Update app.py

app.py

@@ -26,60 +26,54 @@ ALLOWED_FILE_TYPES = ['png', 'jpg', 'jpeg']
 # ======================
 
 def initialize_api_client():
-    """Initialize Groq API client"""
+    """Initialize Groq API client with environment variables"""
     load_dotenv()
     api_key = os.getenv("GROQ_API_KEY")
     if not api_key:
-        st.error("API key not found. Please verify .env configuration.")
+        st.error("API key not found. Please check the .env configuration.")
         st.stop()
     return Groq(api_key=api_key)
 
-
 def encode_image(image_path):
-    """Encode an image to base64"""
+    """Convert image file to base64"""
     try:
         with open(image_path, "rb") as img_file:
             return base64.b64encode(img_file.read()).decode("utf-8")
     except FileNotFoundError:
         return ""
 
-
 def process_image(uploaded_file):
-    """Convert image to base64 string"""
+    """Convert uploaded image file to base64 string"""
     try:
         image = Image.open(uploaded_file)
         buffer = io.BytesIO()
         image.save(buffer, format=image.format)
         return base64.b64encode(buffer.getvalue()).decode('utf-8'), image.format
     except Exception as e:
-        st.error(f"Image processing error: {e}")
+        st.error(f"Error processing image: {e}")
         return None, None
 
-
 def generate_pdf(report_text, logo_b64):
-    """Generate a PDF report with logo"""
+    """Generate PDF report with nutrition analysis and logo"""
     buffer = io.BytesIO()
     doc = SimpleDocTemplate(buffer, pagesize=letter)
     styles = getSampleStyleSheet()
     
-    # Decode the base64 logo image
+    # Decode logo image from base64 and resize
     logo_data = base64.b64decode(logo_b64)
     logo_image = Image.open(io.BytesIO(logo_data))
-    
-    # Resize the logo to fit the page width (you can adjust size if necessary)
     logo_width, logo_height = logo_image.size
     logo_aspect = logo_height / logo_width
     max_logo_width = 150  # Adjust as needed
     logo_width = min(logo_width, max_logo_width)
     logo_height = int(logo_width * logo_aspect)
     
-    # Create a ReportLab Image element to add the logo to the PDF
     logo = ReportLabImage(io.BytesIO(logo_data), width=logo_width, height=logo_height)
     
-    # Build the PDF content
+    # Build PDF content
     story = [
-        logo,  # Add the logo at the top of the page
-        Spacer(1, 12),  # Space after the logo
+        logo,
+        Spacer(1, 12),
         Paragraph("<b>Nutrition Analysis Report</b>", styles['Title']),
         Spacer(1, 12),
         Paragraph(report_text.replace('\n', '<br/>'), styles['BodyText'])
@@ -89,9 +83,8 @@ def generate_pdf(report_text, logo_b64):
     buffer.seek(0)
     return buffer
 
-
 def generate_analysis(uploaded_file, client):
-    """Generate AI-powered food analysis"""
+    """Generate nutrition analysis using AI (Groq API)"""
     base64_image, img_format = process_image(uploaded_file)
     if not base64_image:
         return None
@@ -101,33 +94,24 @@ def generate_analysis(uploaded_file, client):
     try:
         response = client.chat.completions.create(
             model="llama-3.2-11b-vision-preview",
-            messages=[
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": """
-                        You are an expert nutritionist with advanced image analysis capabilities.  
-                        Your task is to analyze the provided image, identify all visible food items, and estimate their calorie content as accurately as possible.  
-
-                        **Instructions:**  
-                        - List each identified food item separately.  
-                        - Use known nutritional data to provide accurate calorie estimates.  
-                        - Consider portion size, cooking method, and density of food.  
-                        - Clearly specify if an item's calorie count is an estimate due to ambiguity.  
-                        - Provide the total estimated calorie count for the entire meal.  
-
-                        **Output Format:**  
-                        - Food Item 1: [Name] – Estimated Calories: [value] kcal  
-                        - Food Item 2: [Name] – Estimated Calories: [value] kcal  
-                        - ...  
-                        - **Total Estimated Calories:** [value] kcal  
-
-                        If the image is unclear or lacks enough details, state the limitations and provide a confidence percentage for the estimation.
-                        """},
-                        {"type": "image_url", "image_url": {"url": image_url}}
-                    ]
-                }
-            ],
+            messages=[{
+                "type": "text",
+                "text": """
+                    You are an expert nutritionist with advanced image analysis capabilities.  
+                    Your task is to analyze the provided image, identify all visible food items, and estimate their calorie content with high accuracy.  
+                    **Instructions:**  
+                    - Identify and list each food item visible in the image.  
+                    - For each item, estimate the calorie content based on standard nutritional data, considering portion size, cooking method, and food density.  
+                    - Clearly mark any calorie estimate as "approximate" if based on assumptions due to unclear details.  
+                    - Calculate and provide the total estimated calories for the entire meal.  
+                    **Output Format:**  
+                    - Food Item 1: [Name] – Estimated Calories: [value] kcal  
+                    - Food Item 2: [Name] – Estimated Calories: [value] kcal  
+                    - ...  
+                    - **Total Estimated Calories:** [value] kcal  
+                    If the image lacks sufficient detail or is unclear, specify the limitations and include your confidence level in the estimate as a percentage.
+                """
+            }],
             temperature=0.2,
             max_tokens=400,
             top_p=0.5
@@ -142,10 +126,10 @@ def generate_analysis(uploaded_file, client):
 # ======================
 
 def display_main_interface():
-    """Render primary application interface"""
+    """Render the primary user interface"""
     logo_b64 = encode_image("src/logo.png")
     
-    # HTML with inline styles to change text colors
+    # Display logo and title
     st.markdown(f"""
         <div style="text-align: center;">
             <img src="data:image/png;base64,{logo_b64}" width="100">
@@ -156,16 +140,16 @@ def display_main_interface():
     
     st.markdown("---")
     
+    # Display analysis results if available
     if st.session_state.get('analysis_result'):
-        # Create two columns: one for download and one for clear button
         col1, col2 = st.columns([1, 1])
         
-        # Left column for the Download button
+        # Column for download button
         with col1:
             pdf_report = generate_pdf(st.session_state.analysis_result, logo_b64)
             st.download_button("📄 Download Nutrition Report", data=pdf_report, file_name="nutrition_report.pdf", mime="application/pdf")
         
-        # Right column for the Clear button
+        # Column for clear button
         with col2:
             if st.button("Clear Analysis 🗑️"):
                 st.session_state.pop('analysis_result')
@@ -175,9 +159,8 @@ def display_main_interface():
         st.markdown("### 🎯 Nutrition Analysis Report")
         st.info(st.session_state.analysis_result)
 
-
 def render_sidebar(client):
-    """Create sidebar UI elements"""
+    """Render the sidebar with image upload and analysis functionality"""
     with st.sidebar:
         st.subheader("Image Upload")
         uploaded_file = st.file_uploader("Upload Food Image", type=ALLOWED_FILE_TYPES)
@@ -195,7 +178,7 @@ def render_sidebar(client):
 # ======================
 
 def main():
-    """Primary application controller"""
+    """Main application controller"""
     client = initialize_api_client()
     display_main_interface()
     render_sidebar(client)