{"case_id": "challenge-coding-001", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "state"], "scorer": "code_python_tests", "expected": {"tests": ["lines = ['# comment', '[db]', ' host = localhost ', 'port=5432', '', '[feature]', 'enabled=true', 'enabled = false']\nassert solution.solve(lines) == {'db': {'host': 'localhost', 'port': '5432'}, 'feature': {'enabled': 'false'}}", "assert solution.solve(['[x]', 'a=1', 'a=2', '[y]', 'b = hi']) == {'x': {'a': '2'}, 'y': {'b': 'hi'}}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(lines: list[str]) -> dict。lines 是简化 INI：空行和以 # 开头的行忽略；[section] 开始新 section；key=value 写入当前 section；key/value 两侧空白要去掉；同一 section 内重复 key 后者覆盖前者。返回嵌套 dict。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2ca132befd6923601a17f24e5efb427ea787e3ae63ae265dd45f0c700cd895d6", "started_at": "2026-06-16T15:49:48.337255+00:00", "latency_ms": 9241, "output": "```python\ndef solve(lines: list[str]) -> dict:\n result = {}\n current_section = None\n for line in lines:\n line = line.strip()\n if not line or line.startswith('#'):\n continue\n if line.startswith('[') and line.endswith(']'):\n current_section = line[1:-1].strip()\n if current_section not in result:\n result[current_section] = {}\n elif '=' in line and current_section is not None:\n key, value = line.split('=', 1)\n result[current_section][key.strip()] = value.strip()\n return result\n```", "usage": {"prompt_tokens": 118, "completion_tokens": 959, "total_tokens": 1077, "cost": 0.00112645, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00112645, "upstream_inference_prompt_cost": 2.36e-05, "upstream_inference_completions_cost": 0.00110285}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781624990-WOmGAb4571gGiqn1m6S3", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-002", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "ledger", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events = ['a credit 100', 'b debit 40', 'a credit 999', 'rev b', 'c debit 10']\nassert solution.solve(events) == 90", "events = ['x debit 5', 'rev y', 'rev x', 'rev x', 'z credit 7']\nassert solution.solve(events) == 7"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[str]) -> int。事件格式：\" credit \" 增加余额，\" debit \" 减少余额，\"rev \" 撤销此前尚未撤销过的同 id 事件。重复交易 id 只保留第一次，未知撤销忽略。返回最终余额。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3d2d5a46a600444476b5ddfd04634035ff394bcb76fcd230d785597c9cf295ae", "started_at": "2026-06-16T15:49:57.620892+00:00", "latency_ms": 54327, "output": "```python\ndef solve(events: list[str]) -> int:\n balance = 0\n seen = set()\n revoked = set()\n transactions = {}\n for event in events:\n parts = event.split()\n if not parts:\n continue\n if parts[0] == 'rev':\n if len(parts) < 2:\n continue\n id_ = parts[1]\n if id_ in transactions and id_ not in revoked:\n typ, amt = transactions[id_]\n if typ == 'credit':\n balance -= amt\n else:\n balance += amt\n revoked.add(id_)\n else:\n if len(parts) < 3:\n continue\n id_ = parts[0]\n typ = parts[1]\n amt = int(parts[2])\n if id_ in seen:\n continue\n seen.add(id_)\n transactions[id_] = (typ, amt)\n if typ == 'credit':\n balance += amt\n else:\n balance -= amt\n return balance\n```", "usage": {"prompt_tokens": 118, "completion_tokens": 4925, "total_tokens": 5043, "cost": 0.00568735, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00568735, "upstream_inference_prompt_cost": 2.36e-05, "upstream_inference_completions_cost": 0.00566375}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781624999-r3KxBBjQvYEeysiDXzF3", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-003", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "topological-sort"], "scorer": "code_python_tests", "expected": {"tests": ["deps = {'build': ['lint', 'test'], 'test': ['install'], 'lint': ['install']}\nassert solution.solve(deps) == [['install'], ['lint', 'test'], ['build']]", "assert solution.solve({'a': ['b'], 'b': ['a']}) == []", "assert solution.solve({'deploy': ['build'], 'build': []}) == [['build'], ['deploy']]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]]) -> list[list[str]]。deps 表示 task -> prerequisites。返回可并行执行的拓扑层，每层任务按字典序排序；如果存在环，返回空列表。所有只出现在 prerequisites 中的任务也要包含。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "413c5b602b0fd1ae1e9c3a49b09ecf03c61769fce4b34dbd96b5d8c6a2c68f90", "started_at": "2026-06-16T15:50:52.001923+00:00", "latency_ms": 18081, "output": "```python\ndef solve(deps):\n from collections import defaultdict\n \n all_tasks = set(deps.keys())\n for prereqs in deps.values():\n all_tasks.update(prereqs)\n \n graph = defaultdict(list)\n indegree = {task: 0 for task in all_tasks}\n \n for task, prereqs in deps.items():\n for pre in prereqs:\n graph[pre].append(task)\n indegree[task] += 1\n \n current_layer = sorted([t for t in all_tasks if indegree[t] == 0])\n result = []\n processed = 0\n \n while current_layer:\n result.append(current_layer)\n processed += len(current_layer)\n next_candidates = []\n for task in current_layer:\n for neighbor in graph[task]:\n indegree[neighbor] -= 1\n if indegree[neighbor] == 0:\n next_candidates.append(neighbor)\n current_layer = sorted(next_candidates)\n \n return result if processed == len(all_tasks) else []\n```", "usage": {"prompt_tokens": 110, "completion_tokens": 1597, "total_tokens": 1707, "cost": 0.00185855, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00185855, "upstream_inference_prompt_cost": 2.2e-05, "upstream_inference_completions_cost": 0.00183655}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625054-wEIKFcvjv1uCZ1kibP4L", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-004", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "lru"], "scorer": "code_python_tests", "expected": {"tests": ["ops = ['put a 1', 'put b 2', 'get a', 'put c 3', 'get b', 'get a', 'get c']\nassert solution.solve(2, ops) == [1, -1, 1, 3]", "assert solution.solve(0, ['put a 1', 'get a']) == [-1]", "assert solution.solve(1, ['put a 1', 'put a 2', 'get a']) == [2]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(capacity: int, ops: list[str]) -> list[int]，模拟 LRU cache。ops 包含 \"put key value\" 和 \"get key\"。get 返回 value，不存在返回 -1。put 已存在 key 要更新并变成最近使用。容量为 0 时所有 get 都返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "840e7b4d0c404f3d7b34ebc9931e87612608d6339755d5f1066fda55bd957375", "started_at": "2026-06-16T15:51:10.125411+00:00", "latency_ms": 10245, "output": "```python\nfrom collections import OrderedDict\n\ndef solve(capacity: int, ops: list[str]) -> list[int]:\n if capacity == 0:\n return [-1 for op in ops if op.startswith(\"get\")]\n \n cache = OrderedDict()\n result = []\n \n for op in ops:\n parts = op.split()\n if parts[0] == \"get\":\n key = int(parts[1])\n if key in cache:\n cache.move_to_end(key)\n result.append(cache[key])\n else:\n result.append(-1)\n else: # put\n key = int(parts[1])\n value = int(parts[2])\n if key in cache:\n cache[key] = value\n cache.move_to_end(key)\n else:\n cache[key] = value\n if len(cache) > capacity:\n cache.popitem(last=False)\n \n return result\n```", "usage": {"prompt_tokens": 123, "completion_tokens": 1072, "total_tokens": 1195, "cost": 0.0012574, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0012574, "upstream_inference_prompt_cost": 2.46e-05, "upstream_inference_completions_cost": 0.0012328}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625072-Z7HbOG0wZZkRCOmRoJ7A", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-dcom7cj8/test_solution.py\", line 4, in \n assert solution.solve(2, ops) == [1, -1, 1, 3]\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/private/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-dcom7cj8/solution.py\", line 20, in solve\n key = int(parts[1])\n ^^^^^^^^^^^^^\nValueError: invalid literal for int() with base 10: 'a'\n"}}, "error": null} {"case_id": "challenge-coding-005", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "json", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base = {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}\npatch = {'b': {'y': None, 'z': 4}, 'c': None}\nassert solution.solve(base, patch) == {'a': 1, 'b': {'x': 1, 'z': 4}}\nassert base == {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}", "assert solution.solve({'a': {'b': 1}}, {'a': 5}) == {'a': 5}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(base: dict, patch: dict) -> dict，执行 JSON Merge Patch：patch 中值为 None 表示删除该 key；两个值都是 dict 时递归合并；其他值覆盖。不能修改输入对象。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8dc22406b418d74ea74b50692fe086d4f80748258269dc93f82290e6c344b5a3", "started_at": "2026-06-16T15:51:20.411731+00:00", "latency_ms": 6264, "output": "```python\nimport copy\n\ndef solve(base: dict, patch: dict) -> dict:\n result = copy.deepcopy(base)\n for key, value in patch.items():\n if value is None:\n result.pop(key, None)\n elif isinstance(value, dict) and isinstance(result.get(key), dict):\n result[key] = solve(result[key], value)\n else:\n result[key] = copy.deepcopy(value)\n return result\n```", "usage": {"prompt_tokens": 98, "completion_tokens": 472, "total_tokens": 570, "cost": 0.0005624, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0005624, "upstream_inference_prompt_cost": 1.96e-05, "upstream_inference_completions_cost": 0.0005428}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625082-5W1mFU1xyBeUycEJm5XM", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-006", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "regex", "duration"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1h 30m 500ms') == 5400500", "assert solution.solve('2d 1h 2s') == 176402000", "assert solution.solve('100ms 2s 3ms') == 2103"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> int，把时长字符串转换成毫秒。支持整数单位 d、h、m、s、ms，可有空格，单位可重复，顺序任意。例如 \"1h 30m 500ms\"。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "ce87366a2f6f080a35c0fdd0872b6a8304a8233e0c5c9361c19fec614c0d1fcb", "started_at": "2026-06-16T15:51:26.719167+00:00", "latency_ms": 7443, "output": "```python\nimport re\n\ndef solve(text: str) -> int:\n text = text.replace(' ', '')\n total = 0\n for num, unit in re.findall(r'(\\d+)(ms|d|h|m|s)', text):\n n = int(num)\n if unit == 'd':\n total += n * 86400000\n elif unit == 'h':\n total += n * 3600000\n elif unit == 'm':\n total += n * 60000\n elif unit == 's':\n total += n * 1000\n elif unit == 'ms':\n total += n\n return total\n```", "usage": {"prompt_tokens": 101, "completion_tokens": 729, "total_tokens": 830, "cost": 0.00085855, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00085855, "upstream_inference_prompt_cost": 2.02e-05, "upstream_inference_completions_cost": 0.00083835}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625089-NS8ahfiQqrixFXUZcemh", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-007", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "quotes"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('{a:[(1)]}') is True", "assert solution.solve(\"{'x': '(]'}\") is True", "assert solution.solve(\"['unterminated]\") is False", "assert solution.solve('([)]') is False", "assert solution.solve(\"\\\"paren \\\\\\\" ) still quoted\\\"\") is True"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(s: str) -> bool，检查括号 ()[]{} 是否配对。单引号或双引号内部的括号忽略；反斜杠会转义引号。输入字符串可以包含普通字符。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2f2e8f01533244c8104f74b3f9c9bc261154f2ff4c46c03a031258f6a5706f9f", "started_at": "2026-06-16T15:51:34.209225+00:00", "latency_ms": 84543, "output": "```python\ndef solve(s: str) -> bool:\n stack = []\n in_string = False\n string_char = None\n i = 0\n n = len(s)\n pairs = {')': '(', ']': '[', '}': '{'}\n \n while i < n:\n if in_string:\n if s[i] == '\\\\':\n i += 2\n continue\n elif s[i] == string_char:\n in_string = False\n string_char = None\n else:\n if s[i] in \"'\\\"\":\n in_string = True\n string_char = s[i]\n elif s[i] in '([{':\n stack.append(s[i])\n elif s[i] in ')]}':\n if not stack or stack[-1] != pairs[s[i]]:\n return False\n stack.pop()\n i += 1\n \n return not stack\n```", "usage": {"prompt_tokens": 96, "completion_tokens": 8178, "total_tokens": 8274, "cost": 0.0094239, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0094239, "upstream_inference_prompt_cost": 1.92e-05, "upstream_inference_completions_cost": 0.0094047}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625096-ok3DNGoCZ6Jrqausk52Q", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-008", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dedupe", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["rows = [{'user':'b','ts':1,'value':'old'}, {'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]\nassert solution.solve(rows) == [{'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]", "rows = [{'user':'a','ts':1,'value':'first'}, {'user':'a','ts':1,'value':'second'}]\nassert solution.solve(rows) == [{'user':'a','ts':1,'value':'second'}]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[dict]) -> list[dict]。每行有 user、ts、value。对每个 user 保留 ts 最大的一行；若 ts 相同，保留在输入中更靠后的行。输出按 user 字典序排序。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a9a2d40a756627e38d28a8ac6afc98311acbafa718d7b3aaaecbedb9f020179", "started_at": "2026-06-16T15:52:58.793485+00:00", "latency_ms": 6814, "output": "```python\ndef solve(rows: list[dict]) -> list[dict]:\n best = {}\n for i, row in enumerate(rows):\n u = row['user']\n if u not in best:\n best[u] = (i, row)\n else:\n bi, br = best[u]\n if row['ts'] > br['ts'] or (row['ts'] == br['ts'] and i > bi):\n best[u] = (i, row)\n return sorted((r for _, r in best.values()), key=lambda x: x['user'])\n```", "usage": {"prompt_tokens": 107, "completion_tokens": 773, "total_tokens": 880, "cost": 0.00091035, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00091035, "upstream_inference_prompt_cost": 2.14e-05, "upstream_inference_completions_cost": 0.00088895}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625181-nLG0sDgf0iISg9RqWoBh", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-debugging-001", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "iterator-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码在 total 之后再次读取数据会变成空列表。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的第一行函数定义>。\n\n```python\ndef summarize(items=iter([1, 2, 3])):\n return sum(items)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7b02a617eebe49b179cee84c9b8347c6bebe382f42a2b199d92b3aa9ed844102", "started_at": "2026-06-16T15:53:05.646371+00:00", "latency_ms": 10509, "output": "### 根因\nPython的函数默认参数在**函数定义阶段就会完成求值**，`iter([1,2,3])`会生成一个仅可单次遍历的迭代器对象，该对象作为默认参数被缓存。首次调用`summarize()`时迭代器被`sum`耗尽，后续调用会复用同一个已耗尽的迭代器，因此读取结果为空。\n\n### 最小修复\n将默认参数改为`None`，在函数内部判断当参数为`None`时重新生成迭代器，避免复用已耗尽的迭代器，修复后完整函数为：\n```python\ndef summarize(items=None):\n if items is None:\n items = iter([1, 2, 3])\n return sum(items)\n```\n\nFIX: def summarize(items=None):", "usage": {"prompt_tokens": 106, "completion_tokens": 761, "total_tokens": 867, "cost": 0.00089635, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00089635, "upstream_inference_prompt_cost": 2.12e-05, "upstream_inference_completions_cost": 0.00087515}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625187-PZK7s6JJaPpnXM86xIhG", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:"}}, "error": null} {"case_id": "challenge-debugging-002", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "defaultdict", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望统计每个用户的事件数，但所有用户计数会互相影响。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 defaultdict 初始化行>。\n\n```python\nfrom collections import defaultdict\nshared = {'seen': []}\ncounts = defaultdict(lambda: shared)\n\ndef add(user, event):\n counts[user]['seen'].append(event)\n return counts[user]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc1eb426cf811456432a61a306862f8bf804417edb8c8fca6dd3b86c1f9a9940", "started_at": "2026-06-16T15:53:16.157657+00:00", "latency_ms": 13136, "output": "### 根因\n`defaultdict`的默认值工厂函数`lambda: shared`返回的是全局唯一的`shared`字典对象，所有用户的`counts`条目都指向同一个`seen`列表，因此事件计数会互相影响。\n\n### 最小修复\n将`defaultdict`的默认值工厂改为每次调用时返回包含独立空`seen`列表的新字典，无需修改`add`函数逻辑。\n\nFIX: counts = defaultdict(lambda: {'seen': []})", "usage": {"prompt_tokens": 131, "completion_tokens": 1156, "total_tokens": 1287, "cost": 0.0013556, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0013556, "upstream_inference_prompt_cost": 2.62e-05, "upstream_inference_completions_cost": 0.0013294}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625198-y766HGg3e2WcPLHfXkoC", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-003", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "off-by-one", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面分页代码会漏掉最后不足 page_size 的一页。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 range 行>。\n\n```python\ndef pages(items, page_size):\n out = []\n for start in range(0, len(items) - page_size, page_size):\n out.append(items[start:start + page_size])\n return out\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c6fe209d60968a3b2d253a065c8ce8255865f73575665a685d957cb52ce82011", "started_at": "2026-06-16T15:53:29.295314+00:00", "latency_ms": 9054, "output": "Bug：`range` 的结束参数写成了 `len(items) - page_size`，导致循环在到达最后一页（或不足一页的剩余部分）的起始索引之前就提前终止。当 `len(items)` 正好是 `page_size` 的整数倍时，会直接漏掉最后一页；有余数时也会漏掉剩余部分。\n\n最小修复：将 `range` 的结束参数改为 `len(items)`，让循环能遍历到最后一个可能的起始索引；配合切片 `items[start:start + page_size]` 的自动越界截断特性，即可正确包含最后不足一页的数据。\n\nFIX: range(0, len(items), page_size)", "usage": {"prompt_tokens": 129, "completion_tokens": 994, "total_tokens": 1123, "cost": 0.0011689, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0011689, "upstream_inference_prompt_cost": 2.58e-05, "upstream_inference_completions_cost": 0.0011431}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625211-wpWY4oFZCTs9aioVwCfT", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:"}}, "error": null} {"case_id": "challenge-debugging-004", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "sorting", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望把数字字符串按数值排序，但结果是字典序。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef order(ids):\n return sorted(ids)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b3f10943f43eaa04524058b0dd7fb30cbd21740003559e79de619ae210a697e4", "started_at": "2026-06-16T15:53:38.351258+00:00", "latency_ms": 5807, "output": "### Bug说明\n`sorted`默认按字符串字典序排序，未将数字字符串转为数值比较，会导致`'10'`这类数值更大的字符串排在`'2'`前，不符合按数值排序的预期。\n\n### 最小修复\n给`sorted`添加`key=int`参数，将元素转为整数后再比较排序。\n\nFIX: return sorted(ids, key=int)", "usage": {"prompt_tokens": 96, "completion_tokens": 423, "total_tokens": 519, "cost": 0.00050565, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00050565, "upstream_inference_prompt_cost": 1.92e-05, "upstream_inference_completions_cost": 0.00048645}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625220-LmwpTfLMU5EUmHT7tYzx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-005", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "memoization", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面缓存装饰器会把不同参数的调用混在一起。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 key 赋值行>。\n\n```python\ncache = {}\ndef memo(fn):\n def wrapper(*args, **kwargs):\n key = fn.__name__\n if key not in cache:\n cache[key] = fn(*args, **kwargs)\n return cache[key]\n return wrapper\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fdaf2df9bffeacf442086f01d24eb1fce336e874cebec386f24acd9175c42fc6", "started_at": "2026-06-16T15:53:44.159965+00:00", "latency_ms": 11620, "output": "Bug: 当前 `key` 仅使用函数名 `fn.__name__`，未包含调用参数，导致不同参数的函数调用会共用同一缓存条目，返回错误的结果。\n\n最小修复：将 `key` 构造为包含函数名、位置参数和关键字参数的元组，以确保不同参数调用对应不同的缓存键。\n\nFIX: key = (fn.__name__, args, tuple(kwargs.items()))", "usage": {"prompt_tokens": 134, "completion_tokens": 1409, "total_tokens": 1543, "cost": 0.00164715, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00164715, "upstream_inference_prompt_cost": 2.68e-05, "upstream_inference_completions_cost": 0.00162035}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625226-ZQKNatWa4rvQZgCuHwUl", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-006", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "aliasing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望浅拷贝列表后独立追加，但原列表也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copy 行>。\n\n```python\ndef append_copy(items, value):\n copied = items\n copied.append(value)\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d79d9daa2c034ff1badc1d0951de62e17f2421bac20433e520a48c2992cae000", "started_at": "2026-06-16T15:53:55.782117+00:00", "latency_ms": 7598, "output": "Bug: `copied = items` 仅将引用赋给新变量，两者指向同一个列表对象，因此 `append` 会同时修改原列表。\n\n最小修复: 使用浅拷贝创建独立的新列表对象。\n\nFIX: copied = items.copy()", "usage": {"prompt_tokens": 107, "completion_tokens": 888, "total_tokens": 995, "cost": 0.0010426, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0010426, "upstream_inference_prompt_cost": 2.14e-05, "upstream_inference_completions_cost": 0.0010212}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625238-NFu6T2S0xFfq8ueRBCiI", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-007", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "json", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望解析 JSON 字符串，但传入已经是 dict 时会报错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 data 赋值行>。\n\n```python\nimport json\n\ndef load(payload):\n data = json.loads(payload)\n return data['id']\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "dae0481dbfca35623cf6eaf5f44910cc59204edc238411f6ec1221586215b6a3", "started_at": "2026-06-16T15:54:03.382410+00:00", "latency_ms": 9028, "output": "**Bug**：`json.loads()` 只能解析 JSON 字符串，当 `payload` 已经是 `dict` 类型时会抛出 `TypeError`。\n\n**最小修复**：在解析前判断 `payload` 的类型，字符串则解析，否则直接使用。\n\n```python\nimport json\n\ndef load(payload):\n data = json.loads(payload) if isinstance(payload, str) else payload\n return data['id']\n```\n\nFIX: data = json.loads(payload) if isinstance(payload, str) else payload", "usage": {"prompt_tokens": 111, "completion_tokens": 864, "total_tokens": 975, "cost": 0.0010158, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0010158, "upstream_inference_prompt_cost": 2.22e-05, "upstream_inference_completions_cost": 0.0009936}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625245-MM9SS4v7s79Na6PmwxOa", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-008", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "finally", "debugging"], "scorer": "contains_any", "expected": {"answers": ["删除 finally 中的 return None", "去掉 finally 的 return None", "不要在 finally 里 return None", "remove return None", "去掉 finally 中的 return None", "删除或替换 finally 中的 return None", "去掉 finally 中的 `return None`", "删除或替换 finally 中的 `return None`", "删除 finally 块中的 `return None`", "删除 finally 块中的 return None", "删除 finally 中的 `return None`", "删除 `finally` 块中的 `return None`", "删除 `finally` 中的 `return None`", "删除 `finally: return None`", "将 `finally:` 中的 `return None` 删除", "finally 中的 return None 删除", "finally: 中的 return None 删除", "删除 finally 块中的 'return None'", "删除 finally 子句中的 `return None`", "删除 finally 子句中的 return None", "delete the line `return None` inside the finally block", "delete the line return None inside the finally block", "finally 块不应包含 return 语句", "finally 块不应包含 return", "finally 不应包含 return"]}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望 finally 后仍保留 try 中返回值，但实际总是返回 None。请指出 bug，并给出最小修复。最后单独一行写 FIX: <要删除或替换的 finally 行说明>。\n\n```python\ndef read_value():\n try:\n return 42\n finally:\n return None\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3cc6ae8fe4f15528225f040b759f5535e31e0ee3dab226c836ed3b9c19707a57", "started_at": "2026-06-16T15:54:12.412313+00:00", "latency_ms": 5378, "output": "### Bug原因\nPython执行逻辑中，`try`块的`return`会先暂存待返回的值，随后执行`finally`块；若`finally`块存在`return`语句，会直接覆盖之前暂存的返回值，因此原本要返回的`42`被`finally`的`return None`覆盖，最终始终返回`None`。\n\n### 最小修复\n删除`finally`块中的`return None`语句，`finally`仅用于执行资源清理等必要逻辑，无需返回值。\n\nFIX: 删除finally块中的return None语句", "usage": {"prompt_tokens": 112, "completion_tokens": 521, "total_tokens": 633, "cost": 0.00062155, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00062155, "upstream_inference_prompt_cost": 2.24e-05, "upstream_inference_completions_cost": 0.00059915}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625254-n0NcDjYnytjM6NEJe8Jn", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"matched": []}}, "error": null} {"case_id": "challenge-reasoning-001", "suite": "reasoning", "case_version": "0.2.0", "tags": ["arithmetic", "multi-step"], "scorer": "exact", "expected": {"answer": "125", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：有 A、B、C、D 四个服务。A 每分钟处理 6 个请求，B 比 A 少 2 个，C 是 B 的 2 倍，D 是 A 和 C 的平均值。四个服务 5 分钟一共处理多少请求？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "06f9a3eb3666e5854b2b742553674373622a42e326be166231a39c67b5604810", "started_at": "2026-06-16T15:54:17.791869+00:00", "latency_ms": 3068, "output": "125", "usage": {"prompt_tokens": 113, "completion_tokens": 109, "total_tokens": 222, "cost": 0.00014795, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00014795, "upstream_inference_prompt_cost": 2.26e-05, "upstream_inference_completions_cost": 0.00012535}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625260-F4qaPNZ4nxECxJLSI3pb", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "125", "actual": "125"}}, "error": null} {"case_id": "challenge-reasoning-002", "suite": "reasoning", "case_version": "0.2.0", "tags": ["constraint-solving"], "scorer": "exact", "expected": {"answer": "D", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答一个字母：五个任务 A、B、C、D、E 排队。A 必须在 B 前，B 必须在 C 前；D 不能在两端；E 必须紧挨在 C 后面。在所有满足条件的队列中，按字典序最小的队列第三个任务是谁？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e273e5a0cd57aef19af9e4ccfcd445a7523180f5cab62526c14aa0e62d5c1cc9", "started_at": "2026-06-16T15:54:20.860894+00:00", "latency_ms": 36884, "output": "D", "usage": {"prompt_tokens": 105, "completion_tokens": 4338, "total_tokens": 4443, "cost": 0.0050097, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0050097, "upstream_inference_prompt_cost": 2.1e-05, "upstream_inference_completions_cost": 0.0049887}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625263-HrKNiilxDoMKrvk3rRLy", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "D", "actual": "D"}}, "error": null} {"case_id": "challenge-reasoning-003", "suite": "reasoning", "case_version": "0.2.0", "tags": ["binary", "symbolic"], "scorer": "exact", "expected": {"answer": "0", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：一个 4 位二进制数从 1011 开始，先左移一位并只保留低 4 位，再与 0110 做异或，最后转成十进制。结果是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "813f5aead205f4aa7a9d2a1e7b7085daae002a54592edd8d8aad2e7d7551897c", "started_at": "2026-06-16T15:54:57.746189+00:00", "latency_ms": 2817, "output": "0", "usage": {"prompt_tokens": 92, "completion_tokens": 160, "total_tokens": 252, "cost": 0.0002024, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002024, "upstream_inference_prompt_cost": 1.84e-05, "upstream_inference_completions_cost": 0.000184}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625300-BHbpybuhgB4J91q7brjU", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "0", "actual": "0"}}, "error": null} {"case_id": "challenge-reasoning-004", "suite": "reasoning", "case_version": "0.2.0", "tags": ["set", "operations"], "scorer": "exact", "expected": {"answer": "18", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：一个集合最初为 {1,2,3,4,5}。依次执行：删除所有偶数；加入 6 和 7；把每个元素乘以 2；删除大于 10 的元素。最终集合元素之和是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3077e41c160e4ebe361234b76e647f42583619ef446b73e7c1e25858312f328e", "started_at": "2026-06-16T15:55:00.565222+00:00", "latency_ms": 3522, "output": "18", "usage": {"prompt_tokens": 98, "completion_tokens": 131, "total_tokens": 229, "cost": 0.00017025, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00017025, "upstream_inference_prompt_cost": 1.96e-05, "upstream_inference_completions_cost": 0.00015065}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625302-8PgzfOcQXMhBT6vGwy9A", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "18", "actual": "18"}}, "error": null} {"case_id": "challenge-reasoning-005", "suite": "reasoning", "case_version": "0.2.0", "tags": ["logic", "sat"], "scorer": "exact", "expected": {"answer": "可满足", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答“可满足”或“不可满足”：有三个布尔变量 x、y、z。约束为：x 或 y 为真；如果 x 为真则 z 为假；如果 y 为真则 z 为真；x 和 y 不能同时为真。是否存在赋值满足全部约束？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1e534bd21af5e75f0c9fd61e3d5a3f660355d4555e34e16a06744234da47e006", "started_at": "2026-06-16T15:55:04.089503+00:00", "latency_ms": 8351, "output": "可满足", "usage": {"prompt_tokens": 111, "completion_tokens": 537, "total_tokens": 648, "cost": 0.00063975, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00063975, "upstream_inference_prompt_cost": 2.22e-05, "upstream_inference_completions_cost": 0.00061755}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625306-TjcFekqc1PGYqY0F0tFY", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "可满足", "actual": "可满足"}}, "error": null} {"case_id": "challenge-rag-001", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "grounded"], "scorer": "text_rules", "expected": {"required": ["人工抽检"], "required_any": [["默认使用", "默认判分", "默认采用", "作为默认判分"]], "forbidden": ["因为成本太高", "因为不支持中文"], "max_chars": 160}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：DracoBench v0.2 的目标是提高区分度，优先增加 coding、debugging、RAG 和 instruction_following 题。\n资料 B：DracoBench v0.2 不会默认使用 LLM-as-judge；开放中文写作题只做少量规则校验和人工抽检。\n资料 C：v0.2 的 HTML 报告必须展示通过率、成本、reasoning tokens、失败样例和逐题明细。\n\n问题：v0.2 为什么没有把 LLM-as-judge 作为默认判分？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7a40b395b42a59b621957d70755d39fca26dba23f4e0c46743018935350319d3", "started_at": "2026-06-16T15:55:12.442983+00:00", "latency_ms": 5956, "output": "根据资料B，DracoBench v0.2针对开放中文写作题仅采用少量规则校验和人工抽检的方式处理，因此没有将LLM-as-judge设为默认判分方式。", "usage": {"prompt_tokens": 167, "completion_tokens": 545, "total_tokens": 712, "cost": 0.00066015, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00066015, "upstream_inference_prompt_cost": 3.34e-05, "upstream_inference_completions_cost": 0.00062675}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625314-iIbC2UN5hDQtRiC2VPtI", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 76, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-002", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "tradeoff", "abstain"], "scorer": "text_rules", "expected": {"required": ["Beta", "成本", "延迟", "判断"], "forbidden": ["Alpha 更适合", "多模态更强"], "max_chars": 180}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：模型 Alpha 在 30 道 challenge 题中通过 24 道，成本 0.08 美元，平均延迟 9 秒。模型 Beta 通过 22 道，成本 0.02 美元，平均延迟 3 秒。资料没有给出两者在多模态任务上的表现。\n\n问题：如果要写低成本高吞吐摘要服务，资料更支持选择哪个模型？另外，多模态表现能否判断？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b25dfce277314b219ab8ccef6f02fb644e23cd169765867993ae58ccd7258c4a", "started_at": "2026-06-16T15:55:18.401094+00:00", "latency_ms": 7535, "output": "对于低成本高吞吐摘要服务，资料更支持选择模型Beta，因为它的成本更低、平均延迟更短，更匹配低成本高吞吐的需求。\n多模态表现无法判断，因为资料未提供两个模型在多模态任务上的相关表现信息。", "usage": {"prompt_tokens": 145, "completion_tokens": 274, "total_tokens": 419, "cost": 0.0003441, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003441, "upstream_inference_prompt_cost": 2.9e-05, "upstream_inference_completions_cost": 0.0003151}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625320-Cs6R3Jl0BsCaEvgfDJG7", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 93, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-003", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "nuance"], "scorer": "text_rules", "expected": {"required": ["题面歧义"], "required_any": [["47/50", "47 题", "47题"], ["空输出", "输出为空", "未输出"]], "forbidden": ["满分", "完全失败"], "max_chars": 240}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：一次评测中，K 模型在 smoke set 上 7/7，通过率 100%；在 hard set 上原始结果 47/50，其中 2 题后来被认定为题面歧义，单独复测通过。另有 1 题因 reasoning tokens 用尽而空输出。\n\n问题：更公平的文字结论应该如何描述 K 模型这次 hard set 表现？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "12db30955792c48368632f01aa0a9c06e9fc27004c4dbf12ce602cb8488494e6", "started_at": "2026-06-16T15:55:25.937650+00:00", "latency_ms": 7467, "output": "K模型在hard set原始作答中正确完成47道题，另有2道题因题面存在歧义，后续单独复测后通过；剩余1道题因推理token耗尽导致空输出，未获得有效得分。", "usage": {"prompt_tokens": 133, "completion_tokens": 602, "total_tokens": 735, "cost": 0.0007189, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007189, "upstream_inference_prompt_cost": 2.66e-05, "upstream_inference_completions_cost": 0.0006923}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625328-ZAukFBYevxVPtN9aDVox", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"missing": ["题面歧义"], "missing_any": [["47/50", "47 题", "47题"]], "present_forbidden": [], "char_count": 78, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-004", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "不包含", "利润率"], "forbidden": ["可以判断", "训练数据"], "max_chars": 100}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答，不要使用资料外知识。\n\n资料：报告字段包括 pass_rate、avg_latency_ms、total_cost、prompt_tokens、completion_tokens、reasoning_tokens。报告不包含模型训练数据来源，也不包含供应商真实利润率。\n\n问题：根据资料，能否从报告判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cb2d9baeb98b0b4836972058965359b461f03aaba6cd096f40ffc813ce331880", "started_at": "2026-06-16T15:55:33.406456+00:00", "latency_ms": 2295, "output": "不能。资料明确说明报告不包含供应商真实利润率，且给出的报告字段也无相关可推导出供应商利润率的内容。", "usage": {"prompt_tokens": 111, "completion_tokens": 88, "total_tokens": 199, "cost": 0.0001234, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0001234, "upstream_inference_prompt_cost": 2.22e-05, "upstream_inference_completions_cost": 0.0001012}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625335-tleyA7VsSCFncyZIZCmM", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 49, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-if-001", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["json", "nested"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["status", "scores", "note"], "additionalProperties": false, "properties": {"status": {"type": "string", "const": "review"}, "scores": {"type": "object", "required": ["coding", "debugging", "rag"], "additionalProperties": false, "properties": {"coding": {"type": "integer"}, "debugging": {"type": "integer"}, "rag": {"type": "integer"}}}, "note": {"type": "string"}}}}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 JSON 对象，不要 Markdown。字段 status 必须是 \"review\"；字段 scores 必须是对象，包含 coding、debugging、rag 三个整数；字段 note 必须是不超过 12 个汉字的中文字符串。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7f670ae329c67bf1957a977815256b403ae7965cb15f2d2db520256cc3f2eb77", "started_at": "2026-06-16T15:55:35.702457+00:00", "latency_ms": 14353, "output": "{\n \"status\": \"review\",\n \"scores\": {\n \"coding\": 85,\n \"debugging\": 80,\n \"rag\": 75\n },\n \"note\": \"代码质量良好，RAG待改进\"\n}", "usage": {"prompt_tokens": 93, "completion_tokens": 1724, "total_tokens": 1817, "cost": 0.0020012, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0020012, "upstream_inference_prompt_cost": 1.86e-05, "upstream_inference_completions_cost": 0.0019826}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625338-L6nmoLj7uVRIMiJk0ilZ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"errors": [], "value": {"status": "review", "scores": {"coding": 85, "debugging": 80, "rag": 75}, "note": "代码质量良好，RAG待改进"}}}, "error": null} {"case_id": "challenge-if-002", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["format", "line-control"], "scorer": "regex", "expected": {"pattern": "^\\s*BEGIN\\s*\\n[^\\n]*模型评测[^\\n]*\\n[^\\n]*HTML报告[^\\n]*\\nEND\\s*$", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 4 行，不要解释。第 1 行是 BEGIN，第 4 行是 END。第 2 行必须包含“模型评测”，第 3 行必须包含“HTML报告”。不能出现任何项目符号。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "773b2e7398be979e738e08c3c8486ca69bae0f71d9a2abe3430cef775f5a59fb", "started_at": "2026-06-16T15:55:50.057708+00:00", "latency_ms": 3383, "output": "BEGIN\n模型评测是评估AI模型性能的关键环节\nHTML报告可以直观展示评测结果\nEND", "usage": {"prompt_tokens": 96, "completion_tokens": 232, "total_tokens": 328, "cost": 0.000286, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000286, "upstream_inference_prompt_cost": 1.92e-05, "upstream_inference_completions_cost": 0.0002668}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625352-IDyiu4Yxql8jAY3JXPsS", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "^\\s*BEGIN\\s*\\n[^\\n]*模型评测[^\\n]*\\n[^\\n]*HTML报告[^\\n]*\\nEND\\s*$"}}, "error": null} {"case_id": "challenge-if-003", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["constraint", "zh"], "scorer": "text_rules", "expected": {"required": ["难题", "区分度"], "forbidden": ["最强", "吊打", "遥遥领先"], "max_chars": 28}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出一个中文句子，不能超过 28 个汉字。必须同时包含“难题”和“区分度”，不能包含“最强”“吊打”“遥遥领先”。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "63d393d3332e09c8d34bfa5fceb4812734bf76c2333f7e6d1585cf977944f0db", "started_at": "2026-06-16T15:55:53.442608+00:00", "latency_ms": 10325, "output": "试卷中的难题区分度很高，能有效检测学生水平。", "usage": {"prompt_tokens": 78, "completion_tokens": 1661, "total_tokens": 1739, "cost": 0.00192575, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00192575, "upstream_inference_prompt_cost": 1.56e-05, "upstream_inference_completions_cost": 0.00191015}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625355-jiW0cBKxVS6T9huwK4XJ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 22, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-zh-writing-001", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["wechat", "conclusion"], "scorer": "text_rules", "expected": {"required": ["简单题", "真实能力", "失败样例"], "forbidden": ["吊打"], "max_chars": 120}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "写一段不超过 120 个汉字的公众号结论，主题是“模型在简单题满分不代表真实强”。必须包含“简单题”“真实能力”“失败样例”，不能出现“吊打”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "f330d4a7913b830c15df0d2a36cf0a9e5c07628ef6fa52408cc1bd2e90074762", "started_at": "2026-06-16T15:56:03.769187+00:00", "latency_ms": 8335, "output": "不少模型刷简单题能拿满分，但这只是基础门槛，完全代表不了真实能力。真正衡量水平得看复杂场景下的表现，还有对失败样例的复盘优化能力，别被简单题满分迷惑了判断。", "usage": {"prompt_tokens": 84, "completion_tokens": 410, "total_tokens": 494, "cost": 0.0004883, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0004883, "upstream_inference_prompt_cost": 1.68e-05, "upstream_inference_completions_cost": 0.0004715}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625366-1sWaVEFKCYRavqiVSWEC", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 78, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-zh-writing-002", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["rewrite", "zh"], "scorer": "text_rules", "expected": {"required": ["复杂调试", "稳定性"], "forbidden": ["猛", "掉链子"], "max_chars": 80}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "把下面口语句改写成专业表达，不超过 80 个汉字：这个模型看起来很猛，但一遇到复杂调试就开始掉链子。必须包含“复杂调试”和“稳定性”，不能包含“猛”“掉链子”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "1628d5e9cbea22d0750b547f0818eafa82d503dcad8fdc41ef2f523f9fbb55a1", "started_at": "2026-06-16T15:56:12.106881+00:00", "latency_ms": 3794, "output": "该模型表面性能表现优异，但面对复杂调试场景时稳定性不足。", "usage": {"prompt_tokens": 92, "completion_tokens": 200, "total_tokens": 292, "cost": 0.0002484, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002484, "upstream_inference_prompt_cost": 1.84e-05, "upstream_inference_completions_cost": 0.00023}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625374-PKyIwXAw7mSD26t6caQr", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 28, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-coding-009", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "aggregation", "dirty-input"], "scorer": "code_python_tests", "expected": {"tests": ["events=[{'user':'b','type':'add','amount':'5'},{'user':'a','type':'add','amount':3},{'user':'b','type':'remove','amount':2},{'user':'a','type':'remove','amount':3}]\nassert solution.solve(events) == {'b': 3}", "assert solution.solve([]) == {}", "assert solution.solve([{'user':'x','type':'remove','amount':'2'}]) == {'x': -2}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[dict]) -> dict[str, int]。每个事件包含 user、type、amount；type 为 \"add\" 或 \"remove\"。按 user 汇总 add 减 remove 后的库存，结果中去掉库存为 0 的用户，按 key 字典序返回普通 dict。amount 可能是字符串数字。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "9b81c7f8e34dbf12cfabd35ebb618802fe09200deca1d146558b4e1c12e6fd1e", "started_at": "2026-06-16T15:56:15.901938+00:00", "latency_ms": 4828, "output": "```python\nfrom collections import defaultdict\n\ndef solve(events: list[dict]) -> dict[str, int]:\n inventory = defaultdict(int)\n for event in events:\n user = event['user']\n t = event['type']\n amount = int(event['amount'])\n if t == 'add':\n inventory[user] += amount\n elif t == 'remove':\n inventory[user] -= amount\n result = {}\n for user in sorted(inventory):\n if inventory[user] != 0:\n result[user] = inventory[user]\n return result\n```", "usage": {"prompt_tokens": 123, "completion_tokens": 559, "total_tokens": 682, "cost": 0.00066745, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00066745, "upstream_inference_prompt_cost": 2.46e-05, "upstream_inference_completions_cost": 0.00064285}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625378-gZNSKgMLQx6vtZuwVw2R", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-010", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "expression"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1 + 2 - 3') == 0", "assert solution.solve('10 - (2 + 3) + 4') == 9", "assert solution.solve('(1+(4+5+2)-3)+(6+8)') == 23"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(expr: str) -> int。expr 只包含非负整数、+、-、空格和括号，计算表达式结果。不要使用 eval。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "662cadd9b4e3fdcfdf38e1d7338201fe3049d948576c89303695cff58950b3b4", "started_at": "2026-06-16T15:56:20.772399+00:00", "latency_ms": 138140, "output": "", "usage": {"prompt_tokens": 85, "completion_tokens": 16384, "total_tokens": 16469, "cost": 0.0188586, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0188586, "upstream_inference_prompt_cost": 1.7e-05, "upstream_inference_completions_cost": 0.0188416}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625383-e5n0cYpRtTOxCYxIuU2u", "finish_reason": "length", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-udyf9kc6/test_solution.py\", line 3, in \n assert solution.solve('1 + 2 - 3') == 0\n ^^^^^^^^^^^^^^\nAttributeError: module 'solution' has no attribute 'solve'\n"}}, "error": null} {"case_id": "challenge-coding-011", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "sorting", "dedupe"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['alice 10','bob 12','alice 15','','bob 11']) == [('alice',15),('bob',12)]", "assert solution.solve(['x -1','a -1','b 0']) == [('b',0),('a',-1),('x',-1)]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[str]) -> list[tuple[str, int]]。每行格式为 \"name score\"，空白数量不定；同名保留最高分；输出按分数降序、同分按 name 升序。忽略空行。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "332bccf5652506856c633d7093431279279a22b2d3a99762f6cba55df7d884af", "started_at": "2026-06-16T15:58:38.950834+00:00", "latency_ms": 26504, "output": "```python\ndef solve(rows: list[str]) -> list[tuple[str, int]]:\n best: dict[str, int] = {}\n for row in rows:\n parts = row.split()\n if len(parts) < 2:\n continue\n name = \" \".join(parts[:-1])\n try:\n score = int(parts[-1])\n except ValueError:\n continue\n if name in best:\n if score > best[name]:\n best[name] = score\n else:\n best[name] = score\n return sorted(best.items(), key=lambda x: (-x[1], x[0]))\n```", "usage": {"prompt_tokens": 103, "completion_tokens": 2623, "total_tokens": 2726, "cost": 0.00303705, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00303705, "upstream_inference_prompt_cost": 2.06e-05, "upstream_inference_completions_cost": 0.00301645}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625521-Vmfc4A8zUmgcR9bLO3wY", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-012", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "wildcard", "dp"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a*b?d', 'axxxbc d'.replace(' ','')) is True", "assert solution.solve('a*c', 'ab') is False", "assert solution.solve('*', '') is True", "assert solution.solve('file-??.txt', 'file-ab.txt') is True"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(pattern: str, text: str) -> bool。pattern 支持 ? 匹配任意单字符，* 匹配任意长度字符串。必须匹配完整 text。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0ac24584e5856726a6e962c43819ac539910b115bdabb48f973f04258dd562d6", "started_at": "2026-06-16T15:59:05.493102+00:00", "latency_ms": 8483, "output": "```python\ndef solve(pattern: str, text: str) -> bool:\n m, n = len(pattern), len(text)\n dp = [[False] * (n + 1) for _ in range(m + 1)]\n dp[0][0] = True\n for i in range(1, m + 1):\n if pattern[i - 1] == '*':\n dp[i][0] = dp[i - 1][0]\n for i in range(1, m + 1):\n for j in range(1, n + 1):\n if pattern[i - 1] == '*':\n dp[i][j] = dp[i - 1][j] or dp[i][j - 1]\n elif pattern[i - 1] == '?' or pattern[i - 1] == text[j - 1]:\n dp[i][j] = dp[i - 1][j - 1]\n return dp[m][n]\n```", "usage": {"prompt_tokens": 86, "completion_tokens": 850, "total_tokens": 936, "cost": 0.0009947, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009947, "upstream_inference_prompt_cost": 1.72e-05, "upstream_inference_completions_cost": 0.0009775}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625547-XSoMdMPyhYB4UVYKkQ6M", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-013", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "recursion", "flatten"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve({'a': {'b': 1, 'c': 'x'}, 'd': 2}) == ['a.b=1','a.c=x','d=2']", "assert solution.solve({'z': {'a': {'b': 3}}}) == ['z.a.b=3']", "assert solution.solve({}) == []"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(tree: dict) -> list[str]。tree 是嵌套字典，叶子是字符串或数字。返回所有叶子的路径，路径用点连接，按字典序排序。例如 {'a': {'b': 1}} -> ['a.b=1']。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e658784bcc7118c9f5e1375c7f1f92aa8147c38fb8790138603de7f2b3722c98", "started_at": "2026-06-16T15:59:14.014060+00:00", "latency_ms": 11445, "output": "```python\ndef solve(tree: dict) -> list[str]:\n result = []\n def dfs(current: dict, path: list[str]):\n for key, value in current.items():\n new_path = path + [str(key)]\n if isinstance(value, dict):\n dfs(value, new_path)\n else:\n result.append('.'.join(new_path) + '=' + str(value))\n dfs(tree, [])\n result.sort()\n return result\n```", "usage": {"prompt_tokens": 107, "completion_tokens": 1144, "total_tokens": 1251, "cost": 0.001337, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001337, "upstream_inference_prompt_cost": 2.14e-05, "upstream_inference_completions_cost": 0.0013156}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625556-iDXiwbpOS23VdldI7bnv", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-014", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dynamic-programming"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,-2,0,3]) == 4", "assert solution.solve([1,-2,-2,3]) == 3", "assert solution.solve([-1,-1,-1]) == -1", "assert solution.solve([2,1,-2,3]) == 6"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int]) -> int。返回删除恰好一个元素后，剩余数组的最大连续子数组和。nums 长度至少为 2，可以全为负数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a7a5de11dacd1864c7d44a3ce983c2f127d1bcff88bec3b15f8727c513f56ea2", "started_at": "2026-06-16T15:59:25.497677+00:00", "latency_ms": 13011, "output": "```python\ndef solve(nums: list[int]) -> int:\n n = len(nums)\n left = [0] * n\n left[0] = nums[0]\n for i in range(1, n):\n left[i] = max(nums[i], left[i-1] + nums[i])\n \n right = [0] * n\n right[-1] = nums[-1]\n for i in range(n-2, -1, -1):\n right[i] = max(nums[i], right[i+1] + nums[i])\n \n ans = max(right[1], left[-2])\n for i in range(1, n-1):\n ans = max(ans, left[i-1] + right[i+1])\n \n return ans\n```", "usage": {"prompt_tokens": 89, "completion_tokens": 1763, "total_tokens": 1852, "cost": 0.00204525, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00204525, "upstream_inference_prompt_cost": 1.78e-05, "upstream_inference_completions_cost": 0.00202745}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625567-Ec2xI37clMkwM1NP31MD", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-fir1rhdb/test_solution.py\", line 4, in \n assert solution.solve([1,-2,-2,3]) == 3\nAssertionError\n"}}, "error": null} {"case_id": "challenge-debugging-009", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "parsing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望把输入按逗号拆分并去掉空白，但会把空字段也保留下来。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef parse(s):\n return [part.strip() for part in s.split(',')]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc78c43e70a6a2fe59904be00b93d579300af6ba72fe5a9629bfe5bd82fad3d6", "started_at": "2026-06-16T15:59:38.543893+00:00", "latency_ms": 10751, "output": "Bug: 当输入包含连续逗号（如 `\"a,,b\"`）或首尾逗号时，`split(',')` 会产生空字符串元素，`strip()` 后仍为空字符串 `''`，列表推导式未将其过滤，导致空字段被保留。\n\n最小修复：在列表推导式中增加条件 `if part.strip()`，过滤掉去除空白后为空的字段。\n\n```python\ndef parse(s):\n return [part.strip() for part in s.split(',') if part.strip()]\n```\n\nFIX: return [part.strip() for part in s.split(',') if part.strip()]", "usage": {"prompt_tokens": 109, "completion_tokens": 1033, "total_tokens": 1142, "cost": 0.00120975, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00120975, "upstream_inference_prompt_cost": 2.18e-05, "upstream_inference_completions_cost": 0.00118795}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625580-r7UPt9ApX6DWBNdgr1JG", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-010", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "datetime", "debugging"], "scorer": "contains_any", "expected": {"answers": ["datetime.fromisoformat", "dateutil.parser", "解析 ts 后排序", "parse ts", "fromisoformat", "int(r['ts'])", "float(r['ts'])", "key=lambda r: int(r['ts'])", "key=lambda r: float(r['ts'])"]}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望用 UTC 时间戳排序，但字符串排序会错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 sort 行>。\n\n```python\nrows.sort(key=lambda r: r['ts'])\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c0d491a68f215902d8b314423a6ab9aea7ac0782e1a34e6d6997670c2ddb8458", "started_at": "2026-06-16T15:59:49.296501+00:00", "latency_ms": 12080, "output": "Bug：`r['ts']` 为字符串类型时，`sort` 默认按字典序（lexicographical order）而非数值序比较，导致时间戳大小顺序错误（例如字符串 `\"9\"` 会排在 `\"10\"` 之后）。\n\n最小修复：将字符串时间戳转换为数值类型（`float` 或 `int`）后再比较，确保按时间数值大小排序。\n\nFIX: rows.sort(key=lambda r: float(r['ts']))", "usage": {"prompt_tokens": 96, "completion_tokens": 1361, "total_tokens": 1457, "cost": 0.00158435, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00158435, "upstream_inference_prompt_cost": 1.92e-05, "upstream_inference_completions_cost": 0.00156515}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625591-vcWl8lgCo23YfHcRp4mq", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"matched": ["float(r['ts'])", "key=lambda r: float(r['ts'])"]}}, "error": null} {"case_id": "challenge-debugging-011", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "truthiness", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码在输入包含 0 时会误判为默认值 10。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 limit 赋值行>。\n\n```python\ndef query(limit=None):\n limit = limit or 10\n return list(range(limit))\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81dfcde4613fe16d52b7386d005b50beaafcb9916e6cb6c0d326eab3c808a843", "started_at": "2026-06-16T16:00:01.378423+00:00", "latency_ms": 7463, "output": "Bug: 使用 `or` 运算符时，输入 `0` 会被当作假值（falsy），从而错误地替换为默认值 `10`。\n\n最小修复: 使用 `is None` 显式检查是否为默认值，而非依赖真值判断。\n\nFIX: limit = 10 if limit is None else limit", "usage": {"prompt_tokens": 109, "completion_tokens": 839, "total_tokens": 948, "cost": 0.00098665, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00098665, "upstream_inference_prompt_cost": 2.18e-05, "upstream_inference_completions_cost": 0.00096485}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625603-QIvej3Emdy6NphD3Ansf", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-012", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "deepcopy", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望复制嵌套配置后修改副本，但原配置也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copied 赋值行>。\n\n```python\ndef update(config):\n copied = dict(config)\n copied['db']['host'] = 'localhost'\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b9ce1efc39e6db4861310a8b269b4f7a5f68b90016ca7ebbef71eb8b6b011913", "started_at": "2026-06-16T16:00:08.843585+00:00", "latency_ms": 16186, "output": "Bug: `dict(config)` 仅执行浅拷贝，`copied['db']` 与 `config['db']` 指向同一字典对象，因此修改副本的嵌套值会同步修改原配置。\n\n最小修复：使用 `copy.deepcopy()` 进行深拷贝，确保所有嵌套层都被复制。\n\nFIX: copied = copy.deepcopy(config)", "usage": {"prompt_tokens": 112, "completion_tokens": 1346, "total_tokens": 1458, "cost": 0.0015703, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0015703, "upstream_inference_prompt_cost": 2.24e-05, "upstream_inference_completions_cost": 0.0015479}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625611-LuJ7D45CoLFj2rvXqwMY", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-013", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "generator", "debugging"], "scorer": "regex", "expected": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望找到第一个匹配项，但找不到时会抛 StopIteration。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef find_user(users, name):\n return next(u for u in users if u['name'] == name)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3f10be3c52149f96743fe37c0fb7327abfb5c8d4b9310088d76b04282b552f5b", "started_at": "2026-06-16T16:00:25.031262+00:00", "latency_ms": 11552, "output": "Bug: 当 `users` 中不存在匹配 `name` 的用户时，生成器为空，`next()` 会抛出 `StopIteration` 异常，而不是返回一个安全的默认值。\n\n最小修复：为 `next()` 提供默认返回值 `None`，使其在找不到时返回 `None` 而非抛异常。\n\nFIX: return next((u for u in users if u['name'] == name), None)", "usage": {"prompt_tokens": 110, "completion_tokens": 1011, "total_tokens": 1121, "cost": 0.00118465, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00118465, "upstream_inference_prompt_cost": 2.2e-05, "upstream_inference_completions_cost": 0.00116265}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625627-PkvfznysHBzYJdTkqlDj", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-014", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "mutable-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望按请求顺序记录日志，但默认参数导致多次调用共用同一个列表。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\ndef log_request(req, logs=[]):\n logs.append(req['id'])\n return logs\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2131fc867d62d7093265e77811a401805ff12d38e7bbdc5e8797b3d01b4c8c59", "started_at": "2026-06-16T16:00:36.586436+00:00", "latency_ms": 8801, "output": "Bug: 默认参数 `logs=[]` 在函数定义时只创建一次，多次调用会共享同一个列表对象，导致日志被意外累积而非每次新建。\n\n最小修复：将默认参数改为 `None`，在函数内部判断并初始化空列表。\n\n```python\ndef log_request(req, logs=None):\n if logs is None:\n logs = []\n logs.append(req['id'])\n return logs\n```\n\nFIX: def log_request(req, logs=None):", "usage": {"prompt_tokens": 109, "completion_tokens": 731, "total_tokens": 840, "cost": 0.00086245, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00086245, "upstream_inference_prompt_cost": 2.18e-05, "upstream_inference_completions_cost": 0.00084065}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625638-Z35LM8ejJUOdwvUoZHBL", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:"}}, "error": null} {"case_id": "challenge-reasoning-006", "suite": "reasoning", "case_version": "0.2.0", "tags": ["symbolic", "sequence"], "scorer": "exact", "expected": {"answer": "3", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：一个队列从左到右是 A,B,C,D,E。依次执行：把第 2 个移到末尾；删除第 3 个；在最前面插入 X；把最后两个反转。最终队列中 C 的位置是第几位？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0defd3c3114d287777b39b65961dfa6fd7469da02e6c49a8c170b4f1be17f971", "started_at": "2026-06-16T16:00:45.389206+00:00", "latency_ms": 3839, "output": "3", "usage": {"prompt_tokens": 98, "completion_tokens": 324, "total_tokens": 422, "cost": 0.0003922, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003922, "upstream_inference_prompt_cost": 1.96e-05, "upstream_inference_completions_cost": 0.0003726}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625647-3Rn0m31Lc6ARyaTnXtEZ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "3", "actual": "3"}}, "error": null} {"case_id": "challenge-reasoning-007", "suite": "reasoning", "case_version": "0.2.0", "tags": ["percentage", "metrics"], "scorer": "exact", "expected": {"answer": "120", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：某缓存命中率从 60% 提升到 75%。如果总请求数为 800，未命中请求减少了多少个？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b5b568242a1b6c56d53db2d69addca2d25e472dcc9fb5aa8669dfa273609c0d4", "started_at": "2026-06-16T16:00:49.229882+00:00", "latency_ms": 2565, "output": "120", "usage": {"prompt_tokens": 74, "completion_tokens": 125, "total_tokens": 199, "cost": 0.00015855, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00015855, "upstream_inference_prompt_cost": 1.48e-05, "upstream_inference_completions_cost": 0.00014375}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625651-IMc3rcDTw9PK6i8J82b9", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "120", "actual": "120"}}, "error": null} {"case_id": "challenge-rag-005", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "mode-comparison"], "scorer": "text_rules", "expected": {"required": ["ability mode", "efficiency mode", "真实能力", "低预算"], "forbidden": ["只看一个模式"], "max_chars": 180}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：A 模型在 ability mode 中通过 46/50，成本 0.12 美元；在 efficiency mode 中通过 34/50，成本 0.04 美元。报告建议把 ability mode 用于能力判断，把 efficiency mode 用于成本和稳定性判断。\n\n问题：如果文章讨论“模型真实能力”，应该优先引用哪个模式？如果讨论“低预算可用性”，应该优先引用哪个模式？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0265f7540e44005627e16c6995d2a9cb458be65bb560cd1d5646c0435265c4e3", "started_at": "2026-06-16T16:00:51.796880+00:00", "latency_ms": 3766, "output": "如果讨论“模型真实能力”，应优先引用ability mode；如果讨论“低预算可用性”，应优先引用efficiency mode。", "usage": {"prompt_tokens": 139, "completion_tokens": 182, "total_tokens": 321, "cost": 0.0002371, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002371, "upstream_inference_prompt_cost": 2.78e-05, "upstream_inference_completions_cost": 0.0002093}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625654-udG1ND15Hm3peYtXcXsw", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 65, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-006", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "failure-analysis"], "scorer": "text_rules", "expected": {"required": ["key"], "required_any": [["字符串", "类型不匹配"], ["整数", "int"], ["类型假设", "假设 key 为整数", "假设 key 是整数", "key 为整数类型"]], "forbidden": [], "max_chars": 120}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：一次失败分析显示，模型输出了 key = int(parts[1])，但测试数据里的 key 是字符串 a、b、c。报告认为这是“擅自补类型假设”，不是 token 截断。\n\n问题：这次失败的根因是什么？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a49a29fca4961af6e5e2b25c2e82cc0a7be110d48893fc55f7af30f6e1804362", "started_at": "2026-06-16T16:14:00.032296+00:00", "latency_ms": 4359, "output": "根因是模型未经授权擅自假设key需要为int类型，对key执行了类型转换操作，输出不符合测试数据要求的字符串类型key的规则，且该问题并非token截断导致。", "usage": {"prompt_tokens": 103, "completion_tokens": 291, "total_tokens": 394, "cost": 0.00035525, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00035525, "upstream_inference_prompt_cost": 2.06e-05, "upstream_inference_completions_cost": 0.00033465}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626442-5KQk6kcpalwOQ2bN83ic", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"missing": [], "missing_any": [["类型假设", "假设 key 为整数", "假设 key 是整数", "key 为整数类型"]], "present_forbidden": [], "char_count": 79, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-007", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["图表", "资料"], "required_any": [["提到", "提及"]], "forbidden": ["已经支持", "折线图", "柱状图"], "max_chars": 100}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：DracoBench 的 HTML 报告目前展示 Summary、By Suite、Failure Examples 和 Case Details。Failure Examples 中包括 Prompt、Mistake Analysis、Scorer Details 和 Output。资料没有提到图表功能。\n\n问题：报告是否已经支持图表？回答时说明依据。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c47ee5e02396d5ba9d3852992bf82351aeea58cd22d81035d26a6bac283f07ba", "started_at": "2026-06-16T16:00:57.176893+00:00", "latency_ms": 3686, "output": "报告目前不支持图表。依据是资料中仅提及DracoBench的HTML报告目前展示Summary、By Suite、Failure Examples和Case Details这几个模块，且明确说明资料没有提到图表功能。", "usage": {"prompt_tokens": 113, "completion_tokens": 171, "total_tokens": 284, "cost": 0.00021925, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00021925, "upstream_inference_prompt_cost": 2.26e-05, "upstream_inference_completions_cost": 0.00019665}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625659-amYkfnjg9AGfFbBjGRgK", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 108, "length_ok": false, "length_scored": false}}, "error": null} {"case_id": "challenge-if-004", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["json", "nested", "strict"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["mode", "limits", "warnings"], "additionalProperties": false, "properties": {"mode": {"type": "string", "const": "ability"}, "limits": {"type": "object", "required": ["max_tokens", "temperature"], "additionalProperties": false, "properties": {"max_tokens": {"type": "integer", "const": 4096}, "temperature": {"type": "integer", "const": 0}}}, "warnings": {"type": "array", "minItems": 2, "maxItems": 2, "items": {"type": "string"}}}}}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 JSON 对象。字段 mode 必须是 \"ability\"；字段 limits 必须是对象，包含 max_tokens:4096 和 temperature:0；字段 warnings 必须是正好两个字符串组成的数组。不要 Markdown。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "14a17039d4b99be719ac311a5d824ceb40affbf22079ddbcf8bf33af6f04fb0a", "started_at": "2026-06-16T16:01:00.864948+00:00", "latency_ms": 5977, "output": "{\"mode\":\"ability\",\"limits\":{\"max_tokens\":4096,\"temperature\":0},\"warnings\":[\"生成内容可能受到模型知识截止日期的限制\",\"请验证重要信息的准确性\"]}", "usage": {"prompt_tokens": 89, "completion_tokens": 239, "total_tokens": 328, "cost": 0.00029265, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00029265, "upstream_inference_prompt_cost": 1.78e-05, "upstream_inference_completions_cost": 0.00027485}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625663-zSOVOYshd3t0X8ba4VJs", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"errors": [], "value": {"mode": "ability", "limits": {"max_tokens": 4096, "temperature": 0}, "warnings": ["生成内容可能受到模型知识截止日期的限制", "请验证重要信息的准确性"]}}}, "error": null} {"case_id": "challenge-if-005", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["markdown", "table"], "scorer": "regex", "expected": {"pattern": "^\\s*\\|\\s*模式\\s*\\|\\s*用途\\s*\\|\\s*风险\\s*\\|\\s*\\n\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|[\\s\\S]*ability mode[\\s\\S]*efficiency mode[\\s\\S]*$", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Markdown 表格，必须有 3 列：模式、用途、风险。必须包含 ability mode 和 efficiency mode 两行。不能添加表格外说明。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0a28a65a8a714a5c613c2e01f5bf2b72b7b18cdd17059ad9d38cea38a6e1ff4f", "started_at": "2026-06-16T16:01:06.843802+00:00", "latency_ms": 5615, "output": "| 模式 | 用途 | 风险 |\n|------|------|------|\n| ability mode | 最大化模型性能，处理复杂推理、创意生成等高级任务 | 可能产生过度复杂的输出，消耗更多计算资源 |\n| efficiency mode | 优化响应速度，减少资源消耗，适合简单任务和高并发场景 | 可能牺牲部分输出质量，复杂任务中表现不足 |", "usage": {"prompt_tokens": 79, "completion_tokens": 383, "total_tokens": 462, "cost": 0.00045625, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00045625, "upstream_inference_prompt_cost": 1.58e-05, "upstream_inference_completions_cost": 0.00044045}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625669-DYL1yYpG1aqwWOcqv0cr", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "^\\s*\\|\\s*模式\\s*\\|\\s*用途\\s*\\|\\s*风险\\s*\\|\\s*\\n\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|[\\s\\S]*ability mode[\\s\\S]*efficiency mode[\\s\\S]*$"}}, "error": null} {"case_id": "challenge-zh-writing-003", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["wechat", "explanation"], "scorer": "text_rules", "expected": {"required": ["原题", "错误解释", "可复查"], "forbidden": ["玄学"], "max_chars": 140}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "写一段不超过 140 个汉字的公众号小结，主题是“为什么要同时展示原题、模型输出和错误解释”。必须包含“原题”“错误解释”“可复查”，不能出现“玄学”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "f0853803e81259a7bee0074883cc95566fe68e7e6f9ce84b4c3bda73b8c0e638", "started_at": "2026-06-16T16:01:12.460615+00:00", "latency_ms": 9578, "output": "公众号科普内容同步展示原题、模型输出与错误解释，既能还原问题场景，也能清晰呈现模型输出偏差，配合错误解释讲清问题根源，全链路可复查，方便大家客观判断内容可靠性。", "usage": {"prompt_tokens": 87, "completion_tokens": 779, "total_tokens": 866, "cost": 0.00091325, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00091325, "upstream_inference_prompt_cost": 1.74e-05, "upstream_inference_completions_cost": 0.00089585}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625674-XbQXGRQhOPUOKSA83tlB", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 80, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-reasoning-008", "suite": "reasoning", "case_version": "0.3.0", "tags": ["state-tracking", "branching"], "scorer": "exact", "expected": {"answer": "15", "normalize": true}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只回答最终数字：变量初始为 x=2, y=5, z=1。若 x list[str]，解析一行简化 CSV：逗号分隔；字段可以用双引号包裹；引号内逗号保留；引号内两个连续双引号表示一个双引号；空字段保留；空格是普通字符，不要自动 trim。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81b6be132a0538b92491e39887550c116b7f09684b97f8dd1ad7df5426e97adb", "started_at": "2026-06-16T16:03:16.772957+00:00", "latency_ms": 145150, "output": "```python\ndef solve(line: str) -> list[str]:\n fields = []\n current = []\n in_quotes = False\n i = 0\n n = len(line)\n \n while i < n:\n char = line[i]\n if in_quotes:\n if char == '\"':\n if i + 1 < n and line[i + 1] == '\"':\n current.append('\"')\n i += 2\n else:\n in_quotes = False\n i += 1\n else:\n current.append(char)\n i += 1\n else:\n if char == '\"':\n if not current and (i == 0 or line[i - 1] == ','):\n in_quotes = True\n i += 1\n else:\n current.append(char)\n i += 1\n elif char == ',':\n fields.append(''.join(current))\n current = []\n i += 1\n else:\n current.append(char)\n i += 1\n \n fields.append(''.join(current))\n return fields\n```", "usage": {"prompt_tokens": 111, "completion_tokens": 14859, "total_tokens": 14970, "cost": 0.01711005, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.01711005, "upstream_inference_prompt_cost": 2.22e-05, "upstream_inference_completions_cost": 0.01708785}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625799-MjIPwWo0Sh3rjRieuOSF", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-016", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "intervals", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([(5,7),(1,2),(3,4),(10,10)]) == [(1,7),(10,10)]", "assert solution.solve([(1,1),(3,3)]) == [(1,1),(3,3)]", "assert solution.solve([]) == []"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]。intervals 是整数闭区间，先按起点排序；重叠或端点相邻的区间要合并，例如 [1,2] 和 [3,4] 合并为 [1,4]。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "6dc22c1e6ae004a46c47dc11d5cc9ed5d57f09ec77549ff0ada57b459929d814", "started_at": "2026-06-16T16:05:41.939844+00:00", "latency_ms": 8796, "output": "```python\ndef solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]:\n if not intervals:\n return []\n intervals.sort(key=lambda x: x[0])\n merged = [intervals[0]]\n for current in intervals[1:]:\n last = merged[-1]\n if current[0] <= last[1] + 1:\n merged[-1] = (last[0], max(last[1], current[1]))\n else:\n merged.append(current)\n return merged\n```", "usage": {"prompt_tokens": 116, "completion_tokens": 651, "total_tokens": 767, "cost": 0.00077185, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00077185, "upstream_inference_prompt_cost": 2.32e-05, "upstream_inference_completions_cost": 0.00074865}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625944-eQkLKJXYFGl01oozHKMQ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-017", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "rate-limit", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events=[('a',1),('a',2),('a',3),('a',4),('a',8)]\nassert solution.solve(events, 5, 2) == [True, True, False, False, True]", "assert solution.solve([('x',10),('x',11),('x',16)], 5, 1) == [True, False, True]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[tuple[str, int]], window: int, limit: int) -> list[bool]，模拟按用户限流。events 按时间非降序排列。某用户在当前事件时间 ts 的窗口 (ts-window, ts] 内，已放行事件数少于 limit 才放行；被拒绝的事件不计入窗口。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1539217453d6af4bac3c7abfbd8df43ed131cd647e58a0ad2a5a670794a91f80", "started_at": "2026-06-16T16:05:50.750710+00:00", "latency_ms": 6199, "output": "```python\nfrom collections import deque\n\ndef solve(events: list[tuple[str, int]], window: int, limit: int) -> list[bool]:\n result = []\n allowed = deque()\n \n for _, ts in events:\n while allowed and allowed[0] <= ts - window:\n allowed.popleft()\n \n if len(allowed) < limit:\n allowed.append(ts)\n result.append(True)\n else:\n result.append(False)\n \n return result\n```", "usage": {"prompt_tokens": 129, "completion_tokens": 674, "total_tokens": 803, "cost": 0.0008009, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0008009, "upstream_inference_prompt_cost": 2.58e-05, "upstream_inference_completions_cost": 0.0007751}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625953-E8o6AzsZAAhqGX6RW6Ec", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-018", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "path", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('/a//b/./c/../') == '/a/b'", "assert solution.solve('/../../x') == '/x'", "assert solution.solve('/') == '/'"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(path: str) -> str，规范化绝对 Unix 路径：处理重复斜杠、.、..；.. 在根目录时仍留在根目录；返回结果必须以 / 开头且除根目录外不能以 / 结尾。不要使用 os.path。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "92e706f1062d7652c2f14c514c44602c6708e65d87771889d3aff7450e33e85d", "started_at": "2026-06-16T16:05:56.989105+00:00", "latency_ms": 7226, "output": "```python\ndef solve(path: str) -> str:\n parts = path.split('/')\n stack = []\n for part in parts:\n if part == '' or part == '.':\n continue\n if part == '..':\n if stack:\n stack.pop()\n else:\n stack.append(part)\n if not stack:\n return '/'\n return '/' + '/'.join(stack)\n```", "usage": {"prompt_tokens": 108, "completion_tokens": 794, "total_tokens": 902, "cost": 0.0009347, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009347, "upstream_inference_prompt_cost": 2.16e-05, "upstream_inference_completions_cost": 0.0009131}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625959-f1as96vc9ga0w4YGqV4N", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-019", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "grouping", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['eat','tea','tan','ate','nat','bat']) == [['eat','tea','ate'], ['tan','nat'], ['bat']]", "assert solution.solve(['b','B','bb']) == [['b'], ['B'], ['bb']]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(words: list[str]) -> list[list[str]]，按变位词分组。大小写敏感；组内保持输入顺序；组的顺序按该组第一个单词在输入中出现的位置。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0a957bf71a0be6fa198a854347b2fe5d2c5d5f9b9a8bd5041dac9cdb46ae06ce", "started_at": "2026-06-16T16:06:04.254664+00:00", "latency_ms": 5377, "output": "```python\ndef solve(words: list[str]) -> list[list[str]]:\n groups = []\n group_index = {}\n for word in words:\n key = ''.join(sorted(word))\n if key not in group_index:\n group_index[key] = len(groups)\n groups.append([])\n groups[group_index[key]].append(word)\n return groups\n```", "usage": {"prompt_tokens": 93, "completion_tokens": 429, "total_tokens": 522, "cost": 0.00051195, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00051195, "upstream_inference_prompt_cost": 1.86e-05, "upstream_inference_completions_cost": 0.00049335}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625966-HP8mw0RCiKma2muZWpQS", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-020", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "front-matter"], "scorer": "code_python_tests", "expected": {"tests": ["text='---\\ntitle: Test\\ntags: [ai, bench, v0]\\ndraft: false\\n---\\nbody'\nassert solution.solve(text) == {'title':'Test','tags':['ai','bench','v0'],'draft':'false'}", "assert solution.solve('hello\\n---\\na: b') == {}", "assert solution.solve('---\\na: 1') == {}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> dict，解析 Markdown front matter。只有第一行正好是 --- 时才解析，直到下一行 --- 结束；每行 key: value，key 和 value 两侧 trim；形如 [a, b] 的 value 返回字符串列表；其他 value 返回字符串。没有完整 front matter 返回 {}。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "4111f2228a7b621a743019a4cad1b5638c8a120765153c2d35f8db2aa136f79c", "started_at": "2026-06-16T16:06:09.670860+00:00", "latency_ms": 138127, "output": "", "usage": {"prompt_tokens": 126, "completion_tokens": 16384, "total_tokens": 16510, "cost": 0.0188668, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0188668, "upstream_inference_prompt_cost": 2.52e-05, "upstream_inference_completions_cost": 0.0188416}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781625971-UkDWxdOHDhgLBAO9XYLD", "finish_reason": "length", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-64fjwovt/test_solution.py\", line 4, in \n assert solution.solve(text) == {'title':'Test','tags':['ai','bench','v0'],'draft':'false'}\n ^^^^^^^^^^^^^^\nAttributeError: module 'solution' has no attribute 'solve'\n"}}, "error": null} {"case_id": "challenge-coding-021", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "frequency", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['b','a','b','c','a','b'], 2) == ['b','a']", "assert solution.solve(['x','y','z','y','z','x'], 2) == ['x','y']", "assert solution.solve(['a'], 5) == ['a']"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(items: list[str], k: int) -> list[str]，返回出现次数最高的前 k 个元素；次数相同按第一次出现的先后排序；k 大于不同元素数量时返回全部。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e73dccf0e991c296063c917fbe5a6b5f99f50fb3baed6d0820cfc35df858c663", "started_at": "2026-06-16T16:08:27.831644+00:00", "latency_ms": 8878, "output": "```python\nfrom collections import Counter\n\ndef solve(items: list[str], k: int) -> list[str]:\n count = Counter(items)\n first_occurrence = {}\n for idx, item in enumerate(items):\n if item not in first_occurrence:\n first_occurrence[item] = idx\n sorted_items = sorted(count.keys(), key=lambda x: (-count[x], first_occurrence[x]))\n return sorted_items[:k]\n```", "usage": {"prompt_tokens": 94, "completion_tokens": 788, "total_tokens": 882, "cost": 0.000925, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000925, "upstream_inference_prompt_cost": 1.88e-05, "upstream_inference_completions_cost": 0.0009062}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626110-BNHgSxJS4LZ2gzjaA09P", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-022", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "nested-dict", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base={'db':{'host':'old','port':5432},'feature':{'x':1}}\noverrides={'db.host':'new','feature.x':None,'api.timeout':30}\nres=solution.solve(base, overrides)\nassert res == {'db':{'host':'new','port':5432},'feature':{},'api':{'timeout':30}}\nassert base == {'db':{'host':'old','port':5432},'feature':{'x':1}}", "assert solution.solve({'a':1}, {'a.b':2}) == {'a': {'b': 2}}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(config: dict, overrides: dict[str, object]) -> dict。overrides 的 key 是点号路径；值为 None 表示删除该路径的叶子 key；其他值写入路径，必要时创建中间 dict；不能修改输入 config。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e21e5bbf42159ba49144d39d17824dcf011df026efab7a9bfb6179aed2bb558a", "started_at": "2026-06-16T16:08:36.750665+00:00", "latency_ms": 20867, "output": "```python\nimport copy\n\ndef solve(config: dict, overrides: dict[str, object]) -> dict:\n result = copy.deepcopy(config)\n for path, value in overrides.items():\n parts = path.split('.')\n current = result\n for i, part in enumerate(parts):\n if i == len(parts) - 1:\n if value is None:\n if isinstance(current, dict) and part in current:\n del current[part]\n else:\n current[part] = value\n else:\n if not isinstance(current, dict) or part not in current or not isinstance(current[part], dict):\n if value is None:\n break\n current[part] = {}\n current = current[part]\n return result\n```", "usage": {"prompt_tokens": 105, "completion_tokens": 1794, "total_tokens": 1899, "cost": 0.0020841, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0020841, "upstream_inference_prompt_cost": 2.1e-05, "upstream_inference_completions_cost": 0.0020631}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626119-iiByTRWLXJ2Ul8hUuVjC", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-023", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "url", "parser"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a=1&b=two+words&a=3') == {'a':['1','3'], 'b':['two words']} ", "assert solution.solve('empty=&flag&x=a%2Bb') == {'empty':[''], 'flag':[''], 'x':['a+b']} ", "assert solution.solve('') == {}"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(query: str) -> dict[str, list[str]]，解析 URL query string。& 分隔参数；没有 = 的参数值为空字符串；+ 表示空格；%XX 需要按 UTF-8 百分号解码；同名 key 保留所有值的列表。可以使用标准库。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cfe8be23444d346039a0740ab1568f54ed98bd44e5d63909779673da2207f393", "started_at": "2026-06-16T16:08:57.659305+00:00", "latency_ms": 29610, "output": "```python\nfrom urllib.parse import unquote_plus\n\ndef solve(query: str) -> dict[str, list[str]]:\n result = {}\n if not query:\n return result\n for pair in query.split('&'):\n if '=' in pair:\n key, value = pair.split('=', 1)\n else:\n key, value = pair, ''\n key = unquote_plus(key)\n value = unquote_plus(value)\n result.setdefault(key, []).append(value)\n return result\n```", "usage": {"prompt_tokens": 113, "completion_tokens": 2921, "total_tokens": 3034, "cost": 0.00338175, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00338175, "upstream_inference_prompt_cost": 2.26e-05, "upstream_inference_completions_cost": 0.00335915}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626139-jMvkbeiHFv6uw74F4CIc", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-024", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('

x

') is True", "assert solution.solve('') is False", "assert solution.solve('text') is True"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(html: str) -> bool，校验简化 HTML 标签是否配对。标签形如 、、
，标签名只含小写字母；自闭合标签不入栈；普通文本忽略。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "088a9867c7f154cf1ee172830e13e8e49c53a8e572707d776f0cdea59f3555cb", "started_at": "2026-06-16T16:09:27.315025+00:00", "latency_ms": 13652, "output": "```python\ndef solve(html: str) -> bool:\n stack = []\n i = 0\n n = len(html)\n \n while i < n:\n if html[i] == '<':\n j = html.find('>', i + 1)\n if j == -1:\n return False\n \n content = html[i+1:j]\n \n if content.startswith('/'):\n tag = content[1:]\n if not tag or not tag.isalpha() or not tag.islower():\n return False\n if not stack or stack[-1] != tag:\n return False\n stack.pop()\n elif content.endswith('/'):\n tag = content[:-1]\n if not tag or not tag.isalpha() or not tag.islower():\n return False\n else:\n tag = content\n if not tag or not tag.isalpha() or not tag.islower():\n return False\n stack.append(tag)\n \n i = j + 1\n else:\n i += 1\n \n return not stack\n```", "usage": {"prompt_tokens": 102, "completion_tokens": 1608, "total_tokens": 1710, "cost": 0.0018696, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0018696, "upstream_inference_prompt_cost": 2.04e-05, "upstream_inference_completions_cost": 0.0018492}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626169-mcahE6qGTZXwq9p7T0z0", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-025", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "bfs", "grid"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['S..','##.','..E']) == 4", "assert solution.solve(['S#','##','E.']) == -1", "assert solution.solve(['SE']) == 1"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(grid: list[str]) -> int。grid 中 S 是起点，E 是终点，# 是墙，. 可走。每步上下左右移动一格，返回从 S 到 E 的最短步数；不可达返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8c6dc47fe32c2eef1e05bed2e6bd50520bb606e6965fe6c18e354a50a1e65085", "started_at": "2026-06-16T16:09:41.007708+00:00", "latency_ms": 5997, "output": "```python\nfrom collections import deque\n\ndef solve(grid: list[str]) -> int:\n rows, cols = len(grid), len(grid[0])\n start = end = None\n for i in range(rows):\n for j in range(cols):\n if grid[i][j] == 'S':\n start = (i, j)\n elif grid[i][j] == 'E':\n end = (i, j)\n if not start or not end:\n return -1\n directions = [(1, 0), (-1, 0), (0, 1), (0, -1)]\n visited = [[False] * cols for _ in range(rows)]\n queue = deque([(start[0], start[1], 0)])\n visited[start[0]][start[1]] = True\n while queue:\n x, y, dist = queue.popleft()\n if (x, y) == end:\n return dist\n for dx, dy in directions:\n nx, ny = x + dx, y + dy\n if 0 <= nx < rows and 0 <= ny < cols and not visited[nx][ny] and grid[nx][ny] != '#':\n visited[nx][ny] = True\n queue.append((nx, ny, dist + 1))\n return -1\n```", "usage": {"prompt_tokens": 108, "completion_tokens": 766, "total_tokens": 874, "cost": 0.0009025, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009025, "upstream_inference_prompt_cost": 2.16e-05, "upstream_inference_completions_cost": 0.0008809}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626183-NykplrBFYqtjscSv7rqI", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-coding-026", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sliding-window", "median"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,3,-1,-3,5,3,6,7], 3) == [1, -1, -1, 3, 5, 6]", "assert solution.solve([1,2,3,4], 2) == [1.5, 2.5, 3.5]"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int], k: int) -> list[float]，返回每个长度为 k 的滑动窗口中位数。k 为奇数时返回中间值；k 为偶数时返回两个中间值平均数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "53547e8e9f25c840b8a6248c7be329b1779ddc5a47484208f5c434403bd8228c", "started_at": "2026-06-16T16:09:47.045048+00:00", "latency_ms": 30542, "output": "```python\nimport heapq\nfrom collections import Counter\n\ndef solve(nums: list[int], k: int) -> list[float]:\n small = []\n large = []\n small_removed = Counter()\n large_removed = Counter()\n \n def prune(heap, removed):\n while heap:\n val = -heap[0] if heap is small else heap[0]\n if removed[val] > 0:\n removed[val] -= 1\n if removed[val] == 0:\n del removed[val]\n heapq.heappop(heap)\n else:\n break\n \n def balance():\n prune(small, small_removed)\n prune(large, large_removed)\n if len(small) > len(large) + 1:\n val = -heapq.heappop(small)\n heapq.heappush(large, val)\n elif len(small) < len(large):\n val = heapq.heappop(large)\n heapq.heappush(small, -val)\n prune(small, small_removed)\n prune(large, large_removed)\n \n def add(num):\n if not small or num <= -small[0]:\n heapq.heappush(small, -num)\n else:\n heapq.heappush(large, num)\n balance()\n \n def remove(num):\n prune(small, small_removed)\n prune(large, large_removed)\n if num <= -small[0]:\n small_removed[num] += 1\n if num == -small[0]:\n prune(small, small_removed)\n else:\n large_removed[num] += 1\n if large and num == large[0]:\n prune(large, large_removed)\n balance()\n \n for i in range(k):\n add(nums[i])\n \n res = []\n if k % 2 == 1:\n res.append(-small[0])\n else:\n res.append((-small[0] + large[0]) / 2.0)\n \n for i in range(k, len(nums)):\n remove(nums[i - k])\n add(nums[i])\n if k % 2 == 1:\n res.append(-small[0])\n else:\n res.append((-small[0] + large[0]) / 2.0)\n \n return res\n```", "usage": {"prompt_tokens": 97, "completion_tokens": 4125, "total_tokens": 4222, "cost": 0.00476315, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00476315, "upstream_inference_prompt_cost": 1.94e-05, "upstream_inference_completions_cost": 0.00474375}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626189-0FlXG5rSIXkYtDrd0ueX", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-v55hwyoa/test_solution.py\", line 3, in \n assert solution.solve([1,3,-1,-3,5,3,6,7], 3) == [1, -1, -1, 3, 5, 6]\nAssertionError\n"}}, "error": null} {"case_id": "challenge-coding-027", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sorting", "semver"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['1.0.0','1.0.0-alpha','1.0.1','1.0.0-beta','0.9.9']) == ['0.9.9','1.0.0-alpha','1.0.0-beta','1.0.0','1.0.1']", "assert solution.solve(['1.0.10','1.0.2']) == ['1.0.2','1.0.10']"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(versions: list[str]) -> list[str]，按简化语义版本排序。版本为 major.minor.patch 或 major.minor.patch-label；major/minor/patch 按数字比较；同一数字版本下，带 label 的预发布版本低于正式版本；label 按字典序比较。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f9b7324425840beb574b30433a6e004d34a834ef548c9cfa579b9b9b6950377d", "started_at": "2026-06-16T16:10:17.631255+00:00", "latency_ms": 16724, "output": "```python\ndef solve(versions: list[str]) -> list[str]:\n def key(v: str):\n if '-' in v:\n num, label = v.split('-', 1)\n return (*map(int, num.split('.')), 1, label)\n return (*map(int, v.split('.')), 0, '')\n return sorted(versions, key=key)\n```", "usage": {"prompt_tokens": 118, "completion_tokens": 1541, "total_tokens": 1659, "cost": 0.00179575, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00179575, "upstream_inference_prompt_cost": 2.36e-05, "upstream_inference_completions_cost": 0.00177215}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626219-AmmdPZLmaNs4GxOpeIvo", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-q2vd7jmj/test_solution.py\", line 3, in \n assert solution.solve(['1.0.0','1.0.0-alpha','1.0.1','1.0.0-beta','0.9.9']) == ['0.9.9','1.0.0-alpha','1.0.0-beta','1.0.0','1.0.1']\nAssertionError\n"}}, "error": null} {"case_id": "challenge-coding-028", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "graph", "reverse-deps"], "scorer": "code_python_tests", "expected": {"tests": ["deps={'app':['lib','ui'],'ui':['core'],'lib':['core'],'core':[],'docs':[]}\nassert solution.solve(deps, ['core']) == ['app','core','lib','ui']", "assert solution.solve({'a':['x']}, ['x']) == ['a','x']", "assert solution.solve({'a':['b'], 'b':[]}, ['a']) == ['a']"], "timeout_seconds": 3}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]。deps 表示 package -> 直接依赖。返回所有 changed 包，以及直接或间接依赖 changed 包的包，按字典序排序；只出现在依赖列表中的包也要能作为 changed 包返回。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a0e51751556bc0e35f2a2a2aa4ed86810eacfc274bb9c5f48e8990611a9a473", "started_at": "2026-06-16T16:10:34.394868+00:00", "latency_ms": 54683, "output": "```python\nfrom collections import defaultdict, deque\n\ndef solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]:\n rev_deps = defaultdict(list)\n for pkg, deps_list in deps.items():\n for dep in deps_list:\n rev_deps[dep].append(pkg)\n \n affected = set(changed)\n queue = deque(changed)\n \n while queue:\n pkg = queue.popleft()\n for dependent in rev_deps.get(pkg, []):\n if dependent not in affected:\n affected.add(dependent)\n queue.append(dependent)\n \n return sorted(affected)\n```", "usage": {"prompt_tokens": 116, "completion_tokens": 5830, "total_tokens": 5946, "cost": 0.0067277, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0067277, "upstream_inference_prompt_cost": 2.32e-05, "upstream_inference_completions_cost": 0.0067045}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626236-SPQUCKTplQlczTTL87YN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null} {"case_id": "challenge-rag-008", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "conflict", "workflow"], "scorer": "text_rules", "expected": {"required": ["50", "审题"], "required_any": [["不跑", "不要立刻", "先不跑", "不应立刻", "不应该立刻", "不应立即", "不应该立即", "不应立刻跑", "不应该立刻跑", "不应立即跑", "不应该立即跑"]], "forbidden": [], "max_chars": 160}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期草案说 v0.3 只新增 20 道题。\n资料 B：2026-06-16 的确认方案是 v0.3-challenge100，在现有 50 题基础上新增 50 道题。\n资料 C：新增题应先生成审题 HTML，确认后再跑模型，不要立即消耗 API。\n\n问题：下一步应该新增多少题？是否应该立刻跑模型？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c99da78812f6f4ab7745f793b9e3dc087033b0cce0591db49bf8642829324a81", "started_at": "2026-06-16T16:11:29.117484+00:00", "latency_ms": 4801, "output": "1. 下一步应新增50道题，依据是资料B的确认方案：v0.3-challenge100是在现有50题基础上新增50道题。\n2. 不应该立刻跑模型，依据是资料C的要求：新增题需先生成审题HTML、确认后再跑模型，不要立即消耗API。", "usage": {"prompt_tokens": 138, "completion_tokens": 241, "total_tokens": 379, "cost": 0.00030475, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00030475, "upstream_inference_prompt_cost": 2.76e-05, "upstream_inference_completions_cost": 0.00027715}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626291-ZIPqAoSlOAoyuFynterx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 115, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-009", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "用户满意度"], "required_any": [["没有包含", "没有提供", "资料没有", "未包含"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：报告展示 pass_rate、avg_latency_ms、total_cost、reasoning_tokens、失败样例和逐题明细。资料没有包含用户满意度调查，也没有包含模型训练数据来源。\n\n问题：能否根据这份报告判断用户满意度？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c072287ee5dbe1d477ab21e37485fb72f07cd11a57b57f199f071287443f404e", "started_at": "2026-06-16T16:11:33.919295+00:00", "latency_ms": 3092, "output": "不能，因为资料明确说明没有包含用户满意度调查相关内容，无法据此判断用户满意度。", "usage": {"prompt_tokens": 103, "completion_tokens": 90, "total_tokens": 193, "cost": 0.0001241, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0001241, "upstream_inference_prompt_cost": 2.06e-05, "upstream_inference_completions_cost": 0.0001035}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626296-IqmOXyGCove41LlqgInQ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 39, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-010", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "tradeoff"], "scorer": "text_rules", "expected": {"required": ["B", "延迟"], "required_any": [["没有超时", "无超时"]], "forbidden": ["选择 A", "选择 C"], "max_chars": 160}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：模型 A 通过 48/50，平均延迟 20 秒，成本 0.20 美元，没有超时失败。模型 B 通过 44/50，平均延迟 4 秒，成本 0.05 美元，没有超时失败。模型 C 通过 46/50，平均延迟 9 秒，成本 0.04 美元，但有 3 次 API 超时。\n\n问题：如果要选低延迟且稳定的生产摘要模型，资料更支持选择哪个？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a17bb8c56d524481eedc45557a1394b5b65b034af6847928cca16e2c8c2428c9", "started_at": "2026-06-16T16:11:37.012537+00:00", "latency_ms": 7824, "output": "更支持选择模型B，理由如下：\n1. 稳定性要求：模型C存在3次API超时，不满足稳定要求，直接排除；模型A、B无超时失败，稳定性达标。\n2. 低延迟要求：模型A平均延迟20秒，模型B平均延迟仅4秒，远低于模型A，符合低延迟要求。", "usage": {"prompt_tokens": 159, "completion_tokens": 642, "total_tokens": 801, "cost": 0.0007701, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007701, "upstream_inference_prompt_cost": 3.18e-05, "upstream_inference_completions_cost": 0.0007383}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626299-IDA9ueKZjFYdT0qV6cTZ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 114, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-011", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["诊断"], "required_any": [["不扣分", "不会", "不会因长度", "不会因此被扣分", "不会直接导致扣分", "不会导致扣分", "不会导致失败或扣分"], ["length_scored", "长度"]], "forbidden": ["直接失败", "必须重跑"], "max_chars": 140}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：DracoBench 当前 scoring policy 中，text_rules 的 max_chars/min_chars 只作为诊断信息记录，length_scored 为 false。缺少 required、required_any 或出现 forbidden 才会导致失败。\n\n问题：如果答案超过 max_chars，但 required 都满足且没有 forbidden，会因为长度直接扣分吗？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1ff7f897fc3d3121f25358f9a8df2a2df2970bc5762ff1218dd63c3f42d7d598", "started_at": "2026-06-16T16:11:44.838131+00:00", "latency_ms": 5483, "output": "不会。根据当前DracoBench的scoring policy，text_rules的max_chars/min_chars仅作为诊断信息记录，length_scored为false，仅当缺少required、required_any或出现forbidden时才会导致失败，满足required要求且无forbidden内容时不会因长度直接扣分。", "usage": {"prompt_tokens": 124, "completion_tokens": 254, "total_tokens": 378, "cost": 0.0003169, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003169, "upstream_inference_prompt_cost": 2.48e-05, "upstream_inference_completions_cost": 0.0002921}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626307-kj1Rj9eocK8jtiUmB9nH", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 174, "length_ok": false, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-012", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "rescoring"], "scorer": "text_rules", "expected": {"required": ["46/50"], "forbidden": ["45/50 更合适", "原始结果为准"], "max_chars": 140}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：某模型原始结果为 45/50。\n资料 B：修正一个同义表达评分规则后，rescored 结果为 46/50。\n资料 C：总览 index 使用 rescored JSONL 作为展示结果。\n\n问题：写文章引用总览结果时，应写 45/50 还是 46/50？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "274c0483d9fd5cae178e795e16add941178c14f5ae34a82f631655c000ff929a", "started_at": "2026-06-16T16:11:50.322538+00:00", "latency_ms": 3989, "output": "应写46/50。\n依据资料C，总览index的展示结果采用修正评分规则后的rescored结果，对应结果为46/50。", "usage": {"prompt_tokens": 120, "completion_tokens": 150, "total_tokens": 270, "cost": 0.0001965, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0001965, "upstream_inference_prompt_cost": 2.4e-05, "upstream_inference_completions_cost": 0.0001725}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626312-D4pdPnM6hzEriCqVIsXS", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 59, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-013", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "reproducibility"], "scorer": "text_rules", "expected": {"required": ["model", "prompt_hash", "parameters", "scorer"], "forbidden": ["chain of thought", "训练数据"], "max_chars": 200}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：为了复现一次 benchmark，记录中包含 model、case_id、prompt_hash、parameters、scorer details、output、latency_ms 和 usage。记录不包含 chain of thought，也不包含训练数据。\n\n问题：复现评测主要应该依赖哪些记录字段？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7455c8e21abbb53f7cb11c9db29ed66ad1dfcc7e60138f6dfccb7cbcacc958c3", "started_at": "2026-06-16T16:11:54.313344+00:00", "latency_ms": 8697, "output": "根据给定资料，复现评测主要依赖的字段有：\n1. model：确定使用的模型，保障模型一致性；\n2. case_id：对应具体测试用例，保障测试场景一致；\n3. prompt_hash：对应具体输入提示内容，保障输入一致；\n4. parameters：模型推理参数，保障推理配置一致；\n5. scorer details：评分规则细节，保障评分逻辑一致；\n6. output：用于验证复现结果是否匹配；\n7. latency_ms、usage：对应性能相关指标，保障性能维度的复现验证。\n\n注：资料明确说明记录不包含chain of thought、训练数据，无需依赖这两类内容。", "usage": {"prompt_tokens": 105, "completion_tokens": 616, "total_tokens": 721, "cost": 0.0007294, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007294, "upstream_inference_prompt_cost": 2.1e-05, "upstream_inference_completions_cost": 0.0007084}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626316-ufZV5qwF9mJBmENnjeQB", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"missing": [], "missing_any": [], "present_forbidden": ["chain of thought", "训练数据"], "char_count": 289, "length_ok": false, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-014", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "mode"], "scorer": "text_rules", "expected": {"required": ["16384"], "forbidden": ["4096"], "max_chars": 100}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期 ability mode 使用 4096 max_tokens。\n资料 B：后来为了公平，ability mode 统一放宽到 16384 max_tokens。\n资料 C：当前总览页只展示 v0.2-challenge50 且 ability16384 的结果。\n\n问题：当前总览页对应的 token limit 是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1d5b45892f4d0509e7805976e9bb60b3893e68657b40fcfa934db89a27eccc7b", "started_at": "2026-06-16T16:12:03.012334+00:00", "latency_ms": 3738, "output": "16384", "usage": {"prompt_tokens": 118, "completion_tokens": 132, "total_tokens": 250, "cost": 0.0001754, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0001754, "upstream_inference_prompt_cost": 2.36e-05, "upstream_inference_completions_cost": 0.0001518}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626325-OKi2Uotf1N2GYyksJVfs", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 5, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-015", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["人工复查", "coding-004"], "required_any": [["rag-006", "规则", "评分规则", "同义表达"], ["不属于", "不是", "不需要"]], "max_chars": 180}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：coding-004 的失败是代码运行时 ValueError，根因是把字符串 key 强转 int。rag-006 的失败曾经是规则没有把 int 类型视作“整数”的同义表达，后来通过人工复查修正规则。\n\n问题：哪类失败更需要人工复查评分规则？回答时也说明 coding-004 是否属于这种情况。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d4725ef21042620eab8231d5671ac8f778c2b71f85afb72d592c3da2278cc9c4", "started_at": "2026-06-16T16:12:06.752101+00:00", "latency_ms": 5231, "output": "规则未覆盖类型同义表达（如未将int类型视作“整数”的同义表达）的失败更需要人工复查评分规则。\ncoding-004不属于这种情况，其失败根因是代码运行时将字符串key强转为int触发ValueError，并非评分规则覆盖不足导致。", "usage": {"prompt_tokens": 123, "completion_tokens": 313, "total_tokens": 436, "cost": 0.00038455, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00038455, "upstream_inference_prompt_cost": 2.46e-05, "upstream_inference_completions_cost": 0.00035995}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626329-k88WJfF1h6SEfdiaPiBe", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 116, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-016", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain", "cost"], "scorer": "text_rules", "expected": {"required": ["不能", "利润率"], "required_any": [["不包含", "没有"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：usage 字段包含 prompt_tokens、completion_tokens、reasoning_tokens 和 cost。报告没有供应商真实利润率，也没有供应商内部成本。\n\n问题：能否从 usage 字段判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "622c02bde50c8b232afe7bb574da76e2ed1e35d49a55a96f63b935dbbbb16175", "started_at": "2026-06-16T16:12:11.984698+00:00", "latency_ms": 3456, "output": "不能。资料明确说明报告没有供应商真实利润率，也没有供应商内部成本，且usage字段仅包含token相关统计信息和cost，没有可用于判断供应商利润率的必要数据。", "usage": {"prompt_tokens": 92, "completion_tokens": 169, "total_tokens": 261, "cost": 0.00021275, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00021275, "upstream_inference_prompt_cost": 1.84e-05, "upstream_inference_completions_cost": 0.00019435}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626334-GOXZbthMayunYI7kPbHC", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 80, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-017", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "index-scope"], "scorer": "text_rules", "expected": {"required": ["v0.2-challenge50", "ability16384"], "required_any": [["不应该", "不展示", "未展示", "不显示", "均不显示", "不应展示"], ["旧版本", "之前的版本"]], "max_chars": 160}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：当前 index 页只显示最后这版 50 道题的 v0.2-challenge50 结果，并且 token limit 都统一为 ability16384。之前的版本和 ability4096 结果不显示在 index 页。\n\n问题：index 页是否应该展示旧版本结果？当前展示范围是什么？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "84234aeba9875f705a8daae80d0f0a287d1cef74de57877dfe6fbd41e6d1e835", "started_at": "2026-06-16T16:12:15.441516+00:00", "latency_ms": 7403, "output": "1. 根据资料，index页不应该展示旧版本结果。\n2. 当前展示范围仅为最后这版50道题的v0.2-challenge50结果，且token limit统一为ability16384，旧版本结果、ability4096对应的结果均不展示。", "usage": {"prompt_tokens": 116, "completion_tokens": 412, "total_tokens": 528, "cost": 0.000497, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000497, "upstream_inference_prompt_cost": 2.32e-05, "upstream_inference_completions_cost": 0.0004738}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626337-mlLhUCDzoM9sq35EQj3V", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 120, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-rag-018", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "truncation"], "scorer": "text_rules", "expected": {"required": ["输出"], "required_any": [["截断", "length", "token"]], "forbidden": [], "max_chars": 140}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只根据资料回答。\n\n资料：某 coding 题中，模型响应的 finish_reason 为 length，output 为空，测试报错为 module has no attribute solve。报告认为这不是算法逻辑错误，而是输出被截断后没有形成可执行函数。\n\n问题：这次失败应如何归因？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f819b3ec516c1c77e6e0c1bbcece217d77fc5a4aaee6e7787be0b4cd5d97c9ff", "started_at": "2026-06-16T16:12:22.846616+00:00", "latency_ms": 4824, "output": "此次失败应归因为模型输出因长度限制被截断，未生成完整的可执行`solve`函数，并非算法逻辑错误，属于输出截断引发的非算法逻辑类失败。", "usage": {"prompt_tokens": 107, "completion_tokens": 298, "total_tokens": 405, "cost": 0.0003641, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003641, "upstream_inference_prompt_cost": 2.14e-05, "upstream_inference_completions_cost": 0.0003427}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626345-Y0NClnRyyMTfdTdJU9pj", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 67, "length_ok": true, "length_scored": false}}, "error": null} {"case_id": "challenge-debugging-015", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "closure", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望 funcs[0]()、funcs[1]()、funcs[2]() 分别返回 0、1、2，但实际都会返回 2。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 append 行>。\n\n```python\nfuncs = []\nfor i in range(3):\n funcs.append(lambda: i)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e90d1ddfafd6f041b7be435f823b34b7ad74ddf85bb4dbb228db8e1183cd8843", "started_at": "2026-06-16T16:12:27.671710+00:00", "latency_ms": 8104, "output": "### 根因\nlambda 闭包默认捕获外部变量 `i` 的引用，而非循环每次迭代时 `i` 的快照，循环结束后 `i` 的取值为 2，因此所有闭包执行时都返回最终的 `i` 值。\n\n### 最小修复\n为 lambda 设置默认参数，将迭代时的 `i` 值绑定到默认参数上，闭包会捕获默认参数的值而非外部变量引用。\n\nFIX: funcs.append(lambda i=i: i)", "usage": {"prompt_tokens": 130, "completion_tokens": 616, "total_tokens": 746, "cost": 0.0007344, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007344, "upstream_inference_prompt_cost": 2.6e-05, "upstream_inference_completions_cost": 0.0007084}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626349-TpLiJcLwiZwplUOoGou7", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-016", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "context-manager", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面 context manager 期望异常继续向外抛出，但实际异常被吞掉。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\nclass Span:\n def __enter__(self):\n return self\n def __exit__(self, exc_type, exc, tb):\n return True\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e7cbf0d9b2df76954e4b3aacf7d21f0a22c40f64ccc2432b115896cdb5a3f123", "started_at": "2026-06-16T16:12:35.777697+00:00", "latency_ms": 7887, "output": "Bug：`__exit__` 返回 `True` 会抑制异常传播（suppress exception），导致异常被吞掉。根据 Python 上下文管理器协议，只有返回 `False` 或 `None` 时，异常才会继续向外抛出。\n\n最小修复：将 `return True` 改为 `return False`。\n\nFIX: return False", "usage": {"prompt_tokens": 119, "completion_tokens": 701, "total_tokens": 820, "cost": 0.00082995, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00082995, "upstream_inference_prompt_cost": 2.38e-05, "upstream_inference_completions_cost": 0.00080615}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626358-H8bdu6oU37OQeKCPFsnL", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-017", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "class-variable", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望每个 Bag 实例都有独立列表，但不同实例会共享 items。请指出 bug，并给出最小修复。最后单独一行写 FIX: <新增到 __init__ 中的赋值行>。\n\n```python\nclass Bag:\n items = []\n def add(self, x):\n self.items.append(x)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c2b320a4b54c57505deb9a6f14ebb63217e6c351a61dbfeed24131e848fe7553", "started_at": "2026-06-16T16:12:43.665903+00:00", "latency_ms": 13104, "output": "Bug：`items = []` 是类变量（class variable），所有 `Bag` 实例共享同一个列表对象，导致一个实例的 `add` 会影响其他实例。\n\n最小修复：在 `__init__` 中将 `items` 初始化为实例变量，使每个实例拥有独立的列表。\n\n```python\nclass Bag:\n def __init__(self):\n self.items = []\n def add(self, x):\n self.items.append(x)\n```\n\nFIX: self.items = []", "usage": {"prompt_tokens": 112, "completion_tokens": 894, "total_tokens": 1006, "cost": 0.0010505, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0010505, "upstream_inference_prompt_cost": 2.24e-05, "upstream_inference_completions_cost": 0.0010281}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626366-Z9pRwE304lPIizBB1L3W", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?"}}, "error": null} {"case_id": "challenge-debugging-018", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "default-argument", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望每次不传 ts 时使用当前时间，但默认时间只会在函数定义时计算一次。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\nfrom datetime import datetime\n\ndef mark(ts=datetime.utcnow()):\n return ts.isoformat()\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "96674f1c8091e56110c21b7b057178e05bd5225812543e3101e86fc6c5d2dba7", "started_at": "2026-06-16T16:12:56.770990+00:00", "latency_ms": 17989, "output": "Bug: 默认参数 `datetime.utcnow()` 在函数定义时执行一次，后续所有不传 `ts` 的调用都会复用同一个时间对象，而非获取最新时间。\n\n最小修复：将默认参数改为 `None`，在函数体内判断并动态赋值。\n\n```python\nfrom datetime import datetime\n\ndef mark(ts=None):\n if ts is None:\n ts = datetime.utcnow()\n return ts.isoformat()\n```\n\nFIX: def mark(ts=None):", "usage": {"prompt_tokens": 118, "completion_tokens": 1459, "total_tokens": 1577, "cost": 0.00170145, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00170145, "upstream_inference_prompt_cost": 2.36e-05, "upstream_inference_completions_cost": 0.00167785}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626379-Z1XbljLJjtX9b9xfBjLe", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:"}}, "error": null} {"case_id": "challenge-debugging-019", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "method-call", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+s\\.strip\\(\\)\\.lower\\(\\)\\s*`?", "flags": "is"}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "下面代码期望返回小写字符串，但实际返回的是方法对象。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef normalize(s):\n return s.strip().lower\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e9d483dafd7852b396cee6b27c6c25c888983460dba83c871f7f9a239dd601ef", "started_at": "2026-06-16T16:13:14.763293+00:00", "latency_ms": 4724, "output": "Bug：`lower` 是字符串方法，代码中缺少调用括号 `()`，导致返回的是方法对象而非小写字符串。\n\n修复：在 `lower` 后添加调用括号。\n\nFIX: return s.strip().lower()", "usage": {"prompt_tokens": 96, "completion_tokens": 212, "total_tokens": 308, "cost": 0.000263, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000263, "upstream_inference_prompt_cost": 1.92e-05, "upstream_inference_completions_cost": 0.0002438}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626397-SPcHsEzG07Wuroh94C2x", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+s\\.strip\\(\\)\\.lower\\(\\)\\s*`?"}}, "error": null} {"case_id": "challenge-if-006", "suite": "instruction_following", "case_version": "0.3.0", "tags": ["json", "nested", "strict"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["version", "ready", "cases"], "additionalProperties": false, "properties": {"version": {"type": "string", "const": "v0.3"}, "ready": {"type": "boolean", "const": true}, "cases": {"type": "array", "minItems": 2, "maxItems": 2, "items": {"type": "object", "required": ["id", "weight", "active"], "additionalProperties": false, "properties": {"id": {"type": "string", "pattern": "^case-[12]$"}, "weight": {"type": "integer"}, "active": {"type": "boolean"}}}}}}}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "只输出 JSON 对象，不要 Markdown。字段 version 必须是 \"v0.3\"；字段 ready 必须是 true；字段 cases 必须是正好两个对象组成的数组。cases 中每个对象只能包含 id、weight、active 三个字段；id 是字符串且匹配 case-1 或 case-2；weight 是整数；active 是布尔值。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7aa2b7b97ec6a230b8e08a0949edc3f573a3979a488949456e1106dcbad11695", "started_at": "2026-06-16T16:13:19.491563+00:00", "latency_ms": 4406, "output": "{\n \"version\": \"v0.3\",\n \"ready\": true,\n \"cases\": [\n {\n \"id\": \"case-1\",\n \"weight\": 1,\n \"active\": true\n },\n {\n \"id\": \"case-2\",\n \"weight\": 2,\n \"active\": false\n }\n ]\n}", "usage": {"prompt_tokens": 121, "completion_tokens": 331, "total_tokens": 452, "cost": 0.00040485, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00040485, "upstream_inference_prompt_cost": 2.42e-05, "upstream_inference_completions_cost": 0.00038065}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626401-9Jxl7r7cAN0J9uSphj76", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"errors": [], "value": {"version": "v0.3", "ready": true, "cases": [{"id": "case-1", "weight": 1, "active": true}, {"id": "case-2", "weight": 2, "active": false}]}}}, "error": null} {"case_id": "challenge-zh-writing-004", "suite": "chinese_writing", "case_version": "0.3.0", "tags": ["wechat", "summary"], "scorer": "text_rules", "expected": {"required": ["推理题", "边界条件", "人工复查"], "forbidden": ["排行榜"], "max_chars": 160}, "model": "stepfun/step-3.7-flash", "provider": null, "prompt": "写一段不超过 160 个汉字的公众号小结，主题是“为什么 v0.3 要扩到 100 题”。必须包含“推理题”“边界条件”“人工复查”，不能出现“排行榜”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "2e406239f22e7454c39c9cc970d8388b92c83522c1edacf056286806f5933790", "started_at": "2026-06-16T16:13:23.899663+00:00", "latency_ms": 10427, "output": "v0.3题库扩容至100题，核心是新增多类推理题，覆盖更多复杂应用场景，同时补充大量边界条件类题目，检验模型在特殊极端场景下的稳定性，所有题目均经过人工复查校准，保障测评维度的全面性，更精准反映模型真实能力。", "usage": {"prompt_tokens": 88, "completion_tokens": 1166, "total_tokens": 1254, "cost": 0.0013585, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0013585, "upstream_inference_prompt_cost": 1.76e-05, "upstream_inference_completions_cost": 0.0013409}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781626406-aZODitB65UdGzPZLumTR", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 104, "length_ok": true, "length_scored": false}}, "error": null}