8 lines
14 KiB
JSON
8 lines
14 KiB
JSON
{"name": "invoice-extraction", "passed": true, "elapsed_s": 2.4416399859983358, "response": {"id": "chatcmpl-9ef1e6844fbb710d", "object": "chat.completion", "created": 1789740786, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"supplier\":\"North Star Ltd\",\"currency\":\"CNY\",\"total\":476,\"due_date\":\"2026-10-03\"}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "The user wants me to extract invoice data into JSON format. Let me parse the information:\n\n- Supplier: North Star Ltd\n- Currency: CNY\n- Rows: 3 items at 125 each = 375, 2 items at 48 each = 96\n- Shipping: 20\n- Discount: 15\n- Total: 375 + 96 + 20 - 15 = 476\n- Due date: 2026-10-03\n\nThe total must be an integer: 476\n\nLet me format as JSON with keys: supplier, currency, total, due_date.\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 90, "total_tokens": 273, "completion_tokens": 183, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 148}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "deduplicate", "passed": true, "elapsed_s": 3.6378728710042196, "response": {"id": "chatcmpl-aebe6528b7dfdb4a", "object": "chat.completion", "created": 1789740789, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"ids\":[\"A\",\"B\",\"D\"],\"total\":48}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "Let me process the orders step by step.\n\nInput orders:\n1. A pending 12\n2. B paid 20\n3. A paid 15\n4. C cancelled 99\n5. D paid 8\n6. B paid 25\n\nStep 1: Keep the last occurrence of each ID.\n- A: last occurrence is \"A paid 15\" (order 3)\n- B: last occurrence is \"B paid 25\" (order 6)\n- C: last occurrence is \"C cancelled 99\" (order 4)\n- D: last occurrence is \"D paid 8\" (order 5)\n\nStep 2: Discard cancelled orders.\n- C is cancelled, so discard it.\n- Remaining: A paid 15, B paid 25, D paid 8\n\nStep 3: Sort IDs alphabetically.\n- A, B, D\n\nStep 4: Calculate total.\n- 15 + 25 + 8 = 48\n\nOutput: {\"ids\":[\"A\",\"B\",\"D\"],\"total\":48}\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 78, "total_tokens": 342, "completion_tokens": 264, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 247}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "schedule", "passed": true, "elapsed_s": 4.258343130997673, "response": {"id": "chatcmpl-80e60d150fade4f6", "object": "chat.completion", "created": 1789740792, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"earliest_finish\": 10, \"critical_path\": [\"A\", \"B\", \"D\"]}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "Let me analyze this scheduling problem carefully.\n\nJobs and their durations:\n- A: 3 hours (starts at hour 0)\n- B: 5 hours, starts after A (so starts at hour 3, finishes at hour 8)\n- C: 4 hours, starts after A (so starts at hour 3, finishes at hour 7)\n- D: 2 hours, starts after both B and C (so starts at max(8, 7) = 8, finishes at hour 10)\n\nLet me trace the timeline:\n- Hour 0: A starts\n- Hour 3: A finishes. B and C can start.\n- Hour 3: B starts, C starts\n- Hour 7: C finishes\n- Hour 8: B finishes. D can start (both B and C are done).\n- Hour 8: D starts\n- Hour 10: D finishes\n\nEarliest finish: 10 hours\n\nCritical path: The longest path through the dependency graph.\n- A → B → D: 3 + 5 + 2 = 10 hours\n- A → C → D: 3 + 4 + 2 = 9 hours\n\nThe critical path is A → B → D, which is [\"A\", \"B\", \"D\"].\n\nThe output should be JSON with earliest_finish and critical_path.\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 68, "total_tokens": 391, "completion_tokens": 323, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 298}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "chinese-policy", "passed": true, "elapsed_s": 2.5289165139984107, "response": {"id": "chatcmpl-a468fc20ce7b6692", "object": "chat.completion", "created": 1789740797, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"甲\":\"主管\",\"乙\":\"经理\",\"丙\":\"经理\",\"丁\":\"总监\"}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "让我仔细分析这个审批制度：\n\n- 金额不超过5000元：主管审批\n- 超过5000且不超过20000：经理审批\n- 超过20000：总监审批\n- 加急不改变审批人\n\n现在分析每个申请：\n\n甲：5000元 → 不超过5000 → 主管\n乙：5001元加急 → 超过5000且不超过20000 → 经理（加急不改变审批人）\n丙：20000元 → 超过5000且不超过20000 → 经理\n丁：20001元 → 超过20000 → 总监\n\n输出JSON格式。\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 106, "total_tokens": 296, "completion_tokens": 190, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 170}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "merge-intervals", "passed": true, "validation_stdout": "passed\n", "validation_stderr": "", "response": {"id": "chatcmpl-981b9ed8509e7638", "object": "chat.completion", "created": 1789740799, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"code\": \"def merge_intervals(intervals):\\n if len(intervals) == 0:\\n return []\\n sorted_intervals = sorted(intervals)\\n merged = [list(sorted_intervals[0])]\\n for i in range(1, len(sorted_intervals)):\\n current = sorted_intervals[i]\\n last = merged[len(merged) - 1]\\n if current[0] <= last[1]:\\n last[1] = max(last[1], current[1])\\n else:\\n merged.append(list(current))\\n return merged\"}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "The user wants a Python function `merge_intervals` that merges overlapping integer intervals, including touching endpoints. Let me think about the requirements:\n\n1. Merge overlapping integer intervals, including touching endpoints (e.g., [1,3] and [3,5] should merge to [1,5])\n2. Return sorted merged intervals as lists\n3. Reply ONLY a JSON object with a code string\n4. No imports, type annotations, decorators, top-level statements or helper functions\n5. Allowed builtins: sorted, len, range, min, max, list, enumerate, sum\n6. Allowed methods: append, sort, copy\n\nLet me write the function:\n\n```python\ndef merge_intervals(intervals):\n if len(intervals) == 0:\n return []\n sorted_intervals = sorted(intervals, key=lambda x: x[0])\n merged = [list(sorted_intervals[0])]\n for i in range(1, len(sorted_intervals)):\n current = sorted_intervals[i]\n last = merged[len(merged) - 1]\n if current[0] <= last[1]: # touching or overlapping\n last[1] = max(last[1], current[1])\n else:\n merged.append(list(current))\n return merged\n```\n\nWait, I need to check: can I use `lambda`? The constraint says no imports, type annotations, decorators, top-level statements or helper functions. Lambda isn't explicitly forbidden. But let me check if `sorted` with `key` is allowed - `sorted` is in the allowed builtins.\n\nActually, let me reconsider. The constraint says \"Allowed builtins: sorted,len,range,min,max,list,enumerate,sum\". This means I can only use these builtins. `lambda` is not a builtin, it's a keyword. Let me think if I can use it...\n\nActually, `lambda` is a keyword expression, not a builtin function. The restriction is on builtins. But to be safe, let me avoid lambda and use a different approach.\n\nI can sort by using `sorted(intervals)` which sorts by first element then second element by default for lists. That should work for intervals.\n\nLet me also check: `list()` is allowed as a builtin. `append` and `sort` are allowed methods.\n\nLet me also make sure I'm not using any helper functions. The function itself is the only function.\n\n```python\ndef merge_intervals(intervals):\n if len(intervals) == 0:\n return []\n sorted_intervals = sorted(intervals)\n merged = [list(sorted_intervals[0])]\n for i in range(1, len(sorted_intervals)):\n current = sorted_intervals[i]\n last = merged[len(merged) - 1]\n if current[0] <= last[1]:\n last[1] = max(last[1], current[1])\n else:\n merged.append(list(current))\n return merged\n```\n\nThis should work. `sorted(intervals)` will sort lists lexicographically, which means by first element, then by second element. That's exactly what we need.\n\nNow I need to return this as a JSON object with a \"code\" string. Let me format it properly.\n\nThe JSON should be: {\"code\": \"def merge_intervals(intervals):\\n if len(intervals) == 0:\\n return []\\n sorted_intervals = sorted(intervals)\\n merged = [list(sorted_intervals[0])]\\n for i in range(1, len(sorted_intervals)):\\n current = sorted_intervals[i]\\n last = merged[len(merged) - 1]\\n if current[0] <= last[1]:\\n last[1] = max(last[1], current[1])\\n else:\\n merged.append(list(current))\\n return merged\"}\n\nLet me double-check: no imports, no type annotations, no decorators, no top-level statements, no helper functions. Only uses sorted, len, range, max, list, append. All allowed. Good.\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 81, "total_tokens": 1090, "completion_tokens": 1009, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 877}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "binary-search", "passed": true, "validation_stdout": "passed\n", "validation_stderr": "", "response": {"id": "chatcmpl-aeb2774a80c34bf9", "object": "chat.completion", "created": 1789740812, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": "\n\n{\"code\":\"def lower_bound(nums, target):\\n lo = 0\\n hi = len(nums)\\n while lo < hi:\\n mid = (lo + hi) // 2\\n if nums[mid] < target:\\n lo = mid + 1\\n else:\\n hi = mid\\n return lo\"}", "refusal": null, "annotations": null, "audio": null, "function_call": null, "reasoning": "The user wants a Python function `lower_bound` that returns the index of the first element >= target in a sorted list `nums`, or `len(nums)` if none exists.\n\nConstraints:\n- Return ONLY a JSON object with a code string\n- No imports, type annotations, decorators, top-level statements, or helper functions\n- Allowed builtins: sorted, len, range, min, max, list, enumerate, sum\n- Allowed methods: append, sort, copy\n\nLet me write a binary search implementation for lower_bound:\n\n```python\ndef lower_bound(nums, target):\n lo = 0\n hi = len(nums)\n while lo < hi:\n mid = (lo + hi) // 2\n if nums[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return lo\n```\n\nThis is a standard binary search for lower bound. Let me check constraints:\n- No imports ✓\n- No type annotations ✓\n- No decorators ✓\n- No top-level statements (just the function definition) ✓\n- No helper functions ✓\n- Uses `len` which is allowed ✓\n- No other builtins needed ✓\n\nNow I need to wrap this in a JSON object with a \"code\" string field.\n"}, "logprobs": null, "finish_reason": "stop", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 92, "total_tokens": 442, "completion_tokens": 350, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 274}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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{"name": "tool-arguments", "passed": true, "response": {"id": "chatcmpl-b686b7cb17c289f3", "object": "chat.completion", "created": 1789740817, "model": "qwen3.8-flash-next", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "refusal": null, "annotations": null, "audio": null, "function_call": null, "tool_calls": [{"id": "chatcmpl-tool-8b3933eec1e344ce", "type": "function", "function": {"name": "create_ticket", "arguments": "{\"title\": \"GPU cooling failure\", \"priority\": \"urgent\", \"asset\": \"GPU-092\"}"}}], "reasoning": "The user wants me to create a ticket with specific parameters:\n- title: \"GPU cooling failure\" (exactly)\n- priority: \"urgent\"\n- asset: \"GPU-092\" (exactly)\n\nThis is straightforward - I'll call the create_ticket function with these exact values.\n"}, "logprobs": null, "finish_reason": "tool_calls", "stop_reason": null, "token_ids": null, "routed_experts": null}], "service_tier": null, "system_fingerprint": "vllm-0.3.1.dev3+g0bfc7a15d-9c4a3436", "usage": {"prompt_tokens": 325, "total_tokens": 447, "completion_tokens": 122, "prompt_tokens_details": null, "completion_tokens_details": {"reasoning_tokens": 65}}, "prompt_logprobs": null, "prompt_token_ids": null, "prompt_text": null, "kv_transfer_params": null, "ec_transfer_params": null, "metrics": null}}
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