Update app.py

app.py

@@ -1,75 +1,38 @@
 import streamlit as st
-import pandas as pd
-import numpy as np
 
-# Streamlit UI for the Amazon PPC Keyword Optimizer
-st.title("Amazon PPC Keyword Optimizer")
-st.write("Suggest optimal keywords for Amazon PPC campaigns based on product details and target audience.")
+# Set the background image using custom CSS
+st.markdown(
+    """
+    <style>
+        body {
+            background-image: url('https://example.com/background-image.jpg');  /* Change the URL to your image URL */
+            background-size: cover;
+            background-position: center;
+            color: white;
+        }
+        .sidebar .sidebar-content {
+            background-color: rgba(255, 255, 255, 0.8);  /* Add transparency for the sidebar */
+            padding: 15px;
+        }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
 
-# Input fields for product details
-st.header("Product Details")
-product_name = st.text_input("Enter product name")
-product_category = st.selectbox("Select product category", ["Electronics", "Clothing", "Home", "Beauty", "Toys"])
-product_features = st.text_area("Enter key product features (e.g., color, size, functionality)")
+# Sidebar content: Beautiful description about nail care
+st.sidebar.title("Health Nail Care")
+st.sidebar.write("""
+    Nail care is essential for maintaining healthy, strong, and beautiful nails. Proper nail care involves regular cleaning, 
+    trimming, and moisturizing. Nails should be protected from harmful chemicals and physical trauma. Eating a balanced diet 
+    rich in vitamins, minerals, and protein is crucial for optimal nail health. Regularly checking for nail infections or 
+    abnormalities can help in early detection and treatment.
+    
+    Here are some tips for healthy nails:
+    - Keep nails clean and trimmed.
+    - Use a moisturizing lotion or oil for your nails.
+    - Avoid biting nails and using them as tools.
+    - Apply a base coat before using nail polish to prevent staining.
+    - Make sure to stay hydrated and eat a balanced diet rich in biotin, zinc, and iron.
+""")
 
-# Input fields for target audience
-st.header("Target Audience")
-audience_gender = st.selectbox("Select audience gender", ["Male", "Female", "Unisex"])
-audience_age = st.slider("Select audience age range", min_value=18, max_value=65, value=(25, 45))
-audience_location = st.text_input("Enter target location (e.g., USA, UK)")
-
-# Input fields for existing product keywords
-st.header("Existing Product Keywords")
-keywords_input = st.text_area("Enter current product keywords (comma-separated)")
-
-# Generate recommended keywords based on input
-def generate_keywords(product_category, product_features, audience_gender, audience_age, audience_location, keywords_input):
-    # Sample logic to generate recommended keywords (can be expanded with a more advanced model)
-    
-    keywords = set(keywords_input.split(","))
-    
-    # Add product-specific features
-    features_keywords = product_features.split(",")
-    for feature in features_keywords:
-        keywords.add(feature.strip())
-    
-    # Add category-related keywords
-    category_keywords = {
-        "Electronics": ["gadgets", "tech", "smartphone", "device", "electronics"],
-        "Clothing": ["fashion", "apparel", "clothing", "t-shirt", "jeans"],
-        "Home": ["home", "furniture", "decor", "household"],
-        "Beauty": ["beauty", "skincare", "cosmetics", "makeup"],
-        "Toys": ["toys", "kids", "play", "educational", "fun"]
-    }
-    
-    for keyword in category_keywords.get(product_category, []):
-        keywords.add(keyword)
-    
-    # Add audience-related keywords
-    if audience_gender:
-        keywords.add(audience_gender.lower())
-    if audience_location:
-        keywords.add(audience_location.lower())
-    keywords.add(f"age{audience_age[0]}-{audience_age[1]}")
-
-    return list(keywords)
-
-# Button to generate recommended keywords
-if st.button("Generate Recommended Keywords"):
-    # Generate keywords based on user input
-    recommended_keywords = generate_keywords(product_category, product_features, audience_gender, audience_age, audience_location, keywords_input)
-    
-    # Display the recommended keywords
-    st.write("### Recommended Keywords")
-    st.write(", ".join(recommended_keywords))
-    
-    # Prepare DataFrame for CSV export
-    df_keywords = pd.DataFrame(recommended_keywords, columns=["Recommended Keywords"])
-    
-    # Button to download the CSV file
-    st.download_button(
-        label="Download Recommended Keywords as CSV",
-        data=df_keywords.to_csv(index=False),
-        file_name="recommended_keywords.csv",
-        mime="text/csv"
-    )
+# Main con