fastapi_14246

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

{"status": "ok", "stdout": "./docs/de/docs/how-to/migrate-from-pydantic-v1-to-pydantic-v2.md:19:Wenn Sie eine \u00e4ltere FastAPI-App mit Pydantic v1 haben, zeige ich Ihnen hier, wie Sie sie zu Pydantic v2 migrieren, und die **neuen Features in FastAPI 0.119.0**, die Ihnen bei einer schrittweisen Migration helfen.\n./docs/de/docs/how-to/migrate-from-pydantic-v1-to-pydantic-v2.md:55:Seit FastAPI 0.119.0 gibt es au\u00dferdem eine teilweise Unterst\u00fctzung f\u00fcr Pydantic v1 innerhalb von Pydantic v2, um die Migration auf v2 zu erleichtern.\n./docs/en/docs/release-notes.md:61:## 0.119.0\n./docs/en/docs/how-to/migrate-from-pydantic-v1-to-pydantic-v2.md:19:If you have an old FastAPI app with Pydantic v1, here I'll show you how to migrate it to Pydantic v2, and the **new features in FastAPI 0.119.0** to help you with a gradual migration.\n./docs/en/docs/how-to/migrate-from-pydantic-v1-to-pydantic-v2.md:55:Since FastAPI 0.119.0, there's also partial support for Pydantic v1 from inside of Pydantic v2, to facilitate the migration to v2.\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/routing.py:235:            # pydantic v1\n", "stderr": "", "exit_code": 0}

{"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:535:        elif isinstance(field_info, (params.Query, temp_pydantic_v1_params.Query)):\nfastapi/dependencies/utils.py:762:            isinstance(field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:828:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:840:        assert isinstance(field_info, (params.Param, temp_pydantic_v1_params.Param)), (\nfastapi/dependencies/utils.py:889:        isinstance(first_field.field_info, (params.Form, temp_pydantic_v1_params.Form))\nfastapi/dependencies/utils.py:907:            isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:914:            and isinstance(field_info, (params.File, temp_pydantic_v1_params.File))\nfastapi/dependencies/utils.py:1021:        isinstance(f.field_info, temp_pydantic_v1_params.File)\nfastapi/dependencies/utils.py:1024:       

{"status": "ok", "stdout": "fastapi/_compat:\n__init__.py\nmain.py\nmay_v1.py\nmodel_field.py\nshared.py\nv1.py\nv2.py\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "57:        model_process_schema,\n104:        model_process_schema,\n177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    )\n    from pydantic.v1.schema import TypeModelSet as TypeModelSet\n    from pydantic.v1.schema import (\n        field_schema,\n        model_process_schema,\n    )\n    from pydantic.v1.schema import (\n        get_annotation_from_field_info as get_annotation_from_field_info,\n    )\n    from pydantic.v1.schema import (\n        get_flat_models_from_field as get_flat_models_from_field,\n    )\n    from pydantic.v1.schema import (\n        get_flat_models_from_fields as get_flat_models_from_fields,\n    )\n    from pydantic.v1.schema import get_model_name_map as get_model_name_map\n    from pydantic.v1.types import (  # type: ignore[assignment]\n        SecretBytes as SecretBytes,\n    )\n    from pydantic.v1.types import (  # type: ignore[assignment]\n        SecretStr as SecretStr,\n    )\n    from pydantic.v1.typing import evaluate_forwardref as evaluate_forwardref\n    from pydantic.v1.utils import lenient_issubclass as lenient_issubclass\n\n\nGetJsonSchemaHandler = Any\nJsonSchemaValue = Dict[str, Any]\nCoreSchema = Any\nUrl = AnyUrl\n\nsequence_shapes = {\n    SHAPE_LIST,\n    SHAPE_SET,\n    SHAPE_FROZENSET,\n    SHAPE_TUPLE,\n    SHAPE_SEQUENCE,\n    SHAPE_TUPLE_ELLIPSIS,\n}\nsequence_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", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "52-    from pydantic.networks import AnyUrl as AnyUrl\n53-    from pydantic.networks import NameEmail as NameEmail\n54-    from pydantic.schema import TypeModelSet as TypeModelSet\n55-    from pydantic.schema import (\n56-        field_schema,\n57:        model_process_schema,\n58-    )\n59-    from pydantic.schema import (\n60-        get_annotation_from_field_info as get_annotation_from_field_info,\n61-    )\n62-    from pydantic.schema import get_flat_models_from_field as get_flat_models_from_field\n--\n99-        NameEmail as NameEmail,\n100-    )\n101-    from pydantic.v1.schema import TypeModelSet as TypeModelSet\n102-    from pydantic.v1.schema import (\n103-        field_schema,\n104:        model_process_schema,\n105-    )\n106-    from pydantic.v1.schema import (\n107-        get_annotation_from_field_info as get_annotation_from_field_info,\n108-    )\n109-    from pydantic.v1.schema import (\n--\n172-    flat_models: Set[Union[Type[BaseModel], Type[Enum]]],\n173-    model_name_map: Dict[Union[Type[BaseModel], Type[Enum]], str],\n174-) -> Dict[str, Any]:\n175-    definitions: Dict[str, Dict[str, Any]] = {}\n176-    for model in flat_models:\n177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n178-            model, model_name_map=model_name_map, ref_prefix=REF_PREFIX\n179-        )\n180-        definitions.update(m_definitions)\n181-        model_name = model_name_map[model]\n182-        definitions[model_name] = m_schema\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:170:def get_model_definitions(\nfastapi/_compat/v1.py:265:    return {}, get_model_definitions(flat_models=models, model_name_map=model_name_map)\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": ") -> 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:64:        get_flat_models_from_fields as get_flat_models_from_fields,\nfastapi/_compat/v1.py:113:        get_flat_models_from_fields as get_flat_models_from_fields,\nfastapi/_compat/v1.py:251:#     models = get_flat_models_from_fields(fields, known_models=set())\nfastapi/_compat/v1.py:264:    models = get_flat_models_from_fields(fields, known_models=set())\nfastapi/_compat/main.py:242:        v1_flat_models = v1.get_flat_models_from_fields(\nfastapi/_compat/main.py:254:        v2_flat_models = v2.get_flat_models_from_fields(\nfastapi/_compat/v2.py:210:    flat_models = get_flat_models_from_fields(fields, known_models=set())\nfastapi/_compat/v2.py:415:    get_flat_models_from_fields(fields, known_models=known_models)\nfastapi/_compat/v2.py:450:def get_flat_models_from_fields(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/may_v1.py:65:        separate_input_output_schemas: bool = True,\nfastapi/_compat/v1.py:243:    separate_input_output_schemas: bool = True,\nfastapi/_compat/v1.py:259:    separate_input_output_schemas: bool = True,\nfastapi/_compat/main.py:271:    separate_input_output_schemas: bool = True,\nfastapi/_compat/main.py:284:            separate_input_output_schemas=separate_input_output_schemas,\nfastapi/_compat/main.py:295:                separate_input_output_schemas=separate_input_output_schemas,\nfastapi/_compat/main.py:309:            separate_input_output_schemas=separate_input_output_schemas,\nfastapi/_compat/main.py:322:    separate_input_output_schemas: bool = True,\nfastapi/_compat/main.py:331:            separate_input_output_schemas=separate_input_output_schemas,\nfastapi/_compat/main.py:341:            separate_input_output_schemas=separate_input_output_schemas,\nfastapi/_compat/v2.py:181:    separate_input_output_schemas: bool = True,\nfastapi/_compat/v2.py:184:        None if separate_input_output_schemas else \"validation\"\nfastapi/_compat/v2.py:201:    separate_input_output_schemas: bool = True,\nfastapi/_compat/v2.py:208:        None if separate_input_output_schemas else \"validation\"\nfastapi/applications.py:786:        separate_input_output_schemas: Annotated[\nfastapi/applications.py:870:        self.separate_input_output_schemas = separate_input_output_schemas\nfastapi/applications.py:1073:                separate_input_output_schemas=self.separate_input_output_schemas,\nfastapi/openapi/utils.py:102:    separate_input_output_schemas: bool = True,\nfastapi/openapi/utils.py:133:                separate_input_output_schemas=separate_input_output_schemas,\nfastapi/openapi/utils.py:175:    separate_input_output_schemas: bool = True,\nfastapi/openapi/utils.py:184:        separate_input_output_schemas=separate_input_output_schemas,\nfastapi/openapi/utils.py:258:    separate_input_output_schemas: bool = True,\nf

{"status": "ok", "stdout": "# 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "57:        model_process_schema,\n104:        model_process_schema,\n177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

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

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0}

{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}, "budget_warning": "Only 10 tool call(s) remaining (50/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 9 tool call(s) remaining (51/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0, "budget_warning": "Only 8 tool call(s) remaining (52/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 7 tool call(s) remaining (53/60 used). Finalize your edits and call submit_patch soon."}

{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}, "budget_warning": "Only 6 tool call(s) remaining (54/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 5 tool call(s) remaining (55/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "def 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", "stderr": "", "exit_code": 0, "budget_warning": "Only 4 tool call(s) remaining (56/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 3 tool call(s) remaining (57/60 used). Finalize your edits and call submit_patch soon."}

{"status": "error", "error_type": "CommandError", "error_message": "", "details": {"stdout": "", "stderr": "", "exit_code": 1}, "budget_warning": "Only 2 tool call(s) remaining (58/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "fastapi/_compat/v1.py:177:        m_schema, m_definitions, m_nested_models = model_process_schema(\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 1 tool call(s) remaining (59/60 used). Finalize your edits and call submit_patch soon."}

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