38 lines
97 KiB
JSON
38 lines
97 KiB
JSON
{"name": "arithmetic-0", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 141, "completion_tokens": 82, "completion_tokens_details": {"reasoning_tokens": 75}}, "ttft_s": 0.08033495700510684, "elapsed_s": 0.5909661660043639, "decode_tps": 158.62720212253586, "max_stream_gap_s": 0.018763815001875628, "events": 29, "content": "\n\n3973", "reasoning": "I need to compute 137 * 29 + 0.\n\n137 * 29 = 137 * 30 - 137 = 4110 - 137 = 3973\n\nAdding 0 doesn't change anything, so the answer is 3973.\n", "sha256": "d929fd317464b07ece811a135b5937af8eb36ea0b1e88ec82bc5137102d0a62c"}
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{"name": "arithmetic-1", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 96, "completion_tokens": 37, "completion_tokens_details": {"reasoning_tokens": 30}}, "ttft_s": 0.08595889700518455, "elapsed_s": 0.3043062380020274, "decode_tps": 164.87491826392582, "max_stream_gap_s": 0.01860671999747865, "events": 13, "content": "\n\n5761", "reasoning": "160 * 36 = 5760. 5760 + 1 = 5761.\n", "sha256": "5cd050422245af84010bf1c71082001dcd6d880bdd6dd7002e69a8402ab6c73c"}
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{"name": "arithmetic-2", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 125, "completion_tokens": 66, "completion_tokens_details": {"reasoning_tokens": 59}}, "ttft_s": 0.08532555599958869, "elapsed_s": 0.5077504829969257, "decode_tps": 153.87349525519303, "max_stream_gap_s": 0.01870621599664446, "events": 24, "content": "\n\n7871", "reasoning": "183 * 43 = 183 * 40 + 183 * 3 = 7320 + 549 = 7869. Then 7869 + 2 = 7871.\n", "sha256": "c6dabe0673abae92ebdac3d245deb7c9ca89c874d316c46b8ce09fde923a752f"}
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{"name": "arithmetic-3", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 98, "completion_tokens": 39, "completion_tokens_details": {"reasoning_tokens": 31}}, "ttft_s": 0.08707080200110795, "elapsed_s": 0.32353630300349323, "decode_tps": 160.69997457944905, "max_stream_gap_s": 0.01859223899373319, "events": 14, "content": "\n\n10303", "reasoning": "206 * 50 = 10300\n10300 + 3 = 10303\n", "sha256": "4f382303f23d66fb4abcb57f3ad914e7f87831db4a3757ab5fdab83d25b58b1b"}
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{"name": "arithmetic-4", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 131, "completion_tokens": 72, "completion_tokens_details": {"reasoning_tokens": 64}}, "ttft_s": 0.08545495500584366, "elapsed_s": 0.5441159190013423, "decode_tps": 154.798436259984, "max_stream_gap_s": 0.018821514000592288, "events": 26, "content": "\n\n13057", "reasoning": "229 * 57 = 229 * 50 + 229 * 7 = 11450 + 1603 = 13053. Then 13053 + 4 = 13057.\n", "sha256": "5c8a761b69d32970d9e4021e9cddda2caf44a6201a9bf34e503844cd2ce1dc0c"}
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{"name": "arithmetic-5", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 101, "completion_tokens": 42, "completion_tokens_details": {"reasoning_tokens": 34}}, "ttft_s": 0.08643778399709845, "elapsed_s": 0.34146275900275214, "decode_tps": 160.7685678592501, "max_stream_gap_s": 0.018947848002426326, "events": 15, "content": "\n\n16133", "reasoning": "252 * 64 = 16128. Then 16128 + 5 = 16133.\n", "sha256": "38ecdb08b2fcabd6a6a91e18d08f90ca325aae7f5c9ee565aa360e4d3cb610e9"}
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{"name": "arithmetic-6", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 130, "completion_tokens": 71, "completion_tokens_details": {"reasoning_tokens": 63}}, "ttft_s": 0.08607953199680196, "elapsed_s": 0.5258115449978504, "decode_tps": 159.18786426821532, "max_stream_gap_s": 0.018670357996597886, "events": 25, "content": "\n\n19531", "reasoning": "275 * 71 = 275 * 70 + 275 * 1 = 19250 + 275 = 19525. Then 19525 + 6 = 19531.\n", "sha256": "7ac565b6322b904ff447bc9ef3ed069ebc4e48b8a51e72f9e18919bd8e3000d1"}
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{"name": "arithmetic-7", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 153, "completion_tokens": 94, "completion_tokens_details": {"reasoning_tokens": 86}}, "ttft_s": 0.08593622500484344, "elapsed_s": 0.6902767670035246, "decode_tps": 153.8867468537349, "max_stream_gap_s": 0.018791513997712173, "events": 33, "content": "\n\n23251", "reasoning": "298 * 78 = 298 * 78. Let me compute this step by step.\n\n298 * 78 = 298 * 80 - 298 * 2 = 23840 - 596 = 23244\n\n23244 + 7 = 23251\n", "sha256": "e7b73eb708d2c4c7d2fc5dca2aed40a571c8b0445cd1867d916b47f57ec4cac0"}
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{"name": "arithmetic-8", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 144, "completion_tokens": 85, "completion_tokens_details": {"reasoning_tokens": 77}}, "ttft_s": 0.08543285400082823, "elapsed_s": 0.6162005010046414, "decode_tps": 158.2613418021625, "max_stream_gap_s": 0.018708337993302848, "events": 29, "content": "\n\n27293", "reasoning": "Let me compute 321 * 85 + 8.\n\n321 * 85 = 321 * 80 + 321 * 5 = 25680 + 1605 = 27285\n\n27285 + 8 = 27293\n", "sha256": "9d93671c15eac2005a27c4fe38e5d4285b3feca77fa1e90f138c71a2b5164db8"}
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{"name": "arithmetic-9", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 59, "total_tokens": 143, "completion_tokens": 84, "completion_tokens_details": {"reasoning_tokens": 76}}, "ttft_s": 0.08579609300068114, "elapsed_s": 0.6164905580008053, "decode_tps": 156.39884241110482, "max_stream_gap_s": 0.018804239996825345, "events": 29, "content": "\n\n31657", "reasoning": "Let me compute 344 * 92 + 9.\n\n344 * 92 = 344 * 90 + 344 * 2 = 30960 + 688 = 31648\n\n31648 + 9 = 31657\n", "sha256": "6b95a8b82a4ba5a8335b5f10899663aeebe71fed7e5673836b82ec74cfa1cbee"}
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{"name": "arithmetic-10", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 60, "total_tokens": 143, "completion_tokens": 83, "completion_tokens_details": {"reasoning_tokens": 75}}, "ttft_s": 0.08569144899956882, "elapsed_s": 0.5975101969961543, "decode_tps": 160.21296664292387, "max_stream_gap_s": 0.018605278004542924, "events": 29, "content": "\n\n36343", "reasoning": "Let me compute 367 * 99 + 10.\n\n367 * 99 = 367 * (100 - 1) = 36700 - 367 = 36333\n\n36333 + 10 = 36343\n", "sha256": "662f32768d742ea67e45b8109190fc2ba55c429346f4be9b9492ff457cdacc48"}
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{"name": "arithmetic-11", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 61, "total_tokens": 151, "completion_tokens": 90, "completion_tokens_details": {"reasoning_tokens": 82}}, "ttft_s": 0.08546528800070519, "elapsed_s": 0.6353967890026979, "decode_tps": 161.8383377526822, "max_stream_gap_s": 0.018794105999404564, "events": 31, "content": "\n\n41351", "reasoning": "Let me compute 390 * 106 + 11.\n\n390 * 106 = 390 * 100 + 390 * 6 = 39000 + 2340 = 41340\n\n41340 + 11 = 41351\n", "sha256": "cdbf70494a3484ed891137af4bad12b7417009befd921930fc1fa5e5e3907e27"}
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{"name": "json", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 66, "total_tokens": 109, "completion_tokens": 43, "completion_tokens_details": {"reasoning_tokens": 26}}, "ttft_s": 0.08568278700113297, "elapsed_s": 0.37689909800246824, "decode_tps": 144.2226908773919, "max_stream_gap_s": 0.018781819999276195, "events": 17, "content": "\n\n{\"name\":\"设备A\",\"count\":7,\"enabled\":true}", "reasoning": "The user wants me to return exactly a specific JSON object with no markdown formatting. Let me provide exactly what they asked for.\n", "sha256": "2acba5868b21fa90ff7d281b66898b4ed66b6ff2f42a3d5a1d5bd11569806949"}
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{"name": "multiturn", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 82, "total_tokens": 145, "completion_tokens": 63, "completion_tokens_details": {"reasoning_tokens": 51}}, "ttft_s": 0.08570619000238366, "elapsed_s": 0.5379072569994605, "decode_tps": 137.10715105499912, "max_stream_gap_s": 0.018587483995361254, "events": 26, "content": "\n\nAQUA-58321", "reasoning": "The user is asking me to recall the code they previously told me to remember. They said \"Remember the code AQUA-58321.\" and now they're asking what it was, with the instruction to reply only with the code.\n", "sha256": "dd12a39a5152c7bd1ce0e00fedc430e10a83c25c8a7850e9be06dcc0b4fe0353"}
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{"name": "image-ocr", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 3135, "total_tokens": 3276, "completion_tokens": 141, "completion_tokens_details": {"reasoning_tokens": 102}}, "ttft_s": 0.37922176600113744, "elapsed_s": 1.3786603870030376, "decode_tps": 140.07863720500933, "max_stream_gap_s": 0.01991734900366282, "events": 54, "content": "\n\nVerification code: SPARK-82741\nSum of amounts: 1368 (125 + 478 + 765)", "reasoning": "The user wants the verification code and the sum of three amounts. From the image: code is SPARK-82741; amounts are 125, 478, 765. Sum: 125+478=603; 603+765=1368. I need to provide a clean, self-contained answer. Reasoning is in English matching the user. Final response: code and sum.\n", "sha256": "9e3c14a4e0973d378dc3fda85c529bfed85154aefd90d72c8313c78df80f6564"}
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{"name": "video-120s", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 12069, "total_tokens": 12213, "completion_tokens": 144, "completion_tokens_details": {"reasoning_tokens": 130}}, "ttft_s": 0.8094746360002318, "elapsed_s": 1.7980530589993577, "decode_tps": 144.65215573507055, "max_stream_gap_s": 0.018804600993462373, "events": 55, "content": "\n\nRed, Green, Blue, Yellow, Purple, White", "reasoning": "The user wants the six background colors in chronological order, replying only with English color names. Looking at the frames: 0-19s red, 20-39s green, 40-59s blue, 60-79s yellow, 80-99s purple, 100-119s white. So the sequence is Red, Green, Blue, Yellow, Purple, White. I need to provide just the names, comma-separated or listed. The instruction says \"Reply only with the English color names.\" I'll give a simple comma-separated list.\n", "sha256": "40374d1d01e9d30a2e10dfcf6ba861c98b6c27c52bed2fc369e82286625e2f93"}
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{"name": "multi-image", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 12356, "total_tokens": 12433, "completion_tokens": 77, "completion_tokens_details": {"reasoning_tokens": 66}}, "ttft_s": 1.4533180090002134, "elapsed_s": 1.9994508850068087, "decode_tps": 139.16027278145802, "max_stream_gap_s": 0.018682743997487705, "events": 31, "content": "\n\nSPARK-82741", "reasoning": "The user wants the verification code from the invoice. All four copies show the same line: \"Verification: SPARK-82741\". I need to extract just the code value, not the label. The code is SPARK-82741. Reply only with the code, no extra text.\n", "sha256": "6948cfaa73343b43893c8bbd5a7faf45ed78d55ac8ae50d67b8b890a8d1bf6c7"}
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{"name": "warmup-code", "passed": true, "finish": "length", "usage": {"prompt_tokens": 77, "total_tokens": 333, "completion_tokens": 256, "completion_tokens_details": {"reasoning_tokens": 256}}, "ttft_s": 0.08620800900098402, "elapsed_s": 2.189102151998668, "decode_tps": 121.26145333996531, "max_stream_gap_s": 0.018632254999829456, "events": 117, "content": "", "reasoning": "We need answer user's request: \"Write a production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, and a detailed explanation.\"\n\nNeed produce final answer with code, tests, explanation. Need likely include a complete utility. Need think through design.\n\nWe need satisfy: production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, detailed explanation.\n\nWe can provide a single-file module maybe csv_importer.py with dataclasses, exceptions, validators, duplicate strategies, error report, CLI? Unit tests using unittest or pytest. Need detailed explanation.\n\nNeed ensure code is correct. Let's design robust CSV import utility.\n\nRequirements:\n- Import CSV into records (maybe database? but generic). Could be utility that reads CSV, validates rows, handles duplicates, reports errors, returns result.\n- Production-quality: type hints, logging, config, encoding, delimiter, quoting, BOM, schema, required fields, types, constraints, custom validators, duplicate keys, strategies (skip, update, fail, replace?), error reporting with row numbers, field, code, message, line, raw row.\n- Unit tests: use unittest or pytest. Need maybe include tests for validation, duplicate handling,", "sha256": "ae01d596ec7a45f3c398b1526e5f345c2a100644fe1e8d2975c98d406465b7ad"}
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{"name": "perf-code-0", "passed": true, "finish": "length", "usage": {"prompt_tokens": 77, "total_tokens": 2125, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.07210104499972658, "elapsed_s": 16.617303178005386, "decode_tps": 123.72166768011161, "max_stream_gap_s": 0.019507625998812728, "events": 920, "content": "", "reasoning": "We need answer user's request: \"Write a production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, and a detailed explanation.\"\n\nNeed produce final answer with code, tests, explanation. Need likely include a complete utility. Need think through design.\n\nWe need satisfy: production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, detailed explanation.\n\nWe can provide a single-file module maybe csv_importer.py with dataclasses, exceptions, validators, duplicate strategies, error report, CLI? Unit tests using unittest or pytest. Need detailed explanation.\n\nNeed ensure code is correct. Let's design robust CSV import utility.\n\nRequirements:\n- Import CSV into records (maybe database? but generic). Could be utility that reads CSV, validates rows, handles duplicates, reports errors, returns result.\n- Production-quality: type hints, logging, config, encoding, delimiter, quoting, BOM, schema, required fields, types, constraints, custom validators, duplicate keys, strategies (skip, update, fail, replace?), error reporting with row numbers, field, code, message, line, raw row.\n- Unit tests: use unittest or pytest. Need maybe include tests for validation, duplicate handling, error reporting, encoding, malformed CSV, custom validators, CLI? Keep manageable.\n- Detailed explanation: architecture, usage, extension.\n\nNeed maybe avoid external dependencies beyond stdlib. Use csv, dataclasses, enum, typing, logging, pathlib, io, hashlib? For duplicate handling maybe in-memory set or callback. Could support database via repository interface.\n\nLet's design:\n\nModule csv_importer.py:\n\nImports:\nfrom __future__ import annotations\nimport csv, logging, re, unicodedata, hashlib, json, argparse, sys\nfrom dataclasses import dataclass, field\nfrom datetime import datetime, date\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import Any, Callable, Iterable, Iterator, Mapping, Sequence, TextIO, TypeVar, Optional, Union\nfrom collections.abc import Mapping? Use typing.\n\nExceptions:\nclass ImportError(Exception) maybe CSVImportError.\nclass SchemaError(CSVImportError)\nclass ValidationError(CSVImportError)\n\nEnums:\nclass DuplicateStrategy(str, Enum): SKIP, UPDATE, FAIL, REPLACE? For import into repository.\nclass OnError(str, Enum): FAIL, SKIP_ROW, SKIP_FILE? Maybe continue.\n\nDataclasses:\n@dataclass(frozen=True)\nclass FieldSpec:\n name: str\n required: bool = False\n type: str = \"str\" # str, int, float, bool, date, datetime, email, uuid?\n nullable: bool = False\n default: Any = None\n min_length: Optional[int] = None\n max_length: Optional[int] = None\n pattern: Optional[str] = None\n choices: Optional[Sequence[str]] = None\n min_value: Optional[float] = None\n max_value: Optional[float] = None\n trim: bool = True\n empty_to_null: bool = True\n validators: tuple[Callable[[Any], None], ...] = ()? dataclass with tuple.\n\nBut validators callable may raise ValidationError.\n\n@dataclass(frozen=True)\nclass Schema:\n fields: tuple[FieldSpec,...]\n duplicate_keys: tuple[str,...] = ()\n allow_extra_fields: bool = False\n required_headers: maybe derived.\n\n@dataclass(frozen=True)\nclass ImportOptions:\n encoding: str = \"utf-8-sig\"\n delimiter: str = \",\"\n quotechar: str = '\"'\n escapechar: Optional[str] = None\n doublequote: bool = True\n skipinitialspace: bool = False\n max_rows: Optional[int] = None\n max_errors: Optional[int] = 100\n on_error: OnError = OnError.SKIP_ROW? For production maybe fail? Let's choose SKIP_ROW to collect errors.\n duplicate_strategy: DuplicateStrategy = DuplicateStrategy.SKIP\n strict_headers: bool = True? maybe exact headers? Could allow extra.\n\n@dataclass(frozen=True)\nclass RowError:\n row_number: int # 1-based data row? include header? Use data_row_number and csv_line_number.\n csv_line_number: int\n field: Optional[str]\n code: str\n message: str\n value: Optional[str]\n raw_row: Optional[Mapping[str, str]]? For security maybe redact? Could include raw row dict.\n\n@dataclass\nclass ImportResult:\n imported: list[dict[str, Any]]\n skipped_duplicates: list[dict[str, Any]]\n updated: list[dict[str, Any]]\n errors: list[RowError]\n total_rows: int\n valid_rows: int\n invalid_rows: int\n duplicate_rows: int\n started_at, finished_at? maybe.\n def ok property.\n\nRepository protocol:\nclass Repository(Protocol):\n def exists(self, key: tuple[Any,...]) -> bool: ...\n def insert(self, record: dict[str, Any]) -> None: ...\n def update(self, record: dict[str, Any]) -> None: ...\n def upsert? Could use exists + insert/update.\n def begin/commit? Maybe transaction.\n\nMemoryRepository:\nclass InMemoryRepository:\n def __init__(self, key_fields): self._store = {}\n def key(self, record): tuple(record.get(k) for k in key_fields)\n exists, insert, update, all.\n\nBut duplicate handling can be done by importer with repository. Need handle duplicates within file too. Use seen_keys set.\n\nValidation:\n- parse headers: first row. Check required headers present. If strict_headers? maybe if allow_extra_fields false, unknown headers error.\n- For each row: csv.DictReader. Need line numbers. DictReader has line_num? csv.reader line_num. Could use csv.reader manually to get line numbers and handle header. Better:\n with open(path, newline='', encoding=...) as f:\n reader = csv.reader(f, **dialect)\n try: headers = next(reader)\n except StopIteration: raise SchemaError(\"empty\")\n header_line = reader.line_num\n normalize headers? strip.\n validate headers.\n for row in reader:\n line_num = reader.line_num\n if len(row) != len(headers): error? DictReader would restkey. We can handle.\n raw = dict(zip(headers, row)) if len row >=? If too few, missing fields. If too many, extra.\n process.\n\nNeed handle BOM: encoding utf-8-sig.\n\nField parsing:\ndef parse_value(raw, spec):\n if raw is None: value = None\n else:\n if spec.trim: raw = raw.strip()\n if raw == \"\" and spec.empty_to_null: value = None else raw\n if value is None:\n if spec.required and not spec.nullable: error REQUIRED\n return spec.default if value is None and spec.default is not None? But if required no.\n type conversion:\n str: ensure str\n int: int(value) maybe underscores? Use int(value, 10). bool: accept true/false/1/0/yes/no/y/n? Need case-insensitive.\n float: float(value)\n date: date.fromisoformat(value)\n datetime: datetime.fromisoformat(value)\n email: regex.\n uuid: uuid.UUID.\n constraints: min_length, max_length, pattern, choices, min_value, max_value.\n custom validators.\n\nNeed collect multiple errors per row? Could stop at first? Production maybe collect all field errors. But duplicate handling after validation. We can collect row_errors list. If any errors, add to result and continue based on on_error. If on_error FAIL, raise? But result? Could raise CSVImportError with errors. Simpler: importer collects errors; if on_error=FAIL and error occurs, stop and return? Maybe raise. But unit tests easier if returns errors. Let's define OnError: FAIL raises CSVImportError after first error? Or collect and stop. For production, fail fast. But error reporting wants errors. Could have max_errors. Let's implement: if on_error == FAIL, raise CSVImportError with errors list. But tests can catch. Or return result with ok false. Hmm.\n\nMaybe simpler: Importer always collects errors up to max_errors, then if on_error == FAIL and errors, raise CSVImportError. But if max_errors reached, stop reading. For SKIP_ROW, continue. For SKIP_FILE? not needed.\n\nDuplicate handling:\n- If schema.duplicate_keys: key = tuple(record.get(k) for k in keys). If any key None? If required fields validated, not None. But if nullable? Could skip duplicate check if any None? Maybe treat None as value.\n- If key in seen_in_file or repo.exists(key): duplicate.\n strategy:\n SKIP: add to skipped_duplicates, continue.\n UPDATE: if repo.exists: repo.update(record), add updated; else insert.\n FAIL: add error DUPLICATE_KEY and maybe stop? If on_error fail? Could treat as error.\n REPLACE: if exists repo.update else insert. Similar to UPDATE? Maybe UPDATE only if exists, REPLACE same. Could define UPDATE = update existing, insert new; REPLACE = delete then insert? Not needed. Maybe strategies: SKIP, UPDATE, FAIL, ERROR", "sha256": "4b5a99c6a2d74362c14314126d243ab0ea75f0d203a637e5635b96bc429e3afb"}
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{"name": "perf-code-1", "passed": true, "finish": "length", "usage": {"prompt_tokens": 77, "total_tokens": 2125, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.07450222100305837, "elapsed_s": 16.60604691500339, "decode_tps": 123.82387961258709, "max_stream_gap_s": 0.018462731000909116, "events": 922, "content": "", "reasoning": "We need answer user's request: \"Write a production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, and a detailed explanation.\"\n\nNeed produce final answer with code, tests, explanation. Need likely include a complete utility. Need think through design.\n\nWe need satisfy: production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, detailed explanation.\n\nWe can provide a single-file module maybe csv_importer.py with dataclasses, exceptions, validators, duplicate strategies, error report, CLI? Unit tests using unittest or pytest. Need detailed explanation.\n\nNeed ensure code is correct. Let's design robust CSV import utility.\n\nRequirements:\n- Import CSV into records (maybe database? but generic). Could be utility that reads CSV, validates rows, handles duplicates, reports errors, returns result.\n- Production-quality: type hints, logging, config, encoding, delimiter, quoting, BOM, schema, required fields, types, constraints, custom validators, duplicate keys, strategies (skip, update, fail, replace?), error reporting with row numbers, field, code, message, line, raw row.\n- Unit tests: use unittest or pytest. Need maybe include tests for validation, duplicate handling, error reporting, encoding, malformed CSV, custom validators, CLI? Keep manageable.\n- Detailed explanation: architecture, usage, extension.\n\nNeed maybe avoid external dependencies beyond stdlib. Use csv, dataclasses, enum, typing, logging, pathlib, io, hashlib? For duplicate handling maybe in-memory set or callback. Could support database via repository interface.\n\nLet's design:\n\nModule csv_importer.py:\n\nImports:\nfrom __future__ import annotations\nimport csv, logging, re, unicodedata, hashlib, json, argparse, sys\nfrom dataclasses import dataclass, field\nfrom datetime import datetime, date\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import Any, Callable, Iterable, Iterator, Mapping, Sequence, TextIO, TypeVar, Optional, Union\nfrom collections.abc import Mapping? Use typing.\n\nExceptions:\nclass ImportError(Exception) maybe CSVImportError.\nclass SchemaError(CSVImportError)\nclass ValidationError(CSVImportError)\n\nEnums:\nclass DuplicateStrategy(str, Enum): SKIP, UPDATE, FAIL, REPLACE? For import into repository.\nclass OnError(str, Enum): FAIL, SKIP_ROW, SKIP_FILE? Maybe continue.\n\nDataclasses:\n@dataclass(frozen=True)\nclass FieldSpec:\n name: str\n required: bool = False\n type: str = \"str\" # str, int, float, bool, date, datetime, email, uuid?\n nullable: bool = False\n default: Any = None\n min_length: Optional[int] = None\n max_length: Optional[int] = None\n pattern: Optional[str] = None\n choices: Optional[Sequence[str]] = None\n min_value: Optional[float] = None\n max_value: Optional[float] = None\n trim: bool = True\n empty_to_null: bool = True\n validators: tuple[Callable[[Any], None], ...] = ()? dataclass with tuple.\n\nBut validators callable may raise ValidationError.\n\n@dataclass(frozen=True)\nclass Schema:\n fields: tuple[FieldSpec,...]\n duplicate_keys: tuple[str,...] = ()\n allow_extra_fields: bool = False\n required_headers: maybe derived.\n\n@dataclass(frozen=True)\nclass ImportOptions:\n encoding: str = \"utf-8-sig\"\n delimiter: str = \",\"\n quotechar: str = '\"'\n escapechar: Optional[str] = None\n doublequote: bool = True\n skipinitialspace: bool = False\n max_rows: Optional[int] = None\n max_errors: Optional[int] = 100\n on_error: OnError = OnError.SKIP_ROW? For production maybe fail? Let's choose SKIP_ROW to collect errors.\n duplicate_strategy: DuplicateStrategy = DuplicateStrategy.SKIP\n strict_headers: bool = True? maybe exact headers? Could allow extra.\n\n@dataclass(frozen=True)\nclass RowError:\n row_number: int # 1-based data row? include header? Use data_row_number and csv_line_number.\n csv_line_number: int\n field: Optional[str]\n code: str\n message: str\n value: Optional[str]\n raw_row: Optional[Mapping[str, str]]? For security maybe redact? Could include raw row dict.\n\n@dataclass\nclass ImportResult:\n imported: list[dict[str, Any]]\n skipped_duplicates: list[dict[str, Any]]\n updated: list[dict[str, Any]]\n errors: list[RowError]\n total_rows: int\n valid_rows: int\n invalid_rows: int\n duplicate_rows: int\n started_at, finished_at? maybe.\n def ok property.\n\nRepository protocol:\nclass Repository(Protocol):\n def exists(self, key: tuple[Any,...]) -> bool: ...\n def insert(self, record: dict[str, Any]) -> None: ...\n def update(self, record: dict[str, Any]) -> None: ...\n def upsert? Could use exists + insert/update.\n def begin/commit? Maybe transaction.\n\nMemoryRepository:\nclass InMemoryRepository:\n def __init__(self, key_fields): self._store = {}\n def key(self, record): tuple(record.get(k) for k in key_fields)\n exists, insert, update, all.\n\nBut duplicate handling can be done by importer with repository. Need handle duplicates within file too. Use seen_keys set.\n\nValidation:\n- parse headers: first row. Check required headers present. If strict_headers? maybe if allow_extra_fields false, unknown headers error.\n- For each row: csv.DictReader. Need line numbers. DictReader has line_num? csv.reader line_num. Could use csv.reader manually to get line numbers and handle header. Better:\n with open(path, newline='', encoding=...) as f:\n reader = csv.reader(f, **dialect)\n try: headers = next(reader)\n except StopIteration: raise SchemaError(\"empty\")\n header_line = reader.line_num\n normalize headers? strip.\n validate headers.\n for row in reader:\n line_num = reader.line_num\n if len(row) != len(headers): error? DictReader would restkey. We can handle.\n raw = dict(zip(headers, row)) if len row >=? If too few, missing fields. If too many, extra.\n process.\n\nNeed handle BOM: encoding utf-8-sig.\n\nField parsing:\ndef parse_value(raw, spec):\n if raw is None: value = None\n else:\n if spec.trim: raw = raw.strip()\n if raw == \"\" and spec.empty_to_null: value = None else raw\n if value is None:\n if spec.required and not spec.nullable: error REQUIRED\n return spec.default if value is None and spec.default is not None? But if required no.\n type conversion:\n str: ensure str\n int: int(value) maybe underscores? Use int(value, 10). bool: accept true/false/1/0/yes/no/y/n? Need case-insensitive.\n float: float(value)\n date: date.fromisoformat(value)\n datetime: datetime.fromisoformat(value)\n email: regex.\n uuid: uuid.UUID.\n constraints: min_length, max_length, pattern, choices, min_value, max_value.\n custom validators.\n\nNeed collect multiple errors per row? Could stop at first? Production maybe collect all field errors. But duplicate handling after validation. We can collect row_errors list. If any errors, add to result and continue based on on_error. If on_error FAIL, raise? But result? Could raise CSVImportError with errors. Simpler: importer collects errors; if on_error=FAIL and error occurs, stop and return? Maybe raise. But unit tests easier if returns errors. Let's define OnError: FAIL raises CSVImportError after first error? Or collect and stop. For production, fail fast. But error reporting wants errors. Could have max_errors. Let's implement: if on_error == FAIL, raise CSVImportError with errors list. But tests can catch. Or return result with ok false. Hmm.\n\nMaybe simpler: Importer always collects errors up to max_errors, then if on_error == FAIL and errors, raise CSVImportError. But if max_errors reached, stop reading. For SKIP_ROW, continue. For SKIP_FILE? not needed.\n\nDuplicate handling:\n- If schema.duplicate_keys: key = tuple(record.get(k) for k in keys). If any key None? If required fields validated, not None. But if nullable? Could skip duplicate check if any None? Maybe treat None as value.\n- If key in seen_in_file or repo.exists(key): duplicate.\n strategy:\n SKIP: add to skipped_duplicates, continue.\n UPDATE: if repo.exists: repo.update(record), add updated; else insert.\n FAIL: add error DUPLICATE_KEY and stop? Or error row.\n REPLACE: if exists repo.update else insert; but within file? If seen, update? Could treat as update.\n- If no duplicate_keys: no duplicate handling.\n\nNeed repository transaction? Could have repository.begin/commit/rollback optional. Use contextlib? Maybe define Repository protocol with", "sha256": "c6a65a378e367e11250c85739caf6c8d1093bd987b88899767d97d623c15bcb9"}
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{"name": "perf-code-2", "passed": true, "finish": "length", "usage": {"prompt_tokens": 77, "total_tokens": 2125, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.08693470500293188, "elapsed_s": 16.638716553999984, "decode_tps": 123.67248545654539, "max_stream_gap_s": 0.018704524001805112, "events": 923, "content": "", "reasoning": "We need answer user's request: \"Write a production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, and a detailed explanation.\"\n\nNeed produce final answer with code, tests, explanation. Need likely include a complete utility. Need think through design.\n\nWe need satisfy: production-quality Python CSV import utility with validation, duplicate handling, error reporting, unit tests, detailed explanation.\n\nWe can provide a single-file module maybe csv_importer.py with dataclasses, exceptions, validators, duplicate strategies, error report, CLI? Unit tests using unittest or pytest. Need detailed explanation.\n\nNeed ensure code is correct. Let's design robust CSV import utility.\n\nRequirements:\n- Import CSV into records (maybe database? but generic). Could be utility that reads CSV, validates rows, handles duplicates, reports errors, returns result.\n- Production-quality: type hints, logging, config, encoding, delimiter, quoting, BOM, schema, required fields, types, constraints, custom validators, duplicate keys, strategies (skip, update, fail, replace?), error reporting with row numbers, field, code, message, line, raw row.\n- Unit tests: use unittest or pytest. Need maybe include tests for validation, duplicate handling, error reporting, encoding, malformed CSV, custom validators, CLI? Keep manageable.\n- Detailed explanation: architecture, usage, extension.\n\nNeed maybe avoid external dependencies beyond stdlib. Use csv, dataclasses, enum, typing, logging, pathlib, io, hashlib? For duplicate handling maybe in-memory set or callback. Could support database via repository interface.\n\nLet's design:\n\nModule csv_importer.py:\n\nImports:\nfrom __future__ import annotations\nimport csv, logging, re, unicodedata, hashlib, json, argparse, sys\nfrom dataclasses import dataclass, field\nfrom datetime import datetime, date\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import Any, Callable, Iterable, Iterator, Mapping, Sequence, TextIO, TypeVar, Optional, Union\nfrom collections.abc import Mapping? Use typing.\n\nExceptions:\nclass ImportError(Exception) maybe CSVImportError.\nclass SchemaError(CSVImportError)\nclass ValidationError(CSVImportError)\n\nEnums:\nclass DuplicateStrategy(str, Enum): SKIP, UPDATE, FAIL, REPLACE? For import into repository.\nclass OnError(str, Enum): FAIL, SKIP_ROW, SKIP_FILE? Maybe continue.\n\nDataclasses:\n@dataclass(frozen=True)\nclass FieldSpec:\n name: str\n required: bool = False\n type: str = \"str\" # str, int, float, bool, date, datetime, email, uuid?\n nullable: bool = False\n default: Any = None\n min_length: Optional[int] = None\n max_length: Optional[int] = None\n pattern: Optional[str] = None\n choices: Optional[Sequence[str]] = None\n min_value: Optional[float] = None\n max_value: Optional[float] = None\n trim: bool = True\n empty_to_null: bool = True\n validators: tuple[Callable[[Any], None], ...] = ()? dataclass with tuple.\n\nBut validators callable may raise ValidationError.\n\n@dataclass(frozen=True)\nclass Schema:\n fields: tuple[FieldSpec,...]\n duplicate_keys: tuple[str,...] = ()\n allow_extra_fields: bool = False\n required_headers: maybe derived.\n\n@dataclass(frozen=True)\nclass ImportOptions:\n encoding: str = \"utf-8-sig\"\n delimiter: str = \",\"\n quotechar: str = '\"'\n escapechar: Optional[str] = None\n doublequote: bool = True\n skipinitialspace: bool = False\n max_rows: Optional[int] = None\n max_errors: Optional[int] = 100\n on_error: OnError = OnError.SKIP_ROW? For production maybe fail? Let's choose SKIP_ROW to collect errors.\n duplicate_strategy: DuplicateStrategy = DuplicateStrategy.SKIP\n strict_headers: bool = True? maybe exact headers? Could allow extra.\n\n@dataclass(frozen=True)\nclass RowError:\n row_number: int # 1-based data row? include header? Use data_row_number and csv_line_number.\n csv_line_number: int\n field: Optional[str]\n code: str\n message: str\n value: Optional[str]\n raw_row: Optional[Mapping[str, str]]? For security maybe redact? Could include raw row dict.\n\n@dataclass\nclass ImportResult:\n imported: list[dict[str, Any]]\n skipped_duplicates: list[dict[str, Any]]\n updated: list[dict[str, Any]]\n errors: list[RowError]\n total_rows: int\n valid_rows: int\n invalid_rows: int\n duplicate_rows: int\n started_at, finished_at? maybe.\n def ok property.\n\nRepository protocol:\nclass Repository(Protocol):\n def exists(self, key: tuple[Any,...]) -> bool: ...\n def insert(self, record: dict[str, Any]) -> None: ...\n def update(self, record: dict[str, Any]) -> None: ...\n def upsert? Could use exists + insert/update.\n def begin/commit? Maybe transaction.\n\nMemoryRepository:\nclass InMemoryRepository:\n def __init__(self, key_fields): self._store = {}\n def key(self, record): tuple(record.get(k) for k in key_fields)\n exists, insert, update, all.\n\nBut duplicate handling can be done by importer with repository. Need handle duplicates within file too. Use seen_keys set.\n\nValidation:\n- parse headers: first row. Check required headers present. If strict_headers? maybe if allow_extra_fields false, unknown headers error.\n- For each row: csv.DictReader. Need line numbers. DictReader has line_num? csv.reader line_num. Could use csv.reader manually to get line numbers and handle header. Better:\n with open(path, newline='', encoding=...) as f:\n reader = csv.reader(f, **dialect)\n try: headers = next(reader)\n except StopIteration: raise SchemaError(\"empty\")\n header_line = reader.line_num\n normalize headers? strip.\n validate headers.\n for row in reader:\n line_num = reader.line_num\n if len(row) != len(headers): error? DictReader would restkey. We can handle.\n raw = dict(zip(headers, row)) if len row >=? If too few, missing fields. If too many, extra.\n process.\n\nNeed handle BOM: encoding utf-8-sig.\n\nField parsing:\ndef parse_value(raw, spec):\n if raw is None: value = None\n else:\n if spec.trim: raw = raw.strip()\n if raw == \"\" and spec.empty_to_null: value = None else raw\n if value is None:\n if spec.required and not spec.nullable: error REQUIRED\n return spec.default if value is None and spec.default is not None? But if required no.\n type conversion:\n str: ensure str\n int: int(value) maybe underscores? Use int(value, 10). bool: accept true/false/1/0/yes/no/y/n? Need case-insensitive.\n float: float(value)\n date: date.fromisoformat(value)\n datetime: datetime.fromisoformat(value)\n email: regex.\n uuid: uuid.UUID.\n constraints: min_length, max_length, pattern, choices, min_value, max_value.\n custom validators.\n\nNeed collect multiple errors per row? Could stop at first? Production maybe collect all field errors. But duplicate handling after validation. We can collect row_errors list. If any errors, add to result and continue based on on_error. If on_error FAIL, raise? But result? Could raise CSVImportError with errors. Simpler: importer collects errors; if on_error=FAIL and error occurs, stop and return? Maybe raise. But unit tests easier if returns errors. Let's define OnError: FAIL raises CSVImportError after first error? Or collect and stop. For production, fail fast. But error reporting wants errors. Could have max_errors. Let's implement: if on_error == FAIL, raise CSVImportError with errors list. But tests can catch. Or return result with ok false. Hmm.\n\nMaybe simpler: Importer always collects errors up to max_errors, then if on_error == FAIL and errors, raise CSVImportError. But if max_errors reached, stop reading. For SKIP_ROW, continue. For SKIP_FILE? not needed.\n\nDuplicate handling:\n- If schema.duplicate_keys: key = tuple(record.get(k) for k in keys). If any key None? If required fields validated, not None. But if nullable? Could skip duplicate check if any None? Maybe treat None as value.\n- If key in seen_in_file or repo.exists(key): duplicate.\n strategy:\n SKIP: add to skipped_duplicates, continue.\n UPDATE: if repo.exists: repo.update(record), add updated; else insert.\n FAIL: add error DUPLICATE_KEY, continue? or fail. We'll add error and count duplicate_rows. If on_error FAIL? duplicate is error.\n REPLACE: if exists repo.update else insert; also seen? For within file, if duplicate, update? Could treat as update.\n- If no duplicate_keys: no duplicate handling.\n\nNeed repository transaction", "sha256": "c6aab7182e88cf796f5b16f8b786142eb9521c9123cb0a049524dde6362b299f"}
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{"name": "warmup-chinese", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 335, "completion_tokens": 256, "completion_tokens_details": {"reasoning_tokens": 182}}, "ttft_s": 0.07400395700096851, "elapsed_s": 1.9887343450027402, "decode_tps": 133.17801900356326, "max_stream_gap_s": 0.0185166260052938, "events": 108, "content": "\n\n# 企业采购系统需求说明书\n\n## 1. 文档说明\n\n### 1.1 文档目的\n\n本文档用于定义企业采购系统的完整业务需求，覆盖采购申请、审批、预算控制、供应商管理、采购执行、库存联动、审计追溯等核心能力，并针对每项关键需求说明异常处理机制，确保系统", "reasoning": "我们需要回答用户中文请求：“请写一份企业采购系统的完整需求说明，覆盖审批、预算、供应商、库存和审计，并逐项说明异常处理。” 需要生成完整需求说明，覆盖审批、预算、供应商、库存、审计，并逐项说明异常处理。需要可能结构化：文档目的、范围、角色、总体流程、功能需求、非功能需求、数据模型、接口、权限、异常处理逐项。用户要求“逐项说明异常处理”，可能每个模块/需求项都要异常处理。需要详尽。无需外部信息。最终中文。确保覆盖审批、预算、供应商、库存、审计。可以包含需求编号、描述、异常处理。可能太长但可接受。需要“完整需求说明”。可以按模块列功能需求，每项异常处理。也可包含状态机、规则、验收标准。注意不要过度啰嗦但足够完整。\n", "sha256": "c7ecb8327c0218df2d04be1c67cec8ee285dd526519e8615316908f083855b7c"}
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{"name": "perf-chinese-0", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 182}}, "ttft_s": 0.08585922900238074, "elapsed_s": 15.984570784006792, "decode_tps": 128.75257173627188, "max_stream_gap_s": 0.01882019199547358, "events": 889, "content": "\n\n# 企业采购系统需求说明书\n\n## 1. 文档说明\n\n### 1.1 文档目的\n\n本文档用于定义企业采购系统的完整业务需求，覆盖采购申请、审批、预算控制、供应商管理、采购执行、库存联动、审计追溯等核心能力，并针对每项关键需求说明异常处理机制，确保系统具备可落地、可审计、可追溯、可运营的业务闭环。\n\n### 1.2 适用范围\n\n本系统适用于企业内部采购业务全流程管理，包括但不限于：\n\n- 采购需求发起\n- 采购审批\n- 预算占用与释放\n- 供应商准入与评估\n- 询价比价、订单生成\n- 收货入库、库存更新\n- 对账、付款前置校验\n- 审计日志与合规追溯\n\n### 1.3 设计目标\n\n系统应满足以下目标：\n\n1. **流程可控**：采购全流程线上化，审批路径清晰可配置。\n2. **预算受控**：采购行为与预算强关联，避免超预算采购。\n3. **供应商可管**：供应商准入、评级、黑名单、合同、资质统一管理。\n4. **库存联动**：采购、收货、入库、退货、调拨与库存实时一致。\n5. **审计可查**：所有关键操作留痕，支持事后审计与责任追溯。\n6. **异常可处理**：对审批异常、预算异常、供应商异常、库存异常、审计异常均有明确处理机制。\n\n---\n\n## 2. 系统角色与权限\n\n### 2.1 主要角色\n\n| 角色 | 职责 |\n|---|---|\n| 申请人 | 发起采购申请、补充资料、跟踪进度 |\n| 部门主管 | 审核业务必要性、合理性 |\n| 财务/预算管理员 | 审核预算、控制预算占用 |\n| 采购员 | 询价、比价、下单、供应商协同 |\n| 采购经理 | 审批采购方案、供应商选择、订单审批 |\n| 仓库管理员 | 收货、入库、库存维护 |\n| 质量/验收人员 | 验收物料、处理质量异常 |\n| 审计员 | 查询日志、导出审计资料、发起合规检查 |\n| 系统管理员 | 配置流程、权限、基础数据、异常规则 |\n\n### 2.2 权限原则\n\n- 最小权限原则\n- 职责分离原则\n- 审批与执行分离\n- 预算控制与采购执行分离\n- 审计只读、不可篡改\n\n---\n\n## 3. 总体业务流程\n\n### 3.1 标准采购流程\n\n1. 申请人提交采购申请\n2. 系统校验预算、物料、供应商、合规规则\n3. 进入审批流\n4. 审批通过后生成采购需求单/采购订单\n5. 采购员选择供应商并下单\n6. 供应商发货\n7. 仓库收货、质检、入库\n8. 库存更新\n9. 对账、付款申请\n10. 全流程审计留痕\n\n### 3.2 异常流程总览\n\n- 审批驳回、撤回、超时、代理审批\n- 预算不足、预算冻结、预算释放失败\n- 供应商失效、资质过期、黑名单、价格异常\n- 收货差异、库存不足、入库失败、退货异常\n- 审计日志缺失、越权操作、数据篡改风险\n\n---\n\n## 4. 功能需求说明\n\n以下按模块逐项说明功能需求及异常处理。\n\n---\n\n# 4.1 采购申请模块\n\n## 4.1.1 需求项：采购申请创建\n\n### 功能说明\n\n系统应支持用户创建采购申请，填写以下信息：\n\n- 申请单号\n- 申请部门\n- 申请人\n- 申请日期\n- 期望到货日期\n- 采购类型（生产物料、办公用品、服务、固定资产等）\n- 物料明细\n- 数量\n- 单位\n- 预估单价\n- 预估金额\n- 预算科目\n- 成本中心\n- 项目编码（可选）\n- 申请原因\n- 附件（报价单、需求说明、图片等）\n\n### 业务规则\n\n- 申请金额 = 数量 × 预估单价\n- 同一申请单可包含多个物料行\n- 申请单保存后进入草稿状态\n- 提交后进入审批中状态\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 必填项缺失 | 前端拦截，提示缺失字段，不允许提交 |\n| 数量或单价为负数 | 禁止提交，提示“数量/单价必须大于0” |\n| 物料编码不存在 | 提示“物料不存在或已停用”，要求重新选择 |\n| 附件格式不支持 | 提示支持格式，拒绝上传 |\n| 附件大小超限 | 提示最大限制，拒绝上传 |\n| 重复提交 | 系统生成唯一提交令牌，防止重复创建 |\n| 网络中断导致提交失败 | 保留草稿，提示用户重新提交，避免数据丢失 |\n| 申请单被他人并发修改 | 采用乐观锁，提示“数据已变更，请刷新后重试” |\n\n---\n\n## 4.1.2 需求项：采购申请编辑与撤回\n\n### 功能说明\n\n- 草稿状态可编辑\n- 审批中状态可撤回（若流程允许）\n- 已审批通过状态不可直接编辑，需走变更流程\n\n### 业务规则\n\n- 仅申请人或授权人可编辑\n- 撤回后状态回到草稿\n- 撤回操作需记录日志\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 非申请人编辑 | 拒绝操作，提示“无权限” |\n| 审批中不允许撤回 | 提示“当前节点不允许撤回” |\n| 撤回时审批人已处理 | 提示“审批已处理，无法撤回” |\n| 撤回后再次提交 | 重新走完整审批流，并保留历史版本 |\n| 撤回失败 | 事务回滚，状态不变，记录失败日志 |\n\n---\n\n## 4.1.3 需求项：采购申请复制与引用\n\n### 功能说明\n\n- 支持从历史申请复制生成新申请\n- 支持从库存请领、项目需求、维修工单等来源生成采购申请\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 源单据已删除 | 提示“源单据不存在” |\n| 源单据无权限查看 | 拒绝复制 |\n| 复制后物料已停用 | 标记异常行，要求用户处理 |\n| 复制后预算科目失效 | 提示重新选择预算科目 |\n\n---\n\n# 4.2 审批模块\n\n## 4.2.1 需求项：审批流配置\n\n### 功能说明\n\n系统应支持按以下条件配置审批流：\n\n- 采购类型\n- 金额区间\n- 部门\n- 项目\n- 物料类别\n- 供应商类型\n- 是否紧急采购\n- 是否超预算\n- 是否指定供应商\n\n### 审批节点类型\n\n- 部门主管审批\n- 财务审批\n- 预算审批\n- 采购经理审批\n- 总经理审批\n- 会签\n- 或签\n- 条件分支\n- 自动通过\n- 自动拒绝\n\n### 业务规则\n\n- 审批流版本化管理\n- 已发起流程按发起时版本执行\n- 新流程仅对新单据生效\n- 支持紧急采购简化审批流\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 审批流未配置 | 提交时提示“未配置审批流”，禁止提交 |\n| 审批流配置冲突 | 保存时校验，提示冲突规则 |\n| 审批流版本被删除 | 已发起流程继续执行，新单据禁止使用 |\n| 条件分支无匹配 | 进入默认审批流或提示配置错误 |\n| 审批节点为空 | 禁止发布流程 |\n| 审批人离职/停用 | 自动转交上级或管理员指定人员，并记录异常 |\n| 审批人长期未处理 | 触发超时提醒、升级、自动转交或自动通过（按配置） |\n| 审批流死循环 | 发布前校验，禁止发布 |\n| 流程实例异常中断 | 支持管理员人工干预、重试、终止 |\n\n---\n\n## 4.2.2 需求项：审批发起\n\n### 功能说明", "reasoning": "我们需要回答用户中文请求：“请写一份企业采购系统的完整需求说明，覆盖审批、预算、供应商、库存和审计，并逐项说明异常处理。” 需要生成完整需求说明，覆盖审批、预算、供应商、库存、审计，并逐项说明异常处理。需要可能结构化：文档目的、范围、角色、总体流程、功能需求、非功能需求、数据模型、接口、权限、异常处理逐项。用户要求“逐项说明异常处理”，可能每个模块/需求项都要异常处理。需要详尽。无需外部信息。最终中文。确保覆盖审批、预算、供应商、库存、审计。可以包含需求编号、描述、异常处理。可能太长但可接受。需要“完整需求说明”。可以按模块列功能需求，每项异常处理。也可包含状态机、规则、验收标准。注意不要过度啰嗦但足够完整。\n", "sha256": "d4c974412272e4560fbce42c1ad1cf265991e6545fd8518f4c0823f8c56bc7ea"}
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{"name": "perf-chinese-1", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 182}}, "ttft_s": 0.07313994099968113, "elapsed_s": 15.988134749000892, "decode_tps": 128.62083994968555, "max_stream_gap_s": 0.018578499999421183, "events": 890, "content": "\n\n# 企业采购系统需求说明书\n\n## 1. 文档说明\n\n### 1.1 文档目的\n\n本文档用于定义企业采购系统的完整业务需求，覆盖采购申请、审批、预算控制、供应商管理、采购执行、库存联动、审计追溯等核心能力，并针对每项关键需求说明异常处理机制，确保系统具备可落地、可审计、可追溯、可运营的业务闭环。\n\n### 1.2 适用范围\n\n本系统适用于企业内部采购业务全流程管理，包括但不限于：\n\n- 采购需求发起\n- 采购审批\n- 预算占用与释放\n- 供应商准入与评估\n- 询价比价、订单生成\n- 收货入库、库存更新\n- 对账、付款前置校验\n- 审计日志与合规追溯\n\n### 1.3 设计目标\n\n系统应满足以下目标：\n\n1. **流程可控**：采购全流程线上化，审批路径清晰可配置。\n2. **预算受控**：采购行为与预算强关联，避免超预算采购。\n3. **供应商可管**：供应商准入、评级、黑名单、合同、资质统一管理。\n4. **库存联动**：采购、收货、入库、退货、调拨与库存实时一致。\n5. **审计可查**：所有关键操作留痕，支持事后审计与责任追溯。\n6. **异常可处理**：对审批异常、预算异常、供应商异常、库存异常、审计异常均有明确处理机制。\n\n---\n\n## 2. 系统角色与权限\n\n### 2.1 主要角色\n\n| 角色 | 职责 |\n|---|---|\n| 申请人 | 发起采购申请、补充资料、跟踪进度 |\n| 部门主管 | 审核业务必要性、合理性 |\n| 财务/预算管理员 | 审核预算、控制预算占用 |\n| 采购员 | 询价、比价、下单、供应商协同 |\n| 采购经理 | 审批采购方案、供应商选择、订单审批 |\n| 仓库管理员 | 收货、入库、库存维护 |\n| 质量/验收人员 | 验收物料、处理质量异常 |\n| 审计员 | 查询日志、导出审计资料、发起合规检查 |\n| 系统管理员 | 配置流程、权限、基础数据、异常规则 |\n\n### 2.2 权限原则\n\n- 最小权限原则\n- 职责分离原则\n- 审批与执行分离\n- 预算控制与采购执行分离\n- 审计只读、不可篡改\n\n---\n\n## 3. 总体业务流程\n\n### 3.1 标准采购流程\n\n1. 申请人提交采购申请\n2. 系统校验预算、物料、供应商、合规规则\n3. 进入审批流\n4. 审批通过后生成采购需求单/采购订单\n5. 采购员选择供应商并下单\n6. 供应商发货\n7. 仓库收货、质检、入库\n8. 库存更新\n9. 对账、付款申请\n10. 全流程审计留痕\n\n### 3.2 异常流程总览\n\n- 审批驳回、撤回、超时、代理审批\n- 预算不足、预算冻结、预算释放失败\n- 供应商失效、资质过期、黑名单、价格异常\n- 收货差异、库存不足、入库失败、退货异常\n- 审计日志缺失、越权操作、数据篡改风险\n\n---\n\n## 4. 功能需求说明\n\n以下按模块逐项说明功能需求及异常处理。\n\n---\n\n# 4.1 采购申请模块\n\n## 4.1.1 需求项：采购申请创建\n\n### 功能说明\n\n系统应支持用户创建采购申请，填写以下信息：\n\n- 申请单号\n- 申请部门\n- 申请人\n- 申请日期\n- 期望到货日期\n- 采购类型（生产物料、办公用品、服务、固定资产等）\n- 物料明细\n- 数量\n- 单位\n- 预估单价\n- 预估金额\n- 预算科目\n- 成本中心\n- 项目编码（可选）\n- 申请原因\n- 附件（报价单、需求说明、图片等）\n\n### 业务规则\n\n- 申请金额 = 数量 × 预估单价\n- 同一申请单可包含多个物料行\n- 申请单保存后进入草稿状态\n- 提交后进入审批中状态\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 必填项缺失 | 前端拦截，提示缺失字段，不允许提交 |\n| 数量或单价为负数 | 禁止提交，提示“数量/单价必须大于0” |\n| 物料编码不存在 | 提示“物料不存在或已停用”，要求重新选择 |\n| 附件格式不支持 | 提示支持格式，拒绝上传 |\n| 附件大小超限 | 提示最大限制，拒绝上传 |\n| 重复提交 | 系统生成唯一提交令牌，防止重复创建 |\n| 网络中断导致提交失败 | 保留草稿，提示用户重新提交，避免数据丢失 |\n| 申请单被他人并发修改 | 采用乐观锁，提示“数据已变更，请刷新后重试” |\n\n---\n\n## 4.1.2 需求项：采购申请编辑与撤回\n\n### 功能说明\n\n- 草稿状态可编辑\n- 审批中状态可撤回（若流程允许）\n- 已审批通过状态不可直接编辑，需走变更流程\n\n### 业务规则\n\n- 仅申请人或授权人可编辑\n- 撤回后状态回到草稿\n- 撤回操作需记录日志\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 非申请人编辑 | 拒绝操作，提示“无权限” |\n| 审批中不允许撤回 | 提示“当前节点不允许撤回” |\n| 撤回时审批人已处理 | 提示“审批已处理，无法撤回” |\n| 撤回后再次提交 | 重新走完整审批流，并保留历史版本 |\n| 撤回失败 | 事务回滚，状态不变，记录失败日志 |\n\n---\n\n## 4.1.3 需求项：采购申请复制与引用\n\n### 功能说明\n\n- 支持从历史申请复制生成新申请\n- 支持从库存请领、项目需求、维修工单等来源生成采购申请\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 源单据已删除 | 提示“源单据不存在” |\n| 源单据无权限查看 | 拒绝复制 |\n| 复制后物料已停用 | 标记异常行，要求用户处理 |\n| 复制后预算科目失效 | 提示重新选择预算科目 |\n\n---\n\n# 4.2 审批模块\n\n## 4.2.1 需求项：审批流配置\n\n### 功能说明\n\n系统应支持按以下条件配置审批流：\n\n- 采购类型\n- 金额区间\n- 部门\n- 项目\n- 物料类别\n- 供应商类型\n- 是否紧急采购\n- 是否超预算\n- 是否指定供应商\n\n### 审批节点类型\n\n- 部门主管审批\n- 财务审批\n- 预算审批\n- 采购经理审批\n- 总经理审批\n- 会签\n- 或签\n- 条件分支\n- 自动通过\n- 自动拒绝\n\n### 业务规则\n\n- 审批流版本化管理\n- 已发起流程按发起时版本执行\n- 新流程仅对新单据生效\n- 支持紧急采购简化审批流\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 审批流未配置 | 提交时提示“未配置审批流”，禁止提交 |\n| 审批流配置冲突 | 保存时校验，提示冲突规则 |\n| 审批流版本被删除 | 已发起流程继续执行，新单据禁止使用 |\n| 条件分支无匹配 | 进入默认审批流或提示配置错误 |\n| 审批节点为空 | 禁止发布流程 |\n| 审批人离职/停用 | 自动转交上级或管理员指定人员，并记录异常 |\n| 审批人长期未处理 | 触发超时提醒、升级、自动转交或自动通过（按配置） |\n| 审批流死循环 | 发布前校验，禁止发布 |\n| 流程实例异常中断 | 支持管理员人工干预、重试、终止、转交 |\n\n---\n\n## 4.2.2 需求项：审批提交与路由", "reasoning": "我们需要回答用户中文请求：“请写一份企业采购系统的完整需求说明，覆盖审批、预算、供应商、库存和审计，并逐项说明异常处理。” 需要生成完整需求说明，覆盖审批、预算、供应商、库存、审计，并逐项说明异常处理。需要可能结构化：文档目的、范围、角色、总体流程、功能需求、非功能需求、数据模型、接口、权限、异常处理逐项。用户要求“逐项说明异常处理”，可能每个模块/需求项都要异常处理。需要详尽。无需外部信息。最终中文。确保覆盖审批、预算、供应商、库存、审计。可以包含需求编号、描述、异常处理。可能太长但可接受。需要“完整需求说明”。可以按模块列功能需求，每项异常处理。也可包含状态机、规则、验收标准。注意不要过度啰嗦但足够完整。\n", "sha256": "8fc19ac2a6425782e63b5c26dd326f7124bce54fc957913963c9fc6ae4ee3341"}
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{"name": "perf-chinese-2", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 182}}, "ttft_s": 0.08644359100435395, "elapsed_s": 15.966877792001469, "decode_tps": 128.90075762988087, "max_stream_gap_s": 0.018619577000208665, "events": 888, "content": "\n\n# 企业采购系统需求说明书\n\n## 1. 文档说明\n\n### 1.1 文档目的\n\n本文档用于定义企业采购系统的完整业务需求，覆盖采购申请、审批、预算控制、供应商管理、采购执行、库存联动、审计追溯等核心能力，并针对每项关键需求说明异常处理机制，确保系统具备可落地、可审计、可追溯、可运营的业务闭环。\n\n### 1.2 适用范围\n\n本系统适用于企业内部采购业务全流程管理，包括但不限于：\n\n- 采购需求发起\n- 采购审批\n- 预算占用与释放\n- 供应商准入与评估\n- 询价比价、订单生成\n- 收货入库、库存更新\n- 对账、付款前置校验\n- 审计日志与合规追溯\n\n### 1.3 设计目标\n\n系统应满足以下目标：\n\n1. **流程可控**：采购全流程线上化，审批路径清晰可配置。\n2. **预算受控**：采购行为与预算强关联，避免超预算采购。\n3. **供应商可管**：供应商准入、评级、黑名单、合同、资质统一管理。\n4. **库存联动**：采购、收货、入库、退货、调拨与库存实时一致。\n5. **审计可查**：所有关键操作留痕，支持事后审计与责任追溯。\n6. **异常可处理**：对审批异常、预算异常、供应商异常、库存异常、审计异常均有明确处理机制。\n\n---\n\n## 2. 系统角色与权限\n\n### 2.1 主要角色\n\n| 角色 | 职责 |\n|---|---|\n| 申请人 | 发起采购申请、补充资料、跟踪进度 |\n| 部门主管 | 审核业务必要性、合理性 |\n| 财务/预算管理员 | 审核预算、控制预算占用 |\n| 采购员 | 询价、比价、下单、供应商协同 |\n| 采购经理 | 审批采购方案、供应商选择、订单审批 |\n| 仓库管理员 | 收货、入库、库存维护 |\n| 质量/验收人员 | 验收物料、处理质量异常 |\n| 审计员 | 查询日志、导出审计资料、发起合规检查 |\n| 系统管理员 | 配置流程、权限、基础数据、异常规则 |\n\n### 2.2 权限原则\n\n- 最小权限原则\n- 职责分离原则\n- 审批与执行分离\n- 预算控制与采购执行分离\n- 审计只读、不可篡改\n\n---\n\n## 3. 总体业务流程\n\n### 3.1 标准采购流程\n\n1. 申请人提交采购申请\n2. 系统校验预算、物料、供应商、合规规则\n3. 进入审批流\n4. 审批通过后生成采购需求单/采购订单\n5. 采购员选择供应商并下单\n6. 供应商发货\n7. 仓库收货、质检、入库\n8. 库存更新\n9. 对账、付款申请\n10. 全流程审计留痕\n\n### 3.2 异常流程总览\n\n- 审批驳回、撤回、超时、代理审批\n- 预算不足、预算冻结、预算释放失败\n- 供应商失效、资质过期、黑名单、价格异常\n- 收货差异、库存不足、入库失败、退货异常\n- 审计日志缺失、越权操作、数据篡改风险\n\n---\n\n## 4. 功能需求说明\n\n以下按模块逐项说明功能需求及异常处理。\n\n---\n\n# 4.1 采购申请模块\n\n## 4.1.1 需求项：采购申请创建\n\n### 功能说明\n\n系统应支持用户创建采购申请，填写以下信息：\n\n- 申请单号\n- 申请部门\n- 申请人\n- 申请日期\n- 期望到货日期\n- 采购类型（生产物料、办公用品、服务、固定资产等）\n- 物料明细\n- 数量\n- 单位\n- 预估单价\n- 预估金额\n- 预算科目\n- 成本中心\n- 项目编码（可选）\n- 申请原因\n- 附件（报价单、需求说明、图片等）\n\n### 业务规则\n\n- 申请金额 = 数量 × 预估单价\n- 同一申请单可包含多个物料行\n- 申请单保存后进入草稿状态\n- 提交后进入审批中状态\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 必填项缺失 | 前端拦截，提示缺失字段，不允许提交 |\n| 数量或单价为负数 | 禁止提交，提示“数量/单价必须大于0” |\n| 物料编码不存在 | 提示“物料不存在或已停用”，要求重新选择 |\n| 附件格式不支持 | 提示支持格式，拒绝上传 |\n| 附件大小超限 | 提示最大限制，拒绝上传 |\n| 重复提交 | 系统生成唯一提交令牌，防止重复创建 |\n| 网络中断导致提交失败 | 保留草稿，提示用户重新提交，避免数据丢失 |\n| 申请单被他人并发修改 | 采用乐观锁，提示“数据已变更，请刷新后重试” |\n\n---\n\n## 4.1.2 需求项：采购申请编辑与撤回\n\n### 功能说明\n\n- 草稿状态可编辑\n- 审批中状态可撤回（若流程允许）\n- 已审批通过状态不可直接编辑，需走变更流程\n\n### 业务规则\n\n- 仅申请人或授权人可编辑\n- 撤回后状态回到草稿\n- 撤回操作需记录日志\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 非申请人编辑 | 拒绝操作，提示“无权限” |\n| 审批中不允许撤回 | 提示“当前节点不允许撤回” |\n| 撤回时审批人已处理 | 提示“审批已处理，无法撤回” |\n| 撤回后再次提交 | 重新走完整审批流，并保留历史版本 |\n| 撤回失败 | 事务回滚，状态不变，记录失败日志 |\n\n---\n\n## 4.1.3 需求项：采购申请复制与引用\n\n### 功能说明\n\n- 支持从历史申请复制生成新申请\n- 支持从库存请领、项目需求、维修工单等来源生成采购申请\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 源单据已删除 | 提示“源单据不存在” |\n| 源单据无权限查看 | 拒绝复制 |\n| 复制后物料已停用 | 标记异常行，要求用户处理 |\n| 复制后预算科目失效 | 提示重新选择预算科目 |\n\n---\n\n# 4.2 审批模块\n\n## 4.2.1 需求项：审批流配置\n\n### 功能说明\n\n系统应支持按以下条件配置审批流：\n\n- 采购类型\n- 金额区间\n- 部门\n- 项目\n- 物料类别\n- 供应商类型\n- 是否紧急采购\n- 是否超预算\n- 是否指定供应商\n\n### 审批节点类型\n\n- 部门主管审批\n- 财务审批\n- 预算审批\n- 采购经理审批\n- 总经理审批\n- 会签\n- 或签\n- 条件分支\n- 自动通过\n- 自动拒绝\n\n### 业务规则\n\n- 审批流版本化管理\n- 已发起流程按发起时版本执行\n- 新流程仅对新单据生效\n- 支持紧急采购简化审批流\n\n### 异常处理\n\n| 异常场景 | 处理方式 |\n|---|---|\n| 审批流未配置 | 提交时提示“未配置审批流”，禁止提交 |\n| 审批流配置冲突 | 保存时校验，提示冲突规则 |\n| 审批流版本被删除 | 已发起流程继续执行，新单据禁止使用 |\n| 条件分支无匹配 | 进入默认审批流或提示配置错误 |\n| 审批节点为空 | 禁止发布流程 |\n| 审批人离职/停用 | 自动转交上级或管理员指定人员，并记录异常 |\n| 审批人长期未处理 | 触发超时提醒、升级、自动转交或自动拒绝（按配置） |\n| 审批流死循环 | 发布前校验，禁止发布 |\n| 流程实例异常中断 | 支持管理员人工干预、重试、终止 |\n\n---\n\n## 4.2.2 需求项：审批发起\n\n### 功能说明", "reasoning": "我们需要回答用户中文请求：“请写一份企业采购系统的完整需求说明，覆盖审批、预算、供应商、库存和审计，并逐项说明异常处理。” 需要生成完整需求说明，覆盖审批、预算、供应商、库存、审计，并逐项说明异常处理。需要可能结构化：文档目的、范围、角色、总体流程、功能需求、非功能需求、数据模型、接口、权限、异常处理逐项。用户要求“逐项说明异常处理”，可能每个模块/需求项都要异常处理。需要详尽。无需外部信息。最终中文。确保覆盖审批、预算、供应商、库存、审计。可以包含需求编号、描述、异常处理。可能太长但可接受。需要“完整需求说明”。可以按模块列功能需求，每项异常处理。也可包含状态机、规则、验收标准。注意不要过度啰嗦但足够完整。\n", "sha256": "488769996df35d3bbedd2a91046c0a137677097523f73433b0919b61c68071b5"}
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{"name": "warmup-reasoning", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 335, "completion_tokens": 256, "completion_tokens_details": {"reasoning_tokens": 256}}, "ttft_s": 0.07434646700130543, "elapsed_s": 2.126096015002986, "decode_tps": 124.28417505848094, "max_stream_gap_s": 0.01840589300263673, "events": 116, "content": "", "reasoning": "We need answer user: \"Explain and prove why Dijkstra works with nonnegative weights. Include a counterexample with negative edges and compare Bellman-Ford.\" Need provide explanation, proof, counterexample, comparison. Need final only. Need be thorough. Let's plan.\n\nWe need explain Dijkstra algorithm: single-source shortest paths in directed/undirected graph with nonnegative edge weights. Greedy: maintain dist labels, priority queue, settled set S. Initially dist(s)=0, others infinity. Repeatedly extract min unsettled vertex u, settle it, relax outgoing edges.\n\nWhy nonnegative weights matter: Once vertex u has minimum tentative distance among unsettled, no unsettled vertex can provide a shorter path to u because any path from s to u through unsettled vertex v has prefix to v with length at least dist[v] (or at least dist[u]?) Need formal proof.\n\nProof by induction: invariant: for each settled vertex x, dist[x]=δ(s,x) true shortest distance. Also for each unsettled vertex v, dist[v] is length of shortest path from s to v whose internal vertices are settled? Or upper bound. Need prove extraction min is correct.\n\nStandard proof: Let u be min tentative among unsett", "sha256": "d557c88f4473c4da0f26d8a2bfdb8aae0734ac1d790d7d3f74c26151b5cbe509"}
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{"name": "perf-reasoning-0", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.07352274699951522, "elapsed_s": 16.837296222998702, "decode_tps": 122.10854572395078, "max_stream_gap_s": 0.018720656000368763, "events": 935, "content": "", "reasoning": "We need answer user: \"Explain and prove why Dijkstra works with nonnegative weights. Include a counterexample with negative edges and compare Bellman-Ford.\" Need provide explanation, proof, counterexample, comparison. Need final only. Need be thorough. Let's plan.\n\nWe need explain Dijkstra algorithm: single-source shortest paths in directed/undirected graph with nonnegative edge weights. Greedy: maintain dist labels, priority queue, settled set S. Initially dist(s)=0, others infinity. Repeatedly extract min unsettled vertex u, settle it, relax outgoing edges.\n\nWhy nonnegative weights matter: Once vertex u has minimum tentative distance among unsettled, no unsettled vertex can provide a shorter path to u because any path from s to u through unsettled vertex v has prefix to v with length at least dist[v] (or at least dist[u]?) Need formal proof.\n\nProof by induction: invariant: for each settled vertex x, dist[x]=δ(s,x) true shortest distance. Also for each unsettled vertex v, dist[v] is length of shortest path from s to v whose internal vertices are settled? Or upper bound. Need prove extraction min is correct.\n\nStandard proof: Let u be min tentative among unsettled. Suppose there is a shorter path P from s to u. Let y be first unsettled vertex on P (u itself if all previous settled? Actually if P shorter than dist[u], since s settled, there is first unsettled vertex y on P; let x be predecessor of y on P, settled. When x was settled, edge (x,y) relaxed, so dist[y] ≤ length(P[s..y]). Since weights nonnegative, length(P[s..y]) ≤ length(P) < dist[u]. Thus dist[y] < dist[u], contradicting u min. This proof uses nonnegative weights to ensure prefix length ≤ full path length. If negative edges, prefix can be longer than full path, so contradiction fails.\n\nAlternative proof: Dijkstra's invariant: settled vertices have final distances. For unsettled, dist[v] is shortest path using only settled internal vertices. When extract min u, any path to u not using only settled vertices has first unsettled vertex y; prefix to y has length ≤ total path due nonnegative, and dist[y] ≤ prefix, so dist[y] ≤ path length. Since u min, dist[u] ≤ dist[y] ≤ path length. Thus dist[u] is shortest.\n\nNeed include counterexample with negative edges. Need show Dijkstra fails. Classic: s->a weight 1, s->b weight 2, a->b weight -2. Shortest s->b = -1 via a, but Dijkstra settles a (dist 1) then b? Let's simulate: initial dist s=0, a=1, b=2. Extract a (1), relax a->b: dist b = -1. Then extract b (-1). Actually Dijkstra would find correct if b not settled before a. Need counterexample where Dijkstra settles vertex too early due negative edge from unsettled vertex. Need graph where vertex v has small tentative but later negative edge from another unsettled vertex reduces it after v settled. Example: s->a=1, s->b=2, b->a=-2. Shortest to a = 0 via b. Dijkstra: dist a=1, b=2. Extract a (1) settle. Then extract b (2), relax b->a gives -1? Wait 2-2=0, but a already settled, Dijkstra doesn't update settled. Final dist a=1, wrong (0). This works. Need ensure nonnegative? Negative edge b->a. Dijkstra picks a before b because 1<2, but path s-b-a length 0 shorter. Good. Could also use s->a=2, s->b=3, b->a=-2 => shortest a=1, Dijkstra settles a=2 wrong. But first example fine. Need maybe directed graph. If undirected negative edge? Dijkstra fails too. Use directed.\n\nNeed compare Bellman-Ford: handles negative weights (no negative cycles reachable from source) by relaxing all edges V-1 times; detects negative cycles. Complexity O(VE), slower than Dijkstra O((V+E) log V) with binary heap or O(E+V log V). Dijkstra requires nonnegative weights; BF can handle negative edges but not negative cycles (shortest paths undefined). BF dynamic programming: after k iterations, dist[v] shortest path with at most k edges. Proof by induction. If negative cycle reachable, distances can decrease indefinitely; BF detects if an edge can still relax on Vth iteration.\n\nNeed maybe mention Dijkstra with negative edges can fail even if no negative cycles. Counterexample no negative cycle. Compare: Dijkstra greedy local optimal; BF exhaustive relaxation. Dijkstra cannot recover from settled vertex; BF can update any vertex repeatedly.\n\nNeed maybe include pseudocode? Could include. Need proof rigorous. Need maybe discuss zero weights okay. Nonnegative includes zero. Need mention if negative edges but no negative cycles, Dijkstra may still work in some cases but not guaranteed. Need maybe mention Johnson reweighting? Not necessary.\n\nNeed final answer structured: 1. Algorithm. 2. Why nonnegative weights. 3. Proof. 4. Counterexample. 5. Bellman-Ford comparison. Maybe include table.\n\nLet's craft final with definitions:\nGraph G=(V,E), weight w:E→R, source s. δ(s,v) shortest path distance. Dijkstra maintains d[v]. S settled.\n\nPseudocode:\nd[s]=0; d[v]=∞; PQ all vertices; S=∅\nwhile PQ not empty:\n u=extract-min(PQ)\n S.add(u)\n for (u,v) in E:\n if d[v] > d[u]+w(u,v): d[v]=d[u]+w(u,v); decrease-key\n\nProof:\nLemma: At start of each iteration, for every settled x, d[x]=δ(s,x). For every unsettled v, d[v] is length of shortest s-v path whose internal vertices are in S (or ∞ if none). Actually after relaxing from settled vertices, d[v] equals min over paths from s to v with all internal vertices settled? Need prove. Initially S empty: d[s]=0 path no internal; others ∞. When settle u, relax edges: for any unsettled v, new paths with internal vertices S∪{u} either old (internal S) or path to u (internal S) + edge u-v. Since d[u]=δ(s,u) and path to u internal S? Need careful: d[u] is shortest path with internal S, but if u settled, d[u]=δ(s,u). For v, d[v] updated to min(old, d[u]+w(u,v)). This gives shortest path with internal S∪{u}. Good.\n\nThen correctness of extracting u: Let u be min d among unsettled. Need show d[u]=δ(s,u). Let P be any shortest s-u path. If all internal vertices settled, then by invariant d[u] ≤ length(P)=δ(s,u); and d[u] always upper bound so equality. If some internal unsettled, let y be first unsettled vertex on P, x predecessor settled (or s). Let P_y prefix s to y. By invariant d[y] ≤ length(P_y). Since weights nonnegative, length(P_y) ≤ length(P)=δ(s,u). Thus d[y] ≤ δ(s,u). If δ(s,u)<d[u], then d[y] < d[u], contradicting u min. Therefore δ(s,u)≥d[u]. Since d[u] is length of some path, d[u]≥δ(s,u). Equality. This proof maybe simpler. Need ensure if y=u? If u is first unsettled, then d[u] ≤ length(P_y)=δ(s,u) directly. If δ<d[u] impossible. But contradiction works.\n\nAlternative proof by contradiction: Suppose u extracted with d[u]>δ(s,u). Let P shortest path. Let y first unsettled on P. Let x predecessor. Since x settled, edge relaxed when x settled, so d[y] ≤ length(P prefix to y). Nonnegative => length(prefix) ≤ length(P) < d[u]. So d[y] < d[u], contradiction. This is concise. Need mention d[y] may have been updated later? It is at most that value at all times after relaxation, so at extraction time still ≤. Good.\n\nNeed maybe discuss negative weights break proof: prefix can be longer than full path, so d[y] may not be < d[u]. In counterexample, shortest path to a is s-b-a length 0; first unsettled y=b? Let's map: Dijkstra extracts a first. Shortest path to a: s->b->a. First unsettled vertex on path is b (since s settled, a target unsettled? Actually path to a: s (settled), b (unsettled), a (target unsettled). First unsettled y=b. Prefix length s-b=2, full path length 0. Nonnegative condition fails: prefix 2 > full 0. d[b]=2, not < d[a]=1, so no contradiction. Dijkstra settles a at 1, later b relaxes to 0 but a settled. Good.\n\nCounterexample details:\nVertices s,a,b. Edges: s→a weight 1, s→b weight 2, b→a weight -2. No negative cycle. Dijkstra:\ninit d[s]=0, d[a]=1, d[b]=2.\nextract s, relax", "sha256": "eec62c20975cfeaada4ad14ef0f726db52eaff6b498dcbbf3f5f515c2c5725c8"}
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{"name": "perf-reasoning-1", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.07170502199733164, "elapsed_s": 16.85341221699491, "decode_tps": 121.97805480780796, "max_stream_gap_s": 0.01876352399995085, "events": 936, "content": "", "reasoning": "We need answer user: \"Explain and prove why Dijkstra works with nonnegative weights. Include a counterexample with negative edges and compare Bellman-Ford.\" Need provide explanation, proof, counterexample, comparison. Need final only. Need be thorough. Let's plan.\n\nWe need explain Dijkstra algorithm: single-source shortest paths in directed/undirected graph with nonnegative edge weights. Greedy: maintain dist labels, priority queue, settled set S. Initially dist(s)=0, others infinity. Repeatedly extract min unsettled vertex u, settle it, relax outgoing edges.\n\nWhy nonnegative weights matter: Once vertex u has minimum tentative distance among unsettled, no unsettled vertex can provide a shorter path to u because any path from s to u through unsettled vertex v has prefix to v with length at least dist[v] (or at least dist[u]?) Need formal proof.\n\nProof by induction: invariant: for each settled vertex x, dist[x]=δ(s,x) true shortest distance. Also for each unsettled vertex v, dist[v] is length of shortest path from s to v whose internal vertices are settled? Or upper bound. Need prove extraction min is correct.\n\nStandard proof: Let u be min tentative among unsettled. Suppose there is a shorter path P from s to u. Let y be first unsettled vertex on P (u itself if all previous settled? Actually if P shorter than dist[u], since s settled, there is first unsettled vertex y on P; let x be predecessor of y on P, settled. When x was settled, edge (x,y) relaxed, so dist[y] ≤ length(P[s..y]). Since weights nonnegative, length(P[s..y]) ≤ length(P) < dist[u]. Thus dist[y] < dist[u], contradicting u min. This proof uses nonnegative weights to ensure prefix length ≤ full path length. If negative edges, prefix can be longer than full path, so contradiction fails.\n\nAlternative proof: Dijkstra's invariant: settled vertices have final distances. For unsettled, dist[v] is shortest path using only settled internal vertices. When extract min u, any path to u not using only settled vertices has first unsettled vertex y; prefix to y has length ≤ total path due nonnegative, and dist[y] ≤ prefix, so dist[y] ≤ path length. Since u min, dist[u] ≤ dist[y] ≤ path length. Thus dist[u] is shortest.\n\nNeed include counterexample with negative edges. Need show Dijkstra fails. Classic: s->a weight 1, s->b weight 2, a->b weight -2. Shortest s->b = -1 via a, but Dijkstra settles a (dist 1) then b? Let's simulate: initial dist s=0, a=1, b=2. Extract a (1), relax a->b: dist b = -1. Then extract b (-1). Actually Dijkstra would find correct if b not settled before a. Need counterexample where Dijkstra settles vertex too early due negative edge from unsettled vertex. Need graph where vertex v has small tentative but later negative edge from another unsettled vertex reduces it after v settled. Example: s->a=1, s->b=2, b->a=-2. Shortest to a = 0 via b. Dijkstra: dist a=1, b=2. Extract a (1) settle. Then extract b (2), relax b->a gives -1? Wait 2-2=0, but a already settled, Dijkstra doesn't update settled. Final dist a=1, wrong (0). This works. Need ensure nonnegative? Negative edge b->a. Dijkstra picks a before b because 1<2, but path s-b-a length 0 shorter. Good. Could also use s->a=2, s->b=3, b->a=-2 => shortest a=1, Dijkstra settles a=2 wrong. But first example fine. Need maybe directed graph. If undirected negative edge? Dijkstra fails too. Use directed.\n\nNeed compare Bellman-Ford: handles negative weights (no negative cycles reachable from source) by relaxing all edges V-1 times; detects negative cycles. Complexity O(VE), slower than Dijkstra O((V+E) log V) with binary heap or O(E+V log V). Dijkstra requires nonnegative weights; BF can handle negative edges but not negative cycles (shortest paths undefined). BF dynamic programming: after k iterations, dist[v] shortest path with at most k edges. Proof by induction. If negative cycle reachable, distances can decrease indefinitely; BF detects if an edge can still relax on Vth iteration.\n\nNeed maybe mention Dijkstra with negative edges can fail even if no negative cycles. Counterexample no negative cycle. Compare: Dijkstra greedy local optimal; BF exhaustive relaxation. Dijkstra cannot recover from settled vertex; BF can update any vertex repeatedly.\n\nNeed maybe include pseudocode? Could include. Need proof rigorous. Need maybe discuss zero weights okay. Nonnegative includes zero. Need mention if negative edges but no negative cycles, Dijkstra may still work in some cases but not guaranteed. Need maybe mention Johnson reweighting? Not necessary.\n\nNeed final answer structured: 1. Algorithm. 2. Why nonnegative weights. 3. Proof. 4. Counterexample. 5. Bellman-Ford comparison. Maybe include table.\n\nLet's craft final with definitions:\nGraph G=(V,E), weight w:E→R, source s. δ(s,v) shortest path distance. Dijkstra maintains d[v]. S settled.\n\nPseudocode:\nd[s]=0; d[v]=∞; PQ all vertices; S=∅\nwhile PQ not empty:\n u=extract-min(PQ)\n S.add(u)\n for (u,v) in E:\n if d[v] > d[u]+w(u,v): d[v]=d[u]+w(u,v); decrease-key\n\nProof:\nLemma: At start of each iteration, for every settled x, d[x]=δ(s,x). For every unsettled v, d[v] is length of shortest s-v path whose internal vertices are in S (or ∞ if none). Actually after relaxing from settled vertices, d[v] equals min over paths from s to v with all internal vertices settled? Need prove. Initially S empty: d[s]=0 path no internal; others ∞. When settle u, relax edges: for any unsettled v, new paths with internal vertices S∪{u} either old (internal S) or path to u (internal S) + edge u-v. Since d[u]=δ(s,u) and path to u internal S? Need careful: d[u] is shortest path with internal S, but if u settled, d[u]=δ(s,u). For v, d[v] updated to min(old, d[u]+w(u,v)). This gives shortest path with internal S∪{u}. Good.\n\nThen correctness of extracting u: Let u be min d among unsettled. Need show d[u]=δ(s,u). Let P be any shortest s-u path. If all internal vertices settled, then by invariant d[u] ≤ length(P)=δ(s,u); and d[u] always upper bound so equality. If some internal unsettled, let y be first unsettled vertex on P, x predecessor settled (or s). Let P_y prefix s to y. By invariant d[y] ≤ length(P_y). Since weights nonnegative, length(P_y) ≤ length(P)=δ(s,u). Thus d[y] ≤ δ(s,u). If δ(s,u)<d[u], then d[y] < d[u], contradicting u min. Therefore δ(s,u)≥d[u]. Since d[u] is length of some path, d[u]≥δ(s,u). Equality. This proof maybe simpler. Need ensure if y=u? If u is first unsettled, then d[u] ≤ length(P_y)=δ(s,u) directly. If δ<d[u] impossible. But contradiction works.\n\nAlternative proof by contradiction: Suppose u extracted with d[u]>δ(s,u). Let P shortest path. Let y first unsettled on P. Let x predecessor. Since x settled, edge relaxed when x settled, so d[y] ≤ length(P prefix to y). Nonnegative => length(prefix) ≤ length(P) < d[u]. So d[y] < d[u], contradiction. This is concise. Need mention d[y] may have been updated later? It is at most that value at all times after relaxation, so at extraction time still ≤. Good.\n\nNeed maybe discuss negative weights break proof: prefix can be longer than full path, so d[y] may not be < d[u]. In counterexample, shortest path to a is s-b-a length 0; first unsettled y=b? Let's map: Dijkstra extracts a first. Shortest path to a: s->b->a. First unsettled vertex on path is b (since s settled, a target unsettled? Actually path to a: s (settled), b (unsettled), a (target unsettled). First unsettled y=b. Prefix length s-b=2, full path length 0. Nonnegative condition fails: prefix 2 > full 0. d[b]=2, not < d[a]=1, so no contradiction. Dijkstra settles a at 1, later b relaxes to 0 but a settled.\n\nCounterexample details:\nVertices s,a,b. Edges: s→a weight 1, s→b weight 2, b→a weight -2. No negative cycle. Dijkstra:\ninit d[s]=0, d[a]=1, d[b]=2.\nextract s, relax: d", "sha256": "8a7cb2cde52eee53562fd48aca68d5267dceb315e35b12b86822b67066eacf58"}
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{"name": "perf-reasoning-2", "passed": true, "finish": "length", "usage": {"prompt_tokens": 79, "total_tokens": 2127, "completion_tokens": 2048, "completion_tokens_details": {"reasoning_tokens": 2048}}, "ttft_s": 0.07260531799693126, "elapsed_s": 16.818446777993813, "decode_tps": 122.23930370354654, "max_stream_gap_s": 0.01878616500471253, "events": 934, "content": "", "reasoning": "We need answer user: \"Explain and prove why Dijkstra works with nonnegative weights. Include a counterexample with negative edges and compare Bellman-Ford.\" Need provide explanation, proof, counterexample, comparison. Need final only. Need be thorough. Let's plan.\n\nWe need explain Dijkstra algorithm: single-source shortest paths in directed/undirected graph with nonnegative edge weights. Greedy: maintain dist labels, priority queue, settled set S. Initially dist(s)=0, others infinity. Repeatedly extract min unsettled vertex u, settle it, relax outgoing edges.\n\nWhy nonnegative weights matter: Once vertex u has minimum tentative distance among unsettled, no unsettled vertex can provide a shorter path to u because any path from s to u through unsettled vertex v has prefix to v with length at least dist[v] (or at least dist[u]?) Need formal proof.\n\nProof by induction: invariant: for each settled vertex x, dist[x]=δ(s,x) true shortest distance. Also for each unsettled vertex v, dist[v] is length of shortest path from s to v whose internal vertices are settled? Or upper bound. Need prove extraction min is correct.\n\nStandard proof: Let u be min tentative among unsettled. Suppose there is a shorter path P from s to u. Let y be first unsettled vertex on P (u itself if all previous settled? Actually if P shorter than dist[u], since s settled, there is first unsettled vertex y on P; let x be predecessor of y on P, settled. When x was settled, edge (x,y) relaxed, so dist[y] ≤ length(P[s..y]). Since weights nonnegative, length(P[s..y]) ≤ length(P) < dist[u]. Thus dist[y] < dist[u], contradicting u min. This proof uses nonnegative weights to ensure prefix length ≤ full path length. If negative edges, prefix can be longer than full path, so contradiction fails.\n\nAlternative proof: Dijkstra's invariant: settled vertices have final distances. For unsettled, dist[v] is shortest path using only settled internal vertices. When extract min u, any path to u not using only settled vertices has first unsettled vertex y; prefix to y has length ≤ total path due nonnegative, and dist[y] ≤ prefix, so dist[y] ≤ path length. Since u min, dist[u] ≤ dist[y] ≤ path length. Thus dist[u] is shortest.\n\nNeed include counterexample with negative edges. Need show Dijkstra fails. Classic: s->a weight 1, s->b weight 2, a->b weight -2. Shortest s->b = -1 via a, but Dijkstra settles a (dist 1) then b? Let's simulate: initial dist s=0, a=1, b=2. Extract a (1), relax a->b: dist b = -1. Then extract b (-1). Actually Dijkstra would find correct if b not settled before a. Need counterexample where Dijkstra settles vertex too early due negative edge from unsettled vertex. Need graph where vertex v has small tentative but later negative edge from another unsettled vertex reduces it after v settled. Example: s->a=1, s->b=2, b->a=-2. Shortest to a = 0 via b. Dijkstra: dist a=1, b=2. Extract a (1) settle. Then extract b (2), relax b->a gives -1? Wait 2-2=0, but a already settled, Dijkstra doesn't update settled. Final dist a=1, wrong (0). This works. Need ensure nonnegative? Negative edge b->a. Dijkstra picks a before b because 1<2, but path s-b-a length 0 shorter. Good. Could also use s->a=2, s->b=3, b->a=-2 => shortest a=1, Dijkstra settles a=2 wrong. But first example fine. Need maybe directed graph. If undirected negative edge? Dijkstra fails too. Use directed.\n\nNeed compare Bellman-Ford: handles negative weights (no negative cycles reachable from source) by relaxing all edges V-1 times; detects negative cycles. Complexity O(VE), slower than Dijkstra O((V+E) log V) with binary heap or O(E+V log V). Dijkstra requires nonnegative weights; BF can handle negative edges but not negative cycles (shortest paths undefined). BF dynamic programming: after k iterations, dist[v] shortest path with at most k edges. Proof by induction. If negative cycle reachable, distances can decrease indefinitely; BF detects if an edge can still relax on Vth iteration.\n\nNeed maybe mention Dijkstra with negative edges can fail even if no negative cycles. Counterexample no negative cycle. Compare: Dijkstra greedy local optimal; BF exhaustive relaxation. Dijkstra cannot recover from settled vertex; BF can update any vertex repeatedly.\n\nNeed maybe include pseudocode? Could include. Need proof rigorous. Need maybe discuss zero weights okay. Nonnegative includes zero. Need mention if negative edges but no negative cycles, Dijkstra may still work in some cases but not guaranteed. Need maybe mention Johnson reweighting? Not necessary.\n\nNeed final answer structured: 1. Algorithm. 2. Why nonnegative weights. 3. Proof. 4. Counterexample. 5. Bellman-Ford comparison. Maybe include table.\n\nLet's craft final with definitions:\nGraph G=(V,E), weight w:E→R, source s. δ(s,v) shortest path distance. Dijkstra maintains d[v]. S settled.\n\nPseudocode:\nd[s]=0; d[v]=∞; PQ all vertices; S=∅\nwhile PQ not empty:\n u=extract-min(PQ)\n S.add(u)\n for (u,v) in E:\n if d[v] > d[u]+w(u,v): d[v]=d[u]+w(u,v); decrease-key\n\nProof:\nLemma: At start of each iteration, for every settled x, d[x]=δ(s,x). For every unsettled v, d[v] is length of shortest s-v path whose internal vertices are in S (or ∞ if none). Actually after relaxing from settled vertices, d[v] equals min over paths from s to v with all internal vertices settled? Need prove. Initially S empty: d[s]=0 path no internal; others ∞. When settle u, relax edges: for any unsettled v, new paths with internal vertices S∪{u} either old (internal S) or path to u (internal S) + edge u-v. Since d[u]=δ(s,u) and path to u internal S? Need careful: d[u] is shortest path with internal S, but if u settled, d[u]=δ(s,u). For v, d[v] updated to min(old, d[u]+w(u,v)). This gives shortest path with internal S∪{u}. Good.\n\nThen correctness of extracting u: Let u be min d among unsettled. Need show d[u]=δ(s,u). Let P be any shortest s-u path. If all internal vertices settled, then by invariant d[u] ≤ length(P)=δ(s,u); and d[u] always upper bound so equality. If some internal unsettled, let y be first unsettled vertex on P, x predecessor settled (or s). Let P_y prefix s to y. By invariant d[y] ≤ length(P_y). Since weights nonnegative, length(P_y) ≤ length(P)=δ(s,u). Thus d[y] ≤ δ(s,u). If δ(s,u)<d[u], then d[y] < d[u], contradicting u min. Therefore δ(s,u)≥d[u]. Since d[u] is length of some path, d[u]≥δ(s,u). Equality. This proof maybe simpler. Need ensure if y=u? If u is first unsettled, then d[u] ≤ length(P_y)=δ(s,u) directly. If δ<d[u] impossible. But contradiction works.\n\nAlternative proof by contradiction: Suppose u extracted with d[u]>δ(s,u). Let P shortest path. Let y first unsettled on P. Let x predecessor. Since x settled, edge relaxed when x settled, so d[y] ≤ length(P prefix to y). Nonnegative => length(prefix) ≤ length(P) < d[u]. So d[y] < d[u], contradiction. This is concise. Need mention d[y] may have been updated later? It is at most that value at all times after relaxation, so at extraction time still ≤. Good.\n\nNeed maybe discuss negative weights break proof: prefix can be longer than full path, so d[y] may not be < d[u]. In counterexample, shortest path to a is s-b-a length 0; first unsettled y=b? Let's map: Dijkstra extracts a first. Shortest path to a: s->b->a. First unsettled vertex on path is b (since s settled, a target unsettled? Actually path to a: s (settled), b (unsettled), a (target unsettled). First unsettled y=b. Prefix length s-b=2, full path length 0. Nonnegative condition fails: prefix 2 > full 0. d[b]=2, not < d[a]=1, so no contradiction. Dijkstra settles a at 1, later b relaxes to 0 but a settled. Good.\n\nCounterexample details:\nVertices s,a,b. Edges: s→a weight 1, s→b weight 2, b→a weight -2. No negative cycle. Dijkstra:\ninit d[s]=0, d[a]=1, d[b]=2.\nextract s, relax", "sha256": "eec62c20975cfeaada4ad14ef0f726db52eaff6b498dcbbf3f5f515c2c5725c8"}
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{"name": "long-context-0", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 125995, "total_tokens": 126111, "completion_tokens": 116, "completion_tokens_details": {"reasoning_tokens": 96}}, "ttft_s": 14.42599186499865, "elapsed_s": 15.14422588799789, "decode_tps": 160.11494348287312, "max_stream_gap_s": 0.01879984400147805, "events": 41, "content": "\n\nNORTH-49273\nSOUTH-18362", "reasoning": "The user is asking me to provide the northern and southern access codes that are embedded in the data. Let me find them:\n\n- The northern access code is NORTH-49273 (found between Item 000019 and Item 000021)\n- The southern access code is SOUTH-18362 (found between Item 002499 and Item 002501)\n", "sha256": "e054eb4577e203d59776c06555ff8dff56d50e49389606fa8a7344884f985155"}
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{"name": "long-context-1", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 125995, "total_tokens": 126114, "completion_tokens": 119, "completion_tokens_details": {"reasoning_tokens": 99}}, "ttft_s": 0.7020562550023897, "elapsed_s": 1.4927438169979723, "decode_tps": 149.23720274818137, "max_stream_gap_s": 0.01888078500633128, "events": 45, "content": "\n\nNORTH-49273\nSOUTH-18362", "reasoning": "The user is asking me to provide both the northern and southern access codes from the data they've provided.\n\nLooking through the data, I can find:\n- \"The northern access code is NORTH-49273.\" (appears after Item 000019)\n- \"The southern access code is SOUTH-18362.\" (appears after Item 002499)\n\nThe user wants only these two codes.\n", "sha256": "109b3120d1bf2f56bd0c1ab331e7692f8a0a37b091eb2adb8d7a0a54731dba54"}
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{"name": "long-context-2", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 125995, "total_tokens": 126114, "completion_tokens": 119, "completion_tokens_details": {"reasoning_tokens": 99}}, "ttft_s": 0.7015097360053915, "elapsed_s": 1.4736580300013884, "decode_tps": 152.82038556263618, "max_stream_gap_s": 0.018826871004421264, "events": 44, "content": "\n\nNORTH-49273\nSOUTH-18362", "reasoning": "The user is asking me to provide both the northern and southern access codes that are embedded in the data.\n\nLooking through the data, I can find:\n- \"The northern access code is NORTH-49273.\" (appears after Item 000019)\n- \"The southern access code is SOUTH-18362.\" (appears after Item 002499)\n\nThe user wants only these two codes.\n", "sha256": "1275326ebe3452473a77c76ba9ec5b91f06f8896ffd6de203abf1f9129842a90"}
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{"name": "long-context-image", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 111670, "total_tokens": 111902, "completion_tokens": 232, "completion_tokens_details": {"reasoning_tokens": 187}}, "ttft_s": 12.815331379999407, "elapsed_s": 14.372689276002347, "decode_tps": 148.32813998174495, "max_stream_gap_s": 0.01881139999750303, "events": 87, "content": "\n\n- **Northern access code:** NORTH-49273\n- **Southern access code:** SOUTH-18362\n- **Invoice verification code:** SPARK-82741", "reasoning": "The user wants three pieces of information: the northern access code, the southern access code, and the invoice verification code. These are embedded in the text and the image.\n\nScanning the text: \"The northern access code is NORTH-49273.\" appears after Item 000019. \"The southern access code is SOUTH-18362.\" appears after Item 002499.\n\nFrom the image: \"Verification: SPARK-82741\".\n\nSo the answer is straightforward extraction. No computation needed. I'll present all three clearly. The reasoning is in English matching the user's English request.\n\nI need to make sure I read the codes correctly: NORTH-49273, SOUTH-18362, SPARK-82741. Yes.\n\nI'll provide a concise complete response.\n", "sha256": "4b7c8fb1d0d992dda6a5a680074a3aa037b1c33fd732b7315720e712693c2335"}
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{"name": "queued-0", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 55, "total_tokens": 119, "completion_tokens": 64, "completion_tokens_details": {"reasoning_tokens": 58}}, "ttft_s": 0.08533696200174745, "elapsed_s": 0.4814725750038633, "decode_tps": 159.0364459346489, "max_stream_gap_s": 0.018437628001265693, "events": 22, "content": "\n\n731", "reasoning": "The user wants me to compute 43 * 17 and reply with only the integer.\n\n43 * 17 = 43 * 10 + 43 * 7 = 430 + 301 = 731\n", "sha256": "c775e82fbe7367311970d698f4880b3e86da93aa21640d45d95ee9475e335166"}
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{"name": "queued-1", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 55, "total_tokens": 98, "completion_tokens": 43, "completion_tokens_details": {"reasoning_tokens": 37}}, "ttft_s": 0.5489882670008228, "elapsed_s": 0.8192126439971616, "decode_tps": 155.42639219617496, "max_stream_gap_s": 0.018371916994510684, "events": 15, "content": "\n\n748", "reasoning": "44 * 17 = 44 * 10 + 44 * 7 = 440 + 308 = 748\n", "sha256": "577bfda055d6b1f136ea30fd3c42b3954036dd654d2eb7cace48396c49aa115a"}
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{"name": "queued-2", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 55, "total_tokens": 119, "completion_tokens": 64, "completion_tokens_details": {"reasoning_tokens": 58}}, "ttft_s": 0.8859058559974073, "elapsed_s": 1.2823282210010802, "decode_tps": 158.92140696808642, "max_stream_gap_s": 0.018409249001706485, "events": 22, "content": "\n\n765", "reasoning": "The user wants me to compute 45 * 17 and reply with only the integer.\n\n45 * 17 = 45 * 10 + 45 * 7 = 450 + 315 = 765\n", "sha256": "4e0dac459752edb516d9c610865ec672d6805ddc71af097d21b28f7c53179b47"}
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{"name": "queued-3", "passed": true, "finish": "stop", "usage": {"prompt_tokens": 55, "total_tokens": 119, "completion_tokens": 64, "completion_tokens_details": {"reasoning_tokens": 58}}, "ttft_s": 1.3495687850008835, "elapsed_s": 1.743830876002903, "decode_tps": 159.79218250449873, "max_stream_gap_s": 0.018336048000492156, "events": 23, "content": "\n\n782", "reasoning": "The user wants me to compute 46 * 17 and reply with just the integer.\n\n46 * 17 = 46 * 10 + 46 * 7 = 460 + 322 = 782\n", "sha256": "fbb92f72869a68308179711e06612346b886a880c1f5fbd390eb0731790dbd0c"}
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