Altered app.py

app.py

@@ -1,726 +1,202 @@
-# import requests
-# import google.generativeai as genai
-# import streamlit as st
-
-# # Configure Gemini API (Use your actual API key)
-# genai.configure(api_key='AIzaSyD5yLv8zkGNC7YbxxODLqlMJJKTv8VWdQw')
-
-# # Function to get data from OpenFoodFacts API
-# def get_data(product_name):
-#     url = "https://world.openfoodfacts.org/cgi/search.pl"
-#     params = {
-#         'search_terms': product_name,
-#         'search_simple': 1,
-#         'json': 1,
-#     }
-#     response = requests.get(url, params=params)
-#     data = response.json()
-#     if 'products' not in data or len(data['products']) == 0:
-#         return []  # Return empty if no products found
-
-#     # Filter products with names and return top 5
-#     data['products'] = [p for p in data['products'] if 'product_name' in p]
-#     return data['products'][:5]
-
-# # Function to generate product analysis using Gemini
-# def generate_summary(product, tone):
-#     name = product.get('product_name', 'Not mentioned')
-#     brand = product.get('brands', 'Not mentioned')
-#     nutriscore_grade = product.get('nutriscore_grade', 'Not mentioned')
-#     eco_score = product.get('ecoscore_grade', 'Not mentioned')
-#     packaging = product.get('packaging', 'Not mentioned')
-#     ingredients = product.get('ingredients_text', 'Not mentioned')
-#     nutrients = product.get('nutriments', 'Not mentioned')
-#     nova = product.get('nova_groups_tags', 'Not mentioned')
-
-#     # Generate prompt based on tone
-#     prompt = f"""
-#     You are an AI assistant analyzing consumer products. Here are the details:
-#     - Name: {name}
-#     - Brand: {brand}
-#     - EcoScore: {eco_score}
-#     - NutriScore: {nutriscore_grade}
-#     - NovaScore: {nova}
-#     - Ingredients: {ingredients}
-#     - Nutrients: {nutrients}
-#     - Packaging: {packaging}
-
-#     Please provide a {tone} analysis including:
-#     1. Positive aspects of the product.
-#     2. Negative aspects of the product.
-#     3. Health impact.
-#     4. Environmental impact.
-#     """
-
-#     model = genai.GenerativeModel(model_name="gemini-1.5-flash")
-#     response = model.generate_content(prompt)
-#     return response.text
-
-# # Streamlit interface
-# def main():
-#     st.title("ConsumeNice")
-#     st.write("Get product details and summaries using OpenFoodFacts and Gemini AI.")
-
-#     product_input = st.text_input("Product Name", placeholder="Enter the product name...")
-#     tone = st.radio("Summary Tone", options=["simple", "deeper"], index=0)
-
-#     if st.button("Search"):
-#         products = get_data(product_input)
-#         if not products:
-#             st.error("No products found for the given name.")
-#         else:
-#             product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
-#             selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
-
-#             # Find the selected product details
-#             selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
-
-#             # Display selected product name
-#             st.write(f"### Selected Product: {selected_product['product_name']} (Brand: {selected_product.get('brands', 'Unknown')})")
-
-#             if selected_product:
-#                 # Use session state to retain summary across selections
-#                 if 'summary' not in st.session_state:
-#                     st.session_state.summary = None
-
-#                 summary = generate_summary(selected_product, tone)
-#                 st.session_state.summary = summary
-
-#                 st.write(f"### Summary:")
-#                 st.write(st.session_state.summary)
-
-# if __name__ == "__main__":
-#     main()
-
-# import requests
-# import google.generativeai as genai
-# import streamlit as st
-
-# # Configure Gemini API (Use your actual API key)
-# genai.configure(api_key='AIzaSyD5yLv8zkGNC7YbxxODLqlMJJKTv8VWdQw')
-
-# # Function to get data from OpenFoodFacts API
-# def get_data(product_name):
-#     url = "https://world.openfoodfacts.org/cgi/search.pl"
-#     params = {
-#         'search_terms': product_name,
-#         'search_simple': 1,
-#         'json': 1,
-#     }
-#     response = requests.get(url, params=params)
-#     data = response.json()
-#     if 'products' not in data or len(data['products']) == 0:
-#         return []  # Return empty if no products found
-
-#     # Filter products with names and return top 5
-#     data['products'] = [p for p in data['products'] if 'product_name' in p]
-#     return data['products'][:5]
-
-# # Function to generate product analysis using Gemini
-# def generate_summary(product, tone):
-#     name = product.get('product_name', 'Not mentioned')
-#     brand = product.get('brands', 'Not mentioned')
-#     nutriscore_grade = product.get('nutriscore_grade', 'Not mentioned')
-#     eco_score = product.get('ecoscore_grade', 'Not mentioned')
-#     packaging = product.get('packaging', 'Not mentioned')
-#     ingredients = product.get('ingredients_text', 'Not mentioned')
-#     nutrients = product.get('nutriments', 'Not mentioned')
-#     nova = product.get('nova_groups_tags', 'Not mentioned')
-
-#     # Generate prompt based on tone
-#     prompt = f"""
-#     You are an AI assistant analyzing consumer products. Here are the details:
-#     - Name: {name}
-#     - Brand: {brand}
-#     - EcoScore: {eco_score}
-#     - NutriScore: {nutriscore_grade}
-#     - NovaScore: {nova}
-#     - Ingredients: {ingredients}
-#     - Nutrients: {nutrients}
-#     - Packaging: {packaging}
-
-#     Please provide a {tone} analysis including:
-#     1. Positive aspects of the product.
-#     2. Negative aspects of the product.
-#     3. Health impact.
-#     4. Environmental impact.
-#     """
-
-#     model = genai.GenerativeModel(model_name="gemini-1.5-flash")
-#     response = model.generate_content(prompt)
-#     return response.text
-
-# # Streamlit interface
-# def main():
-#     # Page setup and header
-#     st.set_page_config(page_title="ConsumeNice", page_icon="🍽️", layout="centered")
-#     st.title("🍽️ ConsumeNice - Product Analysis with AI")
-#     st.write("Welcome to **ConsumeNice**, Know What You Eat")
-
-#     st.sidebar.title("Developed by:")
-#     st.sidebar.markdown("**Srish**")
-#     st.sidebar.markdown("[LinkedIn](https://www.linkedin.com/in/srishrachamalla/)")
-#     st.sidebar.markdown("**Sai Teja**")
-#     st.sidebar.markdown("[LinkedIn](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
-    
-#     st.sidebar.title("Additional Info")
-#     st.sidebar.markdown("This app allows you to search for a product and get an AI-generated analysis.")
-
-#     # Input fields
-#     product_input = st.text_input("Enter Product Name", placeholder="Type product name to search...")
-#     tone = st.radio("Select Summary Tone", options=["Simple", "Deeper"], index=0)
-
-#     if st.button("Search"):
-#         with st.spinner("Fetching product data..."):
-#             products = get_data(product_input)
-#         if not products:
-#             st.error("No products found for the given name.")
-#         else:
-#             product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
-#             selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
-
-#             # Find the selected product details
-#             selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
-
-#             # Display selected product name
-#             st.write(f"### Selected Product: **{selected_product['product_name']}** (Brand: {selected_product.get('brands', 'Unknown')})")
-
-#             if selected_product:
-#                 # Use session state to retain summary across selections
-#                 if 'summary' not in st.session_state:
-#                     st.session_state.summary = None
-
-#                 with st.spinner("Generating AI analysis..."):
-#                     summary = generate_summary(selected_product, tone)
-#                 st.session_state.summary = summary
-
-#                 # Display summary
-#                 st.write("### Summary:")
-#                 st.success(st.session_state.summary)
-
-#     # Footer section
-#     st.markdown("---")
-#     st.write("### About the Hackathon Project")
-#     st.info("This project was developed as part of a hackathon challenge to showcase AI Skills. Built using OpenFoodFacts and Google's Gemini.")
-
-# if __name__ == "__main__":
-#     main()
-
-# import requests
-# import google.generativeai as genai
-# import streamlit as st
-# from PIL import Image
-
-# # Configure Gemini API (Use your actual API key)
-# genai.configure(api_key='AIzaSyD5yLv8zkGNC7YbxxODLqlMJJKTv8VWdQw')
-
-# # Function to get data from OpenFoodFacts API
-# def get_data(product_name):
-#     url = "https://world.openfoodfacts.org/cgi/search.pl"
-#     params = {
-#         'search_terms': product_name,
-#         'search_simple': 1,
-#         'json': 1,
-#     }
-#     response = requests.get(url, params=params)
-#     data = response.json()
-#     if 'products' not in data or len(data['products']) == 0:
-#         return []  # Return empty if no products found
-
-#     # Filter products with names and return top 5
-#     data['products'] = [p for p in data['products'] if 'product_name' in p]
-#     return data['products'][:5]
-
-# # Function to generate product analysis using Gemini
-# def generate_summary(product, tone):
-#     name = product.get('product_name', 'Not mentioned')
-#     brand = product.get('brands', 'Not mentioned')
-#     nutriscore_grade = product.get('nutriscore_grade', 'Not mentioned')
-#     eco_score = product.get('ecoscore_grade', 'Not mentioned')
-#     packaging = product.get('packaging', 'Not mentioned')
-#     ingredients = product.get('ingredients_text', 'Not mentioned')
-#     nutrients = product.get('nutriments', 'Not mentioned')
-#     nova = product.get('nova_groups_tags', 'Not mentioned')
-
-#     # Generate prompt based on tone
-#     prompt = f"""
-#     You are an AI assistant analyzing consumer products. Here are the details:
-#     - Name: {name}
-#     - Brand: {brand}
-#     - EcoScore: {eco_score}
-#     - NutriScore: {nutriscore_grade}
-#     - NovaScore: {nova}
-#     - Ingredients: {ingredients}
-#     - Nutrients: {nutrients}
-#     - Packaging: {packaging}
-
-#     Please provide a {tone} analysis including:
-#     1. Positive aspects of the product.
-#     2. Negative aspects of the product.
-#     3. Health impact.
-#     4. Environmental impact.
-#     """
-
-#     model = genai.GenerativeModel(model_name="gemini-1.5-flash")
-#     response = model.generate_content(prompt)
-#     return response.text
-
-# # Streamlit interface
-# def main():
-#     # Page setup and header with background image
-#     st.set_page_config(page_title="ConsumeNice", page_icon="🍽️", layout="centered")
-
-#     # Custom CSS for better aesthetics
-#     # st.markdown(
-#     #     """
-#     #     <style>
-#     #     .main {background-color: #f0f2f6;}
-#     #     .reportview-container .main .block-container {
-#     #         padding-top: 2rem;
-#     #         padding-right: 3rem;
-#     #         padding-left: 3rem;
-#     #     }
-#     #     .css-1d391kg {color: #ff4b4b !important;}
-#     #     .css-145kmo2 {color: #00b4d8 !important;}
-#     #     h1 {color: #1f3b4d !important;}
-#     #     .stButton>button {background-color: #f63366; color: white;}
-#     #     .stTextInput>div>input {padding: 12px; border-radius: 6px; border: 1px solid #00b4d8;}
-#     #     .stRadio>div>label {color: #1f3b4d !important;}
-#     #     </style>
-#     #     """, 
-#     #     unsafe_allow_html=True
-#     # )
-#     st.markdown(
-#         """
-#         <style>
-#         .main {background-color: #000000;}
-#         .reportview-container .main .block-container {
-#             padding-top: 2rem;
-#             padding-right: 2.5rem;
-#             padding-left: 2.5rem;
-#         }
-#         h1, h2, h3, h4, h5 {color: #ffffff;}
-#         .stButton>button {
-#             background-color: #6c757d; 
-#             color: white;
-#             border-radius: 8px;
-#         }
-#         .stButton>button:hover {
-#             background-color: #5a6268;
-#         }
-#         .stTextInput>div>input {
-#             padding: 10px; 
-#             border-radius: 6px; 
-#             border: 1px solid #ced4da;
-#             background-color: #f8f9fa;
-#         }
-#         .stRadio>div>label {color: #495057 !important;}
-#         .css-1d391kg {color: #495057 !important;}
-#         .css-145kmo2 {color: #495057 !important;}
-#         </style>
-#         """, 
-#         unsafe_allow_html=True
-#     )
-
-
-#     # App logo (assuming you have an image named 'logo.png' in the same directory)
-#     st.image(Image.open(r'C:\Projects\google hack\test\static\images\logo.png'), width=120, caption="ConsumeNice - Know What You Consume", )
-#     # Custom HTML for displaying the image and caption side by side
-# #     image = Image.open(r'C:\Projects\google hack\test\static\images\logo.png')
-# #     st.markdown(
-# #     f"""
-# #     <div style="display: flex; align-items: center;">
-# #         <img src="data:image/png;base64,{st.image(image, use_column_width=False)}" style="width: 10px;">
-# #         <p style="margin-left: 20px; font-size: 18px;">ConsumeNice - Know What You Consume</p>
-# #     </div>
-# #     """,
-# #     unsafe_allow_html=True
-# # )
-
-#     # st.title("🍽️ ConsumeNice - Analyze Products with AI")
-#     st.markdown(
-#     """
-#     <h1 style='text-align: center; color: #fffff;'>🍽️ ConsumeNice - Analyze Products with AI</h1>
-#     """, 
-#     unsafe_allow_html=True
-# )
-#     st.write("Welcome to **ConsumeNice**, where you can search for products and get an AI-generated analysis based on their nutritional, environmental, and packaging details. Built with OpenFoodFacts and Gemini AI.")
-    
-#     # Sidebar for developer profiles and hackathon info
-#     # st.sidebar.title("Developers - 👨‍💻")
-# #     st.sidebar.markdown(
-# #     """
-# #     <h1 style='color: #0072B2;'>Developers - 👨‍💻</h1>
-# #     """, 
-# #     unsafe_allow_html=True
-# # )
-# #     st.sidebar.markdown("[LinkedIn - Srish](https://www.linkedin.com/in/srish-linkedin-url)")
-    
-# #     st.sidebar.markdown("[LinkedIn - Sai Teja](https://www.linkedin.com/in/sai-teja-linkedin-url)")
-
-# #     # st.sidebar.title("Hackathon Project")
-# #     st.sidebar.markdown(
-# #     """
-# #     <h1 style='color: #0072B2;'>Hackathon Project</h1>
-# #     """, 
-# #     unsafe_allow_html=True
-# # )
-# #     st.sidebar.markdown("This project showcases AI integration to analyze consumer products.")
-#     # Sidebar content with custom formatting
-#     st.sidebar.markdown(
-#         """
-#         <h1 style='color: #0072B2;'>🚀 Hackathon Project</h1>
-#         """, 
-#         unsafe_allow_html=True
-#     )
-
-#     st.sidebar.markdown("Welcome to the **ConsumeNice** project, developed for the hackathon to showcase AI integration in product analysis.")
-
-#     # Add some icons/emojis to make it look more engaging
-#     st.sidebar.markdown("### 🔧 Project Features")
-#     st.sidebar.markdown("- Analyze product details using **OpenFoodFacts** API.")
-#     st.sidebar.markdown("- AI-generated analysis using **Google Gemini AI**.")
-#     st.sidebar.markdown("- Environment, packaging, and health analysis.")
-
-#     # Developer details with LinkedIn links
-#     st.sidebar.markdown("### 👨‍💻 Developers")
-#     st.sidebar.markdown("[**Srish**](https://www.linkedin.com/in/srishrachamalla/) - AI/ML Developer")
-#     st.sidebar.markdown("[**Sai Teja**](https://www.linkedin.com/in/saiteja-pallerla-668734225/) - Data Analyst")
-
-#     # Add expander sections for additional content
-#     with st.sidebar.expander("ℹ️ About ConsumeNice"):
-#         st.write("**ConsumeNice** is designed to give consumers more insights into the products they consume, analyzing factors like health impact, environmental footprint, and packaging.")
-
-#     with st.sidebar.expander("📚 Useful Resources"):
-#         st.write("[Google Gemini AI Documentation](https://developers.google.com/ai)")
-#         st.write("[Streamlit Documentation](https://docs.streamlit.io/)")
-
-#     # Add progress indicator for hackathon phases or development stages
-#     st.sidebar.markdown("### ⏳ Hackathon Progress")
-#     st.sidebar.progress(0.99)  # Set progress level (0 to 1)
-
-#     # Sidebar footer with final notes
-#     st.sidebar.markdown("---")
-#     st.sidebar.markdown(
-#         """
-#         <div style="text-align: center; font-size: 0.85em;">
-#             Developed by Srish & Sai Teja • Powered by Google Gemini AI
-#         </div>
-#         """, unsafe_allow_html=True
-#     )
-
-
-#     # User input fields with improved placeholders and hints
-#     product_input = st.text_input("Enter Product Name", placeholder="e.g., Coca-Cola, Oreo, Dove Soap")
-#     tone = st.radio("Choose Analysis Depth", options=["Simple", "In-depth"], index=0)
-
-#     if st.button("Search"):
-#         with st.spinner("Searching for products..."):
-#             products = get_data(product_input)
-        
-#         if not products:
-#             st.error("No products found for the given name.")
-#         else:
-#             product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
-#             selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
-
-#             selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
-
-#             st.write(f"### Product Selected: **{selected_product['product_name']}** (Brand: {selected_product.get('brands', 'Unknown')})")
-
-#             if selected_product:
-#                 if 'summary' not in st.session_state:
-#                     st.session_state.summary = None
-
-#                 with st.spinner("Generating AI-powered analysis..."):
-#                     summary = generate_summary(selected_product, tone.lower())
-#                 st.session_state.summary = summary
-
-#                 st.write("### Product Analysis Summary:")
-#                 st.success(st.session_state.summary)
-
-#     # Footer with hackathon and design details
-#     st.markdown("---")
-#     st.markdown("""
-#         <div style="text-align: center; font-size: 0.9em;">
-#         <p><i>ConsumeNice</i> was developed for a hackathon using <b>Streamlit</b> to showcase AI integration with real-world data sources like .</p>
-#         <p>Developed by Srish & Sai Teja • Powered by Google Gemini AI</p>
-#         </div>
-#         """, unsafe_allow_html=True)
-
-# if __name__ == "__main__":
-#     main()
-
-import requests
-import google.generativeai as genai
-import streamlit as st
-from PIL import Image
-
-# Configure Gemini API (Use your actual API key)
-genai.configure(api_key='AIzaSyD5yLv8zkGNC7YbxxODLqlMJJKTv8VWdQw')
-
-# Function to get data from OpenFoodFacts API
-def get_data(product_name):
-    url = "https://world.openfoodfacts.org/cgi/search.pl"
-    params = {
-        'search_terms': product_name,
-        'search_simple': 1,
-        'json': 1,
-    }
-    response = requests.get(url, params=params)
-    data = response.json()
-    if 'products' not in data or len(data['products']) == 0:
-        return []  # Return empty if no products found
-
-    # Filter products with names and return top 5
-    data['products'] = [p for p in data['products'] if 'product_name' in p]
-    return data['products'][:5]
-
-# Function to generate product analysis using Gemini
-def generate_summary(product, tone):
-    name = product.get('product_name', 'Not mentioned')
-    brand = product.get('brands', 'Not mentioned')
-    nutriscore_grade = product.get('nutriscore_grade', 'Not mentioned')
-    eco_score = product.get('ecoscore_grade', 'Not mentioned')
-    packaging = product.get('packaging', 'Not mentioned')
-    ingredients = product.get('ingredients_text', 'Not mentioned')
-    nutrients = product.get('nutriments', 'Not mentioned')
-    nova = product.get('nova_groups_tags', 'Not mentioned')
-
-    # Generate prompt based on tone
-    prompt = f"""
-    You are an AI assistant analyzing consumer products. Here are the details:
-    - Name: {name}
-    - Brand: {brand}
-    - EcoScore: {eco_score}
-    - NutriScore: {nutriscore_grade}
-    - NovaScore: {nova}
-    - Ingredients: {ingredients}
-    - Nutrients: {nutrients}
-    - Packaging: {packaging}
-
-    Please provide a {tone} analysis including:
-    1. Positive aspects of the product.
-    2. Negative aspects of the product.
-    3. Health impact.
-    4. Environmental impact.
-    """
-
-    model = genai.GenerativeModel(model_name="gemini-1.5-flash")
-    response = model.generate_content(prompt)
-    return response.text
-
-# Streamlit interface
-def main():
-    # Page setup and header with background image
-    st.set_page_config(page_title="ConsumeNice", page_icon="🍽", layout="centered")
-
-    # Custom CSS for better aesthetics
-    st.markdown(
-        """
-        <style>
-        .main {background-color: #000000;}
-        .reportview-container .main .block-container {
-            padding-top: 2rem;
-            padding-right: 2.5rem;
-            padding-left: 2.5rem;
-        }
-        h1, h2, h3, h4, h5 {color: #ffffff;}
-        .stButton>button {
-            background-color: #6c757d; 
-            color: white;
-            border-radius: 8px;
-        }
-        .stButton>button:hover {
-            background-color: #5a6268;
-        }
-        .stTextInput>div>input {
-            padding: 10px; 
-            border-radius: 6px; 
-            border: 1px solid #ced4da;
-            background-color: #f8f9fa;
-        }
-        .stRadio>div>label {color: #495057 !important;}
-        .css-1d391kg {color: #495057 !important;}
-        .css-145kmo2 {color: #495057 !important;}
-        </style>
-        """, 
-        unsafe_allow_html=True
-    )
-
-    # App logo and header side by side
-    col1, col2 = st.columns([1, 3])  # Adjust proportions as needed
-    with col1:
-        st.image(Image.open(r'C:\Projects\google hack\test\static\images\logo.png'), width=120, caption="ConsumeNice - Know What You Consume")
-    with col2:
-        st.markdown(
-            "<h1 style='text-align: left; color: #ffffff;'>🍽️ ConsumeNice - Analyze Products with AI</h1>", 
-            unsafe_allow_html=True
-        )
-
-    st.write("Welcome to ConsumeNice, where you can search for products and get an AI-generated analysis based on their nutritional, environmental, and packaging details.")
-    
-    # Sidebar for developer profiles and hackathon info
-    st.sidebar.markdown(
-        """
-        <h1 style='color: #0072B2;'>🚀 Hackathon Project</h1>
-        """, 
-        unsafe_allow_html=True
-    )
-    st.sidebar.markdown("Welcome to the ConsumeNice project, developed for the hackathon to showcase AI integration in product analysis.")
-
-    # Add some icons/emojis to make it look more engaging
-    st.sidebar.markdown("### 🔧 Project Features")
-    # st.sidebar.markdown("- Analyze product details using OpenFoodFacts API.")
-    st.sidebar.markdown("- AI-generated analysis using Google Gemini AI.")
-    st.sidebar.markdown("- Environment, packaging, and health analysis.")
-
-    # Developer details with LinkedIn links
-    st.sidebar.markdown("### 👨‍💻 Developers")
-    st.sidebar.markdown("[Srish](https://www.linkedin.com/in/srishrachamalla/) - AI/ML Developer")
-    st.sidebar.markdown("[Sai Teja](https://www.linkedin.com/in/saiteja-pallerla-668734225/) - Data Analyst")
-
-    # Add expander sections for additional content
-    with st.sidebar.expander("ℹ About ConsumeNice"):
-        st.write("ConsumeNice is designed to give consumers more insights into the products they consume, analyzing factors like health impact, environmental footprint, and packaging.")
-
-    with st.sidebar.expander("📚 Useful Resources"):
-        st.write("[Google Gemini AI Documentation](https://ai.google.dev/gemini-api/docs)")
-        st.write("[Streamlit Documentation](https://docs.streamlit.io/)")
-
-    # Add progress indicator for hackathon phases or development stages
-    st.sidebar.markdown("### ⏳ Hackathon Progress")
-    st.sidebar.progress(0.99)  # Set progress level (0 to 1)
-
-    # Sidebar footer with final notes
-    st.sidebar.markdown("---")
-    st.sidebar.markdown(
-        """
-        <div style="text-align: center; font-size: 0.85em;">
-            Developed by Srish & Sai Teja • Powered by Google Gemini AI
-        </div>
-        """, unsafe_allow_html=True
-    )
-
-    # User input fields with improved placeholders and hints
-    product_input = st.text_input("Enter Product Name", placeholder="e.g., Coca-Cola, Oreo, Dove Soap")
-    tone = st.radio("Choose Analysis Depth", options=["Simple", "In-depth"], index=0)
-
-    # if st.button("Search"):
-    #     with st.spinner("Searching for products..."):
-    #         products = get_data(product_input)
-        
-    #     if not products:
-    #         st.error("No products found for the given name.")
-    #     else:
-    #         st.write("### Select a Product")
-            
-    #         # Loop through each product and display a radio button with product image and name
-    #         selected_product_name = None
-    #         for product in products:
-    #             col1, col2 = st.columns([1, 4])  # Adjust column ratios as needed
-
-    #             # Display the product image if available
-    #             with col1:
-    #                 image_url = product.get('image_url', None)
-    #                 if image_url:
-    #                     st.image(image_url, width=60)
-    #                 else:
-    #                     st.text("No Image")
-
-    #             # Display the product name with radio buttons
-    #             with col2:
-    #                 if st.radio("Select", [product['product_name']], key=f"product_{product['product_name']}"):
-    #                     selected_product_name = product['product_name']
-            
-    #         # Once a product is selected, find its details
-    #         if selected_product_name:
-    #             selected_product = next(p for p in products if p['product_name'] == selected_product_name)
-    #             st.write(f"### Product Selected: {selected_product['product_name']} (Brand: {selected_product.get('brands', 'Unknown')})")
-
-    #             if selected_product:
-    #                 if 'summary' not in st.session_state:
-    #                     st.session_state.summary = None
-
-    #                 with st.spinner("Generating AI-powered analysis..."):
-    #                     summary = generate_summary(selected_product, tone.lower())
-    #                 st.session_state.summary = summary
-
-    #                 st.write("### Product Analysis Summary:")
-    #                 st.success(st.session_state.summary)
-
-#     ##ss
-    if st.button("Search"):
-        with st.spinner("Searching for products..."):
-            products = get_data(product_input)
-        
-        if not products:
-            st.error("No products found for the given name.")
-        else:
-            product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
-            selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
-            print(selected_product_name)
-
-            selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
-            print(selected_product)
-
-            st.write(f"### Product Selected: {selected_product['product_name']} (Brand: {selected_product.get('brands', 'Unknown')})")
-
-            if selected_product:
-                if 'summary' not in st.session_state:
-                    st.session_state.summary = None
-
-                with st.spinner("Generating AI-powered analysis..."):
-                    summary = generate_summary(selected_product, tone.lower())
-                st.session_state.summary = summary
-
-                st.write("### Product Analysis Summary:")
-                st.success(st.session_state.summary)
-    # if st.button("Search"):
-    #     with st.spinner("Searching for products..."):
-    #         products = get_data(product_input)
-        
-    #     if not products:
-    #         st.error("No products found for the given name.")
-    #     else:
-    #         # Display the product names in a radio button
-    #         product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
-            
-    #         # Allow user to select a product but wait for confirmation
-    #         selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
-    #         print(selected_product_name)
-    #         # Add a "Select" button for confirmation
-    #         if st.button("Confirm Selection"):
-    #             # Find the selected product from the products list
-    #             selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
-    #             print(selected_product)
-
-    #             # Display selected product details
-    #             st.write(f"### Product Selected: **{selected_product['product_name']}** (Brand: {selected_product.get('brands', 'Unknown')})")
-
-    #             if selected_product:
-    #                 if 'summary' not in st.session_state:
-    #                     st.session_state.summary = None
-
-    #                 with st.spinner("Generating AI-powered analysis..."):
-    #                     summary = generate_summary(selected_product, tone.lower())
-    #                 st.session_state.summary = summary
-
-    #                 st.write("### Product Analysis Summary:")
-    #                 st.success(st.session_state.summary)
-
-
-    # Footer with hackathon and design details
-    st.markdown("---")
-    st.markdown("""
-        <div style="text-align: center; font-size: 0.9em;">
-        <p><i>ConsumeNice</i> was developed for a hackathon using <b>Streamlit</b> to showcase AI integration with real-world data sources.</p>
-        <p>Developed by Srish & Sai Teja • Powered by Google Gemini AI</p>
-        </div>
-        """, unsafe_allow_html=True)
-
-if __name__ == "__main__":
-    main()
-
-
-    
+
+
+import requests
+import google.generativeai as genai
+import streamlit as st
+from PIL import Image
+
+# Configure Gemini API (Use your actual API key)
+genai.configure(api_key='AIzaSyD5yLv8zkGNC7YbxxODLqlMJJKTv8VWdQw')
+
+# Function to get data from OpenFoodFacts API
+def get_data(product_name):
+    url = "https://world.openfoodfacts.org/cgi/search.pl"
+    params = {
+        'search_terms': product_name,
+        'search_simple': 1,
+        'json': 1,
+    }
+    response = requests.get(url, params=params)
+    data = response.json()
+    if 'products' not in data or len(data['products']) == 0:
+        return []  # Return empty if no products found
+
+    # Filter products with names and return top 5
+    data['products'] = [p for p in data['products'] if 'product_name' in p]
+    return data['products'][:5]
+
+# Function to generate product analysis using Gemini
+def generate_summary(product, tone):
+    name = product.get('product_name', 'Not mentioned')
+    brand = product.get('brands', 'Not mentioned')
+    nutriscore_grade = product.get('nutriscore_grade', 'Not mentioned')
+    eco_score = product.get('ecoscore_grade', 'Not mentioned')
+    packaging = product.get('packaging', 'Not mentioned')
+    ingredients = product.get('ingredients_text', 'Not mentioned')
+    nutrients = product.get('nutriments', 'Not mentioned')
+    nova = product.get('nova_groups_tags', 'Not mentioned')
+
+    # Generate prompt based on tone
+    prompt = f"""
+    You are an AI assistant analyzing consumer products. Here are the details:
+    - Name: {name}
+    - Brand: {brand}
+    - EcoScore: {eco_score}
+    - NutriScore: {nutriscore_grade}
+    - NovaScore: {nova}
+    - Ingredients: {ingredients}
+    - Nutrients: {nutrients}
+    - Packaging: {packaging}
+
+    Please provide a {tone} analysis including:
+    1. Positive aspects of the product.
+    2. Negative aspects of the product.
+    3. Health impact.
+    4. Environmental impact.
+    """
+
+    model = genai.GenerativeModel(model_name="gemini-1.5-flash")
+    response = model.generate_content(prompt)
+    return response.text
+
+# Streamlit interface
+def main():
+    # Page setup and header with background image
+    st.set_page_config(page_title="ConsumeNice", page_icon="🍽", layout="centered")
+
+    # Custom CSS for better aesthetics
+    st.markdown(
+        """
+        <style>
+        .main {background-color: #000000;}
+        .reportview-container .main .block-container {
+            padding-top: 2rem;
+            padding-right: 2.5rem;
+            padding-left: 2.5rem;
+        }
+        h1, h2, h3, h4, h5 {color: #ffffff;}
+        .stButton>button {
+            background-color: #6c757d; 
+            color: white;
+            border-radius: 8px;
+        }
+        .stButton>button:hover {
+            background-color: #5a6268;
+        }
+        .stTextInput>div>input {
+            padding: 10px; 
+            border-radius: 6px; 
+            border: 1px solid #ced4da;
+            background-color: #f8f9fa;
+        }
+        .stRadio>div>label {color: #495057 !important;}
+        .css-1d391kg {color: #495057 !important;}
+        .css-145kmo2 {color: #495057 !important;}
+        </style>
+        """, 
+        unsafe_allow_html=True
+    )
+
+    # App logo and header side by side
+    col1, col2 = st.columns([1, 3])  # Adjust proportions as needed
+    with col1:
+        st.image(Image.open(r'C:\Projects\google hack\test\static\images\logo.png'), width=120, caption="ConsumeNice - Know What You Consume")
+    with col2:
+        st.markdown(
+            "<h1 style='text-align: left; color: #ffffff;'>🍽️ ConsumeNice - Analyze Products with AI</h1>", 
+            unsafe_allow_html=True
+        )
+
+    st.write("Welcome to ConsumeNice, where you can search for products and get an AI-generated analysis based on their nutritional, environmental, and packaging details.")
+    
+    # Sidebar for developer profiles and hackathon info
+    st.sidebar.markdown(
+        """
+        <h1 style='color: #0072B2;'>🚀 Hackathon Project</h1>
+        """, 
+        unsafe_allow_html=True
+    )
+    st.sidebar.markdown("Welcome to the ConsumeNice project, developed for the hackathon to showcase AI integration in product analysis.")
+
+    # Add some icons/emojis to make it look more engaging
+    st.sidebar.markdown("### 🔧 Project Features")
+    # st.sidebar.markdown("- Analyze product details using OpenFoodFacts API.")
+    st.sidebar.markdown("- AI-generated analysis using Google Gemini AI.")
+    st.sidebar.markdown("- Environment, packaging, and health analysis.")
+
+    # Developer details with LinkedIn links
+    st.sidebar.markdown("### 👨‍💻 Developers")
+    st.sidebar.markdown("[Srish](https://www.linkedin.com/in/srishrachamalla/) - AI/ML Developer")
+    st.sidebar.markdown("[Sai Teja](https://www.linkedin.com/in/saiteja-pallerla-668734225/) - Data Analyst")
+
+    # Add expander sections for additional content
+    with st.sidebar.expander("ℹ About ConsumeNice"):
+        st.write("ConsumeNice is designed to give consumers more insights into the products they consume, analyzing factors like health impact, environmental footprint, and packaging.")
+
+    with st.sidebar.expander("📚 Useful Resources"):
+        st.write("[Google Gemini AI Documentation](https://ai.google.dev/gemini-api/docs)")
+        st.write("[Streamlit Documentation](https://docs.streamlit.io/)")
+
+    # Add progress indicator for hackathon phases or development stages
+    st.sidebar.markdown("### ⏳ Hackathon Progress")
+    st.sidebar.progress(0.99)  # Set progress level (0 to 1)
+
+    # Sidebar footer with final notes
+    st.sidebar.markdown("---")
+    st.sidebar.markdown(
+        """
+        <div style="text-align: center; font-size: 0.85em;">
+            Developed by Srish & Sai Teja • Powered by Google Gemini AI
+        </div>
+        """, unsafe_allow_html=True
+    )
+
+    # User input fields with improved placeholders and hints
+    product_input = st.text_input("Enter Product Name", placeholder="e.g., Coca-Cola, Oreo, Dove Soap")
+    tone = st.radio("Choose Analysis Depth", options=["Simple", "In-depth"], index=0)
+
+   session_state.summary)
+
+#     ##ss
+    if st.button("Search"):
+        with st.spinner("Searching for products..."):
+            products = get_data(product_input)
+        
+        if not products:
+            st.error("No products found for the given name.")
+        else:
+            product_names = [f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" for p in products]
+            selected_product_name = st.radio("Select a Product", product_names, key='product_selection')
+            print(selected_product_name)
+
+            selected_product = next(p for p in products if f"{p['product_name']} (Brand: {p.get('brands', 'Unknown')})" == selected_product_name)
+            print(selected_product)
+
+            st.write(f"### Product Selected: {selected_product['product_name']} (Brand: {selected_product.get('brands', 'Unknown')})")
+
+            if selected_product:
+                if 'summary' not in st.session_state:
+                    st.session_state.summary = None
+
+                with st.spinner("Generating AI-powered analysis..."):
+                    summary = generate_summary(selected_product, tone.lower())
+                st.session_state.summary = summary
+
+                st.write("### Product Analysis Summary:")
+                st.success(st.session_state.summary)
+    
+
+    # Footer with hackathon and design details
+    st.markdown("---")
+    st.markdown("""
+        <div style="text-align: center; font-size: 0.9em;">
+        <p><i>ConsumeNice</i> was developed for a hackathon using <b>Streamlit</b> to showcase AI integration with real-world data sources.</p>
+        <p>Developed by Srish & Sai Teja • Powered by Google Gemini AI</p>
+        </div>
+        """, unsafe_allow_html=True)
+
+if __name__ == "__main__":
+    main()
+
+
+