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projectAIpopular/research/routerarena/output/es-expert.json
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tzt ce0f6170d3 chore: T-P-1 工作区收敛——并行会话成果与历史未入库文件整理入库 
- 入库历史遗漏源码/测试：router_system 9 模块（agent/executors/inference/knowledge/
  memory/planner/skills/trace）、tests 11 个测试文件、config/knowledge 领域知识
- 入库根目录方案文档（v2/v3/可行性×2）、references 文献（arxiv 14-18/cnki_open/
  参考文献清单）、research 论文素材（routerarena/paper/中文文献 PDF）
- 前端构建产物刷新（新 hash）；webapp 误写文档删除
- gitignore 增补：deepseek-harness、research/_refs、.mimosa/.zcode、网关日志/pid、
  临时调试脚本、tests/e2e/node_modules、AI代理功能开发/prefix
- 基线确认：318 passed
2026-09-05 08:28:25 +08:00

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[
{
"global index": "mock_0000",
"prompt": "Implement quicksort in Python",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 分析】\n- 任务：Implement quicksort in Python\n- 关键要素：implement、quicksort、python\n- 目标：输出可运行的代码实现\n- 约束/边界：边界条件（空输入、极端值）；复杂度目标\n- 难度评估：medium\n\n【code 方案设计】\n针对「Implement quicksort in Python」的设计思路：\n1. 明确核心目标与验收标准\n2. 选择合适的方法/数据结构（依据：implement、quicksort、python）\n3. 拆解实现步骤并标注复杂度\n4. 预留边界处理与异常路径\n5. 设计自测用例（正常/边界/异常）\n\n【code 实现】\n```python\ndef solve() -> None:\n # 关键点：implement、quicksort、python\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：implement、quicksort、python；复杂度与边界说明见 design/verify 步骤。\n\n【code 自检】\n- 输入输出覆盖\n- 边界条件\n- 复杂度合理\n- 可运行性",
"success": true,
"model_used": "rule:code:verify",
"token_usage": {
"output_tokens": 370,
"input_tokens": 19
}
},
"cost": 0.00022485,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0001",
"prompt": "Write a function to reverse a linked list",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Write a function to reverse a linked list」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 83,
"input_tokens": 27
}
},
"cost": 0.0007451999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0002",
"prompt": "Debug this TypeError: undefined is not a function",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 分析】\n- 任务：Debug this TypeError: undefined is not a function\n- 关键要素：debug、typeerror、undefined、function\n- 目标：输出可运行的代码实现\n- 约束/边界：边界条件（空输入、极端值）；复杂度目标\n- 难度评估：hard\n\n【code 诊断】\n错误现象：Debug this TypeError: undefined is not a function\n排查步骤：\n1. 复现并定位出错行\n2. 检查变量类型与取值（重点：debug、typeerror、undefined、function）\n3. 核对函数签名、作用域与返回值\n4. 打印中间变量验证假设\n5. 用最小样例隔离问题\n\n【code 修复方案】\n针对「Debug this TypeError: undefined is not a function」：\n1. 根因：见 diagnose 步骤\n2. 修复：调整类型/增加空值判断/修正逻辑分支\n```python\ndef fixed() -> None:\n # 修复点：debug、typeerror、undefined、function\n pass\n```\n3. 回归：补充对应单测后重跑\n\n【code 自检】\n- 输入输出覆盖\n- 边界条件\n- 复杂度合理\n- 可运行性",
"success": true,
"model_used": "rule:code:verify",
"token_usage": {
"output_tokens": 402,
"input_tokens": 32
}
},
"cost": 0.000246,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0003",
"prompt": "Optimize SQL query with index hints",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Optimize SQL query with index hints」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 79,
"input_tokens": 23
}
},
"cost": 0.000702,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0004",
"prompt": "Implement binary search in Java",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 分析】\n- 任务：Implement binary search in Java\n- 关键要素：implement、binary、search、java\n- 目标：输出可运行的代码实现\n- 约束/边界：边界条件（空输入、极端值）；复杂度目标\n- 难度评估：medium\n\n【code 方案设计】\n针对「Implement binary search in Java」的设计思路：\n1. 明确核心目标与验收标准\n2. 选择合适的方法/数据结构（依据：implement、binary、search、java）\n3. 拆解实现步骤并标注复杂度\n4. 预留边界处理与异常路径\n5. 设计自测用例（正常/边界/异常）\n\n【code 实现】\n```python\ndef solve() -> None:\n # 关键点：implement、binary、search、java\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：implement、binary、search、java；复杂度与边界说明见 design/verify 步骤。\n\n【code 自检】\n- 输入输出覆盖\n- 边界条件\n- 复杂度合理\n- 可运行性",
"success": true,
"model_used": "rule:code:verify",
"token_usage": {
"output_tokens": 378,
"input_tokens": 20
}
},
"cost": 0.00022979999999999997,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0005",
"prompt": "用 Python 写一个快速排序函数",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 实现】\n```python\ndef solve() -> None:\n # 关键点：python、写一个快速排序函\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：python、写一个快速排序函；复杂度与边界说明见 design/verify 步骤。",
"success": true,
"model_used": "rule:code:implement",
"token_usage": {
"output_tokens": 124,
"input_tokens": 12
}
},
"cost": 7.619999999999998e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0006",
"prompt": "解释这段 JavaScript 代码的 TypeError",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 分析】\n- 任务：解释这段 JavaScript 代码的 TypeError\n- 关键要素：javascript、typeerror、解释这段、代码的\n- 目标：输出可运行的代码实现\n- 约束/边界：边界条件（空输入、极端值）；复杂度目标\n- 难度评估：easy\n\n【code 诊断】\n错误现象：解释这段 JavaScript 代码的 TypeError\n排查步骤：\n1. 复现并定位出错行\n2. 检查变量类型与取值（重点：javascript、typeerror、解释这段、代码的）\n3. 核对函数签名、作用域与返回值\n4. 打印中间变量验证假设\n5. 用最小样例隔离问题\n\n【code 修复方案】\n针对「解释这段 JavaScript 代码的 TypeError」：\n1. 根因：见 diagnose 步骤\n2. 修复：调整类型/增加空值判断/修正逻辑分支\n```python\ndef fixed() -> None:\n # 修复点：javascript、typeerror、解释这段、代码的\n pass\n```\n3. 回归：补充对应单测后重跑\n\n【code 自检】\n- 输入输出覆盖\n- 边界条件\n- 复杂度合理\n- 可运行性",
"success": true,
"model_used": "rule:code:verify",
"token_usage": {
"output_tokens": 352,
"input_tokens": 19
}
},
"cost": 0.00021404999999999997,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0007",
"prompt": "帮我优化 SQL 索引",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 分析】\n- 任务：帮我优化 SQL 索引\n- 关键要素：sql、帮我优化、索引\n- 目标：输出可运行的代码实现\n- 约束/边界：边界条件（空输入、极端值）；复杂度目标\n- 难度评估：medium\n\n【code 方案设计】\n针对「帮我优化 SQL 索引」的设计思路：\n1. 明确核心目标与验收标准\n2. 选择合适的方法/数据结构（依据：sql、帮我优化、索引）\n3. 拆解实现步骤并标注复杂度\n4. 预留边界处理与异常路径\n5. 设计自测用例（正常/边界/异常）\n\n【code 实现】\n```python\ndef solve() -> None:\n # 关键点：sql、帮我优化、索引\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：sql、帮我优化、索引；复杂度与边界说明见 design/verify 步骤。\n\n【code 自检】\n- 输入输出覆盖\n- 边界条件\n- 复杂度合理\n- 可运行性",
"success": true,
"model_used": "rule:code:verify",
"token_usage": {
"output_tokens": 306,
"input_tokens": 7
}
},
"cost": 0.00018465000000000002,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0008",
"prompt": "Implement merge sort",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Implement merge sort」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 69,
"input_tokens": 13
}
},
"cost": 0.000594,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0009",
"prompt": "Convert JSON to CSV in Python",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 实现】\n```python\ndef solve() -> None:\n # 关键点：convert、json、csv、python\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：convert、json、csv、python；复杂度与边界说明见 design/verify 步骤。",
"success": true,
"model_used": "rule:code:implement",
"token_usage": {
"output_tokens": 135,
"input_tokens": 19
}
},
"cost": 8.384999999999999e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0010",
"prompt": "Solve x^2 - 5x + 6 = 0",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Solve x^2 - 5x + 6 = 0」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 70,
"input_tokens": 14
}
},
"cost": 0.0006048,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0011",
"prompt": "Prove the Pythagorean theorem",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Prove the Pythagorean theorem」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0012",
"prompt": "Calculate the integral of x^2 from 0 to 1",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【math 分析】\n- 任务：Calculate the integral of x^2 from 0 to 1\n- 关键要素：calculate、integral、from\n- 目标：得到问题的解并给出推导\n- 约束/边界：定义域、无解/多解情况、特殊值\n- 难度评估：hard\n\n【math 求解】\n题目：Calculate the integral of x^2 from 0 to 1\n步骤：\n1. 提取已知条件（calculate、integral、from）\n2. 选择方法：代数变形/公式代入/逐步推导\n3. 求解并化简中间结果\n4. 检查特殊值与边界\n结论：在标准假设下可得到闭合形式解；完整推导见正式解答。\n\n【math 自检】\n- 中间步骤正确\n- 结果代入验证\n- 边界/特殊值\n- 单位与符号",
"success": true,
"model_used": "rule:math:verify",
"token_usage": {
"output_tokens": 238,
"input_tokens": 27
}
},
"cost": 0.00030425,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0013",
"prompt": "求方程 x^2+3x+2=0 的根",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【math 求解】\n题目：求方程 x^2+3x+2=0 的根\n步骤：\n1. 提取已知条件（求方程、的根）\n2. 选择方法：代数变形/公式代入/逐步推导\n3. 求解并化简中间结果\n4. 检查特殊值与边界\n结论：在标准假设下可得到闭合形式解；完整推导见正式解答。",
"success": true,
"model_used": "rule:math:solve",
"token_usage": {
"output_tokens": 86,
"input_tokens": 11
}
},
"cost": 0.00011025,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0014",
"prompt": "证明勾股定理",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【math 分析】\n- 任务：证明勾股定理\n- 关键要素：证明勾股定理\n- 目标：得到问题的解并给出推导\n- 约束/边界：定义域、无解/多解情况、特殊值\n- 难度评估：medium\n\n【math 求解】\n题目：证明勾股定理\n步骤：\n1. 提取已知条件（证明勾股定理）\n2. 选择方法：代数变形/公式代入/逐步推导\n3. 求解并化简中间结果\n4. 检查特殊值与边界\n结论：在标准假设下可得到闭合形式解；完整推导见正式解答。\n\n【math 自检】\n- 中间步骤正确\n- 结果代入验证\n- 边界/特殊值\n- 单位与符号",
"success": true,
"model_used": "rule:math:verify",
"token_usage": {
"output_tokens": 170,
"input_tokens": 4
}
},
"cost": 0.0002135,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0015",
"prompt": "计算 3x+5=20 中 x 的值",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「计算 3x+5=20 中 x 的值」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 67,
"input_tokens": 11
}
},
"cost": 0.0005723999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0016",
"prompt": "Find eigenvalues of a 2x2 matrix",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Find eigenvalues of a 2x2 matrix」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 77,
"input_tokens": 21
}
},
"cost": 0.0006804,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0017",
"prompt": "Differentiate sin(x) * cos(x)",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Differentiate sin(x) * cos(x)」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0018",
"prompt": "求 ∫ x^2 dx",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「求 ∫ x^2 dx」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 62,
"input_tokens": 6
}
},
"cost": 0.0005184,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0019",
"prompt": "Compute dot product of two vectors",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Compute dot product of two vectors」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 78,
"input_tokens": 22
}
},
"cost": 0.0006911999999999999,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0020",
"prompt": "Is a non-compete clause for 2 years enforceable?",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Is a non-compete clause for 2 years enforceable?」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 88,
"input_tokens": 32
}
},
"cost": 0.0007991999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0021",
"prompt": "How to calculate severance pay",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to calculate severance pay」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0022",
"prompt": "劳动合同到期不续签是否要给补偿金",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【legal 分析】\n- 任务：劳动合同到期不续签是否要给补偿金\n- 关键要素：劳动合同到期不续、签是否要给补偿金\n- 目标：给出法律结论与依据\n- 约束/边界：以现行有效法律为准，个案需咨询律师\n- 难度评估：easy\n\n【legal 知识检索】\n- 劳动合同期满用人单位不续签的，通常应支付经济补偿（每满一年一个月工资）\n- 劳动合同期满用人单位不续签的，通常应支付经济补偿（每满一年一个月工资）\n\n【legal 结论】\n综合「劳动合同到期不续签是否要给补偿金」：\n1. 事实梳理：劳动合同到期不续、签是否要给补偿金\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性法律分析，不构成正式法律意见；个案请咨询执业律师。",
"success": true,
"model_used": "rule:legal:disclaimer",
"token_usage": {
"output_tokens": 246,
"input_tokens": 10
}
},
"cost": 0.00031,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0023",
"prompt": "加班费怎么计算",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【legal 分析】\n- 任务：加班费怎么计算\n- 关键要素：加班费怎么计算\n- 目标：给出法律结论与依据\n- 约束/边界：以现行有效法律为准，个案需咨询律师\n- 难度评估：easy\n\n【legal 知识检索】\n- 工作日加班支付不低于工资 150% 的报酬；休息日加班不能补休的支付 200%；法定节假日加班支付 300%\n\n【legal 结论】\n综合「加班费怎么计算」：\n1. 事实梳理：加班费怎么计算\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性法律分析，不构成正式法律意见；个案请咨询执业律师。",
"success": true,
"model_used": "rule:legal:disclaimer",
"token_usage": {
"output_tokens": 208,
"input_tokens": 4
}
},
"cost": 0.000261,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0024",
"prompt": "违约金上限 30% 合法吗",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「违约金上限 30% 合法吗」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 64,
"input_tokens": 8
}
},
"cost": 0.00054,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0025",
"prompt": "What counts as wrongful termination",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What counts as wrongful termination」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 79,
"input_tokens": 23
}
},
"cost": 0.000702,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0026",
"prompt": "Can I sue my employer for unpaid wages",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Can I sue my employer for unpaid wages」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 81,
"input_tokens": 25
}
},
"cost": 0.0007236,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0027",
"prompt": "劳动合同里约定竞业限制是否有效",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【legal 分析】\n- 任务：劳动合同里约定竞业限制是否有效\n- 关键要素：劳动合同里约定竞、业限制是否有效\n- 目标：给出法律结论与依据\n- 约束/边界：以现行有效法律为准，个案需咨询律师\n- 难度评估：easy\n\n【legal 知识检索】\n- 竞业限制期限不得超过二年，且用人单位应在限制期内按月给予经济补偿\n- 劳动合同期满用人单位不续签的，通常应支付经济补偿（每满一年一个月工资）\n- 竞业限制期限不得超过二年，且用人单位应在限制期内按月给予经济补偿\n- 劳动合同期满用人单位不续签的，通常应支付经济补偿（每满一年一个月工资）\n\n【legal 结论】\n综合「劳动合同里约定竞业限制是否有效」：\n1. 事实梳理：劳动合同里约定竞、业限制是否有效\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性法律分析，不构成正式法律意见；个案请咨询执业律师。",
"success": true,
"model_used": "rule:legal:disclaimer",
"token_usage": {
"output_tokens": 290,
"input_tokens": 10
}
},
"cost": 0.000365,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0028",
"prompt": "Statute of limitations for breach of contract",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Statute of limitations for breach of contract」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 86,
"input_tokens": 30
}
},
"cost": 0.0007776,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0029",
"prompt": "How does arbitration work in employment disputes",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How does arbitration work in employment disputes」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 88,
"input_tokens": 32
}
},
"cost": 0.0007991999999999999,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0030",
"prompt": "What foods should hypertensive patients avoid",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What foods should hypertensive patients avoid」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 86,
"input_tokens": 30
}
},
"cost": 0.0007776,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0031",
"prompt": "First aid for burns",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「First aid for burns」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 68,
"input_tokens": 12
}
},
"cost": 0.0005832,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0032",
"prompt": "高血压患者日常饮食",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【medical 分析】\n- 任务：高血压患者日常饮食\n- 关键要素：高血压患者日常饮\n- 目标：给出科普性建议\n- 约束/边界：个体差异；非诊断，请遵医嘱\n- 难度评估：easy\n\n【medical 建议】\n关于「高血压患者日常饮食」的一般性建议：\n1. 基础注意事项（高血压患者日常饮）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）\n\n⚠️ 提示：以上内容仅供健康科普，不能替代医生诊断；如有不适请及时就医。",
"success": true,
"model_used": "rule:medical:disclaimer",
"token_usage": {
"output_tokens": 157,
"input_tokens": 6
}
},
"cost": 0.00019775,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0033",
"prompt": "感冒发烧 38.5 度需要吃退烧药吗",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【medical 分析】\n- 任务：感冒发烧 38.5 度需要吃退烧药吗\n- 关键要素：感冒发烧、度需要吃退烧药吗\n- 目标：给出科普性建议\n- 约束/边界：个体差异；非诊断，请遵医嘱\n- 难度评估：easy\n\n【medical 建议】\n关于「感冒发烧 38.5 度需要吃退烧药吗」的一般性建议：\n1. 基础注意事项（感冒发烧、度需要吃退烧药吗）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）\n\n⚠️ 提示：以上内容仅供健康科普，不能替代医生诊断；如有不适请及时就医。",
"success": true,
"model_used": "rule:medical:disclaimer",
"token_usage": {
"output_tokens": 176,
"input_tokens": 12
}
},
"cost": 0.000223,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0034",
"prompt": "Side effects of common blood pressure medications",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Side effects of common blood pressure medications」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 88,
"input_tokens": 32
}
},
"cost": 0.0007991999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0035",
"prompt": "When to go to ER for chest pain",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「When to go to ER for chest pain」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0036",
"prompt": "烫伤后怎么处理",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【medical 分析】\n- 任务：烫伤后怎么处理\n- 关键要素：烫伤后怎么处理\n- 目标：给出科普性建议\n- 约束/边界：个体差异；非诊断，请遵医嘱\n- 难度评估：easy\n\n【medical 建议】\n关于「烫伤后怎么处理」的一般性建议：\n1. 基础注意事项（烫伤后怎么处理）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）\n\n⚠️ 提示：以上内容仅供健康科普，不能替代医生诊断；如有不适请及时就医。",
"success": true,
"model_used": "rule:medical:disclaimer",
"token_usage": {
"output_tokens": 153,
"input_tokens": 4
}
},
"cost": 0.00019225,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0037",
"prompt": "感冒初期如何缓解症状",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【medical 分析】\n- 任务：感冒初期如何缓解症状\n- 关键要素：感冒初期如何缓解、症状\n- 目标：给出科普性建议\n- 约束/边界：个体差异；非诊断，请遵医嘱\n- 难度评估：medium\n\n【medical 建议】\n关于「感冒初期如何缓解症状」的一般性建议：\n1. 基础注意事项（感冒初期如何缓解、症状）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）\n\n⚠️ 提示：以上内容仅供健康科普，不能替代医生诊断；如有不适请及时就医。",
"success": true,
"model_used": "rule:medical:disclaimer",
"token_usage": {
"output_tokens": 164,
"input_tokens": 6
}
},
"cost": 0.0002065,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0038",
"prompt": "How to treat a sprained ankle",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to treat a sprained ankle」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0039",
"prompt": "What are warning signs of diabetes",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【medical 分析】\n- 任务：What are warning signs of diabetes\n- 关键要素：what、warning、signs、diabetes\n- 目标：给出科普性建议\n- 约束/边界：个体差异；非诊断，请遵医嘱\n- 难度评估：easy\n\n【medical 建议】\n关于「What are warning signs of diabetes」的一般性建议：\n1. 基础注意事项（what、warning、signs、diabetes）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）\n\n⚠️ 提示：以上内容仅供健康科普，不能替代医生诊断；如有不适请及时就医。",
"success": true,
"model_used": "rule:medical:disclaimer",
"token_usage": {
"output_tokens": 216,
"input_tokens": 22
}
},
"cost": 0.0002755,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0040",
"prompt": "How to calculate ROI on a fund",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to calculate ROI on a fund」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0041",
"prompt": "What to do when credit card is overdue",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What to do when credit card is overdue」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 81,
"input_tokens": 25
}
},
"cost": 0.0007236,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0042",
"prompt": "基金定投收益率怎么计算",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【finance 分析】\n- 任务：基金定投收益率怎么计算\n- 关键要素：基金定投收益率怎、么计算\n- 目标：给出理财/金融建议与风险提示\n- 约束/边界：市场有风险，投资需谨慎；不构成投资建议\n- 难度评估：easy\n\n【finance 知识检索】\n- 理财投资均存在风险，收益与风险成正比；过往业绩不代表未来表现，切勿用急用钱投资\n\n【finance 结论】\n综合「基金定投收益率怎么计算」：\n1. 事实梳理：基金定投收益率怎、么计算\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性金融科普，不构成投资建议；投资有风险，决策前请结合自身情况并咨询专业人士。",
"success": true,
"model_used": "rule:finance:disclaimer",
"token_usage": {
"output_tokens": 226,
"input_tokens": 7
}
},
"cost": 0.00028425,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0043",
"prompt": "信用卡逾期怎么办",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【finance 分析】\n- 任务：信用卡逾期怎么办\n- 关键要素：信用卡逾期怎么办\n- 目标：给出理财/金融建议与风险提示\n- 约束/边界：市场有风险，投资需谨慎；不构成投资建议\n- 难度评估：easy\n\n【finance 知识检索】\n- 信用卡逾期会影响个人征信记录，产生违约金与利息；建议设置自动还款避免逾期\n\n【finance 结论】\n综合「信用卡逾期怎么办」：\n1. 事实梳理：信用卡逾期怎么办\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性金融科普，不构成投资建议；投资有风险，决策前请结合自身情况并咨询专业人士。",
"success": true,
"model_used": "rule:finance:disclaimer",
"token_usage": {
"output_tokens": 215,
"input_tokens": 5
}
},
"cost": 0.00027,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0044",
"prompt": "房贷利率是 LPR 加多少",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【finance 分析】\n- 任务：房贷利率是 LPR 加多少\n- 关键要素：lpr、房贷利率是、加多少\n- 目标：给出理财/金融建议与风险提示\n- 约束/边界：市场有风险，投资需谨慎；不构成投资建议\n- 难度评估：easy\n\n【finance 知识检索】\n- 房贷利率通常与 LPR（贷款市场报价利率）挂钩，等额本息月供固定、等额本金逐月递减\n\n【finance 结论】\n综合「房贷利率是 LPR 加多少」：\n1. 事实梳理：lpr、房贷利率是、加多少\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性金融科普，不构成投资建议；投资有风险，决策前请结合自身情况并咨询专业人士。",
"success": true,
"model_used": "rule:finance:disclaimer",
"token_usage": {
"output_tokens": 232,
"input_tokens": 8
}
},
"cost": 0.000292,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0045",
"prompt": "Should I refinance my mortgage",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【finance 分析】\n- 任务：Should I refinance my mortgage\n- 关键要素：refinance、mortgage\n- 目标：给出理财/金融建议与风险提示\n- 约束/边界：市场有风险，投资需谨慎；不构成投资建议\n- 难度评估：easy\n\n【finance 知识检索】\n未命中知识库条目；建议以现行有效法规/最新指南为准，并结合个案情况分析（refinance、mortgage）。\n\n【finance 结论】\n综合「Should I refinance my mortgage」：\n1. 事实梳理：refinance、mortgage\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性金融科普，不构成投资建议；投资有风险，决策前请结合自身情况并咨询专业人士。",
"success": true,
"model_used": "rule:finance:disclaimer",
"token_usage": {
"output_tokens": 270,
"input_tokens": 20
}
},
"cost": 0.0003425,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0046",
"prompt": "Best way to save for retirement",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Best way to save for retirement」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0047",
"prompt": "理财产品和基金的区别",
"prediction": "claude-3-haiku-20240307",
"generated_result": {
"generated_answer": "【finance 分析】\n- 任务：理财产品和基金的区别\n- 关键要素：理财产品和基金的、区别\n- 目标：给出理财/金融建议与风险提示\n- 约束/边界：市场有风险，投资需谨慎；不构成投资建议\n- 难度评估：medium\n\n【finance 知识检索】\n- 理财投资均存在风险，收益与风险成正比；过往业绩不代表未来表现，切勿用急用钱投资\n\n【finance 结论】\n综合「理财产品和基金的区别」：\n1. 事实梳理：理财产品和基金的、区别\n2. 适用规则/依据（见 retrieve 步骤）\n3. 结论：在所述前提下，按上述规则处理\n4. 注意事项：个案差异，必要时咨询专业人士\n\n⚠️ 提示：以上为一般性金融科普，不构成投资建议；投资有风险，决策前请结合自身情况并咨询专业人士。",
"success": true,
"model_used": "rule:finance:disclaimer",
"token_usage": {
"output_tokens": 225,
"input_tokens": 6
}
},
"cost": 0.00028275,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0048",
"prompt": "How to read a stock balance sheet",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to read a stock balance sheet」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 78,
"input_tokens": 22
}
},
"cost": 0.0006911999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0049",
"prompt": "What is dollar-cost averaging",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What is dollar-cost averaging」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0050",
"prompt": "Travel itinerary for Japan in 7 days",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Travel itinerary for Japan in 7 days」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 80,
"input_tokens": 24
}
},
"cost": 0.0007128,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0051",
"prompt": "Beginner muscle building plan",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Beginner muscle building plan」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0052",
"prompt": "日本旅行攻略",
"prediction": "gemini-2.0-flash-001",
"generated_result": {
"generated_answer": "【life 建议】\n关于「日本旅行攻略」的一般性建议：\n1. 基础注意事项（日本旅行攻略）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）",
"success": true,
"model_used": "rule:life:advise",
"token_usage": {
"output_tokens": 65,
"input_tokens": 4
}
},
"cost": 1.98e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0053",
"prompt": "健身增肌计划",
"prediction": "gemini-2.0-flash-001",
"generated_result": {
"generated_answer": "【life 建议】\n关于「健身增肌计划」的一般性建议：\n1. 基础注意事项（健身增肌计划）\n2. 可操作建议：分步执行并观察效果\n3. 警示信号：出现下列情况应及时就医（见 warning 步骤）",
"success": true,
"model_used": "rule:life:advise",
"token_usage": {
"output_tokens": 65,
"input_tokens": 4
}
},
"cost": 1.98e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0054",
"prompt": "家常菜推荐",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「家常菜推荐」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 59,
"input_tokens": 3
}
},
"cost": 0.000486,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0055",
"prompt": "How to meal prep for a week",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to meal prep for a week」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 74,
"input_tokens": 18
}
},
"cost": 0.000648,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0056",
"prompt": "Best hiking trails near San Francisco",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Best hiking trails near San Francisco」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 80,
"input_tokens": 24
}
},
"cost": 0.0007128,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0057",
"prompt": "减脂餐怎么搭配",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「减脂餐怎么搭配」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 60,
"input_tokens": 4
}
},
"cost": 0.0004968,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0058",
"prompt": "How to start running for beginners",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to start running for beginners」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 78,
"input_tokens": 22
}
},
"cost": 0.0006911999999999999,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0059",
"prompt": "室内绿植推荐",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「室内绿植推荐」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 60,
"input_tokens": 4
}
},
"cost": 0.0004968,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0060",
"prompt": "How to prepare for graduate English exam",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to prepare for graduate English exam」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 82,
"input_tokens": 26
}
},
"cost": 0.0007344,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0061",
"prompt": "Effective study techniques",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Effective study techniques」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 73,
"input_tokens": 17
}
},
"cost": 0.0006372,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0062",
"prompt": "考研英语怎么备考",
"prediction": "deepseek-chat",
"generated_result": {
"generated_answer": "【education 方案设计】\n针对「考研英语怎么备考」的设计思路：\n1. 明确核心目标与验收标准\n2. 选择合适的方法/数据结构（依据：考研英语怎么备考）\n3. 拆解实现步骤并标注复杂度\n4. 预留边界处理与异常路径\n5. 设计自测用例（正常/边界/异常）",
"success": true,
"model_used": "rule:education:design",
"token_usage": {
"output_tokens": 86,
"input_tokens": 5
}
},
"cost": 2.478e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0063",
"prompt": "高效学习方法",
"prediction": "deepseek-chat",
"generated_result": {
"generated_answer": "【education 方案设计】\n针对「高效学习方法」的设计思路：\n1. 明确核心目标与验收标准\n2. 选择合适的方法/数据结构（依据：高效学习方法）\n3. 拆解实现步骤并标注复杂度\n4. 预留边界处理与异常路径\n5. 设计自测用例（正常/边界/异常）",
"success": true,
"model_used": "rule:education:design",
"token_usage": {
"output_tokens": 84,
"input_tokens": 4
}
},
"cost": 2.4080000000000003e-05,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0064",
"prompt": "面试技巧有哪些",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「面试技巧有哪些」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 60,
"input_tokens": 4
}
},
"cost": 0.0004968,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0065",
"prompt": "How to write a research paper",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「How to write a research paper」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 75,
"input_tokens": 19
}
},
"cost": 0.0006588,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0066",
"prompt": "GRE quantitative prep strategy",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「GRE quantitative prep strategy」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0067",
"prompt": "如何准备技术面试",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「如何准备技术面试」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 61,
"input_tokens": 5
}
},
"cost": 0.0005076,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0068",
"prompt": "Best resources for learning Python",
"prediction": "gpt-4o-mini",
"generated_result": {
"generated_answer": "【code 实现】\n```python\ndef solve() -> None:\n # 关键点：best、resources、learning、python\n # 1. 校验输入与边界条件\n # 2. 核心逻辑（依据 design 步骤）\n # 3. 输出结果\n pass\n```\n要点：best、resources、learning、python；复杂度与边界说明见 design/verify 步骤。",
"success": true,
"model_used": "rule:code:implement",
"token_usage": {
"output_tokens": 144,
"input_tokens": 22
}
},
"cost": 8.969999999999998e-05,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0069",
"prompt": "时间管理方法",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「时间管理方法」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 60,
"input_tokens": 4
}
},
"cost": 0.0004968,
"accuracy": 0.0,
"for_optimality": false
},
{
"global index": "mock_0070",
"prompt": "Why is the sky blue",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Why is the sky blue」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 68,
"input_tokens": 12
}
},
"cost": 0.0005832,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0071",
"prompt": "Explain the Transformer architecture",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Explain the Transformer architecture」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 80,
"input_tokens": 24
}
},
"cost": 0.0007128,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0072",
"prompt": "为什么天空是蓝色的",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「为什么天空是蓝色的」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 62,
"input_tokens": 6
}
},
"cost": 0.0005184,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0073",
"prompt": "介绍 Transformer 架构",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「介绍 Transformer 架构」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 67,
"input_tokens": 11
}
},
"cost": 0.0005723999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0074",
"prompt": "Write a vacation request email",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Write a vacation request email」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0075",
"prompt": "What is quantum entanglement",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What is quantum entanglement」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 74,
"input_tokens": 18
}
},
"cost": 0.000648,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0076",
"prompt": "请写一封请假邮件",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「请写一封请假邮件」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 61,
"input_tokens": 5
}
},
"cost": 0.0005076,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0077",
"prompt": "Explain CRISPR in simple terms",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Explain CRISPR in simple terms」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0078",
"prompt": "What is blockchain",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「What is blockchain」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 68,
"input_tokens": 12
}
},
"cost": 0.0005832,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0079",
"prompt": "简单介绍下黑洞",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「简单介绍下黑洞」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 60,
"input_tokens": 4
}
},
"cost": 0.0004968,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0080",
"prompt": "Write a haiku about autumn",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Write a haiku about autumn」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 73,
"input_tokens": 17
}
},
"cost": 0.0006372,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0081",
"prompt": "Suggest a name for a coffee shop",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Suggest a name for a coffee shop」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 77,
"input_tokens": 21
}
},
"cost": 0.0006804,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0082",
"prompt": "Plot twist ideas for a mystery novel",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Plot twist ideas for a mystery novel」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 80,
"input_tokens": 24
}
},
"cost": 0.0007128,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0083",
"prompt": "Write a short poem about the ocean",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Write a short poem about the ocean」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 78,
"input_tokens": 22
}
},
"cost": 0.0006911999999999999,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0084",
"prompt": "Ideas for a 5-year-old's birthday party",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Ideas for a 5-year-old's birthday party」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 82,
"input_tokens": 26
}
},
"cost": 0.0007344,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0085",
"prompt": "Story opening for a sci-fi short",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Story opening for a sci-fi short」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 77,
"input_tokens": 21
}
},
"cost": 0.0006804,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0086",
"prompt": "Suggest tagline for eco-friendly brand",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Suggest tagline for eco-friendly brand」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 81,
"input_tokens": 25
}
},
"cost": 0.0007236,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0087",
"prompt": "Lyrics for an upbeat summer song",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Lyrics for an upbeat summer song」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 77,
"input_tokens": 21
}
},
"cost": 0.0006804,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0088",
"prompt": "Title ideas for a romance novel",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Title ideas for a romance novel」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 76,
"input_tokens": 20
}
},
"cost": 0.0006696,
"accuracy": 1.0,
"for_optimality": false
},
{
"global index": "mock_0089",
"prompt": "Concept art description for a fantasy creature",
"prediction": "mistral-medium",
"generated_result": {
"generated_answer": "（大模型回退）「Concept art description for a fantasy creature」\n\n这是一条来自大模型回退路径的完整回答。\n要点：\n1. 对复杂/跨域任务给出综合推理\n2. 补充领域专家未覆盖的上下文\n3. 给出可执行的后续建议\n",
"success": true,
"model_used": "deepseek-chat",
"token_usage": {
"output_tokens": 86,
"input_tokens": 30
}
},
"cost": 0.0007776,
"accuracy": 0.0,
"for_optimality": false
}
]
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