diff options
Diffstat (limited to 'data/zh_cn/documentautoml/2022-12-29/api-docs.php')
| -rw-r--r-- | data/zh_cn/documentautoml/2022-12-29/api-docs.php | 7430 |
1 files changed, 3608 insertions, 3822 deletions
diff --git a/data/zh_cn/documentautoml/2022-12-29/api-docs.php b/data/zh_cn/documentautoml/2022-12-29/api-docs.php index 659edce..2441e42 100644 --- a/data/zh_cn/documentautoml/2022-12-29/api-docs.php +++ b/data/zh_cn/documentautoml/2022-12-29/api-docs.php @@ -1,86 +1,60 @@ <?php return [ 'version' => '1.0', - 'info' => [ - 'style' => 'RPC', - 'product' => 'documentAutoml', - 'version' => '2022-12-29', - ], - 'directories' => [ - 'PredictTemplateModel', - 'PredictModel', - 'PredictClassifierModel', - 'CreateModelAsyncPredict', - 'GetModelAsyncPredict', - 'PredictPreTrainModel', - ], + 'info' => ['style' => 'RPC', 'product' => 'documentAutoml', 'version' => '2022-12-29'], + 'directories' => ['PredictTemplateModel', 'PredictModel', 'PredictClassifierModel', 'CreateModelAsyncPredict', 'GetModelAsyncPredict', 'PredictPreTrainModel'], 'components' => [ 'schemas' => [], ], 'apis' => [ - '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', - ], + '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' => 'read', + 'operationType' => 'write', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'get', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + 'systemTags' => ['operationType' => 'create', 'riskType' => 'none', 'chargeType' => 'free'], 'parameters' => [ [ - 'name' => 'TaskId', + 'name' => 'ModelVersion', 'in' => 'query', - 'schema' => [ - 'description' => '任务ID', - 'type' => 'integer', - 'format' => 'int64', - 'required' => true, - 'example' => '1', - ], + '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/demo/demo.png', - ], + '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' => 'BinaryToText', + 'name' => 'ModelId', '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", - ], + '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', - ], + 'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'], ], ], 'responses' => [ @@ -90,831 +64,58 @@ '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" - .' "location": ['."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 199,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 199,'."\n" - .' "y": 69'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 69'."\n" - .' }'."\n" - .' ],'."\n" - .' "word": "方大呆",'."\n" - .' "charInfo": ['."\n" - .' {'."\n" - .' "prob": 0.99,'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 67'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 67'."\n" - .' }'."\n" - .' ],'."\n" - .' "word": "方"'."\n" - .' },'."\n" - .' {'."\n" - .' "prob": 0.99,'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 165,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 165,'."\n" - .' "y": 67'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 67'."\n" - .' }'."\n" - .' ],'."\n" - .' "word": "大"'."\n" - .' },'."\n" - .' {'."\n" - .' "prob": 0.99,'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 167,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 197,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 197,'."\n" - .' "y": 67'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 167,'."\n" - .' "y": 67'."\n" - .' }'."\n" - .' ],'."\n" - .' "word": "呆"'."\n" - .' }'."\n" - .' ]'."\n" - .' }'."\n" - .' ],'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 199,'."\n" - .' "y": 48'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 199,'."\n" - .' "y": 69'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 119,'."\n" - .' "y": 69'."\n" - .' }'."\n" - .' ],'."\n" - .' "fieldWord": "方大呆"'."\n" - .' },'."\n" - .' {'."\n" - .' "prob": 1,'."\n" - .' "fieldName": "性别",'."\n" - .' "fieldWordRaw": "男",'."\n" - .' "wordInfo": ['."\n" - .' {'."\n" - .' "prob": 0.99,'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 117,'."\n" - .' "y": 93'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 93'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 112'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 117,'."\n" - .' "y": 112'."\n" - .' }'."\n" - .' ],'."\n" - .' "word": "男",'."\n" - .' "charInfo": ['."\n" - .' {'."\n" - .' "prob": 0.99,'."\n" - .' "location": ['."\n" - .' {'."\n" - .' "x": 117,'."\n" - .' "y": 93'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 93'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 142,'."\n" - .' "y": 112'."\n" - .' },'."\n" - .' {'."\n" - .' "x": 117,'."\n" - .' 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\\"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" + '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" - .'```', - ], - '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', + .'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'], ], - 'schemes' => [ - 'http', - 'https', + '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' => [], @@ -922,67 +123,12 @@ ], 'operationType' => 'read', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'get', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + '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', + 'name' => 'AsyncPredictId', '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", - ], + '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' => [ @@ -992,198 +138,57 @@ '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" - .'}', - ], + '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 ', - ], - [ - 'errorCode' => '21003', - 'errorMessage' => '模板预测失败 ', - ], - [ - 'errorCode' => '10001', - 'errorMessage' => '参数出错', - ], - [ - 'errorCode' => '10005', - 'errorMessage' => '服务不存在', - ], - [ - 'errorCode' => '16001', - 'errorMessage' => '未找到可预测的模型', - ], - [ - 'errorCode' => '13018', - 'errorMessage' => '未找到模型信息', - ], - [ - 'errorCode' => '16004', - 'errorMessage' => '指定的模型不存在', - ], - [ - 'errorCode' => '23002', - 'errorMessage' => '获取资源HTTP异常', - ], - [ - 'errorCode' => '11002', - 'errorMessage' => '账号没有开通服务', - ], - [ - 'errorCode' => '19999', - 'errorMessage' => '未知异常', - ], + ['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" + '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" - .'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" - .'```', + .'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', - ], + 'methods' => ['post'], + 'schemes' => ['http', 'https'], 'security' => [ [ 'AK' => [], @@ -1191,66 +196,32 @@ ], 'operationType' => 'read', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'get', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + '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', - ], + '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', - ], + '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', - ], + '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", - ], + '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 <br>body为base64的内容时：true', - 'type' => 'boolean', - 'required' => false, - 'example' => 'false', - 'default' => 'false', - ], + 'schema' => ['description' => 'content字段是图片URL时：false <br>body为base64的内容时：true', 'type' => 'boolean', 'required' => false, 'example' => 'false', 'default' => 'false'], ], ], 'responses' => [ @@ -1260,1831 +231,1769 @@ '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" - .' 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\\"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" @@ -3105,104 +2014,70 @@ .'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" .'```', - ], - 'CreateModelAsyncPredict' => [ - 'summary' => '文档自学习创建异步预测任务接口。', - 'methods' => [ - 'post', + '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'], ], - 'schemes' => [ - 'http', - 'https', + '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' => 'write', + 'operationType' => 'read', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'create', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + 'systemTags' => ['operationType' => 'get', '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', - ], + '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' => 'ModelId', + 'name' => 'ModelVersion', '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', - ], + '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' => 'ServiceName', + 'name' => 'ModelId', 'in' => 'query', - 'schema' => [ - 'description' => '预训练服务名称', - 'type' => 'string', - 'required' => false, - 'example' => 'pre_train_service', - ], + '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' => 'ServiceVersion', + 'name' => 'BinaryToText', 'in' => 'query', - 'schema' => [ - 'description' => '预训练服务版本', - 'type' => 'string', - 'required' => false, - 'example' => 'V1', - ], + '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', - ], + 'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n"], ], ], 'responses' => [ @@ -3212,103 +2087,154 @@ '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" - .'}', - ], + '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 ', - ], - [ - 'errorCode' => '21003', - 'errorMessage' => '模板预测失败', - ], - [ - 'errorCode' => '10001', - 'errorMessage' => '参数出错', - ], - [ - 'errorCode' => '10005', - 'errorMessage' => '服务不存在', - ], - [ - 'errorCode' => '16001', - 'errorMessage' => '未找到可预测的模型', - ], - [ - 'errorCode' => '13018', - 'errorMessage' => '未找到模型信息', - ], - [ - 'errorCode' => '16004', - 'errorMessage' => '指定的模型不存在', - ], - [ - 'errorCode' => '23002', - 'errorMessage' => '获取资源HTTP异常', - ], - [ - 'errorCode' => '11002', - 'errorMessage' => '账号没有开通服务', - ], - [ - 'errorCode' => '19999', - 'errorMessage' => '未知异常', - ], + ['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', + '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' => 'Data字段为创建的异步任务ID，通过GetModelAsyncPredict获取结果', - ], - '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', + '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'], ], - 'schemes' => [ - 'http', - 'https', + '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' => [], @@ -3316,24 +2242,36 @@ ], 'operationType' => 'read', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'get', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + 'systemTags' => ['operationType' => 'get', 'riskType' => 'none', 'chargeType' => 'free'], 'parameters' => [ [ - 'name' => 'AsyncPredictId', + 'name' => 'Content', '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', - ], + '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' => [ @@ -3343,105 +2281,535 @@ '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" - .'}', - ], + '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" + .' 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'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' => [], @@ -3449,66 +2817,29 @@ ], 'operationType' => 'read', 'deprecated' => false, - 'systemTags' => [ - 'operationType' => 'get', - 'riskType' => 'none', - 'chargeType' => 'free', - ], + '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', + 'name' => 'TaskId', 'in' => 'query', - 'schema' => [ - 'description' => '预置能力服务版本，默认V1', - 'type' => 'string', - 'required' => false, - 'example' => 'V1', - ], + 'schema' => ['description' => '任务ID', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'example' => '1'], ], [ - 'name' => 'ServiceName', + 'name' => 'Content', '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', - ], + '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', - ], + '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"]}', - ], + 'schema' => ['description' => '图片base64编码内容', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'], ], ], 'responses' => [ @@ -3518,573 +2849,1028 @@ '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" - .' 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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" - .'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：<br>'."\n" - .'score 预测服务置信度 0-1 <br>'."\n" - .'data. 算法返回的预测结果，数组格式<br>'."\n" - .'prob 算法结果置信度 0-1 <br>'."\n" - .'name 抽取key<br>'."\n" - .'fieldWord 抽取value<br>'."\n" - .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点<br>'."\n" - .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息<br>'."\n" - .'specificType 算法类型（formuie-anti:UIE抽取）<br>'."\n" - .'classType preDefinedServer: 预置能力<br>'."\n" - .'predictFile 预测文件地址（失效时间60分钟）', + .'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' => [ [ - 'regionId' => 'cn-beijing', - 'endpoint' => 'documentautoml.cn-beijing.aliyuncs.com', + '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' => [], ], ]; |