app.py

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

# Configure environment
DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_KEY")
API_ENDPOINT = "https://api.deepseek.com/v1/chat/completions"

# Cache expensive operations
@st.cache_data
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

def generate_recommendations(preferences):
    """Generate neighborhood recommendations using Deepseek API"""
    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.
    """
    
    try:
        response = requests.post(
            API_ENDPOINT,
            json={
                "model": "deepseek-chat",
                "messages": [{"role": "user", "content": prompt}],
                "temperature": 0.7,
                "max_tokens": 1500
            },
            headers=headers,
            timeout=30
        )
        return response.json()["choices"][0]["message"]["content"]
    except Exception as e:
        st.error(f"API Error: {str(e)}")
        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"
    ])

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)
            
            # 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.")