fastapi_15589

{"status": "ok", "stdout": "./fastapi/dependencies/utils.py:536:        if not field_info.alias and getattr(field_info, \"convert_underscores\", None):\n./fastapi/dependencies/utils.py:797:    default_convert_underscores = True\n./fastapi/dependencies/utils.py:803:        # If headers are in a Pydantic model, the way to disable convert_underscores\n./fastapi/dependencies/utils.py:804:        # would be with Header(convert_underscores=False) at the Pydantic model level\n./fastapi/dependencies/utils.py:805:        default_convert_underscores = getattr(\n./fastapi/dependencies/utils.py:806:            first_field.field_info, \"convert_underscores\", True\n./fastapi/dependencies/utils.py:817:            # doesn't have a FieldInfo of type Header with the default convert_underscores=True\n./fastapi/dependencies/utils.py:818:            convert_underscores = getattr(\n./fastapi/dependencies/utils.py:819:                field.field_info, \"convert_underscores\", default_convert_underscores\n./fastapi/dependencies/utils.py:821:            if convert_underscores:\n./fastapi/param_functions.py:761:    convert_underscores: Annotated[\n./fastapi/param_functions.py:991:        convert_underscores=convert_underscores,\n./fastapi/params.py:316:        convert_underscores: bool = True,\n./fastapi/params.py:352:        self.convert_underscores = convert_underscores\n./fastapi/openapi/utils.py:128:    default_convert_underscores = True\n./fastapi/openapi/utils.py:132:            default_convert_underscores = getattr(\n./fastapi/openapi/utils.py:133:                first_field.field_info, \"convert_underscores\", True\n./fastapi/openapi/utils.py:148:            convert_underscores = getattr(\n./fastapi/openapi/utils.py:150:                \"convert_underscores\",\n./fastapi/openapi/utils.py:151:                default_convert_underscores,\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "filepath": "fastapi/params.py", "content": "import warnings\nfrom collections.abc import Callable, Sequence\nfrom dataclasses import dataclass\nfrom enum import Enum\nfrom typing import Annotated, Any, Literal\n\nfrom fastapi.exceptions import FastAPIDeprecationWarning\nfrom fastapi.openapi.models import Example\nfrom pydantic import AliasChoices, AliasPath\nfrom pydantic.fields import FieldInfo\nfrom typing_extensions import deprecated\n\nfrom ._compat import (\n    Undefined,\n)\nfrom .datastructures import _Unset\n\n\nclass ParamTypes(Enum):\n    query = \"query\"\n    header = \"header\"\n    path = \"path\"\n    cookie = \"cookie\"\n\n\nclass Param(FieldInfo):  # type: ignore[misc]  # ty: ignore[subclass-of-final-class]\n    in_: ParamTypes\n\n    def __init__(\n        self,\n        default: Any = Undefined,\n        *,\n        default_factory: Callable[[], Any] | None = _Unset,\n        annotation: Any | None = None,\n        alias: str | None = None,\n        alias_priority: int | None = _Unset,\n        validation_alias: str | AliasPath | AliasChoices | None = None,\n        serialization_alias: str | None = None,\n        title: str | None = None,\n        description: str | None = None,\n        gt: float | None = None,\n        ge: float | None = None,\n        lt: float | None = None,\n        le: float | None = None,\n        min_length: int | None = None,\n        max_length: int | None = None,\n        pattern: str | None = None,\n        regex: Annotated[\n            str | None,\n            deprecated(\n                \"Deprecated in FastAPI 0.100.0 and Pydantic v2, use `pattern` instead.\"\n            ),\n        ] = None,\n        discriminator: str | None = None,\n        strict: bool | None = _Unset,\n        multiple_of: float | None = _Unset,\n        allow_inf_nan: bool | None = _Unset,\n        max_digits: int | None = _Unset,\n        decimal_places: int | None = _Unset,\n        examples: list[Any] | None = None,\n 

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

{"status": "ok", "stdout": "303:class Header(Param):  # type: ignore[misc]\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "        )\n\n\nclass Header(Param):  # type: ignore[misc]\n    in_ = ParamTypes.header\n\n    def __init__(\n        self,\n        default: Any = Undefined,\n        *,\n        default_factory: Callable[[], Any] | None = _Unset,\n        annotation: Any | None = None,\n        alias: str | None = None,\n        alias_priority: int | None = _Unset,\n        validation_alias: str | AliasPath | AliasChoices | None = None,\n        serialization_alias: str | None = None,\n        convert_underscores: bool = True,\n        title: str | None = None,\n        description: str | None = None,\n        gt: float | None = None,\n        ge: float | None = None,\n        lt: float | None = None,\n        le: float | None = None,\n        min_length: int | None = None,\n        max_length: int | None = None,\n        pattern: str | None = None,\n        regex: Annotated[\n            str | None,\n            deprecated(\n                \"Deprecated in FastAPI 0.100.0 and Pydantic v2, use `pattern` instead.\"\n            ),\n        ] = None,\n        discriminator: str | None = None,\n        strict: bool | None = _Unset,\n        multiple_of: float | None = _Unset,\n        allow_inf_nan: bool | None = _Unset,\n        max_digits: int | None = _Unset,\n        decimal_places: int | None = _Unset,\n        examples: list[Any] | None = None,\n        example: Annotated[\n            Any | None,\n            deprecated(\n                \"Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, \"\n                \"although still supported. Use examples instead.\"\n            ),\n        ] = _Unset,\n        openapi_examples: dict[str, Example] | None = None,\n        deprecated: deprecated | str | bool | None = None,\n        include_in_schema: bool = True,\n        json_schema_extra: dict[str, Any] | None = None,\n        **extra: Any,\n    ):\n        self.convert_underscores = convert_underscores\n        super().__init__(\n            d

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

{"status": "ok", "stdout": "            return deepcopy(field.default)\n    return value\n\n\ndef request_params_to_args(\n    fields: Sequence[ModelField],\n    received_params: Mapping[str, Any] | QueryParams | Headers,\n) -> tuple[dict[str, Any], list[Any]]:\n    values: dict[str, Any] = {}\n    errors: list[dict[str, Any]] = []\n\n    if not fields:\n        return values, errors\n\n    first_field = fields[0]\n    fields_to_extract = fields\n    single_not_embedded_field = False\n    default_convert_underscores = True\n    if len(fields) == 1 and lenient_issubclass(\n        first_field.field_info.annotation, BaseModel\n    ):\n        fields_to_extract = get_cached_model_fields(first_field.field_info.annotation)\n        single_not_embedded_field = True\n        # If headers are in a Pydantic model, the way to disable convert_underscores\n        # would be with Header(convert_underscores=False) at the Pydantic model level\n        default_convert_underscores = getattr(\n            first_field.field_info, \"convert_underscores\", True\n        )\n\n    params_to_process: dict[str, Any] = {}\n\n    processed_keys = set()\n\n    for field in fields_to_extract:\n        alias = None\n        if isinstance(received_params, Headers):\n            # Handle fields extracted from a Pydantic Model for a header, each field\n            # doesn't have a FieldInfo of type Header with the default convert_underscores=True\n            convert_underscores = getattr(\n                field.field_info, \"convert_underscores\", default_convert_underscores\n            )\n            if convert_underscores:\n                alias = get_validation_alias(field)\n                if alias == field.name:\n                    alias = alias.replace(\"_\", \"-\")\n        value = _get_multidict_value(field, received_params, alias=alias)\n        if value is not None:\n            params_to_process[get_validation_alias(field)] = value\n        processed_keys.add(alias or get_validation_

{"status": "ok", "stdout": "756:    alias = alias or get_validation_alias(field)\n822:                alias = get_validation_alias(field)\n827:            params_to_process[get_validation_alias(field)] = value\n828:        processed_keys.add(alias or get_validation_alias(field))\n858:        loc = (field_info.in_.value, get_validation_alias(field))\n939:            values[get_validation_alias(field)] = value\n940:    field_aliases = {get_validation_alias(field) for field in body_fields}\n982:        loc = (\"body\", get_validation_alias(field))\n986:                value = body_to_process.get(get_validation_alias(field))\n1055:def get_validation_alias(field: ModelField) -> str:\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def get_validation_alias(field: ModelField) -> str:\n    va = getattr(field, \"validation_alias\", None)\n    return va or field.alias\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "        if isinstance(received_params, Headers):\n            # Handle fields extracted from a Pydantic Model for a header, each field\n            # doesn't have a FieldInfo of type Header with the default convert_underscores=True\n            convert_underscores = getattr(\n                field.field_info, \"convert_underscores\", default_convert_underscores\n            )\n            if convert_underscores:\n                alias = get_validation_alias(field)\n                if alias == field.name:\n                    alias = alias.replace(\"_\", \"-\")\n        value = _get_multidict_value(field, received_params, alias=alias)\n        if value is not None:\n            params_to_process[get_validation_alias(field)] = value\n        processed_keys.add(alias or get_validation_alias(field))\n\n    for key in received_params.keys():\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    return any(type(item) is Json for item in field.field_info.metadata)\n\n\ndef _get_multidict_value(\n    field: ModelField, values: Mapping[str, Any], alias: str | None = None\n) -> Any:\n    alias = alias or get_validation_alias(field)\n    if (\n        (not _is_json_field(field))\n        and field_annotation_is_sequence(field.field_info.annotation)\n        and isinstance(values, (ImmutableMultiDict, Headers))\n    ):\n        value = values.getlist(alias)\n    else:\n        value = values.get(alias, None)\n    if (\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "69:    Headers,\n760:        and isinstance(values, (ImmutableMultiDict, Headers))\n786:    received_params: Mapping[str, Any] | QueryParams | Headers,\n804:        # would be with Header(convert_underscores=False) at the Pydantic model level\n815:        if isinstance(received_params, Headers):\n817:            # doesn't have a FieldInfo of type Header with the default convert_underscores=True\n832:            if isinstance(received_params, (ImmutableMultiDict, Headers)):\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    for key in received_params.keys():\n        if key not in processed_keys:\n            if isinstance(received_params, (ImmutableMultiDict, Headers)):\n                value = received_params.getlist(key)\n                if isinstance(value, list) and (len(value) == 1):\n                    params_to_process[key] = value[0]\n                else:\n                    params_to_process[key] = value\n            else:\n                params_to_process[key] = received_params.get(key)\n\n    if single_not_embedded_field:\n        field_info = first_field.field_info\n        assert isinstance(field_info, params.Param), (\n            \"Params must be subclasses of Param\"\n        )\n        loc: tuple[str, ...] = (field_info.in_.value,)\n        v_, errors_ = _validate_value_with_model_field(\n            field=first_field, value=params_to_process, values=values, loc=loc\n        )\n        return {first_field.name: v_}, errors_\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    for key in received_params.keys():\n        if key not in processed_keys:\n            if isinstance(received_params, (ImmutableMultiDict, Headers)):\n                value = received_params.getlist(key)\n                if isinstance(value, list) and (len(value) == 1):\n                    params_to_process[key] = value[0]\n                else:\n                    params_to_process[key] = value\n            else:\n                params_to_process[key] = received_params.get(key)\n\n    if single_not_embedded_field:\n        field_info = first_field.field_info\n        assert isinstance(field_info, params.Param), (\n            \"Params must be subclasses of Param\"\n        )\n", "stderr": "", "exit_code": 0}

{"status": "error", "error_type": "CommandError", "error_message": "/bin/bash: -c: line 1: unexpected EOF while looking for matching `''\n", "details": {"stdout": "", "stderr": "/bin/bash: -c: line 1: unexpected EOF while looking for matching `''\n", "exit_code": 2}}

{"status": "ok", "stdout": "    for key in received_params.keys():\n        if key not in processed_keys:\n            if isinstance(received_params, (ImmutableMultiDict, Headers)):\n                value = received_params.getlist(key)\n                if isinstance(value, list) and (len(value) == 1):\n                    params_to_process[key] = value[0]\n                else:\n                    params_to_process[key] = value\n            else:\n                params_to_process[key] = received_params.get(key)\n\n    if single_not_embedded_field:\n        field_info = first_field.field_info\n        assert isinstance(field_info, params.Param), (\n            \"Params must be subclasses of Param\"\n        )\n", "stderr": "", "exit_code": 0}

{'error': 'Invoking `edit_file()` failed as the following mandatory input parameters are not present:\nold_string\nYou could retry calling this tool, but it is IMPORTANT for you to provide all the mandatory parameters.'}

{'error': 'Invoking `edit_file()` failed as the following mandatory input parameters are not present:\nold_string\nYou could retry calling this tool, but it is IMPORTANT for you to provide all the mandatory parameters.'}

{'error': 'Invoking `edit_file()` failed as the following mandatory input parameters are not present:\nold_string\nYou could retry calling this tool, but it is IMPORTANT for you to provide all the mandatory parameters.'}

{"status": "ok", "patch_size": 0, "files_changed": 0}