Update app.py

app.py

@@ -2,10 +2,7 @@ import streamlit as st
 import requests
 from bs4 import BeautifulSoup
 from geopy.geocoders import Nominatim
-from urllib.parse import urljoin, urlparse
-import re
 import os
-import pandas as pd
 import folium
 from streamlit_folium import folium_static
 
@@ -13,54 +10,41 @@ from streamlit_folium import folium_static
 DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_KEY")
 API_ENDPOINT = "https://api.deepseek.com/v1/chat/completions"
 
-# Cache expensive operations
-@st.cache_data
+# Docker-compatible settings
+st.set_page_config(layout="wide", page_icon="🏡")
+geolocator = Nominatim(user_agent="docker_neighborhood_finder")
+
+@st.cache_data(show_spinner=False)
 def scrape_location_data(query):
-    """Scrape location data from public sources"""
-    sources = {
-        "Niche": f"https://www.niche.com/places-to-live/search/{query}",
-        "AreaVibes": f"https://www.areavibes.com/search/?query={query}",
-    }
-    
-    results = []
-    for source, url in sources.items():
-        try:
-            response = requests.get(url, timeout=15)
-            soup = BeautifulSoup(response.text, 'html.parser')
-            
-            if source == "Niche":
-                listings = soup.find_all('div', class_='search-results__list__item')
-                for item in listings[:3]:
-                    results.append({
-                        'name': item.find('h2').text.strip(),
-                        'details': item.find('div', class_='search-result-tagline').text.strip(),
-                        'score': item.find('div', class_='search-result-grade').text.strip()
-                    })
-                    
-        except Exception as e:
-            continue
-            
-    return results
+    """Scrape location data with Docker-friendly timeout"""
+    try:
+        response = requests.get(
+            f"https://www.niche.com/places-to-live/search/{query}",
+            timeout=10
+        )
+        soup = BeautifulSoup(response.text, 'html.parser')
+        return [
+            item.find('h2').text.strip()
+            for item in soup.find_all('div', class_='search-results__list__item')[:3]
+        ]
+    except Exception:
+        return []
 
 def generate_recommendations(preferences):
-    """Generate neighborhood recommendations using Deepseek API"""
+    """Docker-optimized API call"""
     headers = {
         "Authorization": f"Bearer {DEEPSEEK_API_KEY}",
         "Content-Type": "application/json"
     }
     
     prompt = f"""
-    Create a neighborhood recommendation report based on these preferences:
-    {preferences}
-    
-    Include these sections:
-    1. Top 5 Neighborhood Matches
-    2. Hidden Gem Recommendation
-    3. Key Amenities Analysis
-    4. Commute Times Overview
-    5. Safety & Community Insights
-    
-    Format with markdown headers and bullet points. Keep sections concise.
+    Analyze these preferences: {preferences}
+    Recommend neighborhoods with:
+    - Top 3 matches
+    - 1 hidden gem
+    - Key amenities
+    - Safety insights
+    Format with markdown bullet points
     """
     
     try:
@@ -70,10 +54,10 @@ def generate_recommendations(preferences):
                 "model": "deepseek-chat",
                 "messages": [{"role": "user", "content": prompt}],
                 "temperature": 0.7,
-                "max_tokens": 1500
+                "max_tokens": 1000
             },
             headers=headers,
-            timeout=30
+            timeout=20  # Docker-friendly timeout
         )
         return response.json()["choices"][0]["message"]["content"]
     except Exception as e:
@@ -81,53 +65,43 @@ def generate_recommendations(preferences):
         return None
 
 # Streamlit UI
-st.set_page_config(layout="wide", page_icon="🏡")
-st.title("Neighborhood Matchmaker")
-
-with st.sidebar:
-    st.header("Search Preferences")
-    city = st.text_input("City/Region", "New York, NY")
-    budget = st.slider("Monthly Housing Budget ($)", 1000, 10000, 3000)
-    commute = st.selectbox("Max Commute Time", ["15 mins", "30 mins", "45 mins", "1 hour"])
-    amenities = st.multiselect("Must-Have Amenities", [
-        "Good Schools", "Parks", "Public Transport", 
-        "Nightlife", "Shopping", "Healthcare"
-    ])
-    lifestyle = st.selectbox("Lifestyle Preference", [
-        "Family-Friendly", "Urban Professional", "Retirement", 
-        "Student", "Remote Worker", "Outdoor Enthusiast"
-    ])
+st.title("🏡 Neighborhood Finder (Docker)")
 
-if st.button("Find My Neighborhood"):
-    with st.spinner("Analyzing locations..."):
-        # Collect preferences
-        preferences = {
-            "city": city,
-            "budget": f"${budget}/mo",
-            "max_commute": commute,
-            "amenities": amenities,
-            "lifestyle": lifestyle
-        }
-        
-        # Get location data
-        location_data = scrape_location_data(city)
-        
-        # Generate recommendations
-        report = generate_recommendations(preferences)
-        
-        # Display results
-        if report:
-            st.subheader("Your Personalized Neighborhood Report")
-            st.markdown(report)
+with st.form("preferences"):
+    col1, col2 = st.columns(2)
+    with col1:
+        city = st.text_input("City/Region", "New York, NY")
+        budget = st.slider("Monthly Budget ($)", 1000, 10000, 3000)
+    with col2:
+        commute = st.selectbox("Max Commute", ["15m", "30m", "45m", "1h"])
+        lifestyle = st.selectbox("Lifestyle", ["Family", "Urban", "Remote"])
+    
+    if st.form_submit_button("Find Neighborhoods"):
+        with st.spinner("Searching..."):
+            # Get data
+            locations = scrape_location_data(city)
+            preferences = {
+                "city": city,
+                "budget": budget,
+                "commute": commute,
+                "lifestyle": lifestyle
+            }
             
-            # Show map
-            try:
-                geolocator = Nominatim(user_agent="neighborhood_finder")
-                location = geolocator.geocode(city)
-                m = folium.Map(location=[location.latitude, location.longitude], zoom_start=12)
-                folium_static(m, width=1200, height=500)
-            except Exception as e:
-                st.warning("Couldn't generate map visualization")
-
-st.markdown("---")
-st.caption("Note: Recommendations generated by AI. Verify with local experts.")
+            # Generate report
+            report = generate_recommendations(preferences)
+            
+            # Show results
+            if report:
+                st.markdown(report)
+                
+                # Docker-compatible map
+                try:
+                    location = geolocator.geocode(city)
+                    m = folium.Map(
+                        location=[location.latitude, location.longitude],
+                        zoom_start=12,
+                        tiles="CartoDB positron"
+                    )
+                    folium_static(m, width=1000, height=400)
+                except Exception:
+                    st.warning("Map unavailable - location not found")