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7ff93da | 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 | # -*- coding: utf-8 -*-
"""資料集品質驗證。
檢查項目：
1. 欄位與型別是否對齊 twinkle-ai/tw-function-call-reasoning-10k
2. answer 是否為合法 JSON，且呼叫的函式都在 tools 清單內
3. 參數名稱是否都存在於該函式的 schema
4. messages 三段是否與 query_zhtw / think / answer 完全一致（可還原）
5. 參數值是否「有據可循」——能在題目文字裡找到來源，而非模型臆測
6. train / test 是否有完全重複的樣本
"""
import json
import re
import sys
from collections import Counter
SCHEMA = ["id", "query", "tools", "query_zhtw", "think", "answer", "messages"]
TYPES = {"id": int, "query": str, "tools": str, "query_zhtw": str,
"think": str, "answer": str, "messages": list}
# enum 參數在題目中常以中文表達，驗證溯源時需一併認列
ENUM_ZH = {
"standard": "標準扣除額", "itemized": "列舉扣除額",
"single": "單身", "married_joint": "夫妻合併申報",
"fixed": "固定利率", "floating": "機動利率",
"simple": "單利存本取息", "monthly_compound": "整存整付按月複利",
"equal_total": "本息平均攤還", "equal_principal": "本金平均攤還",
"income_replacement": "所得替代法", "needs_based": "需求分析法",
"stable": "穩定", "moderate": "普通", "volatile": "不穩定",
"mortgage_application": "房貸申請", "credit_card_application": "信用卡申請",
"self_inquiry": "本人查詢", "personal_loan": "信用貸款",
"buy": "買進", "sell": "賣出",
"stock": "股票", "etf": "股票型ETF", "warrant": "權證", "corporate_bond_etf": "債券型ETF",
"dividend": "股利", "bonus": "年終獎金", "rent": "租金",
"professional_fee": "執行業務所得", "part_time_salary": "兼職薪資", "interest": "利息",
"cash_buy": "現金買入", "cash_sell": "現金賣出",
"spot_buy": "即期買入", "spot_sell": "即期賣出",
"rediscount": "重貼現率", "accommodations_with_collateral": "擔保放款融通利率",
"accommodations_without_collateral": "短期融通利率",
"monthly": "月配", "quarterly": "季配", "semiannual": "半年配",
"cash_deposit": "現金存入", "cash_withdrawal": "現金提領",
"wire_transfer": "電匯", "fx_exchange": "結匯",
"individual": "自然人", "corporate": "法人", "trust": "信託",
"beginner": "完全新手", "intermediate": "有基礎", "professional": "從業人員",
"TAIEX": "台股加權指數", "TPEx": "櫃買指數", "TWSE50": "台灣50指數",
"TAIEX_TR": "發行量加權股價報酬指數", "FITX": "台指期近月",
"USD": "美元", "JPY": "日圓", "EUR": "歐元", "CNY": "人民幣",
"AUD": "澳幣", "HKD": "港幣", "GBP": "英鎊", "KRW": "韓元",
"zh-TW": "繁體中文", "close": "收盤", "change_pct": "漲跌",
"open": "開", "high": "高", "low": "低", "volume": "量",
}
def load(p):
with open(p, encoding="utf-8") as f:
return [json.loads(l) for l in f if l.strip()]
def grounded(val, text):
"""參數值是否能在題目文字中找到來源（容許萬元、百分比等常見換算）。"""
if isinstance(val, bool):
return True # 布林多由中文語意表達（如「當沖」「自住」），另由模板保證
if isinstance(val, (int, float)) and not isinstance(val, bool):
s = ("%g" % val)
cands = {s, str(val), "%g" % abs(val)}
if isinstance(val, int):
if val % 10000 == 0:
cands.add(str(val // 10000))
cands.add("{:,}".format(val))
else:
cands.add("%g" % (val * 100))
return any(c in text for c in cands)
if isinstance(val, str):
return val in text or ENUM_ZH.get(val, "\x00") in text
if isinstance(val, list):
return all(grounded(v, text) for v in val)
return True
def check(rows, name, errors, stats):
for r in rows:
rid = r.get("id", "?")
if list(r.keys()) != SCHEMA:
errors.append("%s#%s 欄位不符：%s" % (name, rid, list(r.keys())))
continue
for k, t in TYPES.items():
if not isinstance(r[k], t):
errors.append("%s#%s 欄位 %s 型別應為 %s" % (name, rid, k, t.__name__))
try:
tools = json.loads(r["tools"])
calls = json.loads(r["answer"])
except Exception as e:
errors.append("%s#%s JSON 解析失敗：%s" % (name, rid, e))
continue
tmap = {t["name"]: t for t in tools}
for c in calls:
if c["name"] not in tmap:
errors.append("%s#%s 呼叫了不在 tools 清單的函式 %s" % (name, rid, c["name"]))
continue
params = tmap[c["name"]]["parameters"]
for k, v in c["arguments"].items():
if k not in params:
errors.append("%s#%s 參數 %s 不在 %s 的 schema" % (name, rid, k, c["name"]))
stats["args_total"] += 1
if grounded(v, r["query_zhtw"] + " " + r["query"]):
stats["args_grounded"] += 1
else:
stats["ungrounded"].append((rid, c["name"], k, v))
m = r["messages"]
if len(m) != 3 or [x["role"] for x in m] != ["system", "user", "assistant"]:
errors.append("%s#%s messages 結構不是 system/user/assistant" % (name, rid))
continue
if m[1]["content"] != r["query_zhtw"]:
errors.append("%s#%s messages[1] 與 query_zhtw 不一致" % (name, rid))
if r["think"] not in m[2]["content"]:
errors.append("%s#%s think 未出現在 assistant 訊息" % (name, rid))
found = re.findall(r"<tool_call>\n(.*?)\n</tool_call>", m[2]["content"], re.S)
if len(found) != len(calls):
errors.append("%s#%s tool_call 數量(%d)與 answer(%d)不符"
% (name, rid, len(found), len(calls)))
else:
for got, want in zip(found, calls):
if json.loads(got) != want:
errors.append("%s#%s tool_call 內容與 answer 不一致" % (name, rid))
for t in tools:
if ('"%s"' % t["name"]) not in m[0]["content"]:
errors.append("%s#%s system 訊息缺少工具 %s" % (name, rid, t["name"]))
stats["calls"] += len(calls)
stats["tools_offered"] += len(tools)
def main():
tr = load(sys.argv[1] if len(sys.argv) > 1 else "data/train.jsonl")
te = load(sys.argv[2] if len(sys.argv) > 2 else "data/test.jsonl")
errors = []
stats = Counter()
stats["ungrounded"] = []
check(tr, "train", errors, stats)
check(te, "test", errors, stats)
ids = [r["id"] for r in tr + te]
if len(set(ids)) != len(ids):
errors.append("id 有重複")
tr_keys = {(r["query_zhtw"], r["answer"]) for r in tr}
dup = [r["id"] for r in te if (r["query_zhtw"], r["answer"]) in tr_keys]
if dup:
errors.append("test 有 %d 筆與 train 完全重複：%s" % (len(dup), dup[:10]))
n = len(tr) + len(te)
print("=" * 66)
print("資料集驗證報告")
print("=" * 66)
print("train / test : %d / %d (%.1f%% : %.1f%%)"
% (len(tr), len(te), 100 * len(tr) / n, 100 * len(te) / n))
print("函式呼叫總數 : %d（平均每題 %.2f 次）" % (stats["calls"], stats["calls"] / n))
print("平均提供工具數 : %.2f" % (stats["tools_offered"] / n))
print("參數溯源率 : %d/%d = %.2f%%"
% (stats["args_grounded"], stats["args_total"],
100 * stats["args_grounded"] / max(1, stats["args_total"])))
print("train/test 完全重複 : %d 筆" % len(dup))
print("-" * 66)
if stats["ungrounded"]:
print("題目中找不到來源的參數（前 10 筆）：")
for u in stats["ungrounded"][:10]:
print(" #%s %s.%s = %r" % u)
print()
if errors:
print("發現 %d 項錯誤：" % len(errors))
for e in errors[:25]:
print(" x", e)
sys.exit(1)
print("結果：通過，無結構性錯誤。")
if __name__ == "__main__":
main()
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