"""
完整壓力測試：模擬真實用戶的完整流程
包含：需求分析 → 問題生成 → 用戶選擇 → 結果驗證
"""
import json
import random
from antigravity_inline_generator import generate_questions_inline
# 模擬真實用戶的30個需求場景
test_scenarios = [
# === 簡單需求（初學者）===
{
"user_id": "U001",
"user_type": "學生",
"requirement": "做一個簡單的個人部落格",
"expected_complexity": "basic",
"user_choices": {} # 將在測試時填入
},
{
"user_id": "U002",
"user_type": "小白",
"requirement": "我想做一個Todo清單app",
"expected_complexity": "basic"
},
{
"user_id": "U003",
"user_type": "新手",
"requirement": "建立一個簡單的預約系統，讓客戶可以預約時間",
"expected_complexity": "basic"
},
# === 中等需求（專業人士）===
{
"user_id": "U004",
"user_type": "創業者",
"requirement": "我要做一個電商平台，有商品管理、購物車、訂單系統和支付功能",
"expected_complexity": "advanced"
},
{
"user_id": "U005",
"user_type": "產品經理",
"requirement": "社群平台，用戶可以發文、評論、按讚，需要實時通知",
"expected_complexity": "advanced"
},
{
"user_id": "U006",
"user_type": "餐廳老闆",
"requirement": "線上訂餐系統，客戶下單、廚房接單、外送追蹤",
"expected_complexity": "advanced"
},
{
"user_id": "U007",
"user_type": "健身教練",
"requirement": "會員管理系統，可以預約課程、記錄運動數據、線上支付",
"expected_complexity": "advanced"
},
{
"user_id": "U008",
"user_type": "醫生",
"requirement": "診所預約系統，病患可以線上掛號、查看病歷、視訊問診",
"expected_complexity": "advanced"
},
# === 複雜需求（企業級）===
{
"user_id": "U009",
"user_type": "CTO",
"requirement": "多租戶SaaS平台，支持企業自定義工作流、權限管理、數據隔離",
"expected_complexity": "expert"
},
{
"user_id": "U010",
"user_type": "技術總監",
"requirement": "大型電商，每秒10萬訂單，分散式架構，多倉庫庫存同步",
"expected_complexity": "expert"
},
{
"user_id": "U011",
"user_type": "架構師",
"requirement": "實時直播平台，百萬並發，CDN加速，智能推薦算法",
"expected_complexity": "expert"
},
{
"user_id": "U012",
"user_type": "金融科技",
"requirement": "支付網關系統，高可用99.99%，分散式事務，秒級對帳",
"expected_complexity": "expert"
},
# === 特殊場景 ===
{
"user_id": "U013",
"user_type": "教育工作者",
"requirement": "在線教育平台，直播互動、作業批改、考試系統、學習分析",
"expected_complexity": "expert"
},
{
"user_id": "U014",
"user_type": "區塊鏈開發",
"requirement": "NFT交易平台，支持鑄造、拍賣、版稅分成",
"expected_complexity": "expert"
},
{
"user_id": "U015",
"user_type": "遊戲開發",
"requirement": "多人在線遊戲，實時對戰、排行榜、虛擬物品交易",
"expected_complexity": "expert"
},
]
def simulate_user_choices(questions):
"""
模擬真實用戶的選擇行為
根據問題類型，隨機選擇合理的答案
"""
choices = {}
for i, question in enumerate(questions, 1):
# 隨機選擇A/B/C，模擬真實用戶的不確定性
options = ['A', 'B', 'C']
selected = random.choice(options)
# 記錄用戶的選擇和思考過程
option_obj = None
for opt in question.get('options', []):
if opt['label'].startswith(selected):
option_obj = opt
break
choices[f"q{i}"] = {
"selected": selected,
"option_value": option_obj['value'] if option_obj else None,
"description": option_obj['description'] if option_obj else None,
"risk": option_obj.get('risk_score', 'unknown') if option_obj else None
}
return choices
def run_complete_stress_test():
"""
完整的壓力測試：模擬真實用戶流程
"""
print("=" * 80)
print("🔥 藍圖小老鼠 - 完整壓力測試")
print("=" * 80)
print(f"\n📊 測試場景數: {len(test_scenarios)}")
print("🎯 測試目標: 驗證系統魯棒性和問題質量\n")
results = []
for scenario in test_scenarios:
print("\n" + "─" * 80)
print(f"👤 用戶 {scenario['user_id']} ({scenario['user_type']})")
print(f"📝 需求: {scenario['requirement']}")
print("─" * 80)
try:
# 1. 生成問題
print("\n【階段1: 需求分析與問題生成】")
result = generate_questions_inline(scenario['requirement'], 'zh-TW')
questions = result.get('questions', [])
print(f"✅ 成功生成 {len(questions)} 個問題")
# 2. 展示問題詳情
print("\n【階段2: 蘇格拉底面試問題】")
for i, q in enumerate(questions, 1):
print(f"\n 問題 {i}: {q['text']}")
for opt in q.get('options', []):
print(f" {opt['label']}")
print(f" → {opt['description']}")
print(f" 風險: {opt.get('risk_score', 'N/A')}")
# 3. 模擬用戶選擇
print("\n【階段3: 用戶決策過程】")
choices = simulate_user_choices(questions)
scenario['user_choices'] = choices
for q_id, choice in choices.items():
q_num = int(q_id[1:])
print(f"\n 問題{q_num} 用戶選擇: {choice['selected']}")
print(f" 選項: {choice['option_value']}")
print(f" 說明: {choice['description']}")
print(f" 風險評估: {choice['risk']}")
# 4. 記錄結果
test_result = {
"user_id": scenario['user_id'],
"user_type": scenario['user_type'],
"requirement": scenario['requirement'],
"expected_complexity": scenario['expected_complexity'],
"questions_generated": len(questions),
"question_ids": [q['id'] for q in questions],
"user_choices": choices,
"status": "success"
}
results.append(test_result)
print(f"\n✅ 用戶 {scenario['user_id']} 流程完成")
except Exception as e:
print(f"\n❌ 錯誤: {e}")
results.append({
"user_id": scenario['user_id'],
"status": "failed",
"error": str(e)
})
# 5. 統計分析
print("\n\n" + "=" * 80)
print("📊 壓力測試統計")
print("=" * 80)
total = len(results)
success = sum(1 for r in results if r['status'] == 'success')
failed = total - success
print(f"\n總測試數: {total}")
print(f"成功: {success} ({success/total*100:.1f}%)")
print(f"失敗: {failed} ({failed/total*100:.1f}%)")
# 問題數量統計
question_counts = {}
for r in results:
if r['status'] == 'success':
count = r['questions_generated']
question_counts[count] = question_counts.get(count, 0) + 1
print(f"\n問題數量分佈:")
for count in sorted(question_counts.keys()):
freq = question_counts[count]
print(f" {count}個問題: {freq}次 ({freq/success*100:.1f}%)")
# 保存詳細結果
with open('stress_test_results.json', 'w', encoding='utf-8') as f:
json.dump(results, f, ensure_ascii=False, indent=2)
print(f"\n📄 詳細結果已保存: stress_test_results.json")
return results
if __name__ == '__main__':
results = run_complete_stress_test()
print("\n🎉 壓力測試完成！")
