Update app.py

app.py

@@ -5,114 +5,58 @@ from geopy.geocoders import Nominatim
 import os
 import folium
 from streamlit_folium import folium_static
-from jsonschema import validate, ValidationError
 from fake_useragent import UserAgent
 
 # Configure environment
 DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_KEY")
 API_ENDPOINT = "https://api.deepseek.com/v1/chat/completions"
 
-# JSON Schema for API response validation
-RESPONSE_SCHEMA = {
-    "type": "object",
-    "required": ["choices"],
-    "properties": {
-        "choices": {
-            "type": "array",
-            "minItems": 1,
-            "items": {
-                "type": "object",
-                "required": ["message"],
-                "properties": {
-                    "message": {
-                        "type": "object",
-                        "required": ["content"],
-                        "properties": {
-                            "content": {"type": "string"}
-                        }
-                    }
-                }
-            }
-        }
-    }
-}
+# Customizable branding
+PROMOTION_LINK = "www.myeverydayai.com"
+BRANDING_TEXT = "Powered by [Everyday AI Solutions](https://www.myeverydayai.com)"
 
 def get_scraping_headers():
-    """Generate random browser headers"""
     ua = UserAgent()
     return {
         'User-Agent': ua.chrome,
         'Accept-Language': 'en-US,en;q=0.9',
-        'Referer': 'https://www.google.com/',
-        'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
-        'DNT': '1'
+        'Referer': 'https://www.google.com/'
     }
 
 @st.cache_data
 def scrape_location_data(query):
-    """Scrape location data with advanced anti-bot measures"""
     session = requests.Session()
-    results = []
-    
     try:
-        # First request to get through potential bot checks
-        search_url = f"https://www.niche.com/places-to-live/search/{query}"
         response = session.get(
-            search_url,
+            f"https://www.niche.com/places-to-live/search/{query}",
             headers=get_scraping_headers(),
-            timeout=15,
-            allow_redirects=True
+            timeout=15
         )
-        
-        # Detect bot protection
-        if any(keyword in response.text.lower() for keyword in ['captcha', 'security check']):
-            st.warning("""
-            **Manual Verification Required:**
-            1. Visit [Niche.com](https://www.niche.com) directly
-            2. Complete any security checks
-            3. Return here and try again
-            """)
-            return []
-
-        soup = BeautifulSoup(response.text, 'html.parser')
-        
-        # Resilient CSS selector patterns
-        listings = soup.select('div[class*="search-results__list__item"]')
-        
-        for item in listings[:3]:
-            result = {
-                'name': item.select_one('h2').get_text(strip=True) if item.select_one('h2') else 'N/A',
-                'details': item.select_one('div[class*="tagline"]').get_text(strip=True) if item.select_one('div[class*="tagline"]') else '',
-                'score': item.select_one('div[class*="grade"]').get_text(strip=True) if item.select_one('div[class*="grade"]")') else ''
-            }
-            results.append(result)
-            
-        return results
-        
-    except Exception as e:
-        st.error(f"Data retrieval issue: {str(e)}")
+        # Add scraping logic here
+        return ["Sample Neighborhood 1", "Sample Neighborhood 2"]
+    except Exception:
         return []
 
-def generate_recommendations(preferences):
-    """Generate recommendations with robust error handling"""
-    if not DEEPSEEK_API_KEY:
-        st.error("Missing API key configuration")
-        return None
-
+def generate_recommendations(preferences, custom_factors):
     headers = {
         "Authorization": f"Bearer {DEEPSEEK_API_KEY}",
         "Content-Type": "application/json"
     }
     
-    prompt = f"""
-    Analyze these neighborhood preferences: {preferences}
+    base_prompt = f"""
+    Analyze these neighborhood preferences:
+    {preferences}
+    
+    Additional Custom Factors:
+    {custom_factors}
+    
     Create a detailed report with:
-    - Top 3 matches
-    - 1 hidden gem
-    - Amenity analysis
-    - Safety insights
-    - Price comparisons
-    Format with markdown sections
+    - Top 3 neighborhood matches
+    - Unique benefits for each
+    - Comparison of custom factors
+    - Final recommendation
+    
+    End with: "Want your own AI tool? Visit {PROMOTION_LINK}"
     """
     
     try:
@@ -120,75 +64,82 @@ def generate_recommendations(preferences):
             API_ENDPOINT,
             json={
                 "model": "deepseek-chat",
-                "messages": [{"role": "user", "content": prompt}],
+                "messages": [{"role": "user", "content": base_prompt}],
                 "temperature": 0.7,
                 "max_tokens": 1500
             },
             headers=headers,
             timeout=30
         )
-        
-        if response.status_code != 200:
-            error_msg = response.json().get('error', {}).get('message', 'Unknown API error')
-            st.error(f"API Error {response.status_code}: {error_msg}")
-            return None
-        
-        response_data = response.json()
-        validate(instance=response_data, schema=RESPONSE_SCHEMA)
-        
-        return response_data["choices"][0]["message"]["content"]
-        
-    except ValidationError as ve:
-        st.error(f"Invalid API response: {str(ve)}")
-        return None
-    except Exception as e:
-        st.error(f"Connection Error: {str(e)}")
+        return response.json()["choices"][0]["message"]["content"]
+    except Exception:
         return None
 
 # Streamlit UI
 st.set_page_config(layout="wide", page_icon="🏡")
-st.title("Neighborhood Matchmaker Pro")
+
+# Branding Header
+st.markdown(f"""
+<div style="background:#f0f2f6;padding:10px;border-radius:5px;margin-bottom:20px">
+    <h3 style="color:#1e88e5;text-align:center;">{BRANDING_TEXT}</h3>
+</div>
+""", unsafe_allow_html=True)
+
+st.title("🏡 Smart Neighborhood Finder")
 
 with st.sidebar:
-    st.header("Search Preferences")
+    st.header("Realtor Instructions")
+    st.markdown(f"""
+    Add this tool to your website for free! 
+    [Get your customized version](https://{PROMOTION_LINK})
+    """)
+    st.markdown("---")
+    st.header("Client Preferences")
+    
+    # Core inputs
     city = st.text_input("City/Region", "New York, NY")
-    budget = st.slider("Monthly Budget ($)", 1000, 10000, 3000)
-    commute = st.selectbox("Max Commute", ["15 mins", "30 mins", "45 mins"])
-    lifestyle = st.selectbox("Lifestyle", ["Family", "Urban", "Remote"])
+    budget = st.slider("Price Range ($)", 1000, 5000, (2000, 4000))
+    home_type = st.selectbox("Home Type", ["House", "Apartment", "Condominium"])
+    
+    # Custom factors
+    custom_factors = st.text_area(
+        "Add Your Special Requirements", 
+        placeholder="e.g., Near dog parks, Vegan restaurants, Yoga studios"
+    )
 
-if st.button("Find Neighborhoods"):
-    with st.spinner("Analyzing locations..."):
+# Generate report
+if st.button("Find My Perfect Neighborhood"):
+    with st.spinner("Creating your custom report..."):
         preferences = {
-            "city": city,
-            "budget": budget,
-            "commute": commute,
-            "lifestyle": lifestyle
+            "City": city,
+            "Budget": f"${budget[0]} - ${budget[1]}",
+            "Home Type": home_type
         }
         
-        location_data = scrape_location_data(city)
-        
-        if not location_data:
-            st.info("Using alternative data sources...")
-            # Implement fallback scraping here
-            
-        report = generate_recommendations(preferences)
+        report = generate_recommendations(preferences, custom_factors)
         
         if report:
-            st.subheader("Custom Neighborhood Report")
+            st.subheader("Your Personalized Neighborhood Report")
             st.markdown(report)
             
-            try:
-                geolocator = Nominatim(user_agent="geo_app_v2")
-                location = geolocator.geocode(city)
-                if location:
-                    m = folium.Map(
-                        location=[location.latitude, location.longitude],
-                        zoom_start=12,
-                        tiles="CartoDB positron"
-                    )
-                    folium_static(m, width=1000, height=500)
-            except Exception as e:
-                st.warning(f"Map error: {str(e)}")
+            # Promotional footer
+            st.markdown(f"""
+            ---
+            <div style="text-align:center;margin-top:40px">
+                <h4>Want this AI tool on your website?</h4>
+                <a href="https://{PROMOTION_LINK}">
+                    <button style="background:#1e88e5;color:white;padding:10px 20px;border:none;border-radius:5px">
+                        Get Your Free Version
+                    </button>
+                </a>
+            </div>
+            """, unsafe_allow_html=True)
+        else:
+            st.error("Error generating report. Please try again.")
 
-st.markdown("---")
-st.caption("Note: Results may vary based on data availability")
+# Always show branding footer
+st.markdown(f"""
+<div style="text-align:center;margin-top:50px;padding:20px;background:#f8f9fa">
+    {BRANDING_TEXT} - Provide AI-powered tools to your clients
+</div>
+""", unsafe_allow_html=True)