>", unsafe_allow_html=True)
+
+            # Step 2: Perform Calculations
+            metrics = calculate_metrics(age, gender, height_cm, weight_kg, weight_goal, activity_level, time_frame)
+            st.markdown("<hr>", unsafe_allow_html=True)
+            st.write("#### Metrics Calculated:")
+            st.markdown(f"""
+                <div style='background-color: #f8d7da; color: #721c24; padding: 10px; border-radius: 10px;'>
+                    <p><b>Your BMI:</b> {metrics['BMI']:.2f}</p>
+                    <p><b>Your BMR(Basal metabolic rate):</b> {metrics['BMR']:.2f} calories</p>
+                    <p><b>Your TDEE(Total Daily Energy Expenditure):</b> {metrics['TDEE']:.2f} calories</p>
+                    <p><b>Ideal Body Weight (IBW):</b> {metrics['IBW']:.2f} kg</p>
+                    <p><b>Daily Caloric Needs:</b> {metrics['Daily Caloric Needs']:.2f} calories</p>
+                </div>
+            """, unsafe_allow_html=True)
+
+            # Step 3: Generate diet plan
+            diet_plan = generate_diet_plan(dish_name, metrics["Daily Caloric Needs"], weight_goal)
+            st.markdown("<hr>", unsafe_allow_html=True)
+            st.write("#### Diet Plan Based on Dish & Goal:")
+            st.markdown(f"<div style='background-color: #d1ecf1; color: #0c5460; padding: 10px; border-radius: 10px;'>{diet_plan}</div>", unsafe_allow_html=True)
+
         else:
-            st.error("Please upload a valid image.")
+            st.error("Please upload a valid image in JPEG, PNG, JPG, or GIF format.")
+
+# If the user selects the User Guide, show a detailed guide about the app
 elif menu == "User Guide":
     st.write("## AI Diet Planner User Guide")
+    
     st.markdown("""
     Welcome to the **AI Diet Planner**! This tool helps you calculate various fitness metrics and suggests personalized diet plans.