'1.0', 'info' => ['style' => 'RPC', 'product' => 'documentAutoml', 'version' => '2022-12-29'], 'directories' => ['CreateModelAsyncPredict', 'GetModelAsyncPredict', 'PredictClassifierModel', 'PredictModel', 'PredictPreTrainModel', 'PredictTemplateModel'], 'components' => [ 'schemas' => [], ], 'apis' => [ 'CreateModelAsyncPredict' => [ 'summary' => 'Creates an asynchronous prediction task for Document AutoML.', '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' => 'The model version. If unspecified, the latest active model version is used.', 'type' => 'string', 'required' => false, 'example' => 'V1', 'title' => ''], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => ['description' => 'Specifies how the document content is provided.', 'type' => 'boolean', 'default' => 'false', '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", 'title' => ''], ], [ 'name' => 'Content', 'in' => 'query', 'schema' => ['description' => 'The URL of the image or PDF file.', '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', 'title' => ''], ], [ 'name' => 'ModelId', 'in' => 'query', 'schema' => ['description' => 'The model ID. You can find this ID on the Model List Page in the console.', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123', 'title' => ''], ], [ 'name' => 'ServiceName', 'in' => 'query', 'schema' => ['description' => 'The name of the pre-trained service.', 'type' => 'string', 'required' => false, 'example' => 'pre_train_service', 'title' => ''], ], [ 'name' => 'ServiceVersion', 'in' => 'query', 'schema' => ['description' => 'The version of the pre-trained service.', 'type' => 'string', 'required' => false, 'example' => 'V1', 'title' => ''], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => ['description' => 'The Base64-encoded content of the document.', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx', 'title' => ''], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'The response object.', 'type' => 'object', 'properties' => [ 'RequestId' => ['title' => 'Id of the request', 'description' => 'The request ID.', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'], 'Code' => ['description' => 'The status code of the request. A value of `200` indicates that the request was successful.', 'type' => 'integer', 'format' => 'int32', 'example' => '200', 'title' => ''], 'Message' => ['description' => 'The error message.', 'type' => 'string', 'example' => 'success', 'title' => ''], 'Data' => ['description' => 'A JSON-formatted string that contains the result. The `Data` field within this string is the asynchronous task ID.', 'type' => 'string', 'example' => '{'."\n" .' "RequestId": "292D1584-134C-1221-B9BB-1B847C623D41",'."\n" .' "Message": "",'."\n" .' "Data": 1,'."\n" .' "Code": 200'."\n" .'}', 'title' => ''], ], 'example' => '', ], ], ], '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' => 'Model Asynchronous Prediction API', 'requestParamsDescription' => 'You must specify either the `Content` or `Body` parameter.'."\n" ."\n" .'When providing a document URL, use the `Content` parameter. When providing the document\'s content directly, use the `Body` parameter for the Base64-encoded content and set `BinaryToText` to `true`.'."\n" ."\n" .'PDF files are limited to 20 MB and 10 pages. All prediction services process only the first page, except for services that support the long document type.', 'responseParamsDescription' => 'The `Data` field returns a JSON string. The `Data` field within this string is the asynchronous task ID. Use this ID with the `GetModelAsyncPredict` operation to retrieve the prediction result.', 'changeSet' => [ ['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => 'Request parameters changed'], ], 'ramActions' => [], 'flowControl' => [ 'flowControlList' => [ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'CreateModelAsyncPredict'], ], ], ], 'GetModelAsyncPredict' => [ 'summary' => 'This operation retrieves the results of an asynchronous model prediction. Model prediction can extract information from three types of content: long documents, single receipts, and tables.', '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' => 'The unique identifier for the asynchronous prediction task.', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1', 'title' => ''], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'The root object of the response.', 'type' => 'object', 'properties' => [ 'RequestId' => ['title' => 'Id of the request', 'description' => 'The ID of the request.', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'], 'Code' => ['description' => 'The status of the request. A value of 200 indicates success.', 'type' => 'integer', 'format' => 'int32', 'example' => '200', 'title' => ''], 'Message' => ['description' => 'The message returned for the request.', 'type' => 'string', 'example' => 'success', 'title' => ''], 'Data' => ['description' => 'The data returned by the service. This field contains a stringified JSON object with details about the prediction.', '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" .'}', 'title' => ''], ], 'example' => '', ], ], ], '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' => 'API for retrieving asynchronous model prediction results ', 'responseParamsDescription' => 'The `status` field indicates the task status: `0` for Not Started, `1` for Running, `2` for Completed, and `3` for Failed.'."\n" ."\n" .'If the `status` is `2` (Completed), the `result` field provides a URL to the model prediction output in Object Storage Service (OSS).', 'changeSet' => [], 'flowControl' => [ 'flowControlList' => [ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'GetModelAsyncPredict'], ], ], 'ramActions' => [ [ 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:GetModelAsyncPredict', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], ], ], 'PredictClassifierModel' => [ 'summary' => 'Document self-learning classifier: Prediction API', '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' => 'The classifier ID.', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1', 'title' => ''], ], [ 'name' => 'AutoPrediction', 'in' => 'query', 'schema' => ['description' => 'Specifies whether to enable auto prediction. Valid values: `false` (disabled) and `true` (enabled). Default: `true`.', 'type' => 'boolean', 'default' => 'true', 'required' => false, 'example' => 'true', 'title' => ''], ], [ 'name' => 'Content', 'in' => 'query', 'schema' => ['description' => 'The publicly accessible URL of an image or a PDF file.', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/table.png', 'title' => ''], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => ['description' => 'The Base64-encoded content of the image.', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n", 'title' => ''], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => ['description' => 'Set to `false` when providing a file URL in the `Content` parameter.
Set to `true` when providing Base64-encoded content in the `Body` parameter.
', 'type' => 'boolean', 'default' => 'false', 'required' => false, 'example' => 'false', 'title' => ''], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'Response schema.', 'type' => 'object', 'properties' => [ 'RequestId' => ['title' => 'Id of the request', 'description' => 'A unique identifier for the request.', 'type' => 'string', 'example' => '232B91A8-9938-5C10-B522-127D1E342A57'], 'Code' => ['description' => 'The HTTP status code. A value of 200 indicates success.', 'type' => 'integer', 'format' => 'int32', 'example' => '200', 'title' => ''], 'Data' => ['description' => 'The response data.', '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" .' 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Use the `content` field for an image URL. For base64-encoded content, use the `body` field and set `BinaryToText` to true.'."\n" ."\n" .'PDF files are limited to 20 MB and 10 pages. All prediction services, except for long document model prediction, process only the first page.', 'responseParamsDescription' => 'The classifier service prediction API returns the following fields in the `Data` object:'."\n" ."\n" .'```json'."\n" .'score The prediction confidence, from 0.0 to 1.0.'."\n" .'data An array of the algorithm\'s prediction results.'."\n" .'tables Prediction results for detected table areas.'."\n" .'prob The confidence for a specific result, from 0.0 to 1.0.'."\n" .'fieldName The key of an extracted key-value pair.'."\n" .'fieldWord The value of an extracted key-value pair.'."\n" .'location The coordinates of the extracted result. For example, `{"x": 119, "y": 48}` represents a point on the page.'."\n" .'wordInfo Detailed information about the extracted content, including the location of each character.'."\n" .'specificType The prediction algorithm. Valid values include:'."\n" .' \'infoCustomeKvTemp\': A custom KV template.'."\n" .' \'infoCustomeTableTemp\': A custom table template.'."\n" .' \'infoExtractBill\': Form and receipt extraction.'."\n" .' \'infoExtractDoc\': Long document information extraction.'."\n" .' \'ocr_infoExtractBill\': Information extraction with OCR.'."\n" .'classType The prediction service type, either \'model prediction service\' or \'template prediction service\'.'."\n" .'predictFile A temporary URL for the prediction file. The URL expires in 60 minutes.'."\n" .'```', 'changeSet' => [ ['createdAt' => '2023-05-05T02:13:39.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-23T03:32:36.000Z', 'description' => 'Response parameters changed, Response parameters changed'], ], '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' => 'All Resource', 'arn' => '*'], ], ], ], ], ], 'PredictModel' => [ 'summary' => 'Model prediction supports information extraction from long documents, single receipts, and tables.', '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' => 'The URL of the image or PDF file.', 'type' => 'string', 'required' => false, 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png', 'title' => ''], ], [ 'name' => 'ModelVersion', 'in' => 'query', 'schema' => ['description' => 'The version of the model. If you do not specify this parameter, the system uses the latest active version of the model by default.', 'type' => 'string', 'required' => false, 'example' => '1', 'title' => ''], ], [ 'name' => 'ModelId', 'in' => 'query', 'schema' => ['description' => 'The model ID. You can find the model ID on the Model List page.', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'maximum' => '9999999999999', 'minimum' => '1', 'example' => '123', 'title' => ''], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => ['description' => 'Specifies how the input document is provided. Set this to `true` if you provide the document content as a base64-encoded string in the `Body` parameter. Set this to `false` if you provide the document\'s URL in the `Content` parameter.', 'type' => 'boolean', 'default' => 'false', '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', 'title' => ''], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => ['description' => 'The base64-encoded content of the image file. Use this parameter when `BinaryToText` is set to `true`.', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx'."\n", 'title' => ''], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'The response data.', 'type' => 'object', 'properties' => [ 'RequestId' => ['title' => 'Id of the request', 'description' => 'The request ID.', 'type' => 'string', 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4'], 'Code' => ['description' => 'The status code of the request. A value of `200` indicates success.', 'type' => 'integer', 'format' => 'int32', 'example' => '200', 'title' => ''], 'Message' => ['description' => 'The returned message. If the request fails, this parameter contains the error message.', 'type' => 'string', 'example' => 'success', 'title' => ''], 'Data' => ['description' => 'The returned data object.', '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" .'}', 'title' => ''], ], 'example' => '', ], ], ], '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' => 'Model Service Prediction API ', 'requestParamsDescription' => 'The `BinaryToText` parameter is optional.'."\n" ."\n" .'You must specify either the `Content` parameter with the document\'s URL or the `Body` parameter with the document\'s base64-encoded content. If you use the `Body` parameter, you must also set `BinaryToText` to `true`.'."\n" ."\n" .'PDF files are limited to 20 MB and 10 pages. For prediction types other than long-document extraction, the service processes only the first page.', 'responseParamsDescription' => 'The following describes the fields in the `Data` object for long-document information extraction.'."\n" ."\n" .'```json'."\n" .'originalFileUrl The URL of the original file.'."\n" .'predictFile An array of image URLs parsed from the document that are used for prediction.'."\n" .'data The detailed prediction results.'."\n" .'angle The rotation angle of the image. This field is returned only when `NeedRotate` is `true`. 0 indicates upright, 90 indicates rotated to the right, 180 indicates upside down, and 270 indicates rotated to the left.'."\n" .'content A summary of the text blocks recognized in the image.'."\n" .'height The height of the image after algorithmic correction.'."\n" .'width The width of the image after algorithmic correction.'."\n" .'orgHeight The height of the original image.'."\n" .'orgWidth The width of the original image.'."\n" .'prism_wnum The number of recognized text blocks, which is the size of the `prism_wordsInfo` array.'."\n" .'```'."\n" ."\n" .'The following describes the fields in the `prism_wordsInfo` array:'."\n" ."\n" .'```json'."\n" .'angle The angle of the text block. This angle only affects the `width` and `height` values. If the angle is -90, 90, -270, or 270, you must swap the `width` and `height` values.'."\n" .'height The height of the text block.'."\n" .'width The width of the text block.'."\n" .'pos The coordinates of the four points of the bounding rectangle for the text block, arranged clockwise: top-left, top-right, bottom-right, and bottom-left. If `NeedRotate` is `true` and the `angle` of the parent object is not 0, these coordinates are accurate only after you correct the image based on the parent `angle`.'."\n" .'word The text content of the block.'."\n" .'tableId This field exists if `OutputTable` is `true` and the text block is within a table. It indicates the ID of the table.'."\n" .'tableCellId This field exists if `OutputTable` is `true` and the text block is within a table. It indicates the ID of the table cell.'."\n" .'```'."\n" ."\n" .'The following describes the fields for single-character information (`charInfo`):'."\n" ."\n" .'```json'."\n" .'word The character.'."\n" .'x The x-coordinate of the character\'s top-left corner.'."\n" .'y The y-coordinate of the character\'s top-left corner.'."\n" .'w The width of the character.'."\n" .'h The height of the character.'."\n" .'```'."\n" ."\n" .'The following describes the fields in the `prism_tablesInfo` array:'."\n" ."\n" .'```json'."\n" .'tableId The ID of the table, which corresponds to the `tableId` in the `prism_wordsInfo` object.'."\n" .'xCellSize The number of cells along the x-axis (columns).'."\n" .'yCellSize The number of cells along the y-axis (rows).'."\n" .'```'."\n" ."\n" .'The following describes the fields for cell information (`cellInfos`), which includes the spatial topology of cells within the entire table:'."\n" ."\n" .'```json'."\n" .'tableCellId The ID of the table cell, which corresponds to the `tableCellId` in the `prism_wordsInfo` object.'."\n" .'word The text content of the cell.'."\n" .'xsc `xsc` (xStartCell): The starting column index of the cell. The index is 0-based.'."\n" .'xec `xec` (xEndCell): The ending column index of the cell. The index is 0-based. If `xsc` and `xec` are both 0, the cell spans one column and is in the first column.'."\n" .'ysc `ysc` (yStartCell): The starting row index of the cell. The index is 0-based.'."\n" .'yec `yec` (yEndCell): The ending row index of the cell. The index is 0-based.'."\n" .'pos The coordinates of the four corners of the cell, arranged clockwise: top-left (X,Y), top-right (X,Y), bottom-right (X,Y), and bottom-left (X,Y).'."\n" .'```', 'changeSet' => [ ['createdAt' => '2023-04-10T11:06:46.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-21T04:15:50.000Z', 'description' => 'Response parameters changed'], ], 'flowControl' => [ 'flowControlList' => [ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictModel'], ], ], 'ramActions' => [ [ 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], ], ], 'PredictPreTrainModel' => [ 'summary' => 'UIE extraction is a built-in capability used for general-purpose pre-labeling.', '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' => 'The prediction content, in JSON string format. For UIE extraction, the format is `{"query":"","schema":["",""]}`, where `query` specifies the image URL and `schema` specifies the fields to extract.', 'type' => 'string', 'required' => false, 'example' => '{"query":"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png", "schema":["姓名", "住址"]}', 'title' => ''], ], [ 'name' => 'ServiceVersion', 'in' => 'query', 'schema' => ['description' => 'The version of the pre-built capability service. The default value is `V1`.', 'type' => 'string', 'required' => false, 'example' => 'V1', 'title' => ''], ], [ 'name' => 'ServiceName', 'in' => 'query', 'schema' => ['description' => 'The name of the pre-built capability service. For UIE extraction, set this parameter to `FormUIE`.', 'type' => 'string', 'required' => false, 'example' => 'FormUIE', 'title' => ''], ], [ 'name' => 'BinaryToText', 'in' => 'query', 'schema' => ['description' => 'Set this parameter to `false` when the `Content` parameter contains an image URL. Set this parameter to `true` when the `Body` parameter contains Base64-encoded image data.', 'type' => 'boolean', 'default' => 'false', 'required' => false, 'example' => 'false', 'title' => ''], ], [ 'name' => 'Body', 'in' => 'formData', 'schema' => ['description' => 'The prediction content for a Base64-encoded image, in JSON string format. For UIE extraction, the format is `{"query":"","schema":["",""]}`, where `query` specifies the Base64-encoded image data and `schema` specifies the fields to extract.', 'type' => 'string', 'required' => false, 'example' => '{"query":"data:image/png;base64,xxxxx","schema":["姓名", "住址"]}', 'title' => ''], ], ], 'responses' => [ 200 => [ 'schema' => [ 'title' => 'Schema of Response', 'description' => 'The response object.', 'type' => 'object', 'properties' => [ 'RequestId' => ['title' => 'Id of the request', 'description' => 'A unique identifier for the request.', 'type' => 'string', 'example' => '29413C69-11EF-15CB-BE20-70D318E2F4E9'], 'Code' => ['description' => 'The request status. A value of `200` indicates that the request was successful.', 'type' => 'integer', 'format' => 'int32', 'example' => '200', 'title' => ''], 'Message' => ['description' => 'A message describing the request status. If the request fails, this parameter contains the error message.', 'type' => 'string', 'example' => 'success', 'title' => ''], 'Data' => ['description' => 'An object containing the extracted information.', '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" .' 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'."\n" .'`score`: The overall confidence score for the prediction, ranging from 0.0 to 1.0.
'."\n" .'`data`: An array of detailed prediction results returned by the model.
'."\n" .'`prob`: The confidence score for a specific extracted item, ranging from 0.0 to 1.0.
'."\n" .'`name`: The name of the extracted field, which is the key in a key-value pair.
'."\n" .'`fieldWord`: The value of the extracted field.
'."\n" .'`location`: The location of the extracted item on the page, specified as an array of x and y coordinates that form a bounding box. A single coordinate is represented as `{ "x": 119, "y": 48 }`.
'."\n" .'`wordInfo`: Details of the extracted content, including the location of each character.
'."\n" .'`specificType`: The algorithm type for the extraction. For example, `formuie-anti` indicates Universal Information Extraction (UIE).
'."\n" .'`classType`: The service classification. For example, `preDefinedServer` indicates a pre-built capability.
'."\n" .'`predictFile`: The prediction file URL, which expires in 60 minutes.









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\\"y\\": 302\\n },\\n {\\n \\"x\\": 482,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 467,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"2\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 484,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 499,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 499,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 484,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"2\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 501,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 516,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 516,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 501,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"2\\"\\n }\\n ]\\n }\\n ],\\n \\"location\\": [\\n {\\n \\"x\\": 206,\\n \\"y\\": 301\\n },\\n {\\n \\"x\\": 518,\\n \\"y\\": 301\\n },\\n {\\n \\"x\\": 518,\\n \\"y\\": 320\\n },\\n {\\n \\"x\\": 206,\\n \\"y\\": 320\\n }\\n ],\\n \\"fieldWord\\": \\"310101198610203222\\"\\n },\\n {\\n \\"prob\\": 1,\\n \\"fieldName\\": \\"名族\\",\\n \\"fieldWordRaw\\": \\"汉\\",\\n \\"wordInfo\\": [\\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 \\"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' => 'Template Service Prediction API ', 'requestParamsDescription' => 'You can use either the `content` or `body` parameter, but not both. Provide the image URL in `content`, or the base64-encoded content in `body` and set `BinaryToText` to `true`.'."\n" ."\n" .'PDF files are limited to 20 MB and 10 pages. Except for the long document prediction model, all other prediction services process only the first page.', 'responseParamsDescription' => '```'."\n" .'This section describes the fields in the `Data` object returned by the template service prediction API.'."\n" ."\n" .'score The confidence score of the prediction service, a float value between 0 and 1.'."\n" .'data An array of objects containing the prediction results returned by the algorithm.'."\n" .'prob The confidence score for the algorithm\'s result, a float value between 0 and 1.'."\n" .'fieldName The extracted key.'."\n" .'fieldWord The extracted value.'."\n" .'location The coordinates of the extraction result. For example, { "x": 119, "y": 48 } is a coordinate on the page.'."\n" .'wordInfo Detailed information about the extracted content, including the location of each character.'."\n" .'specificType The algorithm type. Valid values include: infoCustomKvTemp (custom key-value template), infoCustomTableTemp (custom table template), ocr_infoExtractBill (OCR for information extraction), infoExtractBill (form/receipt extraction), and infoExtractDoc (long document information extraction).'."\n" .'classType The type of prediction service, such as a model prediction service or a template service.'."\n" .'predictFile The URL of the file used for prediction, which expires in 60 minutes.'."\n" .'```', 'changeSet' => [ ['createdAt' => '2023-04-10T11:06:47.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-31T10:32:17.000Z', 'description' => 'Request parameters changed'], ['createdAt' => '2023-03-23T03:32:36.000Z', 'description' => 'Response parameters changed'], ], 'flowControl' => [ 'flowControlList' => [ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictTemplateModel'], ], ], 'ramActions' => [ [ 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictTemplateModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], ], ], ], 'endpoints' => [ ['regionId' => 'cn-beijing', 'regionName' => 'China (Beijing)', 'areaId' => 'asiaPacific', 'areaName' => 'Asia Pacific', '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' => ''], ['code' => 'AccountDatasetsExceeded', 'message' => 'The number of account data sets exceeded the threshold. Procedure', 'http_code' => 200, 'description' => ''], ['code' => 'AccountHasNoService', 'message' => 'The account has no service', 'http_code' => 200, 'description' => ''], ['code' => 'AccountInformationError', 'message' => 'Account information error', 'http_code' => 200, 'description' => ''], ['code' => 'AccountNoPermission', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => ''], ['code' => 'AccountServiceOpenError', 'message' => 'Account service is not opened or overdue', 'http_code' => 200, 'description' => ''], ['code' => 'AccountTypeNotSupported', 'message' => 'The account type is not supported', 'http_code' => 200, 'description' => ''], ['code' => 'AddingDataNotSupported', 'message' => 'Adding data to this data set is not supported', 'http_code' => 200, 'description' => ''], ['code' => 'CallLimit', 'message' => 'The call limit has been exceeded', 'http_code' => 200, 'description' => ''], ['code' => 'ClassificationKeywordError', 'message' => 'The picture classification failed because of the keyword. Please check whether it is correct', 'http_code' => 200, 'description' => ''], ['code' => 'ClassificationPhotoError', 'message' => 'Photo sets cause classification failure. Please check whether the configuration is correct', 'http_code' => 200, 'description' => ''], ['code' => 'ClassifierAuthenticationException', 'message' => 'Classifier authentication exception', 'http_code' => 200, 'description' => ''], ['code' => 'ClassifierFailedPublish', 'message' => 'The classifier failed to be published', 'http_code' => 200, 'description' => ''], ['code' => 'ClassifierInformationNotFound', 'message' => 'Classifier information not found', 'http_code' => 200, 'description' => ''], ['code' => 'ClassifierPredictionFailed', 'message' => 'Classifier prediction failed', 'http_code' => 200, 'description' => ''], ['code' => 'ClassifierPredictsTimeout', 'message' => 'Classifier predicts timeout', 'http_code' => 200, 'description' => ''], ['code' => 'ClusterIdDuplication', 'message' => 'Cluster id duplication', 'http_code' => 200, 'description' => ''], ['code' => 'ConfigurationContentException', 'message' => 'Configuration content exception', 'http_code' => 200, 'description' => ''], ['code' => 'ConfigurationNameException', 'message' => 'Configuration name exception', 'http_code' => 200, 'description' => ''], ['code' => 'ConfigurationQueryError', 'message' => 'Configuration query failure', 'http_code' => 200, 'description' => ''], ['code' => 'ConfigurationQueryFailed', 'message' => 'Configuration query failure', 'http_code' => 200, 'description' => ''], ['code' => 'ConfigurationTypeException', 'message' => 'Configuration type exception', 'http_code' => 200, 'description' => ''], ['code' => 'ContentIsNull', 'message' => 'Content is null', 'http_code' => 200, 'description' => ''], ['code' => 'ContentLengthLimit', 'message' => 'The length of content exceeds the limit.', 'http_code' => 200, 'description' => ''], ['code' => 'CreateModelError', 'message' => 'The number of models created has reached the upper limit', 'http_code' => 200, 'description' => ''], ['code' => 'DataFormatError', 'message' => 'Data format error', 'http_code' => 200, 'description' => ''], ['code' => 'DataLookupException', 'message' => 'Data lookup exception', 'http_code' => 200, 'description' => ''], ['code' => 'DataPathEmpty', 'message' => 'The data path is empty', 'http_code' => 200, 'description' => ''], ['code' => 'DatasetMismatch', 'message' => 'Dataset field type mismatch', 'http_code' => 200, 'description' => ''], ['code' => 'DataStorageException', 'message' => 'Data storage exception', 'http_code' => 200, 'description' => ''], ['code' => 'DeployModelError', 'message' => 'The number of models online has reached its limit', 'http_code' => 200, 'description' => ''], ['code' => 'DescriptionFailedToQueryKey', 'message' => 'Description Failed to query the configuration key', 'http_code' => 200, 'description' => ''], ['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' => ''], ['code' => 'ErrorObtainingResource', 'message' => 'Error obtaining resource http', 'http_code' => 200, 'description' => ''], ['code' => 'FailedCreateDateset', 'message' => 'Failed to create the dataset model without being online', 'http_code' => 200, 'description' => ''], ['code' => 'FailedMatchTemplate', 'message' => 'Failed to match the template', 'http_code' => 200, 'description' => ''], ['code' => 'FileCannotEmpty', 'message' => 'The file cannot be empty', 'http_code' => 200, 'description' => ''], ['code' => 'FileFormatException', 'message' => 'The file format is abnormal. Procedure', 'http_code' => 200, 'description' => ''], ['code' => 'FileFormatNotSupported', 'message' => 'The file format is not supported', 'http_code' => 200, 'description' => ''], ['code' => 'FileSizeCannotExceed500MB', 'message' => 'The file size cannot exceed 500MB', 'http_code' => 200, 'description' => ''], ['code' => 'GlossaryDataNotFound', 'message' => 'Upload glossary data not found', 'http_code' => 200, 'description' => ''], ['code' => 'HaveNoAuthority', 'message' => 'Have no authority', 'http_code' => 200, 'description' => ''], ['code' => 'IllegalState', 'message' => 'Illegal state', 'http_code' => 200, 'description' => ''], ['code' => 'InternalInvocationModelRestrictions', 'message' => 'Internal invocation model restrictions', 'http_code' => 200, 'description' => ''], ['code' => 'ItagServiceError', 'message' => 'itag service error', 'http_code' => 200, 'description' => ''], ['code' => 'MappingRuleError', 'message' => 'The mapping rule condition is abnormal', 'http_code' => 200, 'description' => ''], ['code' => 'MappingRulesImplementError', 'message' => 'Mapping rules implement class exceptions', 'http_code' => 200, 'description' => ''], ['code' => 'MappingRuleTypeError', 'message' => 'Mapping rule type is abnormal', 'http_code' => 200, 'description' => ''], ['code' => 'MaximumNumberOfIterationsExceededLimit2', 'message' => 'The maximum number of iterations exceeded the upper limit 2', 'http_code' => 200, 'description' => ''], ['code' => 'MethodUndefined', 'message' => 'Method undefined', 'http_code' => 200, 'description' => ''], ['code' => 'ModelAuthenticationError', 'message' => 'Model authentication is abnormal', 'http_code' => 200, 'description' => ''], ['code' => 'ModelCreatefailed', 'message' => 'Model creation failure', 'http_code' => 200, 'description' => ''], ['code' => 'ModelDeleteFailed', 'message' => 'Model deletion failure', 'http_code' => 200, 'description' => ''], ['code' => 'ModelDoesNotExist.', 'message' => 'The specified Model does not exist.', 'http_code' => 200, 'description' => ''], ['code' => 'ModelGroupInformationNotFound', 'message' => 'Model group information not found', 'http_code' => 200, 'description' => ''], ['code' => 'ModelHasBeenDeleted', 'message' => 'The model has been deleted', 'http_code' => 200, 'description' => ''], ['code' => 'ModelInferenceResultNullError', 'message' => 'The model inference result is null.', 'http_code' => 200, 'description' => ''], ['code' => 'ModelInferenceUnknownException', 'message' => 'Model inference unknown exception', 'http_code' => 200, 'description' => ''], ['code' => 'ModelNameFormatError', 'message' => 'The format of the model name is incorrect', 'http_code' => 200, 'description' => ''], ['code' => 'ModelNameMoreThan32Characters', 'message' => 'The model name is more than 32 characters long', 'http_code' => 200, 'description' => ''], ['code' => 'ModelNotFound', 'message' => 'Model not found', 'http_code' => 200, 'description' => ''], ['code' => 'ModelPredictionTimeExceeds9s', 'message' => 'Model prediction time exceeds 9s', 'http_code' => 200, 'description' => ''], ['code' => 'ModelPretrainingInvalidResults', 'message' => 'Model pretraining predictions returned invalid results', 'http_code' => 200, 'description' => ''], ['code' => 'ModelPublishFailed', 'message' => 'Model was not published successfully', 'http_code' => 200, 'description' => ''], ['code' => 'ModelsExceeded', 'message' => 'The number of custom models exceeded the number of changed specifications', 'http_code' => 200, 'description' => ''], ['code' => 'ModelTrainingMarksLessThan4', 'message' => 'The number of model training marks shall be no less than 4', 'http_code' => 200, 'description' => ''], ['code' => 'ModelTrainingMarksMoreThan5000', 'message' => 'The number of model training marks is no more than 5000', 'http_code' => 200, 'description' => ''], ['code' => 'NoAccessPermission', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => ''], ['code' => 'NoAccessPermissionError', 'message' => 'No access permission, please contact the master account or permission administrator for authorization', 'http_code' => 200, 'description' => ''], ['code' => 'NoAssignableTasks', 'message' => 'There are no assignable tasks', 'http_code' => 200, 'description' => ''], ['code' => 'NoMoreTasks', 'message' => 'There are no more tasks', 'http_code' => 200, 'description' => ''], ['code' => 'NoPredictableModel', 'message' => 'There is no predictable model', 'http_code' => 200, 'description' => ''], ['code' => 'OCRService.NotFound', 'message' => 'ocr service not found', 'http_code' => 200, 'description' => ''], ['code' => 'OCRServiceError', 'message' => 'The ocr service is abnormal', 'http_code' => 200, 'description' => ''], ['code' => 'OnlineModelError', 'message' => 'The number of models online has reached its limit', 'http_code' => 200, 'description' => ''], ['code' => 'ParameterError', 'message' => 'Parameter error', 'http_code' => 200, 'description' => ''], ['code' => 'PictureNotMatch', 'message' => 'The picture does not match the service type', 'http_code' => 200, 'description' => ''], ['code' => 'PredictedPostprocessingError', 'message' => 'Predicted postprocessing error', 'http_code' => 200, 'description' => ''], ['code' => 'PredictionModelError', 'message' => 'Prediction model error, please check pvid', 'http_code' => 200, 'description' => ''], ['code' => 'PredictivePreprocessingError', 'message' => 'Predictive preprocessing error', 'http_code' => 200, 'description' => ''], ['code' => 'ProjectIdNotMatch', 'message' => 'The project Id does not match', 'http_code' => 200, 'description' => ''], ['code' => 'ProjectNotExis', 'message' => 'Project does not exis', 'http_code' => 200, 'description' => ''], ['code' => 'ProjectOffline', 'message' => 'The project is offline', 'http_code' => 200, 'description' => ''], ['code' => 'ProjectTypeException', 'message' => 'Project type exception', 'http_code' => 200, 'description' => ''], ['code' => 'ServiceNotExist', 'message' => 'Service does not exist', 'http_code' => 200, 'description' => ''], ['code' => 'ServiceNotOpened', 'message' => 'Service not opened', 'http_code' => 200, 'description' => ''], ['code' => 'ServiceNotOpenError', 'message' => 'If you have not opened the platform service, please open the service first', 'http_code' => 200, 'description' => ''], ['code' => 'ServiceReadinessFailed', 'message' => 'Service readiness failure', 'http_code' => 200, 'description' => ''], ['code' => 'ServiceRestriction', 'message' => 'Service restriction', 'http_code' => 200, 'description' => ''], ['code' => 'SessionError', 'message' => 'SESSION fails to jump when API is called', 'http_code' => 200, 'description' => ''], ['code' => 'SessionExpiration', 'message' => 'Session expiration', 'http_code' => 200, 'description' => ''], ['code' => 'SingleClassifierMaximum10qps', 'message' => 'Single classifier maximum 10qps', 'http_code' => 200, 'description' => ''], ['code' => 'SingleModelMaximum20qps', 'message' => 'Single model maximum 20qps', 'http_code' => 200, 'description' => ''], ['code' => 'SingleModelUpTo10qps', 'message' => 'Single model version up to 10qps', 'http_code' => 200, 'description' => ''], ['code' => 'SourceLanguageAndTargetLanguageMustDifferent', 'message' => 'Source language The target language must be different', 'http_code' => 200, 'description' => ''], ['code' => 'TaskInstanceEmpty', 'message' => 'The task instance is empty', 'http_code' => 200, 'description' => ''], ['code' => 'TaskInstanceNotFound', 'message' => 'The task instance could not be found', 'http_code' => 200, 'description' => ''], ['code' => 'TasksAreHandledByOthers', 'message' => 'Tasks are handled by others', 'http_code' => 200, 'description' => ''], ['code' => 'TaskWasDoneBySomeone', 'message' => 'The task was done by someone else', 'http_code' => 200, 'description' => ''], ['code' => 'TemplateAuthenticationError', 'message' => 'Template authentication is abnormal', 'http_code' => 200, 'description' => ''], ['code' => 'TemplateFailedToPublished', 'message' => 'Template failed to be published', 'http_code' => 200, 'description' => ''], ['code' => 'TemplateInformationNotFound', 'message' => 'Template information not found', 'http_code' => 200, 'description' => ''], ['code' => 'TemplatePredictionFailed', 'message' => 'Template prediction failed', 'http_code' => 200, 'description' => ''], ['code' => 'TemplatePredictionTimeout', 'message' => 'Template prediction timed out', 'http_code' => 200, 'description' => ''], ['code' => 'TemplateSubmissionFailed.Procedure', 'message' => 'Template submission failed. Procedure', 'http_code' => 200, 'description' => ''], ['code' => 'TooManyPredictiveTasksQueueUp', 'message' => 'Too many predictive tasks queue up', 'http_code' => 200, 'description' => ''], ['code' => 'TooManyUnfinishedTasks', 'message' => 'Too many unfinished tasks', 'http_code' => 200, 'description' => ''], ['code' => 'TrainingDataNotFound', 'message' => 'Training data not found', 'http_code' => 200, 'description' => ''], ['code' => 'UnknownError', 'message' => 'Unknown anomaly', 'http_code' => 200, 'description' => ''], ['code' => 'UnknownError.PleaseTryAgain', 'message' => 'Unknown error, please try again', 'http_code' => 200, 'description' => ''], ['code' => 'UnknownInferenceServiceException', 'message' => 'Unknown inference service exception', 'http_code' => 200, 'description' => ''], ['code' => 'UnsupportedCommodityTypes', 'message' => 'Unsupported commodity types', 'http_code' => 200, 'description' => ''], ['code' => 'UpdateRulesFailed', 'message' => 'update rules failed', 'http_code' => 200, 'description' => ''], ['code' => 'UploadDataError', 'message' => 'Upload data error', 'http_code' => 200, 'description' => ''], ['code' => 'UploadDataNotFound', 'message' => 'Upload data not found', 'http_code' => 200, 'description' => ''], ['code' => 'WorkflowNameEmpty', 'message' => 'The workflow name is empty', 'http_code' => 200, 'description' => ''], ['code' => 'WorkflowUnknownException', 'message' => 'Workflow unknown exception', 'http_code' => 200, 'description' => ''], ], 'changeSet' => [ [ 'apis' => [ ['description' => 'Request parameters changed', 'api' => 'PredictClassifierModel'], ], 'createdAt' => '2023-05-05T02:13:44.000Z', 'description' => '', ], [ 'apis' => [ ['description' => 'Request parameters changed', 'api' => 'CreateModelAsyncPredict'], ['description' => 'Request parameters changed', 'api' => 'PredictClassifierModel'], ['description' => 'Request parameters changed', 'api' => 'PredictModel'], ['description' => 'Request parameters changed', 'api' => 'PredictTemplateModel'], ], 'createdAt' => '2023-04-10T11:06:52.000Z', 'description' => '', ], [ 'apis' => [ ['description' => 'Request parameters changed', 'api' => 'CreateModelAsyncPredict'], ['description' => 'Request parameters changed', 'api' => 'PredictClassifierModel'], ['description' => 'Request parameters changed', 'api' => 'PredictModel'], ['description' => 'Request parameters changed', 'api' => 'PredictTemplateModel'], ], 'createdAt' => '2023-03-31T10:32:22.000Z', 'description' => '', ], [ 'apis' => [ ['description' => 'Response parameters changed', 'api' => 'PredictModel'], ], 'createdAt' => '2023-03-24T08:20:43.000Z', 'description' => '', ], [ 'apis' => [ ['description' => 'Response parameters changed, Response parameters changed', 'api' => 'PredictClassifierModel'], ['description' => 'Response parameters changed', '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' => 'OCR', 'ramCodes' => ['documentautoml'], 'ramLevel' => 'OPERATION', 'ramConditions' => [], 'ramActions' => [ [ 'apiName' => 'PredictTemplateModel', 'description' => '', 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictTemplateModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], [ 'apiName' => 'PredictClassifierModel', 'description' => '', 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictClassifierModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], [ 'apiName' => 'GetModelAsyncPredict', 'description' => '', 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:GetModelAsyncPredict', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], [ 'apiName' => 'PredictPreTrainModel', 'description' => '', 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictPreTrainModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], [ 'apiName' => 'PredictModel', 'description' => '', 'operationType' => 'get', 'ramAction' => [ 'action' => 'documentautoml:PredictModel', 'authLevel' => 'operate', 'actionConditions' => [], 'resources' => [ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'], ], ], ], ], 'resourceTypes' => [], ], ];