Spaces:
Sleeping
Sleeping
File size: 9,188 Bytes
649703e 77c968b 649703e 77c968b 649703e 77c968b 649703e 77c968b 649703e 77c968b 649703e 77c968b 649703e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 | """
orchestrator.py — Tripplanner search orchestrator.
Coordinates Delta, IHG, and Resy subagents sequentially over a single shared
BrowserSession, then merges their results into ranked TripResult objects.
"""
from __future__ import annotations
import os
import asyncio
from typing import Callable
from .models import (
TripSearchRequest,
FlightOption,
HotelOption,
RestaurantOption,
TripResult,
SearchProgress,
)
from .tools.browser import BrowserSession
from .agents.delta_agent import search_companion_cert
from .agents.ihg_agent import search_points_availability
from .agents.resy_agent import find_resy_restaurants
# ---------------------------------------------------------------------------
# Public helpers
# ---------------------------------------------------------------------------
def calculate_cash_out_of_pocket(
flight: FlightOption,
hotel: HotelOption | None,
) -> float:
"""
Return the total cash the traveler pays.
The companion's ticket is covered by the certificate; they only owe the
companion_taxes. Hotel is redeemed with points so costs $0 cash.
Restaurant dining credit is separate from this calculation.
"""
# Primary ticket + companion taxes (companion cert covers the fare itself)
return flight.base_price + flight.companion_taxes
def collect_benefits(
flight: FlightOption,
hotel: HotelOption | None,
restaurant: RestaurantOption | None,
) -> list[str]:
"""Return human-readable benefit strings for a trip combination."""
benefits: list[str] = []
if flight.eligible_for_companion_cert:
benefits.append("Delta companion certificate used")
if hotel is not None:
if hotel.nights_free > 0:
benefits.append(
f"IHG 4th night free ({hotel.nights_free} night{'s' if hotel.nights_free != 1 else ''} free)"
)
else:
benefits.append(f"IHG points redemption at {hotel.property_name}")
if restaurant is not None:
if restaurant.resy_credit_eligible:
benefits.append("Resy $20 dining credit eligible")
if restaurant.global_dining_access:
benefits.append(f"Global Dining Access reservation at {restaurant.name}")
return benefits
# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------
def _score_trip(
flight: FlightOption,
hotel: HotelOption | None,
restaurant: RestaurantOption | None,
) -> float:
"""
Score a trip combination on a 0–100 scale.
Breakdown:
+40 companion cert eligible
+30 hotel found with points availability
+15 restaurant found
+15 value score (lower cash out of pocket relative to flight base price)
"""
score = 0.0
if flight.eligible_for_companion_cert:
score += 40.0
if hotel is not None:
score += 30.0
if restaurant is not None:
score += 15.0
# Value component: full +15 when cash_out == companion_taxes only (i.e.
# traveler saved the most), scaling down as cash_out approaches base_price*2.
cash_out = calculate_cash_out_of_pocket(flight, hotel)
max_possible_cash = flight.base_price * 2 # both tickets at full price
if max_possible_cash > 0:
savings_ratio = 1.0 - (cash_out / max_possible_cash)
# Clamp to [0, 1] so edge cases don't break the scale.
savings_ratio = max(0.0, min(1.0, savings_ratio))
score += savings_ratio * 15.0
return round(score, 2)
def _extract_date_pairs(
flights: list[FlightOption],
) -> list[tuple[str, str]]:
"""Return (check_in_iso, check_out_iso) pairs from flight results."""
return [
(flight.outbound_date.isoformat(), flight.return_date.isoformat())
for flight in flights
]
def _extract_destinations(flights: list[FlightOption]) -> list[str]:
return list(dict.fromkeys(flight.destination for flight in flights))
def _extract_cities_and_arrival_dates(
flights: list[FlightOption],
) -> tuple[list[str], list[str]]:
cities = list(dict.fromkeys(flight.destination for flight in flights))
arrival_dates = list(
dict.fromkeys(flight.outbound_date.isoformat() for flight in flights)
)
return cities, arrival_dates
def _find_matching_hotel(
flight: FlightOption,
hotels: list[HotelOption],
) -> HotelOption | None:
"""Return the first HotelOption whose destination and dates overlap the flight."""
for hotel in hotels:
if hotel.destination != flight.destination:
continue
# Dates overlap when check_in <= return_date AND check_out >= outbound_date
if hotel.check_in <= flight.return_date and hotel.check_out >= flight.outbound_date:
return hotel
return None
def _find_matching_restaurant(
flight: FlightOption,
restaurants: list[RestaurantOption],
) -> RestaurantOption | None:
"""Return the first RestaurantOption matching the flight city and arrival date."""
for restaurant in restaurants:
if (
restaurant.city == flight.destination
and restaurant.reservation_date == flight.outbound_date
):
return restaurant
return None
def _emit(
callback: Callable[[SearchProgress], None],
step: str,
message: str,
progress: int,
) -> None:
callback(SearchProgress(step=step, message=message, progress=progress))
# ---------------------------------------------------------------------------
# Main orchestrator
# ---------------------------------------------------------------------------
async def run_trip_search(
request: TripSearchRequest,
progress_callback: Callable[[SearchProgress], None],
) -> list[TripResult]:
"""
Coordinate Delta, IHG, and Resy subagents and return ranked TripResult list.
All three agents share a single BrowserSession so that login state is
preserved across site transitions.
"""
user_data_dir = os.environ.get("BROWSER_USER_DATA_DIR", "./browser_data")
async with BrowserSession(user_data_dir=user_data_dir) as browser:
# --- Step 1: Delta companion certificate search ---
_emit(
progress_callback,
step="delta",
message="Checking companion certificate availability...",
progress=10,
)
def delta_progress(msg: str) -> None:
_emit(progress_callback, step="delta", message=msg, progress=20)
flights: list[FlightOption] = await search_companion_cert(
request, browser, delta_progress
)
# --- Step 2: IHG points availability ---
_emit(
progress_callback,
step="ihg",
message="Checking IHG points availability...",
progress=40,
)
destinations = _extract_destinations(flights)
date_pairs = _extract_date_pairs(flights)
def ihg_progress(msg: str) -> None:
_emit(progress_callback, step="ihg", message=msg, progress=55)
hotels: list[HotelOption] = await search_points_availability(
destinations, date_pairs, browser,
request.ihg_brands, request.trip_duration_nights, ihg_progress
)
# --- Step 3: Resy dining options ---
_emit(
progress_callback,
step="resy",
message="Finding Resy dining options...",
progress=70,
)
cities, arrival_dates = _extract_cities_and_arrival_dates(flights)
def resy_progress(msg: str) -> None:
_emit(progress_callback, step="resy", message=msg, progress=80)
restaurants: list[RestaurantOption] = await find_resy_restaurants(
cities, arrival_dates, request.party_size, browser, resy_progress
)
# BrowserSession closed — merge results in memory.
# --- Step 4: Merge and rank ---
_emit(
progress_callback,
step="merging",
message="Ranking trip combinations...",
progress=90,
)
results: list[TripResult] = []
for flight in flights:
hotel = _find_matching_hotel(flight, hotels)
restaurant = _find_matching_restaurant(flight, restaurants)
cash_out = calculate_cash_out_of_pocket(flight, hotel)
points_required = hotel.total_points if hotel is not None else 0
benefits = collect_benefits(flight, hotel, restaurant)
score = _score_trip(flight, hotel, restaurant)
results.append(
TripResult(
destination=flight.destination,
flight=flight,
hotel=hotel,
restaurant=restaurant,
total_cash_out_of_pocket=cash_out,
total_points_required=points_required,
benefits_captured=benefits,
score=score,
)
)
results.sort(key=lambda r: r.score, reverse=True)
# --- Step 5: Done ---
_emit(
progress_callback,
step="done",
message="Search complete!",
progress=100,
)
return results
|