'1.0',
'info' => ['style' => 'RPC', 'product' => 'documentAutoml', 'version' => '2022-12-29'],
'directories' => ['PredictTemplateModel', 'PredictModel', 'PredictClassifierModel', 'CreateModelAsyncPredict', 'GetModelAsyncPredict', 'PredictPreTrainModel'],
'components' => [
'schemas' => [],
],
'apis' => [
'CreateModelAsyncPredict' => [
'summary' => '文档自学习创建异步预测任务接口。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'write',
'deprecated' => false,
'systemTags' => ['operationType' => 'create', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'ModelVersion',
'in' => 'query',
'schema' => ['description' => '模型对应的版本号,如果不传入版本号表示默认用模型最新生效的版本。', 'type' => 'string', 'required' => false, 'example' => 'V1'],
],
[
'name' => 'BinaryToText',
'in' => 'query',
'schema' => ['description' => 'content字段是图片URL时:false'."\n"
.'body为base64的内容时:true', 'type' => 'boolean', 'required' => false, 'example' => 'false:表示content传入的是url'."\n"
.'true:表示body是直接传入图片进行base64的内容'."\n", 'default' => 'false'],
],
[
'name' => 'Content',
'in' => 'query',
'schema' => ['description' => '图片或pdf文件访问URL地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/1559855998794593/stage/upload/20230206/oss-hlfCRJ1SorSWs10MkqxK6YcL4OVAFSv4.png?Expires=1675665563&OSSAccessKeyId=XXXX&Signature=WLKghBc3zKzWJ3Td69%2B4C21jrbE%3D'],
],
[
'name' => 'ModelId',
'in' => 'query',
'schema' => ['description' => '模型ID。模型列表页模型ID', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123'],
],
[
'name' => 'ServiceName',
'in' => 'query',
'schema' => ['description' => '预训练服务名称', 'type' => 'string', 'required' => false, 'example' => 'pre_train_service'],
],
[
'name' => 'ServiceVersion',
'in' => 'query',
'schema' => ['description' => '预训练服务版本', 'type' => 'string', 'required' => false, 'example' => 'V1'],
],
[
'name' => 'Body',
'in' => 'formData',
'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'],
'Code' => ['description' => '请求结果状态,200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200'],
'Message' => ['description' => '错误信息。', 'type' => 'string', 'example' => 'success'],
'Data' => ['description' => '返回数据', 'type' => 'string', 'example' => '{'."\n"
.' "RequestId": "292D1584-134C-1221-B9BB-1B847C623D41",'."\n"
.' "Message": "",'."\n"
.' "Data": 1,'."\n"
.' "Code": 200'."\n"
.'}'],
],
],
],
],
'errorCodes' => [
200 => [
['errorCode' => '21002', 'errorMessage' => '模板预测超时 ', 'description' => ''],
['errorCode' => '21003', 'errorMessage' => '模板预测失败', 'description' => ''],
['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', 'description' => ''],
['errorCode' => '13018', 'errorMessage' => '未找到模型信息', 'description' => ''],
['errorCode' => '16004', 'errorMessage' => '指定的模型不存在', 'description' => ''],
['errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', 'description' => ''],
['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
],
],
'staticInfo' => ['returnType' => 'synchronous'],
'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": \\"{\\\\n \\\\\\"RequestId\\\\\\": \\\\\\"292D1584-134C-1221-B9BB-1B847C623D41\\\\\\",\\\\n \\\\\\"Message\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"Data\\\\\\": 1,\\\\n \\\\\\"Code\\\\\\": 200\\\\n}\\"\\n}","type":"json"}]',
'title' => '模型异步预测API',
'requestParamsDescription' => 'BinaryToText为非必填项。'."\n"
."\n"
.'content字段和body字段传参二选一,图片URL则content为图片访问地址。内容为base64编码则传参body,且BinaryToText传true。'."\n"
."\n"
.'pdf 限制20Mb 10页'."\n"
.'除了长文档类型的模型预测以外,其他预测服务只会取第一页进行预测。',
'responseParamsDescription' => 'Data字段为创建的异步任务ID,通过GetModelAsyncPredict获取结果',
'changeSet' => [
['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => '请求参数发生变更'],
],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'CreateModelAsyncPredict'],
],
],
'ramActions' => [],
],
'GetModelAsyncPredict' => [
'summary' => '模型预测分为三种类型:长文档信息抽取、单票据信息抽取、表格信息抽取。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'read',
'deprecated' => false,
'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'AsyncPredictId',
'in' => 'query',
'schema' => ['description' => '异步预测唯一ID,用于查询异步预测结果。', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1'],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'],
'Code' => ['description' => '请求结果状态,200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200'],
'Message' => ['description' => '错误信息。', 'type' => 'string', 'example' => 'success'],
'Data' => ['description' => '返回数据', 'type' => 'string', 'example' => '{'."\n"
.' "RequestId": "A9796F06-F1C4-1E89-8AFD-596583FF4B16",'."\n"
.' "Message": "",'."\n"
.' "Data": {'."\n"
.' "result": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/stage/data/XXXX/asyncPredict/713908/oss-933bbdf4-fa10-4c56-b6ab-9c85f32bbd0e.json?Expires=1991115127&OSSAccessKeyId=XXXX&Signature=5zYLY9yR%2B9Ok1WuRgHYdqtXHK10%3D",'."\n"
.' "asyncPredictId": 713908,'."\n"
.' "errorCode": 200,'."\n"
.' "errorMsg": "",'."\n"
.' "status": 2'."\n"
.' },'."\n"
.' "Code": 200'."\n"
.'}'],
],
],
],
],
'errorCodes' => [
200 => [
['errorCode' => '21002', 'errorMessage' => '模板预测超时', 'description' => ''],
['errorCode' => '21003', 'errorMessage' => '模板预测失败', 'description' => ''],
['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', 'description' => ''],
['errorCode' => '13018', 'errorMessage' => '未找到模型信息', 'description' => ''],
['errorCode' => '16004', 'errorMessage' => '指定的模型不存在', 'description' => ''],
['errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', 'description' => ''],
['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
],
],
'staticInfo' => ['returnType' => 'synchronous'],
'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": \\"{\\\\n \\\\\\"RequestId\\\\\\": \\\\\\"A9796F06-F1C4-1E89-8AFD-596583FF4B16\\\\\\",\\\\n \\\\\\"Message\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"Data\\\\\\": {\\\\n \\\\\\"result\\\\\\": \\\\\\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/stage/data/XXXX/asyncPredict/713908/oss-933bbdf4-fa10-4c56-b6ab-9c85f32bbd0e.json?Expires=1991115127&OSSAccessKeyId=XXXX&Signature=5zYLY9yR%2B9Ok1WuRgHYdqtXHK10%3D\\\\\\",\\\\n \\\\\\"asyncPredictId\\\\\\": 713908,\\\\n \\\\\\"errorCode\\\\\\": 200,\\\\n \\\\\\"errorMsg\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"status\\\\\\": 2\\\\n },\\\\n \\\\\\"Code\\\\\\": 200\\\\n}\\"\\n}","type":"json"}]',
'title' => '获取模型异步预测结果API',
'responseParamsDescription' => 'status 表示任务状态,0:未开始,1:异步任务运行中、 2:异步任务完成 、 3:异步任务运行失败。'."\n"
."\n"
.'当status = 2 时,result为模型预测的结果URL。',
'changeSet' => [],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'GetModelAsyncPredict'],
],
],
'ramActions' => [],
],
'PredictClassifierModel' => [
'summary' => '文档自学习分类器预测接口。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'read',
'deprecated' => false,
'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'ClassifierId',
'in' => 'query',
'schema' => ['description' => '分类器ID', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1'],
],
[
'name' => 'AutoPrediction',
'in' => 'query',
'schema' => ['description' => '是否开启自动预测,false:不开启, true:开启,默认开启', 'type' => 'boolean', 'required' => false, 'example' => 'true', 'default' => 'true'],
],
[
'name' => 'Content',
'in' => 'query',
'schema' => ['description' => '图片或pdf文件可访问地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/table.png'],
],
[
'name' => 'Body',
'in' => 'formData',
'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n"],
],
[
'name' => 'BinaryToText',
'in' => 'query',
'schema' => ['description' => 'content字段是图片URL时:false
body为base64的内容时:true', 'type' => 'boolean', 'required' => false, 'example' => 'false', 'default' => 'false'],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '232B91A8-9938-5C10-B522-127D1E342A57'],
'Code' => ['description' => '成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200'],
'Data' => ['description' => '返回数据。', 'type' => 'object', 'example' => '{'."\n"
.' "score": 1,'."\n"
.' "classID": "269_2b6819527769749d962bf51d034b1820",'."\n"
.' "tables": ['."\n"
.' {'."\n"
.' "columns": ['."\n"
.' {'."\n"
.' "header_value": "姓名",'."\n"
.' "bodies": ['."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生1",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 99'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 99'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 123'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 123'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生1"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生2",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 123'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 123'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 146'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 146'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生2"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生3",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 146'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 146'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 169'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 169'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生3"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生4",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 169'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 169'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 191'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 191'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生4"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生5",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 191'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 191'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 215'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 215'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生5"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生6",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 215'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 215'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 238'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 238'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生6"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生7",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 238'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 238'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 261'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 261'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生7"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生8",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 261'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 261'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 283'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 283'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生8"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生9",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 283'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 283'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 307'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 307'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生9"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "学生10",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 307'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 307'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 330'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 330'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": "学生10"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 330'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 330'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 352'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 352'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": ""'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 352'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 352'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 375'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 375'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": ""'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 375'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 375'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 399'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 399'."\n"
.' }'."\n"
.' ],'."\n"
.' "value": ""'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0,'."\n"
.' "fieldWordRaw": "",'."\n"
.' "wordInfo": [],'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 76,'."\n"
.' "y": 399'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 187,'."\n"
.' "y": 399'."\n"
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\\"y\\": 352\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 375\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 375\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 375\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 375\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 398\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 398\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 398\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 398\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 422\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 422\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 422\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 422\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 444\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 444\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 444\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 444\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 467\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 467\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 467\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 467\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 491\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 491\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 491\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 491\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 514\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 514\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 514\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 514\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 536\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 536\\n }\\n ],\\n \\"value\\": \\"\\"\\n },\\n {\\n \\"prob\\": 0,\\n \\"fieldWordRaw\\": \\"\\",\\n \\"wordInfo\\": [],\\n \\"location\\": [\\n {\\n \\"x\\": 406,\\n \\"y\\": 536\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 536\\n },\\n {\\n \\"x\\": 520,\\n \\"y\\": 559\\n },\\n {\\n \\"x\\": 406,\\n \\"y\\": 559\\n }\\n ],\\n \\"value\\": \\"\\"\\n }\\n ],\\n \\"header_box\\": [\\n {\\n \\"x\\": 430,\\n \\"y\\": 78\\n },\\n {\\n \\"x\\": 493,\\n \\"y\\": 78\\n },\\n {\\n \\"x\\": 493,\\n \\"y\\": 99\\n },\\n {\\n \\"x\\": 430,\\n \\"y\\": 99\\n }\\n ],\\n \\"col_name\\": \\"ID\\"\\n }\\n ],\\n \\"table_id\\": 1675670984484\\n }\\n ],\\n \\"code\\": 0,\\n \\"data\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"fieldWordRaw\\": \\"班级:初二3班\\",\\n \\"wordInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 2,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 51\\n },\\n {\\n \\"x\\": 2,\\n \\"y\\": 51\\n }\\n ],\\n \\"word\\": \\"班级:初二3班\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 2,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 18,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 18,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 2,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"班\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 18,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 32,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 32,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 18,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"级\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 34,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 50,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 50,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 34,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\":\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 52,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 71,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 71,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 52,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"初\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 72,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 88,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 88,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 72,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"二\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 90,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 100,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 100,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 90,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"3\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 103,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 34\\n },\\n {\\n \\"x\\": 124,\\n \\"y\\": 48\\n },\\n {\\n \\"x\\": 103,\\n \\"y\\": 48\\n }\\n ],\\n \\"word\\": \\"班\\"\\n }\\n ]\\n }\\n ],\\n \\"name\\": \\"班级\\",\\n \\"location\\": [\\n {\\n \\"x\\": 1,\\n \\"y\\": 30\\n },\\n {\\n \\"x\\": 1102,\\n \\"y\\": 30\\n },\\n {\\n \\"x\\": 1102,\\n \\"y\\": 54\\n },\\n {\\n \\"x\\": 1,\\n \\"y\\": 54\\n }\\n ],\\n \\"fieldWord\\": \\"班级:初二3班\\"\\n }\\n ],\\n \\"specificType\\": \\"infoCustomeTableTemp\\",\\n \\"className\\": \\"自定义表格模板测试cz02064-学生名\\",\\n \\"originalFileUrl\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D\\",\\n \\"templateID\\": \\"269_2b6819527769749d962bf51d034b1820\\",\\n \\"message\\": \\"\\",\\n \\"classType\\": \\"template\\",\\n \\"predictFile\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D\\"\\n },\\n \\"Message\\": \\"success\\"\\n}","type":"json"}]',
'title' => '分类器服务预测API',
'requestParamsDescription' => 'content字段和body字段传参二选一,图片URL则content为图片访问地址。内容为base64编码则传参body,且BinaryToText传true。'."\n"
."\n"
.'pdf限制20Mb,10页。'."\n"
.'除了长文档类型的模型预测以外,其他预测服务只会取第一页进行预测。',
'responseParamsDescription' => '分类器服务预测接口,返回Data字段解释说明:'."\n"
.'```json'."\n"
.'score 预测服务置信度 0-1'."\n"
.'data 算法返回的预测结果,数组格式 '."\n"
.'tables 表格区域预测结果'."\n"
.'prob 算法结果置信度 0-1 '."\n"
.'fieldName 抽取key '."\n"
.'fieldWord 抽取value '."\n"
.'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点 '."\n"
.'wordInfo 抽取内容详细信息,包括了每个字符的位置信息 '."\n"
.'specificType 算法类型(infoCustomeKvTemp:自定义KV 模板,infoCustomeTableTemp:自定义表格模板,ocr_infoExtractBill:信息抽取OCR识别,infoExtractBill:单据票证抽取,infoExtractDoc:长文档信息抽取 )'."\n"
.'classType 模型预测服务、模板预测服务 '."\n"
.'predictFile 预测文件地址(失效时间60分钟)'."\n"
.'```',
'changeSet' => [
['createdAt' => '2023-05-05T02:13:39.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-23T03:32:36.000Z', 'description' => '响应参数发生变更、响应参数发生变更'],
],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictClassifierModel'],
],
],
'ramActions' => [
[
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictClassifierModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
],
],
'PredictModel' => [
'summary' => '模型预测分为三种类型:长文档信息抽取、单票据信息抽取、表格信息抽取。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'read',
'deprecated' => false,
'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'Content',
'in' => 'query',
'schema' => ['description' => '图片或pdf文件访问URL地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png'],
],
[
'name' => 'ModelVersion',
'in' => 'query',
'schema' => ['description' => '模型对应的版本号,如果不传入版本号表示默认用模型最新生效的版本。', 'type' => 'string', 'required' => false, 'example' => '1'],
],
[
'name' => 'ModelId',
'in' => 'query',
'schema' => ['description' => '模型ID。模型列表页模型ID', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123'],
],
[
'name' => 'BinaryToText',
'in' => 'query',
'schema' => ['description' => 'content字段是图片URL时:false'."\n"
.'body为base64的内容时:true', 'type' => 'boolean', 'required' => false, 'example' => 'false:表示content传入的是url'."\n"
.'true:表示body是直接传入图片进行base64的内容', 'default' => 'false'],
],
[
'name' => 'Body',
'in' => 'formData',
'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n"],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'],
'Code' => ['description' => '请求结果状态,200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200'],
'Message' => ['description' => '错误信息。', 'type' => 'string', 'example' => 'success'],
'Data' => ['description' => '接口返回信息', 'type' => 'object', 'example' => '{'."\n"
.' "RequestId": "0C066DD3-F55D-18F7-8577-DE533E04054D",'."\n"
.' "Message": "",'."\n"
.' "Data": {'."\n"
.' "code": 200,'."\n"
.' "data": {'."\n"
.' "姓名": "xxx",'."\n"
.' "证号": "xxx",'."\n"
.' "性别": "女"'."\n"
.' },'."\n"
.' "specificType": "ocr_infoExtractBill",'."\n"
.' "originalFileUrl": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png",'."\n"
.' "message": "",'."\n"
.' "type": "卡证",'."\n"
.' "version": "1.0.9",'."\n"
.' "predictFile": "",'."\n"
.' "tim_img": "17",'."\n"
.' "score": 1.05,'."\n"
.' "wid": "1544",'."\n"
.' "hgt": "1054",'."\n"
.' "imageUrl": "",'."\n"
.' "angle": "0",'."\n"
.' "orig_hgt": "1054",'."\n"
.' "orig_wid": "1544",'."\n"
.' "tim_ocr": "97",'."\n"
.' "classType": "model",'."\n"
.' "info": ['."\n"
.' {'."\n"
.' "value_loc": "595,314,595,399,398,399,398,314",'."\n"
.' "key_prob": 1,'."\n"
.' "key_loc": "",'."\n"
.' "value_prob": 1,'."\n"
.' "value": "XXX",'."\n"
.' "key": "姓名"'."\n"
.' },'."\n"
.' {'."\n"
.' "value_loc": "1256,234,1256,312,678,312,678,233",'."\n"
.' "key_prob": 1,'."\n"
.' "key_loc": "",'."\n"
.' "value_prob": 1,'."\n"
.' "value": "440305198305101408",'."\n"
.' "key": "证号"'."\n"
.' },'."\n"
.' {'."\n"
.' "value_loc": "965,321,965,394,851,394,851,321",'."\n"
.' "key_prob": 1,'."\n"
.' "key_loc": "",'."\n"
.' "value_prob": 1,'."\n"
.' "value": "女",'."\n"
.' "key": "性别"'."\n"
.' }'."\n"
.' ]'."\n"
.' },'."\n"
.' "Code": 200'."\n"
.'}'],
],
],
],
],
'errorCodes' => [
200 => [
['errorCode' => '21002', 'errorMessage' => '模板预测超时 ', 'description' => ''],
['errorCode' => '21003', 'errorMessage' => '模板预测失败 ', 'description' => ''],
['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', 'description' => ''],
['errorCode' => '13018', 'errorMessage' => '未找到模型信息', 'description' => ''],
['errorCode' => '16004', 'errorMessage' => '指定的模型不存在', 'description' => ''],
['errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', 'description' => ''],
['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
],
],
'staticInfo' => ['returnType' => 'synchronous'],
'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"RequestId\\": \\"0C066DD3-F55D-18F7-8577-DE533E04054D\\",\\n \\"Message\\": \\"\\",\\n \\"Data\\": {\\n \\"code\\": 200,\\n \\"data\\": {\\n \\"姓名\\": \\"xxx\\",\\n \\"证号\\": \\"xxx\\",\\n \\"性别\\": \\"女\\"\\n },\\n \\"specificType\\": \\"ocr_infoExtractBill\\",\\n \\"originalFileUrl\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png\\",\\n \\"message\\": \\"\\",\\n \\"type\\": \\"卡证\\",\\n \\"version\\": \\"1.0.9\\",\\n \\"predictFile\\": \\"\\",\\n \\"tim_img\\": \\"17\\",\\n \\"score\\": 1.05,\\n \\"wid\\": \\"1544\\",\\n \\"hgt\\": \\"1054\\",\\n \\"imageUrl\\": \\"\\",\\n \\"angle\\": \\"0\\",\\n \\"orig_hgt\\": \\"1054\\",\\n \\"orig_wid\\": \\"1544\\",\\n \\"tim_ocr\\": \\"97\\",\\n \\"classType\\": \\"model\\",\\n \\"info\\": [\\n {\\n \\"value_loc\\": \\"595,314,595,399,398,399,398,314\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"XXX\\",\\n \\"key\\": \\"姓名\\"\\n },\\n {\\n \\"value_loc\\": \\"1256,234,1256,312,678,312,678,233\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"440305198305101408\\",\\n \\"key\\": \\"证号\\"\\n },\\n {\\n \\"value_loc\\": \\"965,321,965,394,851,394,851,321\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"女\\",\\n \\"key\\": \\"性别\\"\\n }\\n ]\\n },\\n \\"Code\\": 200\\n }\\n}","type":"json"}]',
'title' => '模型服务预测API',
'requestParamsDescription' => 'BinaryToText为非必填项。'."\n"
."\n"
.'content字段和body字段传参二选一,图片URL则content为图片访问地址。内容为base64编码则传参body,且BinaryToText传true。'."\n"
."\n"
.'pdf 限制20Mb 10页'."\n"
.'除了长文档类型的模型预测以外,其他预测服务只会取第一页进行预测。',
'responseParamsDescription' => '长文档信息抽取模型data返回字段解释说明:'."\n"
.'```json'."\n"
.'originalFileUrl 原始文件url'."\n"
.'predictFile 解析后用于预测的图片url集合'."\n"
.'data 具体预测结果'."\n"
.'angle 图片的角度,当NeedRotate为true时才会返回,0表示正向,90表示图片朝右,180朝下,270朝左'."\n"
.'content 识别出图片的文字块汇总'."\n"
.'height 算法矫正图片后的高度'."\n"
.'width 算法矫正图片后的宽度'."\n"
.'orgHeight 原图的高度'."\n"
.'orgWidth 原图的宽度'."\n"
.'prism_wnum 识别的文字块的数量,prism_wordsInfo数组的大小'."\n"
.'```'."\n"
.'prism-wordsInfo文字块数组内的字段说明'."\n"
.'```json'."\n"
.'angle 文字块的角度,这个角度只影响width和height,当角度为-90、90、-270、270,width和height的值需要自行互换'."\n"
.'height 文字块的高度'."\n"
.'width 文字块的宽度'."\n"
.'pos 文字块的外矩形四个点的坐标按顺时针排列,左上、右上、右下、左下,当NeedRotate为true时,如果最外层的angle不为0,需要按照angle矫正图片后,坐标才准确'."\n"
.'word 文字块的文字'."\n"
.'tableId 当OutputTable为true并且该文字块在表格内则存在该字段,tableId表示表格的id'."\n"
.'tableCellId 当OutputTable为true并且该文字块在表格内则存在该字段,表示表格中单元格的id'."\n"
.'```'."\n"
.'charInfo单字信息'."\n"
.'```json'."\n"
.'word 单字文字'."\n"
.'x 单字左上角横坐标'."\n"
.'y 单字左上角纵坐标'."\n"
.'w 单字宽度'."\n"
.'h 单字高度'."\n"
.'```'."\n"
.'prism-tablesInfo表格数组内的字段说明'."\n"
.'```json'."\n"
.'tableId 表格id,和prism_wordsInfo信息中的tableId对应'."\n"
.'xCellSize 表格中横坐标单元格的数量'."\n"
.'yCellSize 表格中纵坐标单元格的数量'."\n"
.'```'."\n"
.'cellInfos单元格信息,包含单元格在整个表格中的空间拓扑关系'."\n"
.'```json'."\n"
.'tableCellId 表格中单元格id,和prism_wordsInfo信息中的tableCellId对应'."\n"
.'word 单元格中的文字'."\n"
.'xsc xStartCell缩写,表示横轴方向该单元格起始在第几个单元格,第一个单元格值为0'."\n"
.'xec xEndCell缩写,表示横轴方向该单元格结束在第几个单元格,第一个单元格值为0,如果xsc和xec都为0说明该文字在横轴方向占据了一个单元格并且在第一个单元格内'."\n"
.'ysc yStartCell缩写,表示纵轴方向该单元格起始在第几个单元格,第一个单元格值为0'."\n"
.'yec yEndCell缩写,表示纵轴方向该单元格结束在第几个单元格,第一个单元格值为0'."\n"
.'pos 单元格位置,按照单元格四个角的坐标顺时针排列,分别为左上XY坐标、右上XY坐标、右下XY坐标、左下XY坐标'."\n"
.'```',
'changeSet' => [
['createdAt' => '2023-04-10T11:06:46.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-21T04:15:50.000Z', 'description' => '响应参数发生变更'],
],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictModel'],
],
],
'ramActions' => [],
],
'PredictPreTrainModel' => [
'summary' => '预置能力现有:UIE抽取,适用于通用智能预标注。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'read',
'deprecated' => false,
'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'Content',
'in' => 'query',
'schema' => ['description' => '预测内容,格式为JSON字符串。'."\n"
.'UIE抽取参数格式{"query":"xxx","schema":["字段1","字段2"]}, query对应图片URL,schema对应要抽取的字段数组', 'type' => 'string', 'required' => false, 'example' => '{"query":"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png", "schema":["姓名", "住址"]}'],
],
[
'name' => 'ServiceVersion',
'in' => 'query',
'schema' => ['description' => '预置能力服务版本,默认V1', 'type' => 'string', 'required' => false, 'example' => 'V1'],
],
[
'name' => 'ServiceName',
'in' => 'query',
'schema' => ['description' => '预置能力服务名称,必填'."\n"
.'UIE抽取对应“FormUIE”', 'type' => 'string', 'required' => false, 'example' => 'FormUIE'],
],
[
'name' => 'BinaryToText',
'in' => 'query',
'schema' => ['description' => 'content字段内容为图片URL时:false,'."\n"
.'body字段内容为图片base64时:true', 'type' => 'boolean', 'required' => false, 'example' => 'false', 'default' => 'false'],
],
[
'name' => 'Body',
'in' => 'formData',
'schema' => ['description' => '图片传递base64编码时的预测内容,格式为json字符串。'."\n"
.'UIE抽取参数格式{"query":"xxx","schema":["字段1","字段2"]}, query对应图片base64编码,schema对应要抽取的字段数组', 'type' => 'string', 'required' => false, 'example' => '{"query":"data:image/png;base64,xxxxx","schema":["姓名", "住址"]}'],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => '29413C69-11EF-15CB-BE20-70D318E2F4E9'],
'Code' => ['description' => '请求结果状态,200为成功', 'type' => 'integer', 'format' => 'int32', 'example' => '200'],
'Message' => ['description' => '错误信息', 'type' => 'string', 'example' => 'success'],
'Data' => ['description' => '接口返回信息', 'type' => 'object', 'example' => '{'."\n"
.' "RequestId": "29413C69-11EF-15CB-BE20-70D318E2F4E9",'."\n"
.' "Message": "success",'."\n"
.' "Data": {'."\n"
.' "score": 1,'."\n"
.' "data": ['."\n"
.' {'."\n"
.' "prob": 0.9138551354408264,'."\n"
.' "fieldWordRaw": "xx",'."\n"
.' "wordInfo": ['."\n"
.' {'."\n"
.' "prob": 0.9138551354408264,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 153'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 153'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "xx",'."\n"
.' "charInfo": ['."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 471,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 471,'."\n"
.' "y": 153'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 153'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 473,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 153'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 473,'."\n"
.' "y": 153'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' }'."\n"
.' ]'."\n"
.' }'."\n"
.' ],'."\n"
.' "name": "姓名",'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 139'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 476,'."\n"
.' "y": 153'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 468,'."\n"
.' "y": 153'."\n"
.' }'."\n"
.' ],'."\n"
.' "fieldWord": "xx"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.9594210982322693,'."\n"
.' "fieldWordRaw": "xxxxxxxxxxx",'."\n"
.' "wordInfo": ['."\n"
.' {'."\n"
.' "prob": 0.9594210982322693,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "xxxxxxxxxxx",'."\n"
.' "charInfo": ['."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 366,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 383,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 383,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 366,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 384,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 401,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 401,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 384,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 402,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 414,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 414,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 402,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 418,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 427,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 427,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 418,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 429,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 438,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 438,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 429,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 439,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 448,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 448,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 439,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 450,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 179'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 450,'."\n"
.' "y": 179'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 180,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 180,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 180,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 192,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 192,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 180,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 195,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 209,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 209,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 195,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "1"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 211,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 223,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 223,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 211,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "7"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 224,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 236,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 236,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 224,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "2"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 237,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 249,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 249,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 237,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "7"'."\n"
.' },'."\n"
.' {'."\n"
.' "prob": 0.99,'."\n"
.' "pos": ['."\n"
.' {'."\n"
.' "x": 253,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 270,'."\n"
.' "y": 224'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 270,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 253,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "word": "x"'."\n"
.' }'."\n"
.' ]'."\n"
.' }'."\n"
.' ],'."\n"
.' "name": "住址",'."\n"
.' "location": ['."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 164'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 467,'."\n"
.' "y": 239'."\n"
.' },'."\n"
.' {'."\n"
.' "x": 168,'."\n"
.' "y": 239'."\n"
.' }'."\n"
.' ],'."\n"
.' "fieldWord": "xxxxxxxx"'."\n"
.' }'."\n"
.' ],'."\n"
.' "specificType": "formuie-anti",'."\n"
.' "classType": "preDefinedServer",'."\n"
.' "predictFile": "https://xxxx"'."\n"
.' },'."\n"
.' "Code": 200'."\n"
.'}'],
],
],
],
],
'errorCodes' => [
200 => [
['errorCode' => '21002', 'errorMessage' => '模板预测超时', 'description' => ''],
['errorCode' => '21003', 'errorMessage' => '模版预测失败', 'description' => ''],
['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', 'description' => ''],
['errorCode' => '13018', 'errorMessage' => '未找到模型信息', 'description' => ''],
['errorCode' => '16004', 'errorMessage' => '指定模型不存在', 'description' => ''],
['errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', 'description' => ''],
['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
['errorCode' => '50008', 'errorMessage' => '文件过大', 'description' => ''],
['errorCode' => '50007', 'errorMessage' => '文件格式不支持', 'description' => ''],
['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
],
],
'staticInfo' => ['returnType' => 'synchronous'],
'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"29413C69-11EF-15CB-BE20-70D318E2F4E9\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"RequestId\\": \\"29413C69-11EF-15CB-BE20-70D318E2F4E9\\",\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"score\\": 1,\\n \\"data\\": [\\n {\\n \\"prob\\": 0.9138551354408264,\\n \\"fieldWordRaw\\": \\"xx\\",\\n \\"wordInfo\\": [\\n {\\n \\"prob\\": 0.9138551354408264,\\n \\"pos\\": [\\n {\\n \\"x\\": 468,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 476,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 476,\\n \\"y\\": 153\\n },\\n {\\n \\"x\\": 468,\\n \\"y\\": 153\\n }\\n ],\\n \\"word\\": \\"xx\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 468,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 471,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 471,\\n \\"y\\": 153\\n },\\n {\\n \\"x\\": 468,\\n \\"y\\": 153\\n }\\n ],\\n \\"word\\": \\"x\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n 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'title' => '预置能力服务预测API',
'requestParamsDescription' => 'BinaryToText为非必填项'."\n"
."\n"
.'content字段和body字段传参二选一,图片内容是URL,在传递content字段,内容是base64,传递body字段,且BinaryToText传true',
'responseParamsDescription' => '模板服务预测接口,返回Data字段解释说明:
'."\n"
.'score 预测服务置信度 0-1
'."\n"
.'data. 算法返回的预测结果,数组格式
'."\n"
.'prob 算法结果置信度 0-1
'."\n"
.'name 抽取key
'."\n"
.'fieldWord 抽取value
'."\n"
.'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点
'."\n"
.'wordInfo 抽取内容详细信息,包括了每个字符的位置信息
'."\n"
.'specificType 算法类型(formuie-anti:UIE抽取)
'."\n"
.'classType preDefinedServer: 预置能力
'."\n"
.'predictFile 预测文件地址(失效时间60分钟)',
'changeSet' => [],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictPreTrainModel'],
],
],
'ramActions' => [
[
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictPreTrainModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
],
],
'PredictTemplateModel' => [
'summary' => '模板服务预测目前包括两种类型:自定义KV模板和自定义表格模板。',
'methods' => ['post'],
'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
],
],
'operationType' => 'read',
'deprecated' => false,
'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'],
'parameters' => [
[
'name' => 'TaskId',
'in' => 'query',
'schema' => ['description' => '任务ID', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'example' => '1'],
],
[
'name' => 'Content',
'in' => 'query',
'schema' => ['description' => '图片或pdf文件访问URL地址', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/demo.png'],
],
[
'name' => 'BinaryToText',
'in' => 'query',
'schema' => ['description' => 'content字段是图片URL时:false'."\n"
.'body为base64的内容时:true', 'type' => 'boolean', 'required' => false, 'example' => 'false:表示content传入的是url'."\n"
.'true:表示body是直接传入图片进行base64的内容'."\n"],
],
[
'name' => 'Body',
'in' => 'formData',
'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
'description' => 'Schema of Response',
'type' => 'object',
'properties' => [
'RequestId' => ['title' => 'Id of the request', 'description' => 'Id of the request', 'type' => 'string', 'example' => 'F25FBAB4-665A-5D85-8AEF-39AE29F7D588'],
'Data' => ['description' => '返回数据', 'type' => 'object', 'example' => '{'."\n"
.' "score": 0.9091,'."\n"
.' "data": ['."\n"
.' {'."\n"
.' "prob": 1,'."\n"
.' "fieldName": "姓名",'."\n"
.' "fieldWordRaw": "方大呆",'."\n"
.' "wordInfo": ['."\n"
.' {'."\n"
.' "prob": 0.9899999999999999,'."\n"
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.' "y": 48'."\n"
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.' },'."\n"
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.' "fieldName": "性别",'."\n"
.' "fieldWordRaw": "男",'."\n"
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.' ],'."\n"
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.' },'."\n"
.' {'."\n"
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.' "fieldName": "身份证号",'."\n"
.' "fieldWordRaw": "310101********3222",'."\n"
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\\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"word\\": \\"汉\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 232,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"word\\": \\"汉\\"\\n }\\n ]\\n }\\n ],\\n \\"location\\": [\\n {\\n \\"x\\": 232,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 94\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 112\\n },\\n {\\n \\"x\\": 232,\\n \\"y\\": 112\\n }\\n ],\\n \\"fieldWord\\": \\"汉\\"\\n }\\n ],\\n \\"specificType\\": \\"infoCustomeKvTemp\\",\\n \\"width\\": 586,\\n \\"angle\\": 0,\\n \\"classType\\": \\"template\\",\\n \\"height\\": 374,\\n \\"predictFile\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/demo.png\\"\\n },\\n \\"Message\\": \\"successful\\",\\n \\"Code\\": \\"200\\"\\n}","type":"json"}]',
'title' => '模板服务预测API',
'requestParamsDescription' => 'content字段和body字段传参二选一,图片URL则content为图片访问地址。内容为base64编码则传参body,且BinaryToText传true。'."\n"
."\n"
.'pdf 限制20Mb 10页'."\n"
.'除长文档类型的模型预测以外,其他预测服务只会取第一页进行预测。',
'responseParamsDescription' => '```'."\n"
.'模板服务预测接口,返回Data字段解释说明:'."\n"
.'score 预测服务置信度 0-1 '."\n"
.'data. 算法返回的预测结果,数组格式'."\n"
.'prob 算法结果置信度 0-1 '."\n"
.'fieldName 抽取key'."\n"
.'fieldWord 抽取value'."\n"
.'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点'."\n"
.'wordInfo 抽取内容详细信息,包括了每个字符的位置信息'."\n"
.'specificType 算法类型(infoCustomeKvTemp:自定义KV 模板,infoCustomeTableTemp:自定义表格模板,ocr_infoExtractBill:信息抽取OCR识别,infoExtractBill:单据票证抽取,infoExtractDoc:长文档信息抽取 )'."\n"
.'classType 模型预测服务、模板预测服务'."\n"
.'predictFile 预测文件地址(失效时间60分钟)'."\n"
.'```',
'changeSet' => [
['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => '请求参数发生变更'],
['createdAt' => '2023-03-23T03:32:36.000Z', 'description' => '响应参数发生变更'],
],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictTemplateModel'],
],
],
'ramActions' => [],
],
],
'endpoints' => [
['regionId' => 'cn-beijing', 'regionName' => '华北2(北京)', 'areaId' => 'asiaPacific', 'areaName' => '亚太', 'public' => 'documentautoml.cn-beijing.aliyuncs.com', 'endpoint' => 'documentautoml.cn-beijing.aliyuncs.com', 'vpc' => 'documentautoml-vpc.cn-beijing.aliyuncs.com'],
],
'errorCodes' => [
['code' => 'AccountArrears', 'message' => 'Account arrears', 'http_code' => 200, 'description' => '账户欠费'],
['code' => 'AccountDatasetsExceeded', 'message' => 'The number of account data sets exceeded the threshold. Procedure', 'http_code' => 200, 'description' => '单一主账号数据集数量超过阈值'],
['code' => 'AccountHasNoService', 'message' => 'The account has no service', 'http_code' => 200, 'description' => '账号没有开通服务'],
['code' => 'AccountInformationError', 'message' => 'Account information error', 'http_code' => 200, 'description' => '账号信息错误'],
['code' => 'AccountNoPermission', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => '当前用户无访问权限,请联系主账号或权限管理员授权'],
['code' => 'AccountServiceOpenError', 'message' => 'Account service is not opened or overdue', 'http_code' => 200, 'description' => '账号服务没有开通或者欠费'],
['code' => 'AccountTypeNotSupported', 'message' => 'The account type is not supported', 'http_code' => 200, 'description' => '账号类型不支持'],
['code' => 'AddingDataNotSupported', 'message' => 'Adding data to this data set is not supported', 'http_code' => 200, 'description' => '暂不支持该数据集添加数据,请使用API创建数据集'],
['code' => 'CallLimit', 'message' => 'The call limit has been exceeded', 'http_code' => 200, 'description' => '调用额度已超出限制'],
['code' => 'ClassificationKeywordError', 'message' => 'The picture classification failed because of the keyword. Please check whether it is correct', 'http_code' => 200, 'description' => '因关键词导致图片分类失败,请检查关键词配置是否正确'],
['code' => 'ClassificationPhotoError', 'message' => 'Photo sets cause classification failure. Please check whether the configuration is correct', 'http_code' => 200, 'description' => '因图片集导致分类失败,请检查图片集配置是否正确'],
['code' => 'ClassifierAuthenticationException', 'message' => 'Classifier authentication exception', 'http_code' => 200, 'description' => '分类器鉴权异常'],
['code' => 'ClassifierFailedPublish', 'message' => 'The classifier failed to be published', 'http_code' => 200, 'description' => '分类器未发布成功'],
['code' => 'ClassifierInformationNotFound', 'message' => 'Classifier information not found', 'http_code' => 200, 'description' => '未找到分类器信息'],
['code' => 'ClassifierPredictionFailed', 'message' => 'Classifier prediction failed', 'http_code' => 200, 'description' => '分类器预测失败'],
['code' => 'ClassifierPredictsTimeout', 'message' => 'Classifier predicts timeout', 'http_code' => 200, 'description' => '分类器预测超时'],
['code' => 'ClusterIdDuplication', 'message' => 'Cluster id duplication', 'http_code' => 200, 'description' => '集群id重复'],
['code' => 'ConfigurationContentException', 'message' => 'Configuration content exception', 'http_code' => 200, 'description' => '配置内容异常'],
['code' => 'ConfigurationNameException', 'message' => 'Configuration name exception', 'http_code' => 200, 'description' => '配置名称异常'],
['code' => 'ConfigurationQueryError', 'message' => 'Configuration query failure', 'http_code' => 200, 'description' => '查询配置失败'],
['code' => 'ConfigurationQueryFailed', 'message' => 'Configuration query failure', 'http_code' => 200, 'description' => '查询配置失败'],
['code' => 'ConfigurationTypeException', 'message' => 'Configuration type exception', 'http_code' => 200, 'description' => '配置类型异常'],
['code' => 'ContentIsNull', 'message' => 'Content is null', 'http_code' => 200, 'description' => '内容为空'],
['code' => 'ContentLengthLimit', 'message' => 'The length of content exceeds the limit.', 'http_code' => 200, 'description' => '内容长度超过限制'],
['code' => 'CreateModelError', 'message' => 'The number of models created has reached the upper limit', 'http_code' => 200, 'description' => '创建模型数量已达上限'],
['code' => 'DataFormatError', 'message' => 'Data format error', 'http_code' => 200, 'description' => '数据格式错误'],
['code' => 'DataLookupException', 'message' => 'Data lookup exception', 'http_code' => 200, 'description' => '数据查找异常'],
['code' => 'DataPathEmpty', 'message' => 'The data path is empty', 'http_code' => 200, 'description' => '数据路径为空'],
['code' => 'DatasetMismatch', 'message' => 'Dataset field type mismatch', 'http_code' => 200, 'description' => '数据集字段类型匹配错误'],
['code' => 'DataStorageException', 'message' => 'Data storage exception', 'http_code' => 200, 'description' => '数据存储异常'],
['code' => 'DeployModelError', 'message' => 'The number of models online has reached its limit', 'http_code' => 200, 'description' => '模型在线数量已达上限,不能发布'],
['code' => 'DescriptionFailedToQueryKey', 'message' => 'Description Failed to query the configuration key', 'http_code' => 200, 'description' => '查询配置key失败'],
['code' => 'DOCFileTooEarly.UseDOCXVersion', 'message' => 'The version of the uploaded DOC file is too early. You are advised to use the latest DOCX version', 'http_code' => 200, 'description' => '上传的DOC文件类型的版本过低,不支持解析,建议替换为最新版本的DOCX'],
['code' => 'ErrorObtainingResource', 'message' => 'Error obtaining resource http', 'http_code' => 200, 'description' => '获取资源http异常'],
['code' => 'FailedCreateDateset', 'message' => 'Failed to create the dataset model without being online', 'http_code' => 200, 'description' => '没有在线的数据集模型创建失败'],
['code' => 'FailedMatchTemplate', 'message' => 'Failed to match the template', 'http_code' => 200, 'description' => '模板匹配失败'],
['code' => 'FileCannotEmpty', 'message' => 'The file cannot be empty', 'http_code' => 200, 'description' => '文件不能为空'],
['code' => 'FileFormatException', 'message' => 'The file format is abnormal. Procedure', 'http_code' => 200, 'description' => '文件格式适配异常'],
['code' => 'FileFormatNotSupported', 'message' => 'The file format is not supported', 'http_code' => 200, 'description' => '文件格式不支持'],
['code' => 'FileSizeCannotExceed500MB', 'message' => 'The file size cannot exceed 500MB', 'http_code' => 200, 'description' => '文件大小不能超过500MB'],
['code' => 'GlossaryDataNotFound', 'message' => 'Upload glossary data not found', 'http_code' => 200, 'description' => '未找到上传词表数据'],
['code' => 'HaveNoAuthority', 'message' => 'Have no authority', 'http_code' => 200, 'description' => '没有权限'],
['code' => 'IllegalState', 'message' => 'Illegal state', 'http_code' => 200, 'description' => '非法状态'],
['code' => 'InternalInvocationModelRestrictions', 'message' => 'Internal invocation model restrictions', 'http_code' => 200, 'description' => '内部调用模型限制'],
['code' => 'ItagServiceError', 'message' => 'itag service error', 'http_code' => 200, 'description' => 'itag服务错误'],
['code' => 'MappingRuleError', 'message' => 'The mapping rule condition is abnormal', 'http_code' => 200, 'description' => '映射规则条件异常'],
['code' => 'MappingRulesImplementError', 'message' => 'Mapping rules implement class exceptions', 'http_code' => 200, 'description' => '映射规则实现类异常'],
['code' => 'MappingRuleTypeError', 'message' => 'Mapping rule type is abnormal', 'http_code' => 200, 'description' => '映射规则type异常'],
['code' => 'MaximumNumberOfIterationsExceededLimit2', 'message' => 'The maximum number of iterations exceeded the upper limit 2', 'http_code' => 200, 'description' => '超出迭代模型最大上线个数:2'],
['code' => 'MethodUndefined', 'message' => 'Method undefined', 'http_code' => 200, 'description' => '方法未定义'],
['code' => 'ModelAuthenticationError', 'message' => 'Model authentication is abnormal', 'http_code' => 200, 'description' => '模型鉴权异常'],
['code' => 'ModelCreatefailed', 'message' => 'Model creation failure', 'http_code' => 200, 'description' => '模型创建失败'],
['code' => 'ModelDeleteFailed', 'message' => 'Model deletion failure', 'http_code' => 200, 'description' => '模型删除失败'],
['code' => 'ModelDoesNotExist.', 'message' => 'The specified Model does not exist.', 'http_code' => 200, 'description' => '指定的模型不存在'],
['code' => 'ModelGroupInformationNotFound', 'message' => 'Model group information not found', 'http_code' => 200, 'description' => '未找到模型组信息'],
['code' => 'ModelHasBeenDeleted', 'message' => 'The model has been deleted', 'http_code' => 200, 'description' => '模型已经被删除'],
['code' => 'ModelInferenceResultNullError', 'message' => 'The model inference result is null.', 'http_code' => 200, 'description' => '模型推理结果为空'],
['code' => 'ModelInferenceUnknownException', 'message' => 'Model inference unknown exception', 'http_code' => 200, 'description' => '模型推理未知异常'],
['code' => 'ModelNameFormatError', 'message' => 'The format of the model name is incorrect', 'http_code' => 200, 'description' => '模型名称格式错误'],
['code' => 'ModelNameMoreThan32Characters', 'message' => 'The model name is more than 32 characters long', 'http_code' => 200, 'description' => '模型名称超过32个字符'],
['code' => 'ModelNotFound', 'message' => 'Model not found', 'http_code' => 200, 'description' => '未找到模型'],
['code' => 'ModelPredictionTimeExceeds9s', 'message' => 'Model prediction time exceeds 9s', 'http_code' => 200, 'description' => '模型预测时间超过9s'],
['code' => 'ModelPretrainingInvalidResults', 'message' => 'Model pretraining predictions returned invalid results', 'http_code' => 200, 'description' => '模型预训练预测返回无效结果'],
['code' => 'ModelPublishFailed', 'message' => 'Model was not published successfully', 'http_code' => 200, 'description' => '模型未发布成功'],
['code' => 'ModelsExceeded', 'message' => 'The number of custom models exceeded the number of changed specifications', 'http_code' => 200, 'description' => '自定义模型数量已超变更规格数量,请删除自定义模型后进行变更'],
['code' => 'ModelTrainingMarksLessThan4', 'message' => 'The number of model training marks shall be no less than 4', 'http_code' => 200, 'description' => '模型训练标注条数不少于4条'],
['code' => 'ModelTrainingMarksMoreThan5000', 'message' => 'The number of model training marks is no more than 5000', 'http_code' => 200, 'description' => '模型训练标注条数不多于5000条'],
['code' => 'NoAccessPermission', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => '当前用户无访问权限,请联系主账号或权限管理员授权'],
['code' => 'NoAccessPermissionError', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => '当前用户无访问权限,请联系主账号或权限管理员授权'],
['code' => 'NoAssignableTasks', 'message' => 'There are no assignable tasks', 'http_code' => 200, 'description' => '没有可分配任务'],
['code' => 'NoMoreTasks', 'message' => 'There are no more tasks', 'http_code' => 200, 'description' => '没有更多的任务'],
['code' => 'NoPredictableModel', 'message' => 'There is no predictable model', 'http_code' => 200, 'description' => '没有可预测的模型'],
['code' => 'OCRService.NotFound', 'message' => 'ocr service not found', 'http_code' => 200, 'description' => 'ocr服务没找到'],
['code' => 'OCRServiceError', 'message' => 'The ocr service is abnormal', 'http_code' => 200, 'description' => 'ocr服务异常'],
['code' => 'OnlineModelError', 'message' => 'The number of models online has reached its limit', 'http_code' => 200, 'description' => '模型在线数量已达上限,不能操作上线'],
['code' => 'ParameterError', 'message' => 'Parameter error', 'http_code' => 200, 'description' => '参数出错'],
['code' => 'PictureNotMatch', 'message' => 'The picture does not match the service type', 'http_code' => 200, 'description' => '图片和服务类型不匹配'],
['code' => 'PredictedPostprocessingError', 'message' => 'Predicted postprocessing error', 'http_code' => 200, 'description' => '预测后处理错误'],
['code' => 'PredictionModelError', 'message' => 'Prediction model error, please check pvid', 'http_code' => 200, 'description' => '预测模型出错,请排查pvid'],
['code' => 'PredictivePreprocessingError', 'message' => 'Predictive preprocessing error', 'http_code' => 200, 'description' => '预测预处理错误'],
['code' => 'ProjectIdNotMatch', 'message' => 'The project Id does not match', 'http_code' => 200, 'description' => '项目Id不匹配'],
['code' => 'ProjectNotExis', 'message' => 'Project does not exis', 'http_code' => 200, 'description' => '项目不存在'],
['code' => 'ProjectOffline', 'message' => 'The project is offline', 'http_code' => 200, 'description' => '项目离线'],
['code' => 'ProjectTypeException', 'message' => 'Project type exception', 'http_code' => 200, 'description' => '项目类型异常'],
['code' => 'ServiceNotExist', 'message' => 'Service does not exist', 'http_code' => 200, 'description' => '服务不存在'],
['code' => 'ServiceNotOpened', 'message' => 'Service not opened', 'http_code' => 200, 'description' => '服务未开通'],
['code' => 'ServiceNotOpenError', 'message' => 'If you have not opened the platform service, please open the service first', 'http_code' => 200, 'description' => '未开通NLP自学习平台服务,请先开通服务'],
['code' => 'ServiceReadinessFailed', 'message' => 'Service readiness failure', 'http_code' => 200, 'description' => '服务准备失败'],
['code' => 'ServiceRestriction', 'message' => 'Service restriction', 'http_code' => 200, 'description' => '服务限制'],
['code' => 'SessionError', 'message' => 'SESSION fails to jump when API is called', 'http_code' => 200, 'description' => '调用API时SESSION失效跳转'],
['code' => 'SessionExpiration', 'message' => 'Session expiration', 'http_code' => 200, 'description' => '会话过期'],
['code' => 'SingleClassifierMaximum10qps', 'message' => 'Single classifier maximum 10qps', 'http_code' => 200, 'description' => '单分类器最高10qps'],
['code' => 'SingleModelMaximum20qps', 'message' => 'Single model maximum 20qps', 'http_code' => 200, 'description' => '单模型最高20qps'],
['code' => 'SingleModelUpTo10qps', 'message' => 'Single model version up to 10qps', 'http_code' => 200, 'description' => '单模板最高10qps'],
['code' => 'SourceLanguageAndTargetLanguageMustDifferent', 'message' => 'Source language The target language must be different', 'http_code' => 200, 'description' => '源语种目标语种不能相同'],
['code' => 'TaskInstanceEmpty', 'message' => 'The task instance is empty', 'http_code' => 200, 'description' => '任务实例为空'],
['code' => 'TaskInstanceNotFound', 'message' => 'The task instance could not be found', 'http_code' => 200, 'description' => '找不到任务实例'],
['code' => 'TasksAreHandledByOthers', 'message' => 'Tasks are handled by others', 'http_code' => 200, 'description' => '任务由他人处理'],
['code' => 'TaskWasDoneBySomeone', 'message' => 'The task was done by someone else', 'http_code' => 200, 'description' => '该任务被别人完成'],
['code' => 'TemplateAuthenticationError', 'message' => 'Template authentication is abnormal', 'http_code' => 200, 'description' => '模板鉴权异常'],
['code' => 'TemplateFailedToPublished', 'message' => 'Template failed to be published', 'http_code' => 200, 'description' => '模板未发布成功'],
['code' => 'TemplateInformationNotFound', 'message' => 'Template information not found', 'http_code' => 200, 'description' => '未找到模版信息'],
['code' => 'TemplatePredictionFailed', 'message' => 'Template prediction failed', 'http_code' => 200, 'description' => '模板预测失败'],
['code' => 'TemplatePredictionTimeout', 'message' => 'Template prediction timed out', 'http_code' => 200, 'description' => '模板预测超时'],
['code' => 'TemplateSubmissionFailed.Procedure', 'message' => 'Template submission failed. Procedure', 'http_code' => 200, 'description' => '模板提交失败'],
['code' => 'TooManyPredictiveTasksQueueUp', 'message' => 'Too many predictive tasks queue up', 'http_code' => 200, 'description' => '预测任务排队过多'],
['code' => 'TooManyUnfinishedTasks', 'message' => 'Too many unfinished tasks', 'http_code' => 200, 'description' => '过多未完成的任务'],
['code' => 'TrainingDataNotFound', 'message' => 'Training data not found', 'http_code' => 200, 'description' => '未找到训练数据'],
['code' => 'UnknownError', 'message' => 'Unknown anomaly', 'http_code' => 200, 'description' => '未知异常'],
['code' => 'UnknownError.PleaseTryAgain', 'message' => 'Unknown error, please try again', 'http_code' => 200, 'description' => '未知错误,请重试'],
['code' => 'UnknownInferenceServiceException', 'message' => 'Unknown inference service exception', 'http_code' => 200, 'description' => '未知的推理服务异常'],
['code' => 'UnsupportedCommodityTypes', 'message' => 'Unsupported commodity types', 'http_code' => 200, 'description' => '不支持的商品类型'],
['code' => 'UpdateRulesFailed', 'message' => 'update rules failed', 'http_code' => 200, 'description' => '规则更新失败'],
['code' => 'UploadDataError', 'message' => 'Upload data error', 'http_code' => 200, 'description' => '上传数据出错'],
['code' => 'UploadDataNotFound', 'message' => 'Upload data not found', 'http_code' => 200, 'description' => '未找到上传数据'],
['code' => 'WorkflowNameEmpty', 'message' => 'The workflow name is empty', 'http_code' => 200, 'description' => '工作流名称为空'],
['code' => 'WorkflowUnknownException', 'message' => 'Workflow unknown exception', 'http_code' => 200, 'description' => '工作流程未知异常'],
],
'changeSet' => [
[
'apis' => [
['description' => '请求参数发生变更', 'api' => 'PredictClassifierModel'],
],
'createdAt' => '2023-05-05T02:13:44.000Z',
'description' => '',
],
[
'apis' => [
['description' => '请求参数发生变更', 'api' => 'CreateModelAsyncPredict'],
['description' => '请求参数发生变更', 'api' => 'PredictClassifierModel'],
['description' => '请求参数发生变更', 'api' => 'PredictModel'],
['description' => '请求参数发生变更', 'api' => 'PredictTemplateModel'],
],
'createdAt' => '2023-04-10T11:06:52.000Z',
'description' => '',
],
[
'apis' => [
['description' => '请求参数发生变更', 'api' => 'CreateModelAsyncPredict'],
['description' => '请求参数发生变更', 'api' => 'PredictClassifierModel'],
['description' => '请求参数发生变更', 'api' => 'PredictModel'],
['description' => '请求参数发生变更', 'api' => 'PredictTemplateModel'],
],
'createdAt' => '2023-03-31T10:32:22.000Z',
'description' => '',
],
[
'apis' => [
['description' => '响应参数发生变更', 'api' => 'PredictModel'],
],
'createdAt' => '2023-03-24T08:20:43.000Z',
'description' => '',
],
[
'apis' => [
['description' => '响应参数发生变更、响应参数发生变更', 'api' => 'PredictClassifierModel'],
['description' => '响应参数发生变更', 'api' => 'PredictTemplateModel'],
],
'createdAt' => '2023-03-24T08:20:05.000Z',
'description' => '',
],
],
'flowControl' => [
'flowControlList' => [
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictPreTrainModel'],
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'CreateModelAsyncPredict'],
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictClassifierModel'],
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictModel'],
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictTemplateModel'],
['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'GetModelAsyncPredict'],
],
],
'ram' => [
'productCode' => 'DocumentAutoml',
'productName' => '文字识别',
'ramCodes' => ['documentautoml'],
'ramLevel' => '操作级',
'ramConditions' => [],
'ramActions' => [
[
'apiName' => 'PredictTemplateModel',
'description' => '模板服务预测API',
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictTemplateModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
[
'apiName' => 'PredictClassifierModel',
'description' => '分类器服务预测API',
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictClassifierModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
[
'apiName' => 'GetModelAsyncPredict',
'description' => '获取模型异步预测结果API',
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:GetModelAsyncPredict',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
[
'apiName' => 'PredictPreTrainModel',
'description' => '预置能力服务预测API',
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictPreTrainModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
[
'apiName' => 'PredictModel',
'description' => '模型服务预测API',
'operationType' => 'get',
'ramAction' => [
'action' => 'documentautoml:PredictModel',
'authLevel' => 'operate',
'actionConditions' => [],
'resources' => [
['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => '全部资源', 'arn' => '*'],
],
],
],
],
'resourceTypes' => [],
],
];