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3093d7c | 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 | import logging
import sqlite3
import sys
from pathlib import Path
from typing import Tuple, Dict, Any
# 1. Professional Logger Setup
logging.basicConfig(
filename='bot_activity.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
# Add project root to path to ensure models can be imported
sys.path.append(str(Path(__file__).parent.parent))
from models import Action, Observation
DB_PATH = "orders.db"
def init_db():
"""Initializes the database with advanced state tracking columns."""
conn = sqlite3.connect(DB_PATH)
cursor = conn.cursor()
cursor.execute('''
CREATE TABLE IF NOT EXISTS orders (
id TEXT PRIMARY KEY,
status TEXT,
address TEXT,
price REAL,
requires_human INTEGER DEFAULT 0
)
''')
# Seed data strictly aligned with openenv.yaml tasks
seed_data = [
('101', 'Processing', '123 Mumbai St', 500.0, 0),
('102', 'Shipped', '456 Delhi Rd', 1200.0, 0),
('103', 'Delayed', '789 Bandra West', 500.0, 0)
]
cursor.executemany("INSERT OR IGNORE INTO orders VALUES (?, ?, ?, ?, ?)", seed_data)
conn.commit()
conn.close()
init_db()
class EcommerceBotEnvironment:
def _get_connection(self):
return sqlite3.connect(DB_PATH)
def reset(self) -> Observation:
"""Standard OpenEnv Reset Protocol."""
logging.info("System Reset: Database state verified.")
return Observation(status_msg="Database Connected & Ready", success=True)
def step(self, action: Action) -> Tuple[Observation, float, bool, Dict[str, Any]]:
"""
OpenEnv Compliant Step Function.
Returns: (Observation, reward, done, info)
"""
conn = self._get_connection()
cursor = conn.cursor()
# Initialize OpenEnv tracking variables
reward = 0.0
done = False
info = {"task_id": action.order_id}
logging.info(f"EXECUTION: {action.action_type} on Order {action.order_id}")
# --- TASK 0: DYNAMIC ONBOARDING (Registration) ---
if action.action_type == "create_order":
try:
addr, prc = action.data.split(",")
cursor.execute(
"INSERT INTO orders (id, status, address, price, requires_human) VALUES (?, ?, ?, ?, ?)",
(action.order_id, "Processing", addr, float(prc), 0)
)
conn.commit()
conn.close()
return Observation(status_msg="Order Created", success=True), 1.0, True, info
except Exception as e:
conn.close()
return Observation(status_msg=str(e), success=False), 0.0, False, info
# Validate Order Existence
cursor.execute("SELECT status, address, price, requires_human FROM orders WHERE id = ?", (action.order_id,))
row = cursor.fetchone()
if not row:
conn.close()
return Observation(status_msg="Order Not Found", success=False), 0.0, False, info
status, address, price, requires_human = row
# --- SAFETY GUARDRAIL: HITL LOCK ---
if requires_human == 1 and action.action_type != "query_order":
conn.close()
# Penalize for ignoring a security lock
return Observation(status_msg="Order locked for Human Review.", success=False), -0.5, True, info
# --- TASK 1 (MEDIUM): STATUS QUERY ---
if action.action_type == "query_order":
conn.close()
details = {"status": status, "address": address, "price": price}
# Partial reward for information retrieval
if action.order_id == "102" and status == "Shipped":
reward = 1.0
done = True
else:
reward = 0.2
return Observation(status_msg="Found", order_details=details, success=True), reward, done, info
# --- TASK 2 (EASY): ADDRESS UPDATE ---
if action.action_type == "update_address":
# Guardrail: Non-manipulatable state
if status == "Shipped":
conn.close()
return Observation(status_msg="Cannot update shipped order", success=False), 0.0, True, info
# Guardrail: Logistics Constraints
restricted = ["International", "Restricted", "No-Go Zone"]
if any(zone.lower() in action.data.lower() for zone in restricted):
conn.close()
# Reward for identifying a boundary correctly
return Observation(status_msg="Restricted Area detected", success=False), 0.5, True, info
cursor.execute("UPDATE orders SET address = ? WHERE id = ?", (action.data, action.order_id))
conn.commit()
conn.close()
# Grader: Match goal in openenv.yaml
if action.order_id == "101" and action.data == "789 Bandra West":
reward = 1.0
done = True
else:
reward = 0.5
return Observation(status_msg="Address Updated", success=True), reward, done, info
# --- TASK 3 (HARD): REFUND PROCESSING ---
if action.action_type == "issue_refund":
try:
refund_amt = float(action.data)
limit = price * 0.5
# Grader: Escalation Logic
if refund_amt > limit:
cursor.execute("UPDATE orders SET requires_human = 1 WHERE id = ?", (action.order_id,))
conn.commit()
conn.close()
# Reward for identifying high-risk correctly
return Observation(status_msg="Escalated to Human", success=True), 0.8, True, info
cursor.execute("UPDATE orders SET status = 'Refunded' WHERE id = ?", (action.order_id,))
conn.commit()
conn.close()
# Grader: Task Goal
if action.order_id == "103" and refund_amt == 250.0:
reward = 1.0
done = True
else:
reward = 0.4
return Observation(status_msg="Refund Processed", success=True), reward, done, info
except ValueError:
conn.close()
return Observation(status_msg="Invalid Amount", success=False), 0.0, False, info
conn.close()
return Observation(status_msg="Unknown Action", success=False), 0.0, False, info |