{
  "model": "gpt-oss-20b",
  "timestamp": "2026-02-22T14:37:14Z",
  "hardware": "RTX 4090 (24GB)",
  "concurrency_levels": [
    {
      "concurrency": 1,
      "total_time_ms": 3218.6,
      "primary": [
        {
          "role": "primary_turn_1",
          "ttft_ms": 64.5,
          "response_time_ms": 844.4,
          "tokens_generated": 107,
          "tokens_per_sec": 126.7,
          "content_preview": "```python\nfrom fastapi import FastAPI, HTTPException, status\nfrom pydantic import BaseModel\nfrom uuid import uuid4\n\napp = FastAPI()\n\nclass UserCreate(BaseModel):\n    name: str\n    email: str\n    age: int\n\nclass User(UserCreate):\n    id: str\n\n@app.post(\"/users\", status_code=status.HTTP_201_CREATED, response_model=User)\ndef create_user(user: UserCreate):\n    new_user = User(id=str(uuid4()), **user.dict())\n    return new_user\n```",
          "reasoning_preview": "We need to produce a complete runnable FastAPI code with a POST /users endpoint. Use Pydantic model for request body. Return 201 with created user including generated UUID id. Should include import statements, FastAPI app, model definitions, endpoint, and maybe a simple in-memory store. Provide code only. No commentary. Ensure correct status code. Use uuid4. Use Response or return dict. Use status_code=201. Provide code."
        },
        {
          "role": "primary_turn_2",
          "ttft_ms": 89.0,
          "response_time_ms": 756.6,
          "tokens_generated": 76,
          "tokens_per_sec": 100.5,
          "content_preview": "```python\nfrom pydantic import BaseModel, validator, conint, constr\n\nclass UserCreate(BaseModel):\n    name: constr(min_length=1)\n    email: constr(regex=r\"^[^@]+@[^@]+\\.[^@]+$\")\n    age: conint(ge=0, le=150)\n\n    @validator(\"email\")\n    def email_must_contain_at_and_dot(cls, v: str) -> str:\n        if \"@\" not in v or \".\" not in v.split(\"@\", 1)[1]:\n            raise ValueError(\"email must contain '@' and a dot after '@'\")\n        return v\n```",
          "reasoning_preview": "We need to provide updated Pydantic model only. So we need to modify UserCreate model to include validators. Use constr, conint, validator. Provide code snippet with updated model."
        },
        {
          "role": "primary_turn_3",
          "ttft_ms": 85.0,
          "response_time_ms": 1617.3,
          "tokens_generated": 244,
          "tokens_per_sec": 150.9,
          "content_preview": "```python\n# Module\u2011level storage\nusers = {}\n\n# New endpoint\n@app.get(\"/users/{user_id}\")\ndef get_user(user_id: str):\n    user = users.get(user_id)\n    if not user:\n        raise HTTPException(status_code=404, detail=\"User not found\")\n    return user\n```",
          "reasoning_preview": "We need to provide only the new endpoint and the storage dict. The code should be minimal. The storage dict: users = {}. The new endpoint: GET /users/{user_id}. Should return 404 with {\"detail\": \"User not found\"} if not found. Should return the user. Use FastAPI. Should import status. Should use HTTPException. Provide only the new endpoint and storage dict. So output:\n\n```\nusers = {}\n\n@app.get(\"/users/{user_id}\")\ndef get_user(user_id: str):\n    user = users.get(user_id)\n    if not user:\n        "
        }
      ],
      "side_tasks": []
    },
    {
      "concurrency": 2,
      "total_time_ms": 7121.6,
      "primary": [
        {
          "role": "primary_turn_1",
          "ttft_ms": 139.3,
          "response_time_ms": 2872.7,
          "tokens_generated": 140,
          "tokens_per_sec": 48.7,
          "content_preview": "```python\n# main.py\nfrom uuid import uuid4\nfrom fastapi import FastAPI, HTTPException\nfrom fastapi.responses import JSONResponse\nfrom pydantic import BaseModel, EmailStr, Field\n\napp = FastAPI()\n\nclass UserCreate(BaseModel):\n    name: str\n    email: EmailStr\n    age: int = Field(..., ge=0)\n\nclass User(UserCreate):\n    id: str\n\n@app.post(\"/users\", status_code=201, response_model=User)\nasync def create_user(user: UserCreate):\n    new_user = User(id=str(uuid4()), **user.dict())\n    return JSONRespon",
          "reasoning_preview": "We need to produce a complete runnable FastAPI code with a POST /users endpoint that accepts JSON body with fields name, email, age. Use Pydantic model for validation. Return 201 with created user including generated UUID id. Provide complete code. Should include imports, FastAPI app, Pydantic models, endpoint, maybe in-memory storage. Use uuid4. Return JSON with id, name, email, age. Use status_code=201. Use Response or return dict. Provide code. Also include main guard. Provide minimal comment"
        },
        {
          "role": "primary_turn_2",
          "ttft_ms": 130.9,
          "response_time_ms": 3174.9,
          "tokens_generated": 315,
          "tokens_per_sec": 99.2,
          "content_preview": "```python\nfrom pydantic import BaseModel, Field, validator\n\nclass UserCreate(BaseModel):\n    name: str = Field(\n        ...,\n        min_length=1,\n        description=\"Name must not be empty\"\n    )\n    email: str = Field(\n        ...,\n        description=\"Email must contain '@' and a dot after '@'\"\n    )\n    age: int = Field(\n        ...,\n        ge=0,\n        le=150,\n        description=\"Age must be between 0 and 150\"\n    )\n\n    @validator(\"email\")\n    def _validate_email(cls, v: str) -> str:\n ",
          "reasoning_preview": "We need to provide updated Pydantic model only. The user wants email format validation: must contain @ and a dot after @. Age range 0-150. Name non-empty. Return proper 422 error responses with clear messages. Show updated Pydantic model only.\n\nWe need to modify UserCreate model accordingly. Use constr, EmailStr? But EmailStr already validates email format. But they want custom validation: must contain @ and dot after @. We can use regex or custom validator. Use EmailStr? It already ensures emai"
        },
        {
          "role": "primary_turn_3",
          "ttft_ms": 113.9,
          "response_time_ms": 1073.8,
          "tokens_generated": 148,
          "tokens_per_sec": 137.8,
          "content_preview": "```python\n# storage\nusers_db: dict[str, User] = {}\n\n# new endpoint\n@app.get(\"/users/{user_id}\", response_model=User)\nasync def get_user(user_id: str):\n    user = users_db.get(user_id)\n    if not user:\n        raise HTTPException(status_code=404, detail=\"User not found\")\n    return user\n```",
          "reasoning_preview": "We need to provide only the new endpoint and the storage dict. The storage dict is module-level. The new endpoint should be GET /users/{user_id}. It should return 404 with {\"detail\": \"User not found\"} if ID not exists. Use FastAPI. Should use the same User model? The code earlier had User model. We can assume we have User model defined. Provide the dict and endpoint. Provide only the new endpoint and storage dict. So output code snippet with storage dict and endpoint. Use from fastapi import Fas"
        }
      ],
      "side_tasks": [
        {
          "role": "S1_docstring",
          "ttft_ms": 148.0,
          "response_time_ms": 4525.7,
          "tokens_generated": 268,
          "tokens_per_sec": 59.2,
          "verified": true,
          "keywords_found": [
            "sorted",
            "index",
            "target",
            "Args",
            "Returns"
          ],
          "keywords_missing": [],
          "content_preview": "```python\ndef binary_search(arr, target):\n    \"\"\"\n    Perform a binary search for a target value in a sorted list.\n\n    Binary search is an efficient algorithm for finding the position of a\n    target value within a sorted sequence.  It repeatedly divides the\n    search interval in half, comparing the target to the middle element.\n    If the target is found, the function returns its index; otherwise\n    it returns ``-1`` to indicate that the target is not present.\n\n    Args:\n        arr (Sequenc",
          "reasoning_preview": "We need to write a Google-style docstring for the function binary_search. The function takes arr and target. It returns index or -1. Should describe parameters, returns, raises, examples. Provide docstring only. Let's craft.\n\nAlso mention arr must be sorted. Provide type hints? Not needed. Provide description. Let's produce."
        }
      ]
    },
    {
      "concurrency": 3,
      "total_time_ms": 7408.0,
      "primary": [
        {
          "role": "primary_turn_1",
          "ttft_ms": 150.4,
          "response_time_ms": 3881.9,
          "tokens_generated": 174,
          "tokens_per_sec": 44.8,
          "content_preview": "```python\n# main.py\nfrom uuid import uuid4\nfrom typing import Dict\n\nfrom fastapi import FastAPI, HTTPException\nfrom fastapi.responses import JSONResponse\nfrom pydantic import BaseModel, EmailStr\n\napp = FastAPI()\n\nclass UserCreate(BaseModel):\n    name: str\n    email: EmailStr\n    age: int\n\nclass User(UserCreate):\n    id: str\n\n# In\u2011memory store (for demo purposes)\nusers: Dict[str, User] = {}\n\n@app.post(\"/users\", status_code=201, response_model=User)\nasync def create_user(user: UserCreate):\n    use",
          "reasoning_preview": "We need to produce a complete runnable FastAPI code with a POST /users endpoint, using Pydantic model for validation. It should accept JSON body with fields name, email, age. It should generate a UUID id and return 201 with created user including id. Provide complete code. Should include imports, FastAPI app, Pydantic models, endpoint, maybe a simple in-memory store. Use uuid4. Return status code 201. Use Response or return dict. Use status_code=201. Provide code. Also include main guard. Provid"
        },
        {
          "role": "primary_turn_2",
          "ttft_ms": 148.5,
          "response_time_ms": 2143.5,
          "tokens_generated": 116,
          "tokens_per_sec": 54.1,
          "content_preview": "```python\nfrom pydantic import BaseModel, EmailStr, validator, Field\n\nclass UserCreate(BaseModel):\n    name: str = Field(..., min_length=1, description=\"Non\u2011empty name\")\n    email: EmailStr\n    age: int = Field(..., ge=0, le=150, description=\"Age must be between 0 and 150\")\n\n    @validator(\"email\")\n    def email_must_have_dot_after_at(cls, v: str) -> str:\n        if \"@\" not in v or \".\" not in v.split(\"@\", 1)[1]:\n            raise ValueError(\"email must contain '@' and a dot after '@'\")\n        r",
          "reasoning_preview": "We need to provide updated Pydantic model only. Must include email format validation: must contain @ and a dot after @. Age range 0-150. Name non-empty. Return proper 422 error responses with clear messages. Show updated Pydantic model only. So we need to modify UserCreate model accordingly. Use pydantic validators. Provide code snippet."
        },
        {
          "role": "primary_turn_3",
          "ttft_ms": 80.8,
          "response_time_ms": 1382.3,
          "tokens_generated": 191,
          "tokens_per_sec": 138.2,
          "content_preview": "```python\n# storage\nusers: Dict[str, User] = {}\n\n# new endpoint\n@app.get(\"/users/{user_id}\", response_model=User)\nasync def get_user(user_id: str):\n    user = users.get(user_id)\n    if not user:\n        raise HTTPException(status_code=404, detail=\"User not found\")\n    return user\n```",
          "reasoning_preview": "We need to show only the new endpoint and the storage dict. The storage dict is already defined earlier as `users: Dict[str, User] = {}`. But we need to show only the new endpoint and the storage dict. So we should provide code snippet containing the dict and the new endpoint. Should include imports? The user asked \"Show only the new endpoint and the storage dict.\" So we can show:\n\n```\nusers: Dict[str, User] = {}\n\n@app.get(\"/users/{user_id}\", response_model=User)\nasync def get_user(user_id: str)"
        }
      ],
      "side_tasks": [
        {
          "role": "S1_docstring",
          "ttft_ms": 150.0,
          "response_time_ms": 5450.2,
          "tokens_generated": 270,
          "tokens_per_sec": 49.5,
          "verified": true,
          "keywords_found": [
            "sorted",
            "index",
            "target",
            "Args",
            "Returns"
          ],
          "keywords_missing": [],
          "content_preview": "```python\ndef binary_search(arr, target):\n    \"\"\"\n    Perform a binary search for ``target`` in a sorted list ``arr``.\n\n    The function assumes that ``arr`` is sorted in ascending order.  It\n    returns the index of ``target`` if it is present; otherwise it\n    returns ``-1`` to indicate that the element was not found.\n\n    Args:\n        arr (Sequence[int] | Sequence[float] | Sequence[str]): A sorted\n            sequence of comparable elements.  The function works with any\n            type that",
          "reasoning_preview": "We need to write a Google-style docstring for the function binary_search. The function takes arr and target. It returns index or -1. Should mention sorted array assumption. Provide description, arguments, returns, examples, maybe raises. Provide type hints? Not necessary. Just docstring. Use triple quotes. Provide description, Args, Returns, Example. Use Google style: short description, blank line, Args: param type description, Returns: type description, Example: code. Provide details. Let's cra"
        },
        {
          "role": "S2_unit_tests",
          "ttft_ms": 159.0,
          "response_time_ms": 5768.6,
          "tokens_generated": 281,
          "tokens_per_sec": 48.7,
          "verified": true,
          "keywords_found": [
            "def test_",
            "pytest",
            "assert"
          ],
          "keywords_missing": [],
          "content_preview": "",
          "reasoning_preview": "We need to write 3 pytest unit tests for the function calculate_discount. The function has a bug: it raises ValueError but should raise ValueError? Actually ValueError is spelled correctly. But the function uses ValueError, not ValueError? Wait: raise ValueError(\"Discount must be 0-100\") - ValueError is a built-in exception. So it's fine.\n\nWe need tests: normal case, edge case (0% and 100%), and invalid input.\n\nWe need to import the function. We'll write tests in a file, maybe test_discount.py. "
        }
      ]
    },
    {
      "concurrency": 5,
      "total_time_ms": 8245.9,
      "primary": [
        {
          "role": "primary_turn_1",
          "ttft_ms": 289.5,
          "response_time_ms": 6448.1,
          "tokens_generated": 222,
          "tokens_per_sec": 34.4,
          "content_preview": "```python\n# main.py\nfrom uuid import uuid4\n\nfrom fastapi import FastAPI, status\nfrom pydantic import BaseModel\n\napp = FastAPI()\n\n\nclass UserCreate(BaseModel):\n    name: str\n    email: str\n    age: int\n\n\nclass User(UserCreate):\n    id: str\n\n\n@app.post(\"/users\", response_model=User, status_code=status.HTTP_201_CREATED)\ndef create_user(user: UserCreate) -> User:\n    \"\"\"Create a user and return it with a generated UUID.\"\"\"\n    return User(id=str(uuid4()), **user.dict())\n```\n\n**Run it**\n\n```bash\nuvic",
          "reasoning_preview": "We need to produce a complete runnable FastAPI code with a POST /users endpoint. Use Pydantic model for request body: name, email, age. On creation, generate UUID id, return 201 with created user. Should include status code 201. Should return JSON with id, name, email, age. Use FastAPI, uvicorn. Provide code. Should be minimal but complete. Use from fastapi import FastAPI, status, HTTPException. Use pydantic BaseModel. Use uuid4. Provide main function. Provide example. Provide code. Should be ru"
        },
        {
          "role": "primary_turn_2",
          "ttft_ms": 150.7,
          "response_time_ms": 973.2,
          "tokens_generated": 76,
          "tokens_per_sec": 78.1,
          "content_preview": "```python\nfrom pydantic import BaseModel, validator, constr, conint\n\nclass UserCreate(BaseModel):\n    name: constr(min_length=1)          # non\u2011empty\n    email: str\n    age: conint(ge=0, le=150)           # 0\u2011150 inclusive\n\n    @validator(\"email\")\n    def email_must_be_valid(cls, v: str) -> str:\n        if \"@\" not in v or \".\" not in v.split(\"@\")[-1]:\n            raise ValueError(\"email must contain '@' and a dot after '@'\")\n        return v\n```",
          "reasoning_preview": "We need to provide updated Pydantic model only. So we need to modify UserCreate model with validators. Use constr, conint, validator. Provide code snippet."
        },
        {
          "role": "primary_turn_3",
          "ttft_ms": 93.6,
          "response_time_ms": 824.5,
          "tokens_generated": 94,
          "tokens_per_sec": 114.0,
          "content_preview": "```python\n# storage\nusers_db: dict[str, User] = {}\n\n# new endpoint\n@app.get(\"/users/{user_id}\", response_model=User)\ndef get_user(user_id: str) -> User:\n    user = users_db.get(user_id)\n    if not user:\n        raise HTTPException(status_code=404, detail=\"User not found\")\n    return user\n```",
          "reasoning_preview": "We need to provide only the new endpoint and the storage dict. The code should be minimal but correct. The storage dict: maybe `users_db: dict[str, User] = {}`. The new endpoint: `@app.get(\"/users/{user_id}\")`. It should return 404 with detail if not found. Use `HTTPException`. Should return the user. Provide only the new endpoint and storage dict. So output code snippet with those parts."
        }
      ],
      "side_tasks": [
        {
          "role": "S1_docstring",
          "ttft_ms": 279.1,
          "response_time_ms": 5454.4,
          "tokens_generated": 245,
          "tokens_per_sec": 44.9,
          "verified": true,
          "keywords_found": [
            "sorted",
            "index",
            "target",
            "Args",
            "Returns"
          ],
          "keywords_missing": [],
          "content_preview": "```python\ndef binary_search(arr, target):\n    \"\"\"\n    Perform a binary search for a target value in a sorted list.\n\n    Binary search repeatedly divides the search interval in half.  If the\n    target value is found, the index of the target is returned; otherwise\n    ``-1`` is returned to indicate that the target is not present.\n\n    Args:\n        arr: A list of comparable elements that is sorted in ascending order.\n        target: The value to search for.  It must be comparable to the\n         ",
          "reasoning_preview": "We need to write a Google-style docstring for the function binary_search. The function takes arr and target. It returns index or -1. Should include description, arguments, returns, maybe raises. Should be clear. Provide only docstring. Let's craft.\n\nWe need to include description: \"Performs binary search on sorted array.\" Then Args: arr: list of comparable items sorted ascending. target: item to search. Returns: int index or -1. Also mention time complexity O(log n). Provide examples maybe. But "
        },
        {
          "role": "S2_unit_tests",
          "ttft_ms": 278.8,
          "response_time_ms": 6796.8,
          "tokens_generated": 377,
          "tokens_per_sec": 55.5,
          "verified": false,
          "keywords_found": [
            "pytest",
            "assert"
          ],
          "keywords_missing": [
            "def test_"
          ],
          "content_preview": "",
          "reasoning_preview": "We need to write 3 pytest unit tests for the function calculate_discount. The function has a bug: it raises ValueError, but correct exception is ValueError? Actually ValueError is spelled ValueError, but correct is ValueError? In Python it's ValueError? Actually it's ValueError? Wait, the built-in exception is ValueError, not ValueError. The code uses ValueError, which is not defined. So tests will fail. But we should test that it raises ValueError. But since it's not defined, it will raise Name"
        },
        {
          "role": "S3_find_bug",
          "ttft_ms": 289.2,
          "response_time_ms": 6806.2,
          "tokens_generated": 322,
          "tokens_per_sec": 47.3,
          "verified": false,
          "keywords_found": [
            "ceil"
          ],
          "keywords_missing": [
            "last page",
            "remainder"
          ],
          "content_preview": "",
          "reasoning_preview": "We need to find bug. The function calculates total_pages incorrectly: should be ceil division, not floor. For example items length 10, page_size 3 => total_pages = 10//3 = 3, but there are 4 pages (3,3,3,1). So page_num > total_pages incorrectly rejects page 4. Also if items empty, total_pages=0, page_num 1 > 0 returns [], correct. But also if page_num exactly total_pages but there are items left? Actually if items length 9, page_size 3 => total_pages=3, correct. But if items length 10, page_siz"
        },
        {
          "role": "S4_async_convert",
          "ttft_ms": 290.0,
          "response_time_ms": 2710.6,
          "tokens_generated": 101,
          "tokens_per_sec": 37.3,
          "verified": true,
          "keywords_found": [
            "async def",
            "await",
            "aiofiles"
          ],
          "keywords_missing": [],
          "content_preview": "```python\nimport json\nimport aiofiles\n\nasync def read_config(path: str) -> dict:\n    async with aiofiles.open(path, mode=\"r\") as f:\n        content = await f.read()\n    return json.loads(content)\n```",
          "reasoning_preview": "We need to convert to async using aiofiles. Provide only async version. Should import aiofiles and json. Use async with aiofiles.open. Use async def read_config. Use await f.read() then json.loads. Or use json.load with file object? aiofiles returns file object that supports read. So:\n\nasync def read_config(path: str) -> dict:\n    async with aiofiles.open(path, mode='r') as f:\n        content = await f.read()\n    return json.loads(content)\n\nAlso need to import aiofiles. Provide only async versio"
        }
      ]
    }
  ]
}