fastapi_13207

{"status": "ok", "stdout": "./fastapi/_compat/may_v1.py:65:        separate_input_output_schemas: bool = True,\n./fastapi/_compat/v1.py:243:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/v1.py:259:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/main.py:271:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/main.py:284:            separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/_compat/main.py:295:                separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/_compat/main.py:309:            separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/_compat/main.py:322:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/main.py:331:            separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/_compat/main.py:341:            separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/_compat/v2.py:181:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/v2.py:184:        None if separate_input_output_schemas else \"validation\"\n./fastapi/_compat/v2.py:201:    separate_input_output_schemas: bool = True,\n./fastapi/_compat/v2.py:208:        None if separate_input_output_schemas else \"validation\"\n./fastapi/applications.py:791:        separate_input_output_schemas: Annotated[\n./fastapi/applications.py:875:        self.separate_input_output_schemas = separate_input_output_schemas\n./fastapi/applications.py:1078:                separate_input_output_schemas=self.separate_input_output_schemas,\n./fastapi/openapi/utils.py:102:    separate_input_output_schemas: bool = True,\n./fastapi/openapi/utils.py:133:                separate_input_output_schemas=separate_input_output_schemas,\n./fastapi/openapi/utils.py:175:    separate_input_output_schemas: bool = True,\n", "stderr": "grep: ./.git/index: binary file matches\n", "exit_code": 0}

{"status": "ok", "stdout": "        Tuple[ModelField, Literal[\"validation\", \"serialization\"]], JsonSchemaValue\n    ],\n    separate_input_output_schemas: bool = True,\n) -> List[Dict[str, Any]]:\n    parameters = []\n    flat_dependant = get_flat_dependant(dependant, skip_repeats=True)\n    path_params = _get_flat_fields_from_params(flat_dependant.path_params)\n    query_params = _get_flat_fields_from_params(flat_dependant.query_params)\n    header_params = _get_flat_fields_from_params(flat_dependant.header_params)\n    cookie_params = _get_flat_fields_from_params(flat_dependant.cookie_params)\n    parameter_groups = [\n        (ParamTypes.path, path_params),\n        (ParamTypes.query, query_params),\n        (ParamTypes.header, header_params),\n        (ParamTypes.cookie, cookie_params),\n    ]\n    default_convert_underscores = True\n    if len(flat_dependant.header_params) == 1:\n        first_field = flat_dependant.header_params[0]\n        if lenient_issubclass(first_field.type_, BaseModel):\n            default_convert_underscores = getattr(\n                first_field.field_info, \"convert_underscores\", True\n            )\n    for param_type, param_group in parameter_groups:\n        for param in param_group:\n            field_info = param.field_info\n            # field_info = cast(Param, field_info)\n            if not getattr(field_info, \"include_in_schema\", True):\n                continue\n            param_schema = get_schema_from_model_field(\n                field=param,\n                model_name_map=model_name_map,\n                field_mapping=field_mapping,\n                separate_input_output_schemas=separate_input_output_schemas,\n            )\n            name = param.alias\n            convert_underscores = getattr(\n                param.field_info,\n                \"convert_underscores\",\n                default_convert_underscores,\n            )\n            if (\n                param_type == ParamTypes.header\n        

{"status": "ok", "stdout": "13:    get_schema_from_model_field,\n129:            param_schema = get_schema_from_model_field(\n180:    body_schema = get_schema_from_model_field(\n352:                        response_schema = get_schema_from_model_field(\n385:                        additional_field_schema = get_schema_from_model_field(\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:236:def get_schema_from_model_field(\n./fastapi/_compat/main.py:314:def get_schema_from_model_field(\n./fastapi/_compat/v2.py:174:def get_schema_from_model_field(\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "def _get_model_config(model: BaseModel) -> Any:\n    return model.model_config\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    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    # This expects that GenerateJsonSchema was already used to generate the definitions\n    json_schema = field_mapping[(field, override_mode or field.mode)]\n    if \"$ref\" not in json_schema:\n        # TODO remove when deprecating Pydantic v1\n        # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207\n        json_schema[\"title\"] = field.field_info.title or field.alias.title().replace(\n            \"_\", \" \"\n        )\n    return json_schema\n\n\ndef get_definitions(\n    *,\n    fields: Sequence[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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    validation_fields = [field for field in fields if field.mode == \"validation\"]\n    serialization_fields = [field for field in fields if field.mode == \"serialization\"]\n    flat_validation_models = get_flat_models_from_fields(\n        validation_fields, known_models=set()\n    )\n    flat_serialization_models = get_flat_models_from_fields(\n        serialization_fields, known_models=set()\n    )\n    flat_validation_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"validation\",\n        )\n        for model in flat_validation_models\n    ]\n    flat_serialization_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"serialization\",\n        )\n        for model in flat_serialization_models\n    ]\n    flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields\n    input_types = {f.type_ for f in fields}\n    unique_flat_model_fields = {\n        f for f in flat_model_fields if f.type_ not in input_types\n    }\n\n    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\n        definitions=definitions,  # type: ignore[arg-type]\n        field_mapping=field_mapping,\n    )\n    return new_mapping, new_definitions\n\n\ndef _replace_refs(\n    *,\n    schema: D

{"status": "ok", "stdout": "./tests/test_computed_fields.py:12:    from pydantic import BaseModel, computed_field\n./tests/test_computed_fields.py:18:        @computed_field\n./docs/en/docs/release-notes.md:2807:* \u2728 Enable Pydantic's serialization mode for responses, add support for Pydantic's `computed_field`, better OpenAPI for response models, proper required attributes, better generated clients. PR [#10011](https://github.com/tiangolo/fastapi/pull/10011) by [@tiangolo](https://github.com/tiangolo).\n", "stderr": "grep: ./.git/index: binary file matches\n", "exit_code": 0}

{"status": "ok", "stdout": "import pytest\nfrom fastapi import FastAPI\nfrom fastapi.testclient import TestClient\n\nfrom .utils import needs_pydanticv2\n\n\n@pytest.fixture(name=\"client\")\ndef get_client():\n    app = FastAPI()\n\n    from pydantic import BaseModel, computed_field\n\n    class Rectangle(BaseModel):\n        width: int\n        length: int\n\n        @computed_field\n        @property\n        def area(self) -> int:\n            return self.width * self.length\n\n    @app.get(\"/\")\n    def read_root() -> Rectangle:\n        return Rectangle(width=3, length=4)\n\n    @app.get(\"/responses\", responses={200: {\"model\": Rectangle}})\n    def read_responses() -> Rectangle:\n        return Rectangle(width=3, length=4)\n\n    client = TestClient(app)\n    return client\n\n\n@pytest.mark.parametrize(\"path\", [\"/\", \"/responses\"])\n@needs_pydanticv2\ndef test_get(client: TestClient, path: str):\n    response = client.get(path)\n    assert response.status_code == 200, response.text\n    assert response.json() == {\"width\": 3, \"length\": 4, \"area\": 12}\n\n\n@needs_pydanticv2\ndef test_openapi_schema(client: TestClient):\n    response = client.get(\"/openapi.json\")\n    assert response.status_code == 200, response.text\n    assert response.json() == {\n        \"openapi\": \"3.1.0\",\n        \"info\": {\"title\": \"FastAPI\", \"version\": \"0.1.0\"},\n        \"paths\": {\n            \"/\": {\n                \"get\": {\n                    \"summary\": \"Read Root\",\n                    \"operationId\": \"read_root__get\",\n                    \"responses\": {\n                        \"200\": {\n                            \"description\": \"Successful Response\",\n                            \"content\": {\n                                \"application/json\": {\n                                    \"schema\": {\"$ref\": \"#/components/schemas/Rectangle\"}\n                                }\n                            },\n                 

{"status": "error", "error_type": "CommandError", "error_message": "Traceback (most recent call last):\n  File \"/tmp/repro.py\", line 31, in <module>\n    test_openapi()\n    ~~~~~~~~~~~~^^\n  File \"/tmp/repro.py\", line 28, in test_openapi\n    assert \"area\" in rectangle_schema[\"properties\"], \"area should be in properties\"\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: area should be in properties\n", "details": {"stdout": "{\n  \"properties\": {\n    \"width\": {\n      \"type\": \"integer\",\n      \"title\": \"Width\"\n    },\n    \"length\": {\n      \"type\": \"integer\",\n      \"title\": \"Length\"\n    }\n  },\n  \"type\": \"object\",\n  \"required\": [\n    \"width\",\n    \"length\"\n  ],\n  \"title\": \"Rectangle\"\n}\n", "stderr": "Traceback (most recent call last):\n  File \"/tmp/repro.py\", line 31, in <module>\n    test_openapi()\n    ~~~~~~~~~~~~^^\n  File \"/tmp/repro.py\", line 28, in test_openapi\n    assert \"area\" in rectangle_schema[\"properties\"], \"area should be in properties\"\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: area should be in properties\n", "exit_code": 1}}

{"status": "ok", "stdout": "{\n  \"properties\": {\n    \"width\": {\n      \"type\": \"integer\",\n      \"title\": \"Width\"\n    },\n    \"length\": {\n      \"type\": \"integer\",\n      \"title\": \"Length\"\n    },\n    \"area\": {\n      \"type\": \"integer\",\n      \"title\": \"Area\",\n      \"readOnly\": true\n    }\n  },\n  \"type\": \"object\",\n  \"required\": [\n    \"width\",\n    \"length\",\n    \"area\"\n  ],\n  \"title\": \"Rectangle\"\n}\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    validation_fields = [field for field in fields if field.mode == \"validation\"]\n    serialization_fields = [field for field in fields if field.mode == \"serialization\"]\n    flat_validation_models = get_flat_models_from_fields(\n        validation_fields, known_models=set()\n    )\n    flat_serialization_models = get_flat_models_from_fields(\n        serialization_fields, known_models=set()\n    )\n    flat_validation_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"validation\",\n        )\n        for model in flat_validation_models\n    ]\n    flat_serialization_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"serialization\",\n        )\n        for model in flat_serialization_models\n    ]\n    flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields\n    input_types = {f.type_ for f in fields}\n    unique_flat_model_fields = {\n        f for f in flat_model_fields if f.type_ not in input_types\n    }\n\n    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\n        definitions=definitions,  # type: ignore[arg-type]\n        field_mapping=field_mapping,\n    )\n    return new_mapping, new_definitions\n\n\ndef _replace_refs(\n    *,\n    schema: D

{"status": "ok", "stdout": "def _get_model_config(model: BaseModel) -> Any:\n    return model.model_config\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    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    # This expects that GenerateJsonSchema was already used to generate the definitions\n    json_schema = field_mapping[(field, override_mode or field.mode)]\n    if \"$ref\" not in json_schema:\n        # TODO remove when deprecating Pydantic v1\n        # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207\n        json_schema[\"title\"] = field.field_info.title or field.alias.title().replace(\n            \"_\", \" \"\n        )\n    return json_schema\n\n\ndef get_definitions(\n    *,\n    fields: Sequence[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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    validation_fields = [field for field in fields if field.mode == \"validation\"]\n    serialization_fields = [field for field in fields if field.mode == \"serialization\"]\n    flat_validation_models = get_flat_models_from_fields(\n        validation_fields, known_models=set()\n    )\n    flat_serialization_models = get_flat_models_from_fields(\n        serialization_fields, known_models=set()\n    )\n    flat_validation_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"validation\",\n        )\n        for model in flat_validation_models\n    ]\n    flat_serialization_model_fields = [\n        ModelField(\n            field_info=FieldInfo(annotation=model),\n            name=model.__name__,\n            mode=\"serialization\",\n        )\n        for model in flat_serialization_models\n    ]\n    flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields\n    input_types = {f.type_ for f in fields}\n    unique_flat_model_fields = {\n        f for f in flat_model_fields if f.type_ not in input_types\n    }\n\n    inputs = [\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\n        definitions=definitions,  # type: ignore[arg-type]\n        field_mapping=field_mapping,\n    )\n    return new_mapping, new_definitions\n\n\ndef _replace_refs(\n    *,\n    schema: Dict[str, Any],\n    old_name_to_new_name_map: Dict[str, str],\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    ],\n    separate_input_output_schemas: bool = True,\n) -> Dict[str, Any]:\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    # This expects that GenerateJsonSchema was already used to generate the definitions\n    json_schema = field_mapping[(field, override_mode or field.mode)]\n    if \"$ref\" not in json_schema:\n        # TODO remove when deprecating Pydantic v1\n        # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207\n        json_schema[\"title\"] = field.field_info.title or field.alias.title().replace(\n            \"_\", \" \"\n        )\n    return json_schema\n\n\ndef get_definitions(\n    *,\n    fields: Sequence[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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "            mode=\"serialization\",\n        )\n        for model in flat_serialization_models\n    ]\n    flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields\n    input_types = {f.type_ for f in fields}\n    unique_flat_model_fields = {\n        f for f in flat_model_fields if f.type_ not in input_types\n    }\n\n    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "    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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0}

{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0, "budget_warning": "Only 9 tool call(s) remaining (51/60 used). Finalize your edits and call submit_patch soon."}

{"status": "error", "error_type": "CommandError", "error_message": "Traceback (most recent call last):\n  File \"/tmp/repro.py\", line 31, in <module>\n    test_openapi()\n    ~~~~~~~~~~~~^^\n  File \"/tmp/repro.py\", line 28, in test_openapi\n    assert \"area\" in rectangle_schema[\"properties\"], \"area should be in properties\"\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: area should be in properties\n", "details": {"stdout": "{\n  \"properties\": {\n    \"width\": {\n      \"type\": \"integer\",\n      \"title\": \"Width\"\n    },\n    \"length\": {\n      \"type\": \"integer\",\n      \"title\": \"Length\"\n    }\n  },\n  \"type\": \"object\",\n  \"required\": [\n    \"width\",\n    \"length\"\n  ],\n  \"title\": \"Rectangle\"\n}\n", "stderr": "Traceback (most recent call last):\n  File \"/tmp/repro.py\", line 31, in <module>\n    test_openapi()\n    ~~~~~~~~~~~~^^\n  File \"/tmp/repro.py\", line 28, in test_openapi\n    assert \"area\" in rectangle_schema[\"properties\"], \"area should be in properties\"\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: area should be in properties\n", "exit_code": 1}, "budget_warning": "Only 8 tool call(s) remaining (52/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "", "stderr": "", "exit_code": 0, "budget_warning": "Only 7 tool call(s) remaining (53/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "    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    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)\n    override_mode: Union[Literal[\"validation\"], None] = (\n        None if separate_input_output_schemas else \"validation\"\n    )\n    validation_fields = [field for field in fields if field.mode == \"validation\"]\n", "stderr": "", "exit_code": 0, "budget_warning": "Only 6 tool call(s) remaining (54/60 used). Finalize your edits and call submit_patch soon."}

{"status": "ok", "stdout": "    inputs = [\n        (field, override_mode or field.mode, field._type_adapter.core_schema)\n        for field in list(fields) + list(unique_flat_model_fields)\n    ]\n    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)\n    for item_def in cast(Dict[str, Dict[str, Any]], definitions).values():\n        if \"description\" in item_def:\n            item_description = cast(str, item_def[\"description\"]).split(\"\\f\")[0]\n            item_def[\"description\"] = item_description\n    new_mapping, new_definitions = _remap_definitions_and_field_mappings(\n        model_name_map=model_name_map,\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": "            mode=\"serialization\",\n        )\n        for model in flat_serialization_models\n    ]\n    flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields\n    input_types = {f.type_ for f in fields}\n    unique_flat_model_fields = {\n        f for f in flat_model_fields if f.type_ not in input_types\n    }\n\n    inputs = [\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": "error", "error_type": "CommandError", "error_message": "/bin/bash: line 1: submit_patch: command not found\n", "details": {"stdout": "", "stderr": "/bin/bash: line 1: submit_patch: command not found\n", "exit_code": 127}, "budget_warning": "Only 3 tool call(s) remaining (57/60 used). Finalize your edits and call submit_patch soon."}

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