"""Deterministic FlowBench v3 tools. This file contains no task answers.""" REGIONS = ["NA", "EU", "APAC", "LATAM"] CATEGORIES = ["A", "B", "C", "D"] CURRENCIES = {"NA": "USD", "EU": "EUR", "APAC": "JPY", "LATAM": "BRL"} FX_TO_USD_BP = {"USD": 10000, "EUR": 10900, "JPY": 67, "BRL": 1850} TIERS = ["std", "gold", "plat"] DISCOUNT_PCT = {"std": 0, "gold": 10, "plat": 20} CHANNELS = ["web", "store", "partner"] MONTHS = [202601, 202602, 202603, 202604, 202605, 202606] N_CUSTOMERS = 72 N_PRODUCTS = 48 N_ORDERS = 720 N_TICKETS = 260 N_RETURNS = 180 def _h(*xs): import hashlib s = "|".join(str(x) for x in xs).encode() return int.from_bytes(hashlib.sha256(s).digest()[:8], "big") & 0x7FFFFFFF def build_data(): customers = [] for cid in range(N_CUSTOMERS): region = REGIONS[_h("region", cid) % len(REGIONS)] customers.append({ "customer_id": cid, "region": region, "tier": TIERS[_h("tier", cid) % len(TIERS)], "segment": ["consumer", "smb", "enterprise"][_h("segment", cid) % 3], }) products = [] for pid in range(N_PRODUCTS): cat = CATEGORIES[_h("cat", pid) % len(CATEGORIES)] unit_price = 12 + _h("price", pid) % 240 cogs = unit_price * (45 + _h("margin", pid) % 35) // 100 products.append({ "product_id": pid, "category": cat, "unit_price_usd": unit_price, "unit_cogs_usd": cogs, "lead_time_days": 3 + _h("lead", pid) % 18, }) inventory = [] for pid in range(N_PRODUCTS): for region in REGIONS: inventory.append({ "product_id": pid, "region": region, "on_hand": 10 + _h("onhand", pid, region) % 140, "reserved": _h("reserved", pid, region) % 28, "inbound": _h("inbound", pid, region) % 85, }) orders = [] for oid in range(N_ORDERS): customer_id = _h("ocust", oid) % N_CUSTOMERS product_id = _h("oprod", oid) % N_PRODUCTS month = MONTHS[_h("month", oid) % len(MONTHS)] qty = 1 + _h("qty", oid) % 9 ship_days = 1 + _h("shipdays", oid) % 16 promised_days = 3 + _h("promise", oid) % 9 status = ["paid", "paid", "paid", "paid", "cancelled", "refunded"][ _h("status", oid) % 6] orders.append({ "order_id": oid, "customer_id": customer_id, "product_id": product_id, "month": month, "qty": qty, "status": status, "channel": CHANNELS[_h("channel", oid) % len(CHANNELS)], "ship_days": ship_days, "promised_days": promised_days, }) returns = [] for rid in range(N_RETURNS): oid = _h("roid", rid) % N_ORDERS order = orders[oid] if order["status"] == "cancelled": continue returned_qty = 1 + _h("rqty", rid) % max(1, order["qty"]) reason = ["defect", "late", "changed_mind", "wrong_item"][_h("reason", rid) % 4] returns.append({ "return_id": rid, "order_id": oid, "month": MONTHS[_h("rmonth", rid) % len(MONTHS)], "returned_qty": returned_qty, "reason": reason, }) tickets = [] for tid in range(N_TICKETS): oid = _h("toid", tid) % N_ORDERS severity = ["low", "medium", "high", "critical"][_h("sev", tid) % 4] opened = MONTHS[_h("tmonth", tid) % len(MONTHS)] first_response_hours = 1 + _h("resp", tid) % 96 resolution_hours = first_response_hours + _h("res", tid) % 240 tickets.append({ "ticket_id": tid, "order_id": oid, "opened_month": opened, "severity": severity, "first_response_hours": first_response_hours, "resolution_hours": resolution_hours, }) return { "customers": customers, "products": products, "inventory": inventory, "orders": orders, "returns": returns, "tickets": tickets, "fx_to_usd_bp": FX_TO_USD_BP, } DATA = build_data() CUSTOMERS = {c["customer_id"]: c for c in DATA["customers"]} PRODUCTS = {p["product_id"]: p for p in DATA["products"]} ORDERS = {o["order_id"]: o for o in DATA["orders"]} def region_currency(region: str) -> str: return CURRENCIES[region] def get_orders(region: str, category: str, month_start: int, month_end: int) -> list: """Paid/refunded order ids in a region/category/month window.""" out = [] for o in DATA["orders"]: if o["status"] not in ("paid", "refunded"): continue c = CUSTOMERS[o["customer_id"]] p = PRODUCTS[o["product_id"]] if c["region"] == region and p["category"] == category and month_start <= o["month"] <= month_end: out.append(o["order_id"]) return sorted(out) def order_gross_usd(order_id: int) -> int: o = ORDERS[order_id] p = PRODUCTS[o["product_id"]] return o["qty"] * p["unit_price_usd"] def order_margin_usd(order_id: int) -> int: o = ORDERS[order_id] p = PRODUCTS[o["product_id"]] return o["qty"] * (p["unit_price_usd"] - p["unit_cogs_usd"]) def refund_usd(order_id: int) -> int: o = ORDERS[order_id] p = PRODUCTS[o["product_id"]] qty = sum(r["returned_qty"] for r in DATA["returns"] if r["order_id"] == order_id) qty = min(qty, o["qty"]) return qty * p["unit_price_usd"] def customer_tier(order_id: int) -> str: o = ORDERS[order_id] return CUSTOMERS[o["customer_id"]]["tier"] def apply_discount(amount_usd: int, tier: str) -> int: return amount_usd * (100 - DISCOUNT_PCT[tier]) // 100 def net_revenue_usd(order_id: int) -> int: gross = apply_discount(order_gross_usd(order_id), customer_tier(order_id)) return max(0, gross - refund_usd(order_id)) def to_local(amount_usd: int, currency: str) -> int: return amount_usd * 10000 // FX_TO_USD_BP[currency] def inventory_position(product_id: int, region: str) -> int: row = next(x for x in DATA["inventory"] if x["product_id"] == product_id and x["region"] == region) return row["on_hand"] - row["reserved"] + row["inbound"] def product_lead_time(product_id: int) -> int: return PRODUCTS[product_id]["lead_time_days"] def product_id_for_top_seller(region: str, category: str, month_start: int, month_end: int) -> int: totals = {} for oid in get_orders(region, category, month_start, month_end): o = ORDERS[oid] totals[o["product_id"]] = totals.get(o["product_id"], 0) + o["qty"] if not totals: return -1 return min((-qty, pid) for pid, qty in totals.items())[1] def units_sold(product_id: int, region: str, month_start: int, month_end: int) -> int: total = 0 for o in DATA["orders"]: if o["product_id"] != product_id or o["status"] not in ("paid", "refunded"): continue c = CUSTOMERS[o["customer_id"]] if c["region"] == region and month_start <= o["month"] <= month_end: total += o["qty"] return total def tickets_for_orders(order_ids: list, severity: str) -> list: s = set(order_ids) return sorted(t["ticket_id"] for t in DATA["tickets"] if t["order_id"] in s and t["severity"] == severity) def ticket_order_id(ticket_id: int) -> int: return next(t["order_id"] for t in DATA["tickets"] if t["ticket_id"] == ticket_id) def sla_breached(ticket_id: int, first_response_limit_hours: int, resolution_limit_hours: int) -> bool: t = next(x for x in DATA["tickets"] if x["ticket_id"] == ticket_id) return (t["first_response_hours"] > first_response_limit_hours or t["resolution_hours"] > resolution_limit_hours) def delayed_orders(order_ids: list) -> list: s = set(order_ids) return sorted(o["order_id"] for o in DATA["orders"] if o["order_id"] in s and o["ship_days"] > o["promised_days"]) def unique_customers(order_ids: list) -> list: return sorted({ORDERS[oid]["customer_id"] for oid in order_ids}) def count_items(values: list) -> int: return len(values) def sum_values(values: list) -> int: return sum(values) def count_true(values: list) -> int: return sum(1 for v in values if bool(v)) def count_below(values: list, threshold: int) -> int: return sum(1 for v in values if v < threshold) TOOLS = { "region_currency": ("region_currency(region: str) -> str", "ISO currency code for a region.", region_currency), "get_orders": ("get_orders(region: str, category: str, month_start: int, month_end: int) -> list[int]", "Paid/refunded order ids for a region, product category, and inclusive month window.", get_orders), "order_gross_usd": ("order_gross_usd(order_id: int) -> int", "Gross order revenue in USD before discounts/refunds.", order_gross_usd), "order_margin_usd": ("order_margin_usd(order_id: int) -> int", "Gross order margin in USD before discounts/refunds.", order_margin_usd), "refund_usd": ("refund_usd(order_id: int) -> int", "Refund amount in USD for returned quantity on an order.", refund_usd), "customer_tier": ("customer_tier(order_id: int) -> str", "Customer loyalty tier for an order.", customer_tier), "apply_discount": ("apply_discount(amount_usd: int, tier: str) -> int", "Apply the order customer's loyalty discount to a USD amount.", apply_discount), "net_revenue_usd": ("net_revenue_usd(order_id: int) -> int", "Net USD revenue after loyalty discount and refunds.", net_revenue_usd), "to_local": ("to_local(amount_usd: int, currency: str) -> int", "Convert a USD integer amount to a local-currency integer.", to_local), "inventory_position": ("inventory_position(product_id: int, region: str) -> int", "Available inventory position: on_hand - reserved + inbound.", inventory_position), "product_lead_time": ("product_lead_time(product_id: int) -> int", "Supplier lead time in days for a product.", product_lead_time), "product_id_for_top_seller": ( "product_id_for_top_seller(region: str, category: str, month_start: int, month_end: int) -> int", "Product id with the highest units sold in a region/category/month window.", product_id_for_top_seller), "units_sold": ("units_sold(product_id: int, region: str, month_start: int, month_end: int) -> int", "Units sold for one product in a region and month window.", units_sold), "tickets_for_orders": ("tickets_for_orders(order_ids: list[int], severity: str) -> list[int]", "Support ticket ids for given orders and severity.", tickets_for_orders), "ticket_order_id": ("ticket_order_id(ticket_id: int) -> int", "Order id associated with a support ticket.", ticket_order_id), "sla_breached": ( "sla_breached(ticket_id: int, first_response_limit_hours: int, resolution_limit_hours: int) -> bool", "Whether a support ticket breaches first-response or resolution SLA.", sla_breached), "delayed_orders": ("delayed_orders(order_ids: list[int]) -> list[int]", "Subset of order ids whose ship_days exceeded promised_days.", delayed_orders), "unique_customers": ("unique_customers(order_ids: list[int]) -> list[int]", "Unique customer ids among the given orders.", unique_customers), "count_items": ("count_items(values: list) -> int", "Length of a list.", count_items), "sum_values": ("sum_values(values: list[int]) -> int", "Sum a list of integers.", sum_values), "count_true": ("count_true(values: list[bool]) -> int", "Count true values.", count_true), "count_below": ("count_below(values: list[int], threshold: int) -> int", "Count values below a threshold.", count_below), } __all__ = [name for name in TOOLS.keys()] + ['TOOLS']