fastapi_14186

{"status": "ok", "stdout": "fastapi/dependencies/utils.py:51:from fastapi._compat.shared import annotation_is_pydantic_v1\nfastapi/dependencies/utils.py:79:from .. import temp_pydantic_v1_params\nfastapi/dependencies/utils.py:323:            param_details.field.field_info, (params.Body, temp_pydantic_v1_params.Body)\nfastapi/dependencies/utils.py:392:                    temp_pydantic_v1_params.Param,\nfastapi/dependencies/utils.py:394:                    temp_pydantic_v1_params.Body,\nfastapi/dependencies/utils.py:483:            if annotation_is_pydantic_v1(use_annotation):\nfastapi/dependencies/utils.py:484:                field_info = temp_pydantic_v1_params.Body(\nfastapi/dependencies/utils.py:500:                field_info, (params.Path, temp_pydantic_v1_params.Path)\nfastapi/dependencies/utils.py:506:            isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param))\nfastapi/dependencies/utils.py:515:        if isinstance(field_info, (params.Form, temp_pydantic_v1_params.Form)):\nfastapi/dependencies/utils.py:534:        elif isinstance(field_info, (params.Query, temp_pydantic_v1_params.Query)):\nfastapi/dependencies/utils.py:761:            isinstance(field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:827:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:839:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:888:        isinstance(first_field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:906:            isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:913:            and isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:1020:        isinstance(f.field_info, temp_pydantic_v1_params.File)\nfastapi/dependencies/utils.py:1023:       

{"status": "ok", "stdout": "fastapi/dependencies/utils.py:79:from .. import temp_pydantic_v1_params\nfastapi/dependencies/utils.py:323:            param_details.field.field_info, (params.Body, temp_pydantic_v1_params.Body)\nfastapi/dependencies/utils.py:392:                    temp_pydantic_v1_params.Param,\nfastapi/dependencies/utils.py:394:                    temp_pydantic_v1_params.Body,\nfastapi/dependencies/utils.py:484:                field_info = temp_pydantic_v1_params.Body(\nfastapi/dependencies/utils.py:500:                field_info, (params.Path, temp_pydantic_v1_params.Path)\nfastapi/dependencies/utils.py:506:            isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param))\nfastapi/dependencies/utils.py:515:        if isinstance(field_info, (params.Form, temp_pydantic_v1_params.Form)):\nfastapi/dependencies/utils.py:534:        elif isinstance(field_info, (params.Query, temp_pydantic_v1_params.Query)):\nfastapi/dependencies/utils.py:761:            isinstance(field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:827:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:839:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:888:        isinstance(first_field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:906:            isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:913:            and isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:1020:        isinstance(f.field_info, temp_pydantic_v1_params.File)\nfastapi/dependencies/utils.py:1023:        BodyFieldInfo: Type[temp_pydantic_v1_params.Body] = temp_pydantic_v1_params.File  # type: ignore[no-redef]\nfastapi/dependencies/utils.py:1027:        isinstance(f.field_info, temp_pydant

{"status": "ok", "stdout": "fastapi/__init__.py\n", "stderr": "", "exit_code": 0}

{"status": "ok", "filepath": "fastapi/__init__.py", "content": "\"\"\"FastAPI framework, high performance, easy to learn, fast to code, ready for production\"\"\"\n\n__version__ = \"0.119.0\"\n\nfrom starlette import status as status\n\nfrom .applications import FastAPI as FastAPI\nfrom .background import BackgroundTasks as BackgroundTasks\nfrom .datastructures import UploadFile as UploadFile\nfrom .exceptions import HTTPException as HTTPException\nfrom .exceptions import WebSocketException as WebSocketException\nfrom .param_functions import Body as Body\nfrom .param_functions import Cookie as Cookie\nfrom .param_functions import Depends as Depends\nfrom .param_functions import File as File\nfrom .param_functions import Form as Form\nfrom .param_functions import Header as Header\nfrom .param_functions import Path as Path\nfrom .param_functions import Query as Query\nfrom .param_functions import Security as Security\nfrom .requests import Request as Request\nfrom .responses import Response as Response\nfrom .routing import APIRouter as APIRouter\nfrom .websockets import WebSocket as WebSocket\nfrom .websockets import WebSocketDisconnect as WebSocketDisconnect", "start_line": 1, "end_line": 25, "total_lines": 25, "is_truncated": false}

{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}}

{"status": "ok", "stdout": "fastapi/temp_pydantic_v1_params.py\n", "stderr": "", "exit_code": 0}

{"status": "ok", "filepath": "fastapi/temp_pydantic_v1_params.py", "content": "import warnings\nfrom typing import Any, Callable, Dict, List, Optional, Union\n\nfrom fastapi.openapi.models import Example\nfrom fastapi.params import ParamTypes\nfrom typing_extensions import Annotated, deprecated\n\nfrom ._compat.shared import PYDANTIC_VERSION_MINOR_TUPLE\nfrom ._compat.v1 import FieldInfo, Undefined\n\n_Unset: Any = Undefined\n\n\nclass Param(FieldInfo):  # type: ignore[misc]\n    in_: ParamTypes\n\n    def __init__(\n        self,\n        default: Any = Undefined,\n        *,\n        default_factory: Union[Callable[[], Any], None] = _Unset,\n        annotation: Optional[Any] = None,\n        alias: Optional[str] = None,\n        alias_priority: Union[int, None] = _Unset,\n        # TODO: update when deprecating Pydantic v1, import these types\n        # validation_alias: str | AliasPath | AliasChoices | None\n        validation_alias: Union[str, None] = None,\n        serialization_alias: Union[str, None] = None,\n        title: Optional[str] = None,\n        description: Optional[str] = None,\n        gt: Optional[float] = None,\n        ge: Optional[float] = None,\n        lt: Optional[float] = None,\n        le: Optional[float] = None,\n        min_length: Optional[int] = None,\n        max_length: Optional[int] = None,\n        pattern: Optional[str] = None,\n        regex: Annotated[\n            Optional[str],\n            deprecated(\n                \"Deprecated in FastAPI 0.100.0 and Pydantic v2, use `pattern` instead.\"\n            ),\n        ] = None,\n        discriminator: Union[str, None] = None,\n        strict: Union[bool, None] = _Unset,\n        multiple_of: Union[float, None] = _Unset,\n        allow_inf_nan: Union[bool, None] = _Unset,\n        max_digits: Union[int, None] = _Unset,\n        decimal_places: Union[int, None] = _Unset,\n        examples: Optional[List[Any]] = None,\n        example: Annotated[\n            Optional[Any],\n     

{"status": "ok", "filepath": "fastapi/_compat/shared.py", "content": "import sys\nimport types\nimport typing\nfrom collections import deque\nfrom dataclasses import is_dataclass\nfrom typing import (\n    Any,\n    Deque,\n    FrozenSet,\n    List,\n    Mapping,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n)\n\nfrom fastapi._compat import v1\nfrom fastapi.types import UnionType\nfrom pydantic import BaseModel\nfrom pydantic.version import VERSION as PYDANTIC_VERSION\nfrom starlette.datastructures import UploadFile\nfrom typing_extensions import Annotated, get_args, get_origin\n\n# Copy from Pydantic v2, compatible with v1\nif sys.version_info < (3, 9):\n    # Pydantic no longer supports Python 3.8, this might be incorrect, but the code\n    # this is used for is also never reached in this codebase, as it's a copy of\n    # Pydantic's lenient_issubclass, just for compatibility with v1\n    # TODO: remove when dropping support for Python 3.8\n    WithArgsTypes: Tuple[Any, ...] = ()\nelif sys.version_info < (3, 10):\n    WithArgsTypes: tuple[Any, ...] = (typing._GenericAlias, types.GenericAlias)  # type: ignore[attr-defined]\nelse:\n    WithArgsTypes: tuple[Any, ...] = (\n        typing._GenericAlias,  # type: ignore[attr-defined]\n        types.GenericAlias,\n        types.UnionType,\n    )  # pyright: ignore[reportAttributeAccessIssue]\n\nPYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nPYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n\n\nsequence_annotation_to_type = {\n    Sequence: list,\n    List: list,\n    list: list,\n    Tuple: tuple,\n    tuple: tuple,\n    Set: set,\n    set: set,\n    FrozenSet: frozenset,\n    frozenset: frozenset,\n    Deque: deque,\n    deque: deque,\n}\n\nsequence_types = tuple(sequence_annotation_to_type.keys())\n\nUrl: Type[Any]\n\n\n# Copy of Pydantic v2, compatible with v1\ndef lenient_issubclass(\n    cls: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...], None]

{"status": "ok", "filepath": "fastapi/_compat/v1.py", "content": "from copy import copy\nfrom dataclasses import dataclass, is_dataclass\nfrom enum import Enum\nfrom typing import (\n    Any,\n    Callable,\n    Dict,\n    List,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n)\n\nfrom fastapi._compat import shared\nfrom fastapi.openapi.constants import REF_PREFIX as REF_PREFIX\nfrom fastapi.types import ModelNameMap\nfrom pydantic.version import VERSION as PYDANTIC_VERSION\nfrom typing_extensions import Literal\n\nPYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nPYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n# Keeping old \"Required\" functionality from Pydantic V1, without\n# shadowing typing.Required.\nRequiredParam: Any = Ellipsis\n\nif not PYDANTIC_V2:\n    from pydantic import BaseConfig as BaseConfig\n    from pydantic import BaseModel as BaseModel\n    from pydantic import ValidationError as ValidationError\n    from pydantic import create_model as create_model\n    from pydantic.class_validators import Validator as Validator\n    from pydantic.color import Color as Color\n    from pydantic.error_wrappers import ErrorWrapper as ErrorWrapper\n    from pydantic.errors import MissingError\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        SHAPE_FROZENSET,\n        SHAPE_LIST,\n        SHAPE_SEQUENCE,\n        SHAPE_SET,\n        SHAPE_SINGLETON,\n        SHAPE_TUPLE,\n        SHAPE_TUPLE_ELLIPSIS,\n    )\n    from pydantic.fields import FieldInfo as FieldInfo\n    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined]\n    from pydantic.fields import Undefined as Undefined  # type: ignore[attr-defined]\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        UndefinedType as UndefinedType,\n    )\n    from pydantic.networks import AnyUrl as AnyUrl\n    from pydantic.networks import NameEmail as NameEmail\n    from pydantic.schema import 

{"status": "error", "error_type": "FileReadError", "error_message": "'>' not supported between instances of 'int' and 'str'"}

{"status": "error", "error_type": "FileReadError", "error_message": "'>' not supported between instances of 'int' and 'str'"}

{"status": "ok", "stdout": "72:    from pydantic.v1 import BaseConfig as BaseConfig  # type: ignore[assignment]\n73:    from pydantic.v1 import BaseModel as BaseModel  # type: ignore[assignment]\n74:    from pydantic.v1 import (  # type: ignore[assignment]\n77:    from pydantic.v1 import create_model as create_model  # type: ignore[no-redef]\n78:    from pydantic.v1.class_validators import Validator as Validator\n79:    from pydantic.v1.color import Color as Color  # type: ignore[assignment]\n80:    from pydantic.v1.error_wrappers import ErrorWrapper as ErrorWrapper\n81:    from pydantic.v1.errors import MissingError\n82:    from pydantic.v1.fields import (\n91:    from pydantic.v1.fields import FieldInfo as FieldInfo  # type: ignore[assignment]\n92:    from pydantic.v1.fields import ModelField as ModelField\n93:    from pydantic.v1.fields import Undefined as Undefined\n94:    from pydantic.v1.fields import UndefinedType as UndefinedType\n95:    from pydantic.v1.networks import AnyUrl as AnyUrl\n96:    from pydantic.v1.networks import (  # type: ignore[assignment]\n99:    from pydantic.v1.schema import TypeModelSet as TypeModelSet\n100:    from pydantic.v1.schema import (\n105:    from pydantic.v1.schema import (\n108:    from pydantic.v1.schema import (\n111:    from pydantic.v1.schema import get_model_name_map as get_model_name_map\n112:    from pydantic.v1.types import (  # type: ignore[assignment]\n115:    from pydantic.v1.types import (  # type: ignore[assignment]\n118:    from pydantic.v1.typing import evaluate_forwardref as evaluate_forwardref\n119:    from pydantic.v1.utils import lenient_issubclass as lenient_issubclass\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "3.13.14 (main, Jun 23 2026, 15:18:27) [Clang 22.1.3 ]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "2.13.5\n", "stderr": "", "exit_code": 0}

{"status": "error", "error_type": "FileReadError", "error_message": "'>' not supported between instances of 'int' and 'str'"}

{"status": "ok", "stdout": "from copy import copy\nfrom dataclasses import dataclass, is_dataclass\nfrom enum import Enum\nfrom typing import (\n    Any,\n    Callable,\n    Dict,\n    List,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n)\n\nfrom fastapi._compat import shared\nfrom fastapi.openapi.constants import REF_PREFIX as REF_PREFIX\nfrom fastapi.types import ModelNameMap\nfrom pydantic.version import VERSION as PYDANTIC_VERSION\nfrom typing_extensions import Literal\n\nPYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nPYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n# Keeping old \"Required\" functionality from Pydantic V1, without\n# shadowing typing.Required.\nRequiredParam: Any = Ellipsis\n\nif not PYDANTIC_V2:\n    from pydantic import BaseConfig as BaseConfig\n    from pydantic import BaseModel as BaseModel\n    from pydantic import ValidationError as ValidationError\n    from pydantic import create_model as create_model\n    from pydantic.class_validators import Validator as Validator\n    from pydantic.color import Color as Color\n    from pydantic.error_wrappers import ErrorWrapper as ErrorWrapper\n    from pydantic.errors import MissingError\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        SHAPE_FROZENSET,\n        SHAPE_LIST,\n        SHAPE_SEQUENCE,\n        SHAPE_SET,\n        SHAPE_SINGLETON,\n        SHAPE_TUPLE,\n        SHAPE_TUPLE_ELLIPSIS,\n    )\n    from pydantic.fields import FieldInfo as FieldInfo\n    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined]\n    from pydantic.fields import Undefined as Undefined  # type: ignore[attr-defined]\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        UndefinedType as UndefinedType,\n    )\n    from pydantic.networks import AnyUrl as AnyUrl\n    from pydantic.networks import NameEmail as NameEmail\n    from pydantic.schema import TypeModelSet as TypeModelSet\n    from

{"status": "ok", "stdout": ") -> List[Dict[str, Any]]:\n    updated_loc_errors: List[Any] = [\n        {**err, \"loc\": loc_prefix + err.get(\"loc\", ())}\n        for err in _normalize_errors(errors)\n    ]\n\n    return updated_loc_errors\n\n\ndef _model_rebuild(model: Type[BaseModel]) -> None:\n    model.update_forward_refs()\n\n\ndef _model_dump(\n    model: BaseModel, mode: Literal[\"json\", \"python\"] = \"json\", **kwargs: Any\n) -> Any:\n    return model.dict(**kwargs)\n\n\ndef _get_model_config(model: BaseModel) -> Any:\n    return model.__config__  # type: ignore[attr-defined]\n\n\ndef get_schema_from_model_field(\n    *,\n    field: ModelField,\n    model_name_map: ModelNameMap,\n    field_mapping: Dict[\n        Tuple[ModelField, Literal[\"validation\", \"serialization\"]], JsonSchemaValue\n    ],\n    separate_input_output_schemas: bool = True,\n) -> Dict[str, Any]:\n    return field_schema(  # type: ignore[no-any-return]\n        field, model_name_map=model_name_map, ref_prefix=REF_PREFIX\n    )[0]\n\n\n# def get_compat_model_name_map(fields: List[ModelField]) -> ModelNameMap:\n#     models = get_flat_models_from_fields(fields, known_models=set())\n#     return get_model_name_map(models)  # type: ignore[no-any-return]\n\n\ndef get_definitions(\n    *,\n    fields: List[ModelField],\n    model_name_map: ModelNameMap,\n    separate_input_output_schemas: bool = True,\n) -> Tuple[\n    Dict[Tuple[ModelField, Literal[\"validation\", \"serialization\"]], JsonSchemaValue],\n    Dict[str, Dict[str, Any]],\n]:\n    models = get_flat_models_from_fields(fields, known_models=set())\n    return {}, get_model_definitions(flat_models=models, model_name_map=model_name_map)\n\n\ndef is_scalar_field(field: ModelField) -> bool:\n    return is_pv1_scalar_field(field)\n\n\ndef is_sequence_field(field: ModelField) -> bool:\n    return field.shape in sequence_shapes or shared._annotation_is_sequence(field.type_)\n\n\ndef is_scalar_sequence_field(field: ModelField) -> bool:\n

{"status": "ok", "stdout": "sys.version_info(major=3, minor=13, micro=14, releaselevel='final', serial=0)\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "2.13.5\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/_compat/__init__.py:35:from .shared import PYDANTIC_VERSION_MINOR_TUPLE as PYDANTIC_VERSION_MINOR_TUPLE\nfastapi/_compat/shared.py:42:PYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nfastapi/_compat/shared.py:43:PYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\nfastapi/_compat/v1.py:22:PYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nfastapi/_compat/v1.py:23:PYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\nfastapi/_compat/v2.py:91:            if shared.PYDANTIC_VERSION_MINOR_TUPLE >= (2, 12):\nfastapi/temp_pydantic_v1_params.py:8:from ._compat.shared import PYDANTIC_VERSION_MINOR_TUPLE\nfastapi/temp_pydantic_v1_params.py:101:        if PYDANTIC_VERSION_MINOR_TUPLE < (2, 7):\nfastapi/temp_pydantic_v1_params.py:544:        if PYDANTIC_VERSION_MINOR_TUPLE < (2, 7):\nfastapi/params.py:11:    PYDANTIC_VERSION_MINOR_TUPLE,\nfastapi/params.py:112:        if PYDANTIC_VERSION_MINOR_TUPLE < (2, 7):\nfastapi/params.py:568:        if PYDANTIC_VERSION_MINOR_TUPLE < (2, 7):\n", "stderr": "", "exit_code": 0}

{"status": "ok", "filepath": "fastapi/_compat/v1.py", "content": "from copy import copy\nfrom dataclasses import dataclass, is_dataclass\nfrom enum import Enum\nfrom typing import (\n    Any,\n    Callable,\n    Dict,\n    List,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n)\n\nfrom fastapi._compat import shared\nfrom fastapi.openapi.constants import REF_PREFIX as REF_PREFIX\nfrom fastapi.types import ModelNameMap\nfrom pydantic.version import VERSION as PYDANTIC_VERSION\nfrom typing_extensions import Literal\n\nPYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nPYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n# Keeping old \"Required\" functionality from Pydantic V1, without\n# shadowing typing.Required.\nRequiredParam: Any = Ellipsis\n\nif not PYDANTIC_V2:\n    from pydantic import BaseConfig as BaseConfig\n    from pydantic import BaseModel as BaseModel\n    from pydantic import ValidationError as ValidationError\n    from pydantic import create_model as create_model\n    from pydantic.class_validators import Validator as Validator\n    from pydantic.color import Color as Color\n    from pydantic.error_wrappers import ErrorWrapper as ErrorWrapper\n    from pydantic.errors import MissingError\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        SHAPE_FROZENSET,\n        SHAPE_LIST,\n        SHAPE_SEQUENCE,\n        SHAPE_SET,\n        SHAPE_SINGLETON,\n        SHAPE_TUPLE,\n        SHAPE_TUPLE_ELLIPSIS,\n    )\n    from pydantic.fields import FieldInfo as FieldInfo\n    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined]\n    from pydantic.fields import Undefined as Undefined  # type: ignore[attr-defined]\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        UndefinedType as UndefinedType,\n    )\n    from pydantic.networks import AnyUrl as AnyUrl\n    from pydantic.networks import NameEmail as NameEmail\n    from pydantic.schema import 

{"status": "ok", "stdout": "sequence_shape_to_type = {\n    SHAPE_LIST: list,\n    SHAPE_SET: set,\n    SHAPE_TUPLE: tuple,\n    SHAPE_SEQUENCE: list,\n    SHAPE_TUPLE_ELLIPSIS: list,\n}\n\n\n@dataclass\nclass GenerateJsonSchema:\n    ref_template: str\n\n\nclass PydanticSchemaGenerationError(Exception):\n    pass\n\n\nRequestErrorModel: Type[BaseModel] = create_model(\"Request\")\n\n\ndef with_info_plain_validator_function(\n    function: Callable[..., Any],\n    *,\n    ref: Union[str, None] = None,\n    metadata: Any = None,\n    serialization: Any = None,\n) -> Any:\n    return {}\n\n\ndef get_model_definitions(\n    *,\n    flat_models: Set[Union[Type[BaseModel], Type[Enum]]],\n    model_name_map: Dict[Union[Type[BaseModel], Type[Enum]], str],\n) -> Dict[str, Any]:\n    definitions: Dict[str, Dict[str, Any]] = {}\n    for model in flat_models:\n        m_schema, m_definitions, m_nested_models = model_process_schema(\n            model, model_name_map=model_name_map, ref_prefix=REF_PREFIX\n        )\n        definitions.update(m_definitions)\n        model_name = model_name_map[model]\n        definitions[model_name] = m_schema\n    for m_schema in definitions.values():\n        if \"description\" in m_schema:\n            m_schema[\"description\"] = m_schema[\"description\"].split(\"\\f\")[0]\n    return definitions\n\n\ndef is_pv1_scalar_field(field: ModelField) -> bool:\n    from fastapi import params\n\n    field_info = field.field_info\n    if not (\n        field.shape == SHAPE_SINGLETON\n        and not lenient_issubclass(field.type_, BaseModel)\n        and not lenient_issubclass(field.type_, dict)\n        and not shared.field_annotation_is_sequence(field.type_)\n        and not is_dataclass(field.type_)\n        and not isinstance(field_info, params.Body)\n    ):\n        return False\n    if field.sub_fields:\n        if not all(is_pv1_scalar_field(f) for f in field.sub_fields):\n            return False\n    return True\n\n\ndef is_pv1_scalar_sequenc

{"status": "ok", "stdout": "sys.version_info(major=3, minor=13, micro=14, releaselevel='final', serial=0)\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "2.13.5\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "22:PYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\n23:PYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "42:PYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\n43:PYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "91:            if shared.PYDANTIC_VERSION_MINOR_TUPLE >= (2, 12):\n", "stderr": "", "exit_code": 0}

{"status": "ok", "filepath": "fastapi/_compat/v1.py", "content": "from copy import copy\nfrom dataclasses import dataclass, is_dataclass\nfrom enum import Enum\nfrom typing import (\n    Any,\n    Callable,\n    Dict,\n    List,\n    Sequence,\n    Set,\n    Tuple,\n    Type,\n    Union,\n)\n\nfrom fastapi._compat import shared\nfrom fastapi.openapi.constants import REF_PREFIX as REF_PREFIX\nfrom fastapi.types import ModelNameMap\nfrom pydantic.version import VERSION as PYDANTIC_VERSION\nfrom typing_extensions import Literal\n\nPYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(\".\")[:2])\nPYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2\n# Keeping old \"Required\" functionality from Pydantic V1, without\n# shadowing typing.Required.\nRequiredParam: Any = Ellipsis\n\nif not PYDANTIC_V2:\n    from pydantic import BaseConfig as BaseConfig\n    from pydantic import BaseModel as BaseModel\n    from pydantic import ValidationError as ValidationError\n    from pydantic import create_model as create_model\n    from pydantic.class_validators import Validator as Validator\n    from pydantic.color import Color as Color\n    from pydantic.error_wrappers import ErrorWrapper as ErrorWrapper\n    from pydantic.errors import MissingError\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        SHAPE_FROZENSET,\n        SHAPE_LIST,\n        SHAPE_SEQUENCE,\n        SHAPE_SET,\n        SHAPE_SINGLETON,\n        SHAPE_TUPLE,\n        SHAPE_TUPLE_ELLIPSIS,\n    )\n    from pydantic.fields import FieldInfo as FieldInfo\n    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined]\n    from pydantic.fields import Undefined as Undefined  # type: ignore[attr-defined]\n    from pydantic.fields import (  # type: ignore[attr-defined]\n        UndefinedType as UndefinedType,\n    )\n    from pydantic.networks import AnyUrl as AnyUrl\n    from pydantic.networks import NameEmail as NameEmail\n    from pydantic.schema import 

{"status": "ok", "stdout": "sequence_shape_to_type = {\n    SHAPE_LIST: list,\n    SHAPE_SET: set,\n    SHAPE_TUPLE: tuple,\n    SHAPE_SEQUENCE: list,\n    SHAPE_TUPLE_ELLIPSIS: list,\n}\n\n\n@dataclass\nclass GenerateJsonSchema:\n    ref_template: str\n\n\nclass PydanticSchemaGenerationError(Exception):\n    pass\n\n\nRequestErrorModel: Type[BaseModel] = create_model(\"Request\")\n\n\ndef with_info_plain_validator_function(\n    function: Callable[..., Any],\n    *,\n    ref: Union[str, None] = None,\n    metadata: Any = None,\n    serialization: Any = None,\n) -> Any:\n    return {}\n\n\ndef get_model_definitions(\n    *,\n    flat_models: Set[Union[Type[BaseModel], Type[Enum]]],\n    model_name_map: Dict[Union[Type[BaseModel], Type[Enum]], str],\n) -> Dict[str, Any]:\n    definitions: Dict[str, Dict[str, Any]] = {}\n    for model in flat_models:\n        m_schema, m_definitions, m_nested_models = model_process_schema(\n            model, model_name_map=model_name_map, ref_prefix=REF_PREFIX\n        )\n        definitions.update(m_definitions)\n        model_name = model_name_map[model]\n        definitions[model_name] = m_schema\n    for m_schema in definitions.values():\n        if \"description\" in m_schema:\n            m_schema[\"description\"] = m_schema[\"description\"].split(\"\\f\")[0]\n    return definitions\n\n\ndef is_pv1_scalar_field(field: ModelField) -> bool:\n    from fastapi import params\n\n    field_info = field.field_info\n    if not (\n        field.shape == SHAPE_SINGLETON\n        and not lenient_issubclass(field.type_, BaseModel)\n        and not lenient_issubclass(field.type_, dict)\n        and not shared.field_annotation_is_sequence(field.type_)\n        and not is_dataclass(field.type_)\n        and not isinstance(field_info, params.Body)\n    ):\n        return False\n    if field.sub_fields:\n        if not all(is_pv1_scalar_field(f) for f in field.sub_fields):\n            return False\n    return True\n\n\ndef is_pv1_scalar_sequenc