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- New tools/real_estate.py: MockProvider with realistic 2024 data for 10 US cities. TTL in-memory cache (5-min). Feature flag: ENABLE_REAL_ESTATE=true/false — false = zero behavior change. - tools/__init__.py: 3 new TOOL_REGISTRY entries (append-only). - README.md: Real Estate demo section with 2-minute run instructions. Made-with: Cursorpull/6453/head
Priyanka Punukollu
1 month ago
3 changed files with 806 additions and 0 deletions
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""" |
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Real Estate Tool — AgentForge integration |
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========================================== |
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Feature flag: set ENABLE_REAL_ESTATE=true in .env to activate. |
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When the flag is absent or false, all functions return a disabled stub |
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and the graph never routes queries here. |
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|
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Three capabilities: |
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1. search_listings(query) — find homes by city/zip/neighborhood |
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2. get_neighborhood_snapshot(location) — market stats for an area |
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3. get_listing_details(listing_id) — full detail for one listing |
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|
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Provider strategy: |
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- MockProvider (default, always safe): realistic sample data for 10 US cities. |
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Works offline, zero latency, no API key required. |
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- Real provider (future drop-in): swap _PROVIDER to "attom" or "rapidapi" and |
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set REAL_ESTATE_API_KEY. The normalize schema is identical. |
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|
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Data schema (NormalizedListing): |
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id, address, city, state, zip, price, bedrooms, bathrooms, sqft, |
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price_per_sqft, days_on_market, listing_type, status, year_built, |
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hoa_monthly, estimated_monthly_rent, cap_rate_estimate, description |
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Data schema (NeighborhoodSnapshot): |
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city, state, median_price, price_per_sqft, median_dom, |
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price_change_yoy_pct, inventory_level, walk_score, listings_count, |
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rent_to_price_ratio, market_summary |
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""" |
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import os |
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import time |
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from datetime import datetime |
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# --------------------------------------------------------------------------- |
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# Feature flag |
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# --------------------------------------------------------------------------- |
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|
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def is_real_estate_enabled() -> bool: |
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"""Returns True only when ENABLE_REAL_ESTATE=true in environment.""" |
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return os.getenv("ENABLE_REAL_ESTATE", "false").strip().lower() == "true" |
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_FEATURE_DISABLED_RESPONSE = { |
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"tool_name": "real_estate", |
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"success": False, |
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"tool_result_id": "real_estate_disabled", |
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"error": "FEATURE_DISABLED", |
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"message": ( |
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"The Real Estate feature is not currently enabled. " |
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"Set ENABLE_REAL_ESTATE=true in your environment to activate it." |
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), |
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} |
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|
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# --------------------------------------------------------------------------- |
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# In-memory TTL cache (5-minute TTL, safe for a single-process server) |
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# --------------------------------------------------------------------------- |
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|
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_cache: dict[str, dict] = {} |
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_CACHE_TTL_SECONDS = 300 |
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|
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def _cache_get(key: str) -> dict | None: |
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entry = _cache.get(key) |
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if entry and (time.time() - entry["ts"]) < _CACHE_TTL_SECONDS: |
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return entry["data"] |
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return None |
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def _cache_set(key: str, data: dict) -> None: |
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_cache[key] = {"ts": time.time(), "data": data} |
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def cache_clear() -> None: |
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"""Clears the entire in-memory cache. Used in tests.""" |
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_cache.clear() |
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|
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# --------------------------------------------------------------------------- |
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# Mock data — realistic 2024 US market data for 10 metros |
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# --------------------------------------------------------------------------- |
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_MOCK_SNAPSHOTS: dict[str, dict] = { |
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"austin": { |
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"city": "Austin", "state": "TX", |
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"median_price": 485_000, "price_per_sqft": 285, |
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"median_dom": 24, "price_change_yoy_pct": -3.2, |
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"inventory_level": "low", "walk_score": 48, |
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"listings_count": 1_847, "rent_to_price_ratio": 0.48, |
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"market_summary": ( |
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"Austin remains a seller's market with limited inventory. " |
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"Prices have cooled slightly YoY (-3.2%) after the pandemic spike, " |
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"creating buying opportunities for long-term investors. " |
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"Tech sector concentration adds income stability to the renter pool." |
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), |
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}, |
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"san francisco": { |
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"city": "San Francisco", "state": "CA", |
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"median_price": 1_250_000, "price_per_sqft": 980, |
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"median_dom": 18, "price_change_yoy_pct": -5.8, |
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"inventory_level": "very low", "walk_score": 88, |
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"listings_count": 612, "rent_to_price_ratio": 0.33, |
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"market_summary": ( |
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"San Francisco has seen significant price correction (-5.8% YoY) " |
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"driven by remote-work migration. Very low inventory keeps prices " |
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"elevated despite demand softening. High rental demand from remaining " |
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"tech workforce supports rental yields." |
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), |
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}, |
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"new york": { |
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"city": "New York", "state": "NY", |
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"median_price": 750_000, "price_per_sqft": 820, |
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"median_dom": 31, "price_change_yoy_pct": 1.4, |
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"inventory_level": "moderate", "walk_score": 95, |
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"listings_count": 4_200, "rent_to_price_ratio": 0.52, |
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"market_summary": ( |
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"NYC market shows resilience with modest 1.4% YoY appreciation. " |
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"Moderate inventory gives buyers more negotiating power than 2021–2022. " |
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"Strong rental demand across all boroughs supports investor ROI. " |
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"High walkability (95) is a key demand driver." |
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), |
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}, |
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"denver": { |
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"city": "Denver", "state": "CO", |
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"median_price": 520_000, "price_per_sqft": 310, |
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"median_dom": 19, "price_change_yoy_pct": -1.7, |
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"inventory_level": "low", "walk_score": 60, |
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"listings_count": 2_100, "rent_to_price_ratio": 0.46, |
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"market_summary": ( |
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"Denver market stabilizing after rapid appreciation. " |
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"Slight YoY decline (-1.7%) brings affordability back into range. " |
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"Strong job market in tech and healthcare supports buyer demand. " |
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"Low inventory keeps days-on-market competitive at 19 days." |
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), |
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}, |
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"seattle": { |
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"city": "Seattle", "state": "WA", |
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"median_price": 780_000, "price_per_sqft": 490, |
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"median_dom": 14, "price_change_yoy_pct": 2.1, |
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"inventory_level": "very low", "walk_score": 73, |
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"listings_count": 890, "rent_to_price_ratio": 0.38, |
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"market_summary": ( |
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"Seattle is one of the tightest markets nationally, averaging just " |
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"14 days on market. Amazon and Microsoft campuses sustain strong " |
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"demand. Prices ticked up 2.1% YoY. Very low inventory means " |
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"buyers face competition and often waive contingencies." |
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), |
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}, |
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"miami": { |
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"city": "Miami", "state": "FL", |
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"median_price": 620_000, "price_per_sqft": 425, |
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"median_dom": 38, "price_change_yoy_pct": 4.3, |
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"inventory_level": "moderate", "walk_score": 62, |
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"listings_count": 3_540, "rent_to_price_ratio": 0.55, |
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"market_summary": ( |
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"Miami continues to attract domestic migration from high-tax states, " |
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"pushing prices up 4.3% YoY — one of the strongest gains in the US. " |
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"Rising insurance costs are a headwind for buyers. " |
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"Strong Airbnb and short-term rental demand boosts investor returns." |
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), |
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}, |
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"chicago": { |
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"city": "Chicago", "state": "IL", |
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"median_price": 310_000, "price_per_sqft": 195, |
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"median_dom": 28, "price_change_yoy_pct": 0.8, |
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"inventory_level": "moderate", "walk_score": 78, |
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"listings_count": 5_100, "rent_to_price_ratio": 0.68, |
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"market_summary": ( |
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"Chicago offers strong cash-flow potential with the highest " |
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"rent-to-price ratio (0.68%) of major metros. Stable pricing " |
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"with modest 0.8% YoY appreciation. Property taxes are a key " |
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"consideration for investors — factor 2–3% of home value annually." |
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), |
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}, |
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"phoenix": { |
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"city": "Phoenix", "state": "AZ", |
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"median_price": 415_000, "price_per_sqft": 240, |
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"median_dom": 32, "price_change_yoy_pct": -2.1, |
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"inventory_level": "high", "walk_score": 41, |
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"listings_count": 6_200, "rent_to_price_ratio": 0.50, |
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"market_summary": ( |
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"Phoenix is a buyer's market with the highest inventory of major metros. " |
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"Prices down 2.1% YoY after the post-pandemic boom. " |
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"Longer days on market (32) gives buyers negotiating leverage. " |
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"Strong population growth from CA migration supports long-term demand." |
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), |
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}, |
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"nashville": { |
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"city": "Nashville", "state": "TN", |
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"median_price": 450_000, "price_per_sqft": 265, |
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"median_dom": 21, "price_change_yoy_pct": 1.2, |
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"inventory_level": "low", "walk_score": 32, |
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"listings_count": 1_650, "rent_to_price_ratio": 0.49, |
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"market_summary": ( |
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"Nashville is a fast-growing Sun Belt market with strong employment " |
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"from healthcare, tech, and entertainment sectors. Low inventory and " |
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"short DOM (21 days) reflect healthy demand. " |
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"No state income tax makes it attractive for relocators." |
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), |
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}, |
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"dallas": { |
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"city": "Dallas", "state": "TX", |
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"median_price": 395_000, "price_per_sqft": 215, |
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"median_dom": 27, "price_change_yoy_pct": -0.5, |
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"inventory_level": "moderate", "walk_score": 37, |
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"listings_count": 4_800, "rent_to_price_ratio": 0.53, |
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"market_summary": ( |
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"Dallas-Fort Worth offers solid value with near-flat YoY pricing. " |
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"Large inventory gives buyers choices without the frenzy of 2021–2022. " |
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"Corporate relocations (Goldman Sachs, Oracle, HP) provide long-term " |
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"demand foundation. No state income tax is a major draw." |
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), |
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}, |
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} |
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_MOCK_LISTINGS: dict[str, list[dict]] = { |
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"austin": [ |
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{ |
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"id": "atx-001", "address": "2847 Barton Hills Dr", "city": "Austin", "state": "TX", "zip": "78704", |
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"price": 525_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_850, "price_per_sqft": 284, |
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"days_on_market": 12, "listing_type": "Single Family", "status": "Active", "year_built": 2018, |
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"hoa_monthly": None, "estimated_monthly_rent": 2_800, "cap_rate_estimate": 4.8, |
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"description": "Modern craftsman in sought-after 78704. Open floor plan, chef's kitchen, private backyard.", |
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}, |
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{ |
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"id": "atx-002", "address": "5120 Mueller Blvd #403", "city": "Austin", "state": "TX", "zip": "78723", |
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"price": 389_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_100, "price_per_sqft": 354, |
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"days_on_market": 34, "listing_type": "Condo", "status": "Active", "year_built": 2021, |
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"hoa_monthly": 285, "estimated_monthly_rent": 2_200, "cap_rate_estimate": 4.2, |
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"description": "Luxury condo in Mueller district. Rooftop deck, concierge, walkable to restaurants.", |
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}, |
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{ |
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"id": "atx-003", "address": "3901 Govalle Ave", "city": "Austin", "state": "TX", "zip": "78702", |
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"price": 595_000, "bedrooms": 4, "bathrooms": 3.0, "sqft": 2_200, "price_per_sqft": 270, |
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"days_on_market": 7, "listing_type": "Single Family", "status": "Active", "year_built": 2016, |
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"hoa_monthly": None, "estimated_monthly_rent": 3_200, "cap_rate_estimate": 5.0, |
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"description": "Spacious east Austin home. ADU potential, mature trees, 5 min from downtown.", |
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}, |
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{ |
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"id": "atx-004", "address": "1204 W 6th St #8", "city": "Austin", "state": "TX", "zip": "78703", |
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"price": 699_000, "bedrooms": 3, "bathrooms": 2.5, "sqft": 1_950, "price_per_sqft": 358, |
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"days_on_market": 19, "listing_type": "Townhouse", "status": "Active", "year_built": 2020, |
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"hoa_monthly": 175, "estimated_monthly_rent": 3_600, "cap_rate_estimate": 4.5, |
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"description": "Premium Clarksville townhome. Rooftop terrace with downtown skyline views.", |
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}, |
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{ |
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"id": "atx-005", "address": "7824 Manchaca Rd", "city": "Austin", "state": "TX", "zip": "78745", |
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"price": 349_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_450, "price_per_sqft": 241, |
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"days_on_market": 42, "listing_type": "Single Family", "status": "Price Reduced", "year_built": 2003, |
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"hoa_monthly": None, "estimated_monthly_rent": 2_100, "cap_rate_estimate": 5.4, |
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"description": "Best value in South Austin. Newly renovated kitchen, large yard, no HOA.", |
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}, |
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], |
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"san francisco": [ |
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{ |
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"id": "sfo-001", "address": "1847 Castro St", "city": "San Francisco", "state": "CA", "zip": "94114", |
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"price": 1_450_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_600, "price_per_sqft": 906, |
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"days_on_market": 9, "listing_type": "Single Family", "status": "Active", "year_built": 1924, |
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"hoa_monthly": None, "estimated_monthly_rent": 5_200, "cap_rate_estimate": 3.4, |
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"description": "Classic Victorian in the Castro. Period details preserved, updated kitchen and baths.", |
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}, |
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{ |
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"id": "sfo-002", "address": "488 Folsom St #2105", "city": "San Francisco", "state": "CA", "zip": "94105", |
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"price": 1_100_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_050, "price_per_sqft": 1_048, |
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"days_on_market": 22, "listing_type": "Condo", "status": "Active", "year_built": 2018, |
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"hoa_monthly": 890, "estimated_monthly_rent": 4_800, "cap_rate_estimate": 3.2, |
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"description": "Luxury high-rise with bay views. Full-service building, concierge, parking included.", |
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}, |
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{ |
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"id": "sfo-003", "address": "222 Dolores St #7", "city": "San Francisco", "state": "CA", "zip": "94103", |
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"price": 875_000, "bedrooms": 1, "bathrooms": 1.0, "sqft": 780, "price_per_sqft": 1_122, |
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"days_on_market": 14, "listing_type": "Condo", "status": "Active", "year_built": 2015, |
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"hoa_monthly": 620, "estimated_monthly_rent": 3_600, "cap_rate_estimate": 3.0, |
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"description": "Designer Mission condo. Chef's kitchen, private patio, storage included.", |
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}, |
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], |
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"new york": [ |
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{ |
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"id": "nyc-001", "address": "200 Water St #8B", "city": "New York", "state": "NY", "zip": "10038", |
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"price": 895_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_100, "price_per_sqft": 814, |
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"days_on_market": 18, "listing_type": "Condo", "status": "Active", "year_built": 2006, |
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"hoa_monthly": 1_240, "estimated_monthly_rent": 5_800, "cap_rate_estimate": 4.6, |
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"description": "FiDi condo with East River views. Doorman, gym, roof deck. Minutes from Wall St.", |
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}, |
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{ |
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"id": "nyc-002", "address": "78 N 7th St #4D", "city": "Brooklyn", "state": "NY", "zip": "11249", |
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"price": 1_100_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_350, "price_per_sqft": 815, |
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"days_on_market": 25, "listing_type": "Condo", "status": "Active", "year_built": 2019, |
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"hoa_monthly": 780, "estimated_monthly_rent": 5_500, "cap_rate_estimate": 4.2, |
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"description": "Williamsburg luxury condo. Industrial chic design, private outdoor space.", |
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}, |
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{ |
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"id": "nyc-003", "address": "310 W 55th St #7C", "city": "New York", "state": "NY", "zip": "10019", |
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"price": 649_000, "bedrooms": 1, "bathrooms": 1.0, "sqft": 650, "price_per_sqft": 998, |
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"days_on_market": 31, "listing_type": "Coop", "status": "Active", "year_built": 1967, |
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"hoa_monthly": 1_450, "estimated_monthly_rent": 3_800, "cap_rate_estimate": 3.5, |
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"description": "Classic midtown co-op. Full-service white glove building, 4 blocks from Central Park.", |
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}, |
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], |
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"denver": [ |
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{ |
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"id": "den-001", "address": "2345 Larimer St #601", "city": "Denver", "state": "CO", "zip": "80205", |
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"price": 545_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_400, "price_per_sqft": 389, |
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"days_on_market": 11, "listing_type": "Condo", "status": "Active", "year_built": 2017, |
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"hoa_monthly": 340, "estimated_monthly_rent": 2_600, "cap_rate_estimate": 4.3, |
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"description": "RiNo district condo. Exposed brick, mountain views, walkable to food & art scene.", |
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}, |
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{ |
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"id": "den-002", "address": "4812 W 32nd Ave", "city": "Denver", "state": "CO", "zip": "80212", |
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"price": 698_000, "bedrooms": 4, "bathrooms": 3.0, "sqft": 2_400, "price_per_sqft": 291, |
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"days_on_market": 17, "listing_type": "Single Family", "status": "Active", "year_built": 2015, |
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"hoa_monthly": None, "estimated_monthly_rent": 3_400, "cap_rate_estimate": 4.8, |
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"description": "Highland neighborhood gem. Chef's kitchen, finished basement, large backyard deck.", |
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}, |
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], |
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"seattle": [ |
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{ |
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"id": "sea-001", "address": "1417 NW 63rd St", "city": "Seattle", "state": "WA", "zip": "98107", |
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"price": 895_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_750, "price_per_sqft": 511, |
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"days_on_market": 8, "listing_type": "Single Family", "status": "Active", "year_built": 2014, |
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"hoa_monthly": None, "estimated_monthly_rent": 3_800, "cap_rate_estimate": 4.1, |
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"description": "Ballard Craftsman with Puget Sound views. Eco-smart systems, attached garage.", |
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}, |
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{ |
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"id": "sea-002", "address": "220 2nd Ave S #1102", "city": "Seattle", "state": "WA", "zip": "98104", |
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"price": 699_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_200, "price_per_sqft": 583, |
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"days_on_market": 13, "listing_type": "Condo", "status": "Active", "year_built": 2020, |
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"hoa_monthly": 595, "estimated_monthly_rent": 3_200, "cap_rate_estimate": 3.9, |
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"description": "Pioneer Square luxury condo. Amazon HQ walking distance, Elliott Bay views.", |
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}, |
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], |
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"miami": [ |
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{ |
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"id": "mia-001", "address": "1600 Brickell Ave #3204", "city": "Miami", "state": "FL", "zip": "33129", |
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"price": 1_200_000, "bedrooms": 3, "bathrooms": 3.0, "sqft": 2_100, "price_per_sqft": 571, |
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"days_on_market": 22, "listing_type": "Condo", "status": "Active", "year_built": 2022, |
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"hoa_monthly": 1_850, "estimated_monthly_rent": 7_500, "cap_rate_estimate": 5.2, |
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"description": "Brickell ultra-luxury unit. Bayfront views, private balcony, 5-star amenities.", |
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}, |
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{ |
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"id": "mia-002", "address": "355 NE 1st Ave #712", "city": "Miami", "state": "FL", "zip": "33132", |
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"price": 435_000, "bedrooms": 1, "bathrooms": 1.0, "sqft": 780, "price_per_sqft": 558, |
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"days_on_market": 40, "listing_type": "Condo", "status": "Active", "year_built": 2014, |
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"hoa_monthly": 680, "estimated_monthly_rent": 2_800, "cap_rate_estimate": 4.8, |
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"description": "Downtown Miami studio + den. Airbnb-allowed building, strong short-term rental income.", |
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}, |
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], |
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"chicago": [ |
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{ |
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"id": "chi-001", "address": "900 N Michigan Ave #2400", "city": "Chicago", "state": "IL", "zip": "60611", |
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"price": 625_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_800, "price_per_sqft": 347, |
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"days_on_market": 29, "listing_type": "Condo", "status": "Active", "year_built": 1991, |
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"hoa_monthly": 980, "estimated_monthly_rent": 4_200, "cap_rate_estimate": 5.8, |
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"description": "Magnificent Mile full-floor unit. Lake Michigan views, white glove service.", |
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}, |
|||
{ |
|||
"id": "chi-002", "address": "2140 N Damen Ave", "city": "Chicago", "state": "IL", "zip": "60647", |
|||
"price": 485_000, "bedrooms": 3, "bathrooms": 2.5, "sqft": 2_100, "price_per_sqft": 231, |
|||
"days_on_market": 20, "listing_type": "Single Family", "status": "Active", "year_built": 2008, |
|||
"hoa_monthly": None, "estimated_monthly_rent": 3_200, "cap_rate_estimate": 6.2, |
|||
"description": "Bucktown greystone townhome. Finished basement, private garage, top-rated schools.", |
|||
}, |
|||
], |
|||
"phoenix": [ |
|||
{ |
|||
"id": "phx-001", "address": "4820 E Camelback Rd", "city": "Phoenix", "state": "AZ", "zip": "85018", |
|||
"price": 625_000, "bedrooms": 4, "bathrooms": 3.0, "sqft": 2_800, "price_per_sqft": 223, |
|||
"days_on_market": 38, "listing_type": "Single Family", "status": "Price Reduced", "year_built": 2005, |
|||
"hoa_monthly": 95, "estimated_monthly_rent": 3_200, "cap_rate_estimate": 4.9, |
|||
"description": "Arcadia location with Camelback Mountain views. Pool, 3-car garage, gourmet kitchen.", |
|||
}, |
|||
], |
|||
"nashville": [ |
|||
{ |
|||
"id": "nas-001", "address": "600 12th Ave S #405", "city": "Nashville", "state": "TN", "zip": "37203", |
|||
"price": 489_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_350, "price_per_sqft": 362, |
|||
"days_on_market": 15, "listing_type": "Condo", "status": "Active", "year_built": 2020, |
|||
"hoa_monthly": 320, "estimated_monthly_rent": 2_800, "cap_rate_estimate": 5.1, |
|||
"description": "The Gulch walkable condo. No-state-income-tax advantage, steps to Broadway.", |
|||
}, |
|||
], |
|||
"dallas": [ |
|||
{ |
|||
"id": "dfw-001", "address": "3421 McKinney Ave #207", "city": "Dallas", "state": "TX", "zip": "75204", |
|||
"price": 389_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_200, "price_per_sqft": 324, |
|||
"days_on_market": 21, "listing_type": "Condo", "status": "Active", "year_built": 2019, |
|||
"hoa_monthly": 290, "estimated_monthly_rent": 2_400, "cap_rate_estimate": 5.4, |
|||
"description": "Uptown Dallas condo. Pet-friendly, resort-style amenities, walkable to dining.", |
|||
}, |
|||
], |
|||
} |
|||
|
|||
|
|||
def _normalize_city(location: str) -> str: |
|||
"""Maps query string to a canonical city key in mock data.""" |
|||
loc = location.lower().strip() |
|||
mapping = { |
|||
"atx": "austin", "austin tx": "austin", "austin, tx": "austin", |
|||
"sf": "san francisco", "sfo": "san francisco", "san francisco ca": "san francisco", |
|||
"nyc": "new york", "new york city": "new york", "manhattan": "new york", "brooklyn": "new york", |
|||
"denver co": "denver", "denver, co": "denver", |
|||
"seattle wa": "seattle", "seattle, wa": "seattle", |
|||
"miami fl": "miami", "miami, fl": "miami", |
|||
"chicago il": "chicago", "chicago, il": "chicago", |
|||
"phoenix az": "phoenix", "phoenix, az": "phoenix", |
|||
"nashville tn": "nashville", "nashville, tn": "nashville", |
|||
"dallas tx": "dallas", "dallas, tx": "dallas", "dfw": "dallas", |
|||
} |
|||
if loc in mapping: |
|||
return mapping[loc] |
|||
for city_key in _MOCK_SNAPSHOTS: |
|||
if city_key in loc: |
|||
return city_key |
|||
return "" |
|||
|
|||
|
|||
# --------------------------------------------------------------------------- |
|||
# Public tool functions — all follow the standard tool result schema |
|||
# --------------------------------------------------------------------------- |
|||
|
|||
async def get_neighborhood_snapshot(location: str) -> dict: |
|||
""" |
|||
Returns market-level stats for a city or neighborhood. |
|||
Covers: median price, DOM, YoY change, inventory level, walk score, |
|||
rent-to-price ratio, market summary. |
|||
""" |
|||
if not is_real_estate_enabled(): |
|||
return _FEATURE_DISABLED_RESPONSE |
|||
|
|||
location = location.strip() |
|||
tool_result_id = f"re_snapshot_{location.lower().replace(' ', '_')}_{int(datetime.utcnow().timestamp())}" |
|||
|
|||
cache_key = f"snapshot:{location.lower()}" |
|||
cached = _cache_get(cache_key) |
|||
if cached: |
|||
return cached |
|||
|
|||
city_key = _normalize_city(location) |
|||
snap = _MOCK_SNAPSHOTS.get(city_key) |
|||
|
|||
if not snap: |
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": False, |
|||
"tool_result_id": tool_result_id, |
|||
"error": "LOCATION_NOT_FOUND", |
|||
"message": ( |
|||
f"No data found for '{location}'. " |
|||
f"Supported cities: {', '.join(c.title() for c in _MOCK_SNAPSHOTS)}." |
|||
), |
|||
} |
|||
return result |
|||
|
|||
monthly_rent_estimate = round(snap["median_price"] * snap["rent_to_price_ratio"] / 100, 0) |
|||
gross_yield = round(snap["rent_to_price_ratio"] * 12 / 100 * 100, 2) |
|||
|
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": True, |
|||
"tool_result_id": tool_result_id, |
|||
"timestamp": datetime.utcnow().isoformat(), |
|||
"result": { |
|||
"location": f"{snap['city']}, {snap['state']}", |
|||
"median_price": snap["median_price"], |
|||
"price_per_sqft": snap["price_per_sqft"], |
|||
"median_days_on_market": snap["median_dom"], |
|||
"price_change_yoy_pct": snap["price_change_yoy_pct"], |
|||
"inventory_level": snap["inventory_level"], |
|||
"walk_score": snap["walk_score"], |
|||
"active_listings_count": snap["listings_count"], |
|||
"estimated_median_monthly_rent": monthly_rent_estimate, |
|||
"gross_rental_yield_pct": gross_yield, |
|||
"market_summary": snap["market_summary"], |
|||
"data_source": "MockProvider v1 — realistic 2024 US market estimates", |
|||
}, |
|||
} |
|||
_cache_set(cache_key, result) |
|||
return result |
|||
|
|||
|
|||
async def search_listings(query: str, max_results: int = 5) -> dict: |
|||
""" |
|||
Searches for listings matching a location query. |
|||
Returns up to max_results normalized listings with key metrics. |
|||
""" |
|||
if not is_real_estate_enabled(): |
|||
return _FEATURE_DISABLED_RESPONSE |
|||
|
|||
query = query.strip() |
|||
tool_result_id = f"re_search_{query.lower().replace(' ', '_')}_{int(datetime.utcnow().timestamp())}" |
|||
|
|||
cache_key = f"search:{query.lower()}:{max_results}" |
|||
cached = _cache_get(cache_key) |
|||
if cached: |
|||
return cached |
|||
|
|||
city_key = _normalize_city(query) |
|||
listings = _MOCK_LISTINGS.get(city_key, []) |
|||
|
|||
if not listings: |
|||
all_cities = list(_MOCK_LISTINGS.keys()) |
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": False, |
|||
"tool_result_id": tool_result_id, |
|||
"error": "NO_LISTINGS_FOUND", |
|||
"message": ( |
|||
f"No listings found for '{query}'. " |
|||
f"Try one of: {', '.join(c.title() for c in all_cities)}." |
|||
), |
|||
} |
|||
return result |
|||
|
|||
capped = listings[:max_results] |
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": True, |
|||
"tool_result_id": tool_result_id, |
|||
"timestamp": datetime.utcnow().isoformat(), |
|||
"result": { |
|||
"query": query, |
|||
"total_returned": len(capped), |
|||
"listings": capped, |
|||
"data_source": "MockProvider v1 — realistic 2024 US market estimates", |
|||
}, |
|||
} |
|||
_cache_set(cache_key, result) |
|||
return result |
|||
|
|||
|
|||
async def get_listing_details(listing_id: str) -> dict: |
|||
""" |
|||
Returns full detail for a single listing by its ID (e.g. 'atx-001'). |
|||
""" |
|||
if not is_real_estate_enabled(): |
|||
return _FEATURE_DISABLED_RESPONSE |
|||
|
|||
listing_id = listing_id.strip().lower() |
|||
tool_result_id = f"re_detail_{listing_id}_{int(datetime.utcnow().timestamp())}" |
|||
|
|||
cache_key = f"detail:{listing_id}" |
|||
cached = _cache_get(cache_key) |
|||
if cached: |
|||
return cached |
|||
|
|||
for city_listings in _MOCK_LISTINGS.values(): |
|||
for listing in city_listings: |
|||
if listing["id"].lower() == listing_id: |
|||
# Enrich with affordability metrics |
|||
enriched = dict(listing) |
|||
monthly_payment_est = round(listing["price"] * 0.8 * 0.00532, 0) # ~6.5% 30yr, 20% down |
|||
annual_rent = listing["estimated_monthly_rent"] * 12 |
|||
enriched["estimated_monthly_mortgage"] = monthly_payment_est |
|||
enriched["annual_gross_rental_income"] = annual_rent |
|||
enriched["gross_cap_rate_pct"] = listing["cap_rate_estimate"] |
|||
|
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": True, |
|||
"tool_result_id": tool_result_id, |
|||
"timestamp": datetime.utcnow().isoformat(), |
|||
"result": enriched, |
|||
} |
|||
_cache_set(cache_key, result) |
|||
return result |
|||
|
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": False, |
|||
"tool_result_id": tool_result_id, |
|||
"error": "LISTING_NOT_FOUND", |
|||
"message": ( |
|||
f"Listing '{listing_id}' not found. " |
|||
"Use search_listings first to get valid listing IDs." |
|||
), |
|||
} |
|||
return result |
|||
|
|||
|
|||
async def compare_neighborhoods(location_a: str, location_b: str) -> dict: |
|||
""" |
|||
Compares two cities/neighborhoods side by side on key investment metrics. |
|||
Returns a structured comparison useful for commute/affordability tradeoffs. |
|||
""" |
|||
if not is_real_estate_enabled(): |
|||
return _FEATURE_DISABLED_RESPONSE |
|||
|
|||
tool_result_id = f"re_compare_{int(datetime.utcnow().timestamp())}" |
|||
|
|||
snap_a = await get_neighborhood_snapshot(location_a) |
|||
snap_b = await get_neighborhood_snapshot(location_b) |
|||
|
|||
failed = [] |
|||
if not snap_a.get("success"): |
|||
failed.append(location_a) |
|||
if not snap_b.get("success"): |
|||
failed.append(location_b) |
|||
|
|||
if failed: |
|||
return { |
|||
"tool_name": "real_estate", |
|||
"success": False, |
|||
"tool_result_id": tool_result_id, |
|||
"error": "LOCATION_NOT_FOUND", |
|||
"message": f"Could not find data for: {', '.join(failed)}.", |
|||
} |
|||
|
|||
a = snap_a["result"] |
|||
b = snap_b["result"] |
|||
|
|||
def _winner(val_a, val_b, lower_is_better: bool = False): |
|||
if lower_is_better: |
|||
return a["location"] if val_a < val_b else b["location"] |
|||
return a["location"] if val_a > val_b else b["location"] |
|||
|
|||
comparison = { |
|||
"location_a": a["location"], |
|||
"location_b": b["location"], |
|||
"metrics": { |
|||
"median_price": {"a": a["median_price"], "b": b["median_price"], |
|||
"more_affordable": _winner(a["median_price"], b["median_price"], lower_is_better=True)}, |
|||
"price_per_sqft": {"a": a["price_per_sqft"], "b": b["price_per_sqft"], |
|||
"more_affordable": _winner(a["price_per_sqft"], b["price_per_sqft"], lower_is_better=True)}, |
|||
"gross_rental_yield_pct": {"a": a["gross_rental_yield_pct"], "b": b["gross_rental_yield_pct"], |
|||
"higher_yield": _winner(a["gross_rental_yield_pct"], b["gross_rental_yield_pct"])}, |
|||
"days_on_market": {"a": a["median_days_on_market"], "b": b["median_days_on_market"], |
|||
"less_competitive": _winner(a["median_days_on_market"], b["median_days_on_market"])}, |
|||
"walk_score": {"a": a["walk_score"], "b": b["walk_score"], |
|||
"more_walkable": _winner(a["walk_score"], b["walk_score"])}, |
|||
"yoy_price_change_pct": {"a": a["price_change_yoy_pct"], "b": b["price_change_yoy_pct"]}, |
|||
"inventory": {"a": a["inventory_level"], "b": b["inventory_level"]}, |
|||
}, |
|||
"summaries": { |
|||
a["location"]: a["market_summary"], |
|||
b["location"]: b["market_summary"], |
|||
}, |
|||
"data_source": "MockProvider v1 — realistic 2024 US market estimates", |
|||
} |
|||
|
|||
result = { |
|||
"tool_name": "real_estate", |
|||
"success": True, |
|||
"tool_result_id": tool_result_id, |
|||
"timestamp": datetime.utcnow().isoformat(), |
|||
"result": comparison, |
|||
} |
|||
return result |
|||
Loading…
Reference in new issue