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742 lines
34 KiB
742 lines
34 KiB
"""
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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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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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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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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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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": {
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"code": "REAL_ESTATE_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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_cache: dict[str, dict] = {}
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_CACHE_TTL_SECONDS = 300
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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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# Invocation logging (in-memory, no sensitive data stored)
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# ---------------------------------------------------------------------------
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_invocation_log: list[dict] = []
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_MAX_LOG_ENTRIES = 500 # prevent unbounded growth
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def _log_invocation(
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function: str,
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query: str,
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duration_ms: float,
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success: bool,
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) -> None:
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"""
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Records a single tool call to the in-memory log.
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query is truncated to 80 chars — no sensitive data stored.
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"""
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entry = {
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"timestamp": datetime.utcnow().isoformat(),
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"function": function,
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"query": query[:80],
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"duration_ms": round(duration_ms, 1),
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"success": success,
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}
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_invocation_log.append(entry)
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# Keep log size bounded
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if len(_invocation_log) > _MAX_LOG_ENTRIES:
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del _invocation_log[: len(_invocation_log) - _MAX_LOG_ENTRIES]
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def get_invocation_log() -> list[dict]:
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"""Returns a copy of the invocation log. Called by the /real-estate/log endpoint."""
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return list(_invocation_log)
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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",
|
|
"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",
|
|
"price": 545_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_400, "price_per_sqft": 389,
|
|
"days_on_market": 11, "listing_type": "Condo", "status": "Active", "year_built": 2017,
|
|
"hoa_monthly": 340, "estimated_monthly_rent": 2_600, "cap_rate_estimate": 4.3,
|
|
"description": "RiNo district condo. Exposed brick, mountain views, walkable to food & art scene.",
|
|
},
|
|
{
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|
"id": "den-002", "address": "4812 W 32nd Ave", "city": "Denver", "state": "CO", "zip": "80212",
|
|
"price": 698_000, "bedrooms": 4, "bathrooms": 3.0, "sqft": 2_400, "price_per_sqft": 291,
|
|
"days_on_market": 17, "listing_type": "Single Family", "status": "Active", "year_built": 2015,
|
|
"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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|
],
|
|
"seattle": [
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{
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|
"id": "sea-001", "address": "1417 NW 63rd St", "city": "Seattle", "state": "WA", "zip": "98107",
|
|
"price": 895_000, "bedrooms": 3, "bathrooms": 2.0, "sqft": 1_750, "price_per_sqft": 511,
|
|
"days_on_market": 8, "listing_type": "Single Family", "status": "Active", "year_built": 2014,
|
|
"hoa_monthly": None, "estimated_monthly_rent": 3_800, "cap_rate_estimate": 4.1,
|
|
"description": "Ballard Craftsman with Puget Sound views. Eco-smart systems, attached garage.",
|
|
},
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|
{
|
|
"id": "sea-002", "address": "220 2nd Ave S #1102", "city": "Seattle", "state": "WA", "zip": "98104",
|
|
"price": 699_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_200, "price_per_sqft": 583,
|
|
"days_on_market": 13, "listing_type": "Condo", "status": "Active", "year_built": 2020,
|
|
"hoa_monthly": 595, "estimated_monthly_rent": 3_200, "cap_rate_estimate": 3.9,
|
|
"description": "Pioneer Square luxury condo. Amazon HQ walking distance, Elliott Bay views.",
|
|
},
|
|
],
|
|
"miami": [
|
|
{
|
|
"id": "mia-001", "address": "1600 Brickell Ave #3204", "city": "Miami", "state": "FL", "zip": "33129",
|
|
"price": 1_200_000, "bedrooms": 3, "bathrooms": 3.0, "sqft": 2_100, "price_per_sqft": 571,
|
|
"days_on_market": 22, "listing_type": "Condo", "status": "Active", "year_built": 2022,
|
|
"hoa_monthly": 1_850, "estimated_monthly_rent": 7_500, "cap_rate_estimate": 5.2,
|
|
"description": "Brickell ultra-luxury unit. Bayfront views, private balcony, 5-star amenities.",
|
|
},
|
|
{
|
|
"id": "mia-002", "address": "355 NE 1st Ave #712", "city": "Miami", "state": "FL", "zip": "33132",
|
|
"price": 435_000, "bedrooms": 1, "bathrooms": 1.0, "sqft": 780, "price_per_sqft": 558,
|
|
"days_on_market": 40, "listing_type": "Condo", "status": "Active", "year_built": 2014,
|
|
"hoa_monthly": 680, "estimated_monthly_rent": 2_800, "cap_rate_estimate": 4.8,
|
|
"description": "Downtown Miami studio + den. Airbnb-allowed building, strong short-term rental income.",
|
|
},
|
|
],
|
|
"chicago": [
|
|
{
|
|
"id": "chi-001", "address": "900 N Michigan Ave #2400", "city": "Chicago", "state": "IL", "zip": "60611",
|
|
"price": 625_000, "bedrooms": 2, "bathrooms": 2.0, "sqft": 1_800, "price_per_sqft": 347,
|
|
"days_on_market": 29, "listing_type": "Condo", "status": "Active", "year_built": 1991,
|
|
"hoa_monthly": 980, "estimated_monthly_rent": 4_200, "cap_rate_estimate": 5.8,
|
|
"description": "Magnificent Mile full-floor unit. Lake Michigan views, white glove service.",
|
|
},
|
|
{
|
|
"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())}"
|
|
_start = time.time()
|
|
|
|
cache_key = f"snapshot:{location.lower()}"
|
|
cached = _cache_get(cache_key)
|
|
if cached:
|
|
_log_invocation("get_neighborhood_snapshot", location, (time.time() - _start) * 1000, True)
|
|
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": {
|
|
"code": "REAL_ESTATE_PROVIDER_UNAVAILABLE",
|
|
"message": (
|
|
f"No data found for '{location}'. "
|
|
f"Supported cities: {', '.join(c.title() for c in _MOCK_SNAPSHOTS)}."
|
|
),
|
|
},
|
|
}
|
|
_log_invocation("get_neighborhood_snapshot", location, (time.time() - _start) * 1000, False)
|
|
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)
|
|
_log_invocation("get_neighborhood_snapshot", location, (time.time() - _start) * 1000, True)
|
|
return result
|
|
|
|
|
|
async def search_listings(
|
|
query: str,
|
|
max_results: int = 5,
|
|
min_beds: int | None = None,
|
|
max_price: int | None = None,
|
|
) -> dict:
|
|
"""
|
|
Searches for listings matching a location query with optional filters.
|
|
|
|
Args:
|
|
query: City/neighborhood name (e.g. "Austin", "Seattle").
|
|
max_results: Cap on number of listings returned (default 5).
|
|
min_beds: Minimum bedroom count filter (e.g. 3 → only 3+ bed listings).
|
|
max_price: Maximum price filter in USD (e.g. 500000 → ≤$500k only).
|
|
"""
|
|
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())}"
|
|
_start = time.time()
|
|
|
|
# Cache key incorporates filters so filtered/unfiltered calls are stored separately
|
|
cache_key = f"search:{query.lower()}:{max_results}:beds={min_beds}:price={max_price}"
|
|
cached = _cache_get(cache_key)
|
|
if cached:
|
|
_log_invocation("search_listings", query, (time.time() - _start) * 1000, True)
|
|
return cached
|
|
|
|
city_key = _normalize_city(query)
|
|
listings = list(_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": {
|
|
"code": "REAL_ESTATE_PROVIDER_UNAVAILABLE",
|
|
"message": (
|
|
f"No listings found for '{query}'. "
|
|
f"Try one of: {', '.join(c.title() for c in all_cities)}."
|
|
),
|
|
},
|
|
}
|
|
_log_invocation("search_listings", query, (time.time() - _start) * 1000, False)
|
|
return result
|
|
|
|
# Apply optional filters before capping
|
|
if min_beds is not None:
|
|
listings = [l for l in listings if l["bedrooms"] >= min_beds]
|
|
if max_price is not None:
|
|
listings = [l for l in listings if l["price"] <= max_price]
|
|
|
|
filters_applied = {}
|
|
if min_beds is not None:
|
|
filters_applied["min_beds"] = min_beds
|
|
if max_price is not None:
|
|
filters_applied["max_price"] = max_price
|
|
|
|
capped = listings[:max_results]
|
|
result = {
|
|
"tool_name": "real_estate",
|
|
"success": True,
|
|
"tool_result_id": tool_result_id,
|
|
"timestamp": datetime.utcnow().isoformat(),
|
|
"result": {
|
|
"query": query,
|
|
"filters_applied": filters_applied,
|
|
"total_returned": len(capped),
|
|
"listings": capped,
|
|
"data_source": "MockProvider v1 — realistic 2024 US market estimates",
|
|
},
|
|
}
|
|
_cache_set(cache_key, result)
|
|
_log_invocation("search_listings", query, (time.time() - _start) * 1000, True)
|
|
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())}"
|
|
_start = time.time()
|
|
|
|
cache_key = f"detail:{listing_id}"
|
|
cached = _cache_get(cache_key)
|
|
if cached:
|
|
_log_invocation("get_listing_details", listing_id, (time.time() - _start) * 1000, True)
|
|
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)
|
|
_log_invocation("get_listing_details", listing_id, (time.time() - _start) * 1000, True)
|
|
return result
|
|
|
|
result = {
|
|
"tool_name": "real_estate",
|
|
"success": False,
|
|
"tool_result_id": tool_result_id,
|
|
"error": {
|
|
"code": "REAL_ESTATE_PROVIDER_UNAVAILABLE",
|
|
"message": (
|
|
f"Listing '{listing_id}' not found. "
|
|
"Use search_listings first to get valid listing IDs."
|
|
),
|
|
},
|
|
}
|
|
_log_invocation("get_listing_details", listing_id, (time.time() - _start) * 1000, False)
|
|
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())}"
|
|
_start = time.time()
|
|
|
|
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:
|
|
_log_invocation(
|
|
"compare_neighborhoods",
|
|
f"{location_a} vs {location_b}",
|
|
(time.time() - _start) * 1000,
|
|
False,
|
|
)
|
|
return {
|
|
"tool_name": "real_estate",
|
|
"success": False,
|
|
"tool_result_id": tool_result_id,
|
|
"error": {
|
|
"code": "REAL_ESTATE_PROVIDER_UNAVAILABLE",
|
|
"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,
|
|
}
|
|
_log_invocation(
|
|
"compare_neighborhoods",
|
|
f"{location_a} vs {location_b}",
|
|
(time.time() - _start) * 1000,
|
|
True,
|
|
)
|
|
return result
|
|
|