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9ae6197 | 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 | from openenv.core.env_client import EnvClient
from openenv.core.client_types import StepResult
try:
from .models import JewelryAction, JewelryObservation, JewelryState, PRODUCT_CATALOG
except ImportError:
from models import JewelryAction, JewelryObservation, JewelryState, PRODUCT_CATALOG
class JewelryShopEnv(EnvClient[JewelryAction, JewelryObservation, JewelryState]):
"""
Client for the Jewelry Shop RL environment.
Usage:
env = JewelryShopEnv(base_url="http://localhost:8000")
obs = await env.reset()
# Phase 1 β Market (buy or wait)
obs = await env.step(JewelryAction(market_action="wait"))
obs = await env.step(JewelryAction(market_action="buy", gold_qty=2.0))
# Phase 2 β Warehouse (choose product)
obs = await env.step(JewelryAction(product_choice="ring"))
# Phase 3 β Showroom (negotiate)
obs = await env.step(JewelryAction(message="How about $600?"))
obs = await env.step(JewelryAction(message="I accept"))
"""
# ββ 1. PACK action β dict (sent TO server) ββββββββββββββββββββββββββββββ
def _step_payload(self, action: JewelryAction) -> dict:
payload = {}
if action.market_action is not None:
payload["market_action"] = action.market_action
if action.gold_qty is not None:
payload["gold_qty"] = action.gold_qty
if action.product_choice is not None:
payload["product_choice"] = action.product_choice
if action.message is not None:
payload["message"] = action.message
if action.target_price_usd is not None:
payload["target_price_usd"] = action.target_price_usd
if action.ai_confidence_pct is not None:
payload["ai_confidence_pct"] = action.ai_confidence_pct
if action.ai_reasoning is not None:
payload["ai_reasoning"] = action.ai_reasoning
if action.inventory_urgent is not None:
payload["inventory_urgent"] = action.inventory_urgent
if action.need_gold_grams is not None:
payload["need_gold_grams"] = action.need_gold_grams
if action.buy_deadline_iso is not None:
payload["buy_deadline_iso"] = action.buy_deadline_iso
return payload
# ββ 2. UNPACK dict β typed observation (received FROM server) βββββββββββ
def _parse_result(self, payload: dict) -> StepResult:
obs_data = payload.get("observation", {})
# Force reward and cumulative_reward to Python floats. JSON over the wire
# can deliver int (e.g. 0) which would later break formatters / training.
try:
_reward = float(payload.get("reward")) if payload.get("reward") is not None else 0.0
except (TypeError, ValueError):
_reward = 0.0
try:
_cum = float(obs_data.get("cumulative_reward", 0.0))
except (TypeError, ValueError):
_cum = 0.0
observation = JewelryObservation(
# Base fields
done=payload.get("done", False),
reward=_reward,
# Phase info
phase=obs_data.get("phase", "market"),
# Finances & inventory
cash=obs_data.get("cash", 1000.0),
gold_oz=obs_data.get("gold_oz", 0.0),
gold_grams=obs_data.get("gold_grams", 0.0),
# Market
gold_price=obs_data.get("gold_price", 0.0),
gold_price_history=obs_data.get("gold_price_history", []),
market_round=obs_data.get("market_round", 0),
max_market_rounds=obs_data.get("max_market_rounds", 0),
market_mode=obs_data.get("market_mode", "real"),
gold_price_source=obs_data.get("gold_price_source", ""),
inventory_urgent=obs_data.get("inventory_urgent", False),
need_gold_grams=obs_data.get("need_gold_grams", None),
buy_deadline_iso=obs_data.get("buy_deadline_iso", None),
cannot_wait=obs_data.get("cannot_wait", False),
market_reentries=obs_data.get("market_reentries", 0),
max_market_reentries=obs_data.get("max_market_reentries", 2),
# Warehouse
demand=obs_data.get("demand", {}),
demand_forecast=obs_data.get("demand_forecast", {}),
product_catalog=obs_data.get("product_catalog", PRODUCT_CATALOG),
inventory=obs_data.get("inventory", {}),
# Showroom
product_for_sale=obs_data.get("product_for_sale", None),
cost_basis=obs_data.get("cost_basis", 0.0),
current_offer=obs_data.get("current_offer", None),
negotiation_round=obs_data.get("negotiation_round", 0),
# Per-task grading
task_id=obs_data.get("task_id", "profit_negotiator"),
weights=obs_data.get("weights", []),
cumulative_reward=_cum,
# Feedback
message=obs_data.get("message", ""),
)
return StepResult(
observation=observation,
reward=_reward,
done=payload.get("done", False),
)
# ββ 3. UNPACK dict β typed state (server internal state) ββββββββββββββββ
def _parse_state(self, payload: dict) -> JewelryState:
return JewelryState(
episode_id=payload.get("episode_id", None),
step_count=payload.get("step_count", 0),
cash=payload.get("cash", 1000.0),
gold_oz=payload.get("gold_oz", 0.0),
gold_price=payload.get("gold_price", 0.0),
gold_price_history=payload.get("gold_price_history", []),
market_round=payload.get("market_round", 0),
max_market_rounds=payload.get("max_market_rounds", 0),
use_fifo_lots=payload.get("use_fifo_lots", False),
market_mode=payload.get("market_mode", "real"),
gold_price_source=payload.get("gold_price_source", ""),
demand=payload.get("demand", {}),
demand_forecast=payload.get("demand_forecast", {}),
inventory=payload.get("inventory", {}),
phase=payload.get("phase", "market"),
product_for_sale=payload.get("product_for_sale", None),
cost_basis=payload.get("cost_basis", 0.0),
negotiation_round=payload.get("negotiation_round", 0),
current_offer=payload.get("current_offer", 0.0),
base_offer=payload.get("base_offer", 0.0),
lowest_price_seen=payload.get("lowest_price_seen", 0.0),
inventory_urgent=payload.get("inventory_urgent", False),
need_gold_grams=payload.get("need_gold_grams", None),
buy_deadline_iso=payload.get("buy_deadline_iso", None),
market_reentries=payload.get("market_reentries", 0),
max_market_reentries=payload.get("max_market_reentries", 2),
task_id=payload.get("task_id", "profit_negotiator"),
weights=payload.get("weights", []),
cumulative_reward=payload.get("cumulative_reward", 0.0),
last_phase_emitted_reward=payload.get("last_phase_emitted_reward", 0.0),
) |