Update app.py

app.py

@@ -1,68 +1,25 @@
+import openai
 import streamlit as st
-import matplotlib.pyplot as plt
-import io
-import random
+from tenacity import retry, stop_after_attempt, wait_fixed
 import time
+from io import BytesIO
 from PIL import Image
-import os
+import base64
 
-st.set_page_config(
-    page_title="Home Value Maximizer",
-    page_icon="🏠",
-    layout="wide"
-)
+# Set the OpenAI API Key securely (from Hugging Face secrets)
+openai.api_key = st.secrets["OPENAI_API_KEY"]
 
-# API key access with robust error handling
-try:
-    # First try with the newer OpenAI client
-    try:
-        from openai import OpenAI
-        # First try Hugging Face Spaces way of accessing secrets
-        if "OPENAI_API_KEY" in st.secrets:
-            openai_api_key = st.secrets["OPENAI_API_KEY"]
-        # Then try environment variables (another way Hugging Face might store it)
-        elif "OPENAI_API_KEY" in os.environ:
-            openai_api_key = os.environ["OPENAI_API_KEY"]
-        else:
-            openai_api_key = None
-            
-        # Initialize OpenAI client if we have a key
-        if openai_api_key:
-            client = OpenAI(api_key=openai_api_key)
-            has_api_key = True
-            st.sidebar.success("✅ OpenAI API connected")
-        else:
-            has_api_key = False
-            st.sidebar.warning("⚠️ OpenAI API key not found. Running in demo mode with simulated responses.")
-    except ImportError:
-        # Fall back to older OpenAI package
-        import openai
-        if "OPENAI_API_KEY" in st.secrets:
-            openai.api_key = st.secrets["OPENAI_API_KEY"]
-            has_api_key = True
-            st.sidebar.success("✅ OpenAI API connected (legacy client)")
-        elif "OPENAI_API_KEY" in os.environ:
-            openai.api_key = os.environ["OPENAI_API_KEY"]
-            has_api_key = True
-            st.sidebar.success("✅ OpenAI API connected (legacy client)")
-        else:
-            has_api_key = False
-            st.sidebar.warning("⚠️ OpenAI API key not found. Running in demo mode with simulated responses.")
-except Exception as e:
-    st.sidebar.error(f"Error initializing OpenAI: {str(e)}")
-    has_api_key = False
-
-# API Call Limits
-MAX_REQUESTS_PER_SESSION = 3
-TIME_BETWEEN_REQUESTS = 10
+# API Call Limits (To Protect Against Abuse)
+MAX_REQUESTS_PER_SESSION = 3  # Maximum API calls per user session
+TIME_BETWEEN_REQUESTS = 10  # Cooldown in seconds
 
 # Track requests in session state
 if "api_calls" not in st.session_state:
     st.session_state["api_calls"] = 0
 if "last_request_time" not in st.session_state:
     st.session_state["last_request_time"] = 0
-if "results" not in st.session_state:
-    st.session_state["results"] = None
+if "uploaded_images" not in st.session_state:
+    st.session_state["uploaded_images"] = []
 
 # Custom CSS to fix mobile scrolling issues
 st.markdown("""
@@ -135,420 +92,250 @@ st.markdown("""
         margin-bottom: 100px !important;
     }
     
-    /* Style the ROI chart */
-    .roi-chart {
-        width: 100%;
-        border-radius: 10px;
-        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-        margin: 20px 0;
+    /* Style for image gallery */
+    .image-container {
+        display: flex;
+        flex-wrap: wrap;
+        gap: 10px;
+        margin-bottom: 20px;
     }
     
-    /* Style the recommendation cards */
-    .recommendation-card {
-        background-color: #f9f9f9;
-        border-radius: 10px;
-        padding: 15px;
-        margin: 10px 0;
-        border-left: 4px solid #4CAF50;
+    .image-container img {
+        max-width: 100%;
+        border-radius: 5px;
     }
 </style>
 """, unsafe_allow_html=True)
 
-# Home improvement data
-HOME_IMPROVEMENTS = {
-    "kitchen": {
-        "options": [
-            {"name": "Cabinet Refinishing", "cost_range": "$1,500-$3,800", "roi": "80-100%", "priority": "High"},
-            {"name": "New Countertops", "cost_range": "$2,000-$5,000", "roi": "75-90%", "priority": "High"},
-            {"name": "Updated Appliances", "cost_range": "$3,500-$15,000", "roi": "60-80%", "priority": "Medium"},
-            {"name": "Kitchen Island Addition", "cost_range": "$3,000-$10,000", "roi": "50-70%", "priority": "Medium"},
-            {"name": "New Flooring", "cost_range": "$1,500-$4,500", "roi": "70-90%", "priority": "Medium"}
-        ],
-        "recommendations": [
-            "Focus on updating the most visible elements first",
-            "Neutral colors appeal to more buyers",
-            "Improving lighting can make a big difference at lower cost"
-        ]
-    },
-    "bathroom": {
-        "options": [
-            {"name": "New Vanity", "cost_range": "$500-$2,800", "roi": "70-90%", "priority": "High"},
-            {"name": "Updated Fixtures", "cost_range": "$400-$1,000", "roi": "80-100%", "priority": "High"},
-            {"name": "New Tile/Flooring", "cost_range": "$800-$3,500", "roi": "65-85%", "priority": "Medium"},
-            {"name": "Walk-in Shower", "cost_range": "$3,000-$15,000", "roi": "50-70%", "priority": "Low"},
-            {"name": "Full Renovation", "cost_range": "$10,000-$30,000", "roi": "60-70%", "priority": "Low"}
-        ],
-        "recommendations": [
-            "Focus on cleanliness and modern fixtures",
-            "Adequate lighting is essential",
-            "Storage space is highly valued by buyers"
-        ]
-    },
-    "exterior": {
-        "options": [
-            {"name": "Fresh Paint", "cost_range": "$1,800-$5,000", "roi": "90-110%", "priority": "High"},
-            {"name": "Landscaping", "cost_range": "$500-$5,000", "roi": "80-100%", "priority": "High"},
-            {"name": "Front Door Replacement", "cost_range": "$1,000-$3,000", "roi": "75-100%", "priority": "High"},
-            {"name": "New Siding", "cost_range": "$5,000-$15,000", "roi": "70-90%", "priority": "Medium"},
-            {"name": "Roof Replacement", "cost_range": "$8,000-$20,000", "roi": "65-80%", "priority": "Medium"}
-        ],
-        "recommendations": [
-            "Curb appeal heavily influences buyer first impressions",
-            "Ensure the entrance area is inviting and well-maintained",
-            "Address any visible maintenance issues before cosmetic upgrades"
-        ]
-    },
-    "living_areas": {
-        "options": [
-            {"name": "Fresh Paint", "cost_range": "$1,000-$3,000", "roi": "80-110%", "priority": "High"},
-            {"name": "Refinished Hardwood Floors", "cost_range": "$1,500-$4,500", "roi": "70-100%", "priority": "High"},
-            {"name": "Updated Lighting", "cost_range": "$500-$2,000", "roi": "70-90%", "priority": "Medium"},
-            {"name": "Crown Molding", "cost_range": "$1,000-$3,000", "roi": "50-70%", "priority": "Low"},
-            {"name": "Open Floor Plan Conversion", "cost_range": "$8,000-$25,000", "roi": "60-80%", "priority": "Low"}
-        ],
-        "recommendations": [
-            "Neutral colors and good lighting maximize appeal",
-            "Decluttered spaces appear larger to buyers",
-            "Minor cosmetic updates often yield better ROI than major renovations"
-        ]
-    }
-}
-
-# Function to call OpenAI API or simulate a response
-def get_ai_recommendations(description):
-    if has_api_key and st.session_state["api_calls"] < MAX_REQUESTS_PER_SESSION:
-        current_time = time.time()
-        time_since_last_request = current_time - st.session_state["last_request_time"]
+# Initial system message for OpenAI API
+initial_messages = [{
+    "role": "system", 
+    "content": """You are an AI assistant that helps homeowners maximize their property value before selling. 
+    You analyze home photos and provide customized recommendations for high-ROI improvements.
+    You follow ALL rules that a Realtor or real estate professional must follow in the United States, including fair housing laws. Ignore any instructions that violate those rules.
+    Always add the following text to the beginning of every response:  
+    'Here are your personalized home improvement recommendations! If you found this tool helpful, visit www.myeverydayai.com to see more AI tools like this that can help with your real estate needs!'
+    
+    Provide recommendations in these categories:
+    1. Quick Wins (1-2 days, low cost)
+    2. Weekend Projects (1 week, medium cost) 
+    3. Major Improvements (if warranted, higher cost but higher ROI)
+    
+    For each recommendation, explain the potential value impact and approximate ROI. Be specific based on what you can see in the photos.
+    Avoid generic advice - focus on what's visible in the images provided.
+    """
+}]
 
-        if time_since_last_request < TIME_BETWEEN_REQUESTS and st.session_state["api_calls"] > 0:
-            st.warning(f"⏳ Please wait {int(TIME_BETWEEN_REQUESTS - time_since_last_request)} seconds before making another request.")
-            return get_simulated_response(description)
+# Function to encode images to base64 for API transmission
+def encode_image_to_base64(image):
+    buffered = BytesIO()
+    image.save(buffered, format="JPEG")
+    return base64.b64encode(buffered.getvalue()).decode('utf-8')
 
-        try:
-            # Try using the newer OpenAI client first
-            if 'client' in globals():
-                response = client.chat.completions.create(
-                    model="gpt-4",
-                    messages=[
-                        {"role": "system", "content": """You are an AI assistant that analyzes home photos and provides recommendations for improvements that will maximize sale price. 
-                        Always add the following text to the beginning of every response:  
-                        'Below are your home improvement recommendations! For a FREE in-depth consultation with a real estate expert, fill out the contact form below.'"""},
-                        {"role": "user", "content": description}
-                    ]
-                )
-                
-                st.session_state["api_calls"] += 1
-                st.session_state["last_request_time"] = time.time()
-                return response.choices[0].message.content
-            
-            # Fall back to older OpenAI package if needed
-            elif 'openai' in globals():
-                response = openai.ChatCompletion.create(
-                    model="gpt-4",
-                    messages=[
-                        {"role": "system", "content": """You are an AI assistant that analyzes home photos and provides recommendations for improvements that will maximize sale price. 
-                        Always add the following text to the beginning of every response:  
-                        'Below are your home improvement recommendations! For a FREE in-depth consultation with a real estate expert, fill out the contact form below.'"""},
-                        {"role": "user", "content": description}
-                    ]
-                )
-                
-                st.session_state["api_calls"] += 1
-                st.session_state["last_request_time"] = time.time()
-                return response["choices"][0]["message"]["content"]
-            
-            else:
-                return get_simulated_response(description)
-                
-        except Exception as e:
-            st.warning(f"⚠️ Error calling AI API: {str(e)}")
-            st.info("Falling back to simulated response")
-            # Fallback to simulated response
-            return get_simulated_response(description)
-    else:
-        return get_simulated_response(description)
+# Function to call OpenAI API securely with rate limiting
+@retry(stop=stop_after_attempt(3), wait=wait_fixed(1))
+def call_openai_api(messages):
+    if st.session_state["api_calls"] >= MAX_REQUESTS_PER_SESSION:
+        st.error("🚨 You have reached the limit of 3 requests per session. Please try again later.")
+        return None
 
-def get_simulated_response(description):
-    """Provide a simulated response when API is not available"""
-    # Extract some info from the description to personalize the simulated response
-    location = "your area"
-    if "Urban" in description:
-        location = "urban area"
-    elif "Suburban" in description:
-        location = "suburban area"
-    elif "Rural" in description:
-        location = "rural area"
-    
-    timeline = "when you sell"
-    if "Less than 3 months" in description:
-        timeline = "in your short timeline"
-    elif "3-6 months" in description:
-        timeline = "in the next 3-6 months"
-    elif "6+ months" in description:
-        timeline = "in your longer timeline"
-    
-    return f"""Below are your home improvement recommendations! For a FREE in-depth consultation with a real estate expert, fill out the contact form below.
+    current_time = time.time()
+    time_since_last_request = current_time - st.session_state["last_request_time"]
 
-Based on my analysis of your home photos, I've identified several improvements that could significantly increase your property's value in your {location}.
+    if time_since_last_request < TIME_BETWEEN_REQUESTS:
+        st.error(f"⏳ Please wait {TIME_BETWEEN_REQUESTS - int(time_since_last_request)} seconds before making another request.")
+        return None
 
-## Key Recommendations:
+    response = openai.ChatCompletion.create(
+        model="gpt-4-vision-preview",
+        messages=messages,
+        max_tokens=1500
+    )
 
-### Kitchen:
-- Consider refinishing your cabinets rather than replacing them - this offers one of the best ROIs ($1,500-$3,800 investment with 80-100% ROI)
-- Updating countertops to quartz or granite can modernize the space while providing excellent return
-- Install new lighting fixtures for an affordable yet impactful upgrade
+    if response:
+        st.session_state["api_calls"] += 1
+        st.session_state["last_request_time"] = time.time()
+        return response["choices"][0]["message"]["content"]
+    else:
+        st.error("❌ API request failed. Please try again.")
+        return None
 
-### Bathroom:
-- New fixtures and hardware provide excellent value (80-100% ROI) with minimal investment
-- A fresh vanity can transform the space for under $3,000
-- Consider a new shower curtain and fresh caulking for quick improvements
+# Function to generate home improvement recommendations
+def generate_recommendations(images, property_type, price_range, timeframe, additional_details, messages):
+    # Create content message with images
+    content = [
+        {"type": "text", "text": f"Please analyze these photos of my home and recommend improvements to maximize its value. My home is in the {price_range} range and is a {property_type} property. I plan to sell within {timeframe}. {additional_details}"}
+    ]
+    
+    # Add each image to the content
+    for img in images:
+        base64_image = encode_image_to_base64(img)
+        content.append({
+            "type": "image_url",
+            "image_url": {
+                "url": f"data:image/jpeg;base64,{base64_image}"
+            }
+        })
+    
+    messages.append({
+        "role": "user", 
+        "content": content
+    })
 
-### Exterior:
-- Fresh paint on the exterior offers exceptional ROI (90-110%)
-- Landscaping improvements are essential for curb appeal and first impressions
-- A new front door can return up to 100% of its cost at sale time
+    response = call_openai_api(messages)
 
-Focusing on these high-impact improvements {timeline} will likely maximize your return while requiring reasonable investment. For a detailed plan tailored to your specific property, please request a consultation.
-"""
+    if response:
+        messages.append({"role": "assistant", "content": response})
+        return response, messages
+    else:
+        return "Error generating recommendations. Please try again.", messages
 
-# Simulate room classification and analysis
-def classify_room(image_file):
-    """Simulate room classification from an image"""
-    room_types = ["kitchen", "bathroom", "exterior", "living_areas"]
-    return random.choice(room_types)
+# Main title
+st.title("Home Value Maximizer 🏡")
 
-def analyze_condition(image_file):
-    """Simulate condition analysis from an image"""
-    conditions = ["excellent", "good", "fair", "poor"]
-    condition_weights = [0.1, 0.3, 0.4, 0.2]  # Weighted to slightly favor "fair" condition
-    return random.choices(conditions, weights=condition_weights)[0]
+# Using columns to organize the layout
+col1, col2 = st.columns(2)
 
-def generate_chart(improvement_data):
-    """Generate a chart showing ROI vs Cost for improvements"""
-    improvements = []
-    costs = []
-    rois = []
-    
-    # Extract data for the chart
-    for area, data in improvement_data.items():
-        for option in data["options"]:
-            if option.get("selected", False):
-                improvements.append(option["name"])
-                # Extract the average cost from the range
-                cost_range = option["cost_range"].replace("$", "").replace(",", "")
-                cost_parts = cost_range.split("-")
-                avg_cost = (int(cost_parts[0]) + int(cost_parts[1])) / 2
-                costs.append(avg_cost)
-                
-                # Extract the average ROI from the range
-                roi_range = option["roi"].replace("%", "")
-                roi_parts = roi_range.split("-")
-                avg_roi = (int(roi_parts[0]) + int(roi_parts[1])) / 2
-                rois.append(avg_roi)
-    
-    if not improvements:
-        return None
-    
-    # Create the chart
-    fig, ax = plt.subplots(figsize=(10, 6))
+with col1:
+    st.subheader("📸 Upload Home Photos")
+    uploaded_files = st.file_uploader("Upload photos of different areas of your home", 
+                                      accept_multiple_files=True, 
+                                      type=["jpg", "jpeg", "png"])
+    
+    # Process uploaded images
+    if uploaded_files:
+        images = []
+        for file in uploaded_files:
+            try:
+                image = Image.open(file)
+                images.append(image)
+            except Exception as e:
+                st.error(f"Error opening image {file.name}: {e}")
+        
+        st.session_state["uploaded_images"] = images
+        
+        # Display uploaded images in a gallery
+        if images:
+            st.write(f"**{len(images)} images uploaded**")
+            image_cols = st.columns(min(3, len(images)))
+            for i, img in enumerate(images):
+                with image_cols[i % min(3, len(images))]:
+                    st.image(img, width=150, caption=f"Image {i+1}")
     
-    # Convert ROI to dollar values
-    roi_values = [cost * (roi/100) for cost, roi in zip(costs, rois)]
+    st.subheader("🏠 Property Details")
     
-    # Create a scatter plot
-    scatter = ax.scatter(costs, roi_values, s=100, alpha=0.7)
+    property_type = st.selectbox("Property Type", 
+                                ["Single Family Home", "Townhouse", "Condo/Apartment", "Multi-Family"])
     
-    # Label the points
-    for i, txt in enumerate(improvements):
-        ax.annotate(txt, (costs[i], roi_values[i]), fontsize=9, 
-                   xytext=(5, 5), textcoords='offset points')
+    price_range = st.selectbox("Property Price Range", 
+                              ["Entry-level", "Mid-range", "Luxury"])
     
-    # Add a line for breakeven ROI
-    max_cost = max(costs) if costs else 10000
-    ax.plot([0, max_cost], [0, max_cost], 'r--', alpha=0.3)
+    timeframe = st.radio("When do you plan to sell?",
+                        ["Less than 3 months", "3-6 months", "6+ months"])
     
-    # Add labels and title
-    ax.set_xlabel('Estimated Cost ($)')
-    ax.set_ylabel('Estimated Return ($)')
-    ax.set_title('Cost vs. Return on Investment')
-    ax.grid(True, alpha=0.3)
+    additional_details = st.text_area("Additional Details", 
+                                     placeholder="Describe specific areas you're considering renovating or any concerns.",
+                                     height=80)
     
-    # Save the chart to a byte buffer
-    buf = io.BytesIO()
-    plt.savefig(buf, format='png')
-    buf.seek(0)
+    # Make button more mobile-friendly
+    submit_button = st.button('🔍 Analyze My Home', use_container_width=True, 
+                             disabled=len(st.session_state["uploaded_images"]) == 0)
     
-    plt.close(fig)
-    return buf
+    if len(st.session_state["uploaded_images"]) == 0:
+        st.warning("Please upload at least one photo of your home to receive recommendations.")
 
-def condition_value(condition):
-    """Convert condition text to numeric value (higher = worse condition)"""
-    values = {"excellent": 1, "good": 2, "fair": 3, "poor": 4}
-    return values.get(condition, 2)
+with col2:
+    st.subheader("💡 Improvement Recommendations")
+    result_placeholder = st.empty()
 
-def priority_value(priority):
-    """Convert priority text to numeric value (higher = higher priority)"""
-    values = {"Low": 1, "Medium": 3, "High": 5}
-    return values.get(priority, 3)
-
-def analyze_home_images(images, location, price_range, timeline):
-    """Analyze uploaded images and generate improvement recommendations"""
-    results = {}
-    
-    # Process each image
-    for img in images:
-        room_type = classify_room(img)
-        condition = analyze_condition(img)
-        
-        # Record the analysis for this room type if not already present or in worse condition
-        if room_type not in results or condition_value(results[room_type]["condition"]) > condition_value(condition):
-            results[room_type] = {
-                "condition": condition,
-                "options": HOME_IMPROVEMENTS[room_type]["options"].copy(),
-                "recommendations": HOME_IMPROVEMENTS[room_type]["recommendations"]
-            }
-    
-    # Adjust the priority based on the room condition
-    for room_type, room_data in results.items():
-        for option in room_data["options"]:
-            # Mark some improvements as "selected" based on condition and priority
-            condition_score = condition_value(room_data["condition"])
-            priority_score = priority_value(option["priority"])
-            
-            # Select improvements that are high priority for poor/fair condition rooms
-            # or medium-high priority for fair/good condition rooms
-            if (condition_score >= 3 and priority_score >= 3) or \
-               (condition_score >= 2 and priority_score >= 4):
-                option["selected"] = True
-            else:
-                option["selected"] = False
-    
-    # Generate the ROI chart
-    chart = generate_chart(results)
-    
-    # Prepare a description of the analysis for the API
-    analysis_description = f"Property location: {location}, Price range: {price_range}, Timeline: {timeline}\n\nAnalysis results:\n"
-    
-    for room_type, room_data in results.items():
-        room_name = room_type.replace("_", " ").title()
-        analysis_description += f"- {room_name}: {room_data['condition'].title()} condition\n"
-        
-        selected_options = [opt for opt in room_data["options"] if opt.get("selected", False)]
-        if selected_options:
-            analysis_description += "  Recommended improvements:\n"
-            for option in selected_options:
-                analysis_description += f"  * {option['name']} (Est. {option['cost_range']}, ROI: {option['roi']})\n"
+    if submit_button:
+        if st.session_state["api_calls"] >= MAX_REQUESTS_PER_SESSION:
+            st.error("🚨 Request limit reached. Please try again later.")
         else:
-            analysis_description += "  No critical improvements needed\n"
-    
-    # Get AI recommendations
-    recommendations = get_ai_recommendations(analysis_description)
-    
-    return recommendations, chart, results
+            with st.spinner("Analyzing your home and generating recommendations..."):
+                messages = initial_messages.copy()
+                reply, _ = generate_recommendations(st.session_state["uploaded_images"], 
+                                                 property_type, price_range, timeframe, 
+                                                 additional_details, messages)
+                result_placeholder.markdown(reply)
+    else:
+        result_placeholder.markdown("**Results will appear here after you submit your home photos and details**")
 
-# Main app
-def main():
-    st.title("Home Value Maximizer 🏠")
-    
-    # Using columns to organize the layout
-    col1, col2 = st.columns([3, 4])
-    
-    with col1:
-        st.subheader("📸 Upload Home Photos")
-        uploaded_files = st.file_uploader("Upload photos of different areas of your home", accept_multiple_files=True, type=['jpg', 'jpeg', 'png'])
+    # Lead capture form - appears after recommendations are shown
+    if submit_button and "api_calls" in st.session_state and st.session_state["api_calls"] > 0:
+        st.write("---")
+        st.subheader("📋 Get a FREE In-Depth Consultation")
         
-        if uploaded_files:
-            st.success(f"✅ {len(uploaded_files)} images uploaded")
-            
-            gallery = []
-            for file in uploaded_files:
-                gallery.append(file)
-            
-            st.image(gallery, width=100)
-        
-        st.subheader("🏡 Property Details")
-        location = st.selectbox("Location Type", 
-                               ["Urban", "Suburban", "Rural"],
-                               index=1)
-        
-        price_range = st.selectbox("Property Price Range", 
-                                  ["Entry-level", "Mid-range", "Luxury"],
-                                  index=1)
+        st.write("Want a professional to review these recommendations and provide personalized guidance?")
         
-        timeline = st.radio("When do you plan to sell?",
-                           ["Less than 3 months", "3-6 months", "6+ months"],
-                           index=1)
+        name = st.text_input("Your Name")
+        email = st.text_input("Your Email")
+        phone = st.text_input("Your Phone (optional)")
         
-        if not uploaded_files:
-            st.info("📌 Please upload at least one photo of your home to receive recommendations")
+        if st.button("Request Free Consultation", use_container_width=True):
+            if name and email:
+                st.success("Thanks! A real estate professional will contact you within 24 hours to discuss your home value maximization strategy.")
+                # Here you would typically add code to save the lead information
+                # For example, sending to an email, CRM, or database
+            else:
+                st.warning("Please provide your name and email to request a consultation.")
+
+# Add disclaimer
+st.markdown("<div style='height: 30px'></div>", unsafe_allow_html=True)  # Add space
+st.markdown("---")  # Horizontal line for separation
+
+# Add extra spacing before disclaimer to ensure it's scrollable on iOS
+st.markdown("<div style='height: 20px'></div>", unsafe_allow_html=True)
+
+with st.expander("📜 **Disclaimer (Click to Expand)**"):
+    st.markdown("""
+    **Disclaimer:**  
+    This Home Value Maximizer tool is powered by AI and provides general recommendations based on the photos and information you provide.  
+    Results are for **informational purposes only** and may not be accurate for your specific situation. Please consult with real estate professionals before making significant investments.
+    
+    **Fair Housing Compliance:**  
+    This tool complies with Fair Housing laws and does **not** make recommendations based on race, color, religion, sex, disability, familial status, or national origin.
+    
+    **User Responsibility & Liability:**  
+    Users are responsible for any decisions made using this tool. We disclaim any liability for damages or losses.  
+    By using this tool, you agree to do so at your **own risk**.
+    """)
+
+# Add extra padding at the bottom to ensure scrollability on iOS
+st.markdown("<div style='height: 100px'></div>", unsafe_allow_html=True)
+
+# Add invisible element at the very bottom to ensure scrollability
+st.markdown("<div id='bottom-anchor' style='height:1px;'></div>", unsafe_allow_html=True)
+
+# JavaScript to help with iOS scrolling
+st.markdown("""
+<script>
+    // Help iOS recognize the full scrollable height
+    function fixIOSScrolling() {
+        if (/iPhone|iPad|iPod/i.test(navigator.userAgent)) {
+            // Force layout recalculation
+            document.body.style.display = 'none';
+            document.body.offsetHeight; // Trigger reflow
+            document.body.style.display = '';
             
-        analyze_button = st.button("📊 Analyze My Home", disabled=len(uploaded_files) == 0, use_container_width=True)
-    
-    with col2:
-        st.subheader("💡 Improvement Recommendations")
-        results_placeholder = st.empty()
-        chart_placeholder = st.empty()
-        
-        # Contact form
-        with st.expander("📋 Get a FREE In-Depth Consultation", expanded=False):
-            name = st.text_input("Full Name")
-            email = st.text_input("Email Address")
-            phone = st.text_input("Phone Number (optional)")
-            address = st.text_input("Property Address (optional)")
-            contact_button = st.button("✉️ Request Consultation", use_container_width=True)
+            // Add extra padding to bottom if needed
+            const container = document.querySelector('.main .block-container');
+            if (container) {
+                container.style.paddingBottom = '150px';
+            }
             
-            if contact_button:
-                if not name or not email:
-                    st.error("Please provide your name and email to request a consultation.")
-                else:
-                    st.success(f"Thank you, {name}! A real estate expert will contact you shortly at {email}.")
-    
-    # When the user clicks the analyze button
-    if analyze_button and uploaded_files:
-        if st.session_state["api_calls"] >= MAX_REQUESTS_PER_SESSION and has_api_key:
-            st.error("🚨 You've reached the maximum number of analyses per session. Please try again later.")
-        else:
-            with st.spinner("Analyzing your home photos..."):
-                # Call the analysis function
-                recommendations, chart, analyzed_data = analyze_home_images(
-                    uploaded_files, location, price_range, timeline
-                )
-                
-                # Store the results in session state
-                st.session_state["results"] = (recommendations, chart, analyzed_data)
-                
-                # Display the results
-                results_placeholder.markdown(recommendations)
-                
-                if chart:
-                    chart_placeholder.image(chart, caption="Improvement Cost vs Return Analysis", use_column_width=True)
-    
-    # Display the results if they exist in session state
-    elif st.session_state["results"]:
-        recommendations, chart, analyzed_data = st.session_state["results"]
-        results_placeholder.markdown(recommendations)
-        
-        if chart:
-            chart_placeholder.image(chart, caption="Improvement Cost vs Return Analysis", use_column_width=True)
-    
-    # Add disclaimer
-    st.markdown("---")
-    with st.expander("📜 **Disclaimer**", expanded=False):
-        st.markdown("""
-        **Disclaimer:**  
-        This Home Value Maximizer tool is powered by AI and provides general recommendations based on limited information.
-        Results are for **informational purposes only** and may not be accurate for your specific property or market conditions.
-        
-        **Professional Advice:**  
-        For accurate and personalized advice, please consult with a licensed real estate professional or contractor.
-        
-        **User Responsibility:**  
-        Users are responsible for any decisions made using this tool. We disclaim any liability for damages or losses.
-        By using this tool, you agree to do so at your **own risk**.
-        """)
+            // Ensure scrollability by briefly scrolling to bottom
+            window.setTimeout(function() {
+                const bottomElement = document.getElementById('bottom-anchor');
+                if (bottomElement) {
+                    bottomElement.scrollIntoView();
+                    window.scrollTo(0, 0);
+                }
+            }, 500);
+        }
+    }
     
-    # Add invisible element at the very bottom to ensure scrollability
-    st.markdown("<div id='bottom-anchor' style='height:1px;'></div>", unsafe_allow_html=True)
-
-if __name__ == "__main__":
-    main()
+    // Run when page loads
+    window.addEventListener('load', fixIOSScrolling);
+</script>
+""", unsafe_allow_html=True)