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authorZhineng Li <im@zhineng.li>2026-07-12 17:11:17 +0800
committerZhineng Li <im@zhineng.li>2026-07-12 17:11:17 +0800
commit1c7f908ce09f98fdcbf79ed2a8ae21be60eaa634 (patch)
tree5f0857666365b7e40cdaa3733ebe1f3ba9e13c67 /data/en_us/documentautoml/2022-12-29
parent7347bac4ab7e136157fc94777e6cf87ef9e08599 (diff)
downloadafterglow-metadata-full-1c7f908ce09f98fdcbf79ed2a8ae21be60eaa634.tar.gz
afterglow-metadata-full-1c7f908ce09f98fdcbf79ed2a8ae21be60eaa634.zip
update APIs 20260712
Diffstat (limited to 'data/en_us/documentautoml/2022-12-29')
-rw-r--r--data/en_us/documentautoml/2022-12-29/api-docs.php4443
1 files changed, 3688 insertions, 755 deletions
diff --git a/data/en_us/documentautoml/2022-12-29/api-docs.php b/data/en_us/documentautoml/2022-12-29/api-docs.php
index 2b828ec..89f542e 100644
--- a/data/en_us/documentautoml/2022-12-29/api-docs.php
+++ b/data/en_us/documentautoml/2022-12-29/api-docs.php
@@ -1,184 +1,120 @@
<?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' => ['CreateModelAsyncPredict', 'GetModelAsyncPredict', 'PredictClassifierModel', 'PredictModel', 'PredictPreTrainModel', 'PredictTemplateModel'],
'components' => [
'schemas' => [],
],
'apis' => [
- 'PredictTemplateModel' => [
- 'summary' => '文档自学习模版模型预测接口',
- 'methods' => [
- 'post',
- ],
- 'schemes' => [
- 'http',
- 'https',
- ],
+ 'CreateModelAsyncPredict' => [
+ 'summary' => 'Creates an asynchronous prediction task for Document AutoML.',
+ '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' => '',
- 'type' => 'integer',
- 'format' => 'int64',
- 'required' => true,
- 'example' => '',
- ],
+ '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '',
- ],
+ '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' => 'BinaryToText',
+ 'name' => 'ModelId',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'boolean',
- 'required' => false,
- 'example' => '',
- ],
+ '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'data:image/png;base64,xxxxx',
- ],
+ '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' => 'Schema of Response',
+ 'description' => 'The response object.',
'type' => 'object',
'properties' => [
- 'RequestId' => [
- 'title' => 'Id of the request',
- 'description' => 'Id of the request',
- 'type' => 'string',
- 'example' => 'F25FBAB4-665A-5D85-8AEF-39AE29F7D588',
- ],
- 'Data' => [
- 'description' => '',
- 'type' => 'object',
- 'example' => '',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'successful',
- ],
- 'Code' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => '200',
- ],
+ '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',
- ],
- [
- 'errorCode' => '21003',
- 'errorMessage' => '模板预测失败',
- ],
- [
- 'errorCode' => '21004',
- 'errorMessage' => '模板提交失败 ',
- ],
- [
- 'errorCode' => '10001',
- 'errorMessage' => '参数出错 ',
- ],
- [
- 'errorCode' => '10005',
- 'errorMessage' => '服务不存在 ',
- ],
- [
- 'errorCode' => '21018',
- 'errorMessage' => '未找到模板信息 ',
- ],
- [
- 'errorCode' => '16001',
- 'errorMessage' => '未找到可预测的模型',
- ],
- [
- 'errorCode' => '16004',
- 'errorMessage' => '指定的模型不存在',
- ],
- [
- 'errorCode' => '23002',
- 'errorMessage' => '获取资源HTTP异常 ',
- ],
- [
- 'errorCode' => '22002',
- 'errorMessage' => 'ocr服务异常 ',
- ],
- [
- '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\\": \\"F25FBAB4-665A-5D85-8AEF-39AE29F7D588\\",\\n \\"Data\\": {\\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 \\"y\\": 112\\n }\\n ],\\n \\"word\\": \\"男\\"\\n }\\n ]\\n }\\n ],\\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 \\"fieldWord\\": \\"男\\"\\n },\\n {\\n \\"prob\\": 1,\\n \\"fieldName\\": \\"身份证号\\",\\n \\"fieldWordRaw\\": \\"310101********3222\\",\\n \\"wordInfo\\": [\\n {\\n \\"prob\\": 0.9899999999999998,\\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 \\"word\\": \\"310101198610203222\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 206,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 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{\\n \\"x\\": 344,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 359,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 359,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 344,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"8\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 361,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 376,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 376,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 361,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"6\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 380,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 395,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 395,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 380,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"1\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 396,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 411,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 411,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 396,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"0\\"\\n },\\n {\\n \\"prob\\": 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\\"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"}]',
- ],
- 'PredictModel' => [
- 'summary' => '文档自学习模型预测接口',
- 'methods' => [
- 'post',
+ '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'],
],
- 'schemes' => [
- 'http',
- 'https',
+ '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' => [],
@@ -186,158 +122,85 @@
],
'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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '',
- ],
- ],
- [
- 'name' => 'ModelVersion',
- 'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '1',
- ],
- ],
- [
- 'name' => 'ModelId',
- 'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int64',
- 'required' => true,
- 'maximum' => '9999999999999',
- 'minimum' => '1',
- 'example' => '123',
- ],
- ],
- [
- 'name' => 'BinaryToText',
+ 'name' => 'AsyncPredictId',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'boolean',
- 'required' => false,
- 'example' => '',
- 'default' => 'false',
- ],
- ],
- [
- 'name' => 'Body',
- 'in' => 'formData',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'data:image/png;base64,xxxxx'."\n",
- ],
+ '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' => 'Schema of Response',
+ 'description' => 'The root object of the 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' => '',
- 'type' => 'integer',
- 'format' => 'int32',
- 'example' => '200',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'success',
- ],
- 'Data' => [
- 'description' => '',
- 'type' => 'object',
- 'example' => '',
- ],
+ '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 ',
- ],
- [
- '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',
+ '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' => '*'],
+ ],
+ ],
+ ],
],
- '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"}]',
],
'PredictClassifierModel' => [
- 'summary' => '文档自学习分类器预测接口',
- 'methods' => [
- 'post',
- ],
- 'schemes' => [
- 'http',
- 'https',
- ],
+ 'summary' => 'Document self-learning classifier: Prediction API',
+ 'methods' => ['post'],
+ 'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
@@ -345,357 +208,2071 @@
],
'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' => '',
- 'type' => 'integer',
- 'format' => 'int64',
- 'required' => false,
- 'maximum' => '99999999999999',
- 'minimum' => '1',
- 'example' => '',
- ],
+ 'schema' => ['description' => 'The classifier ID.', 'type' => 'integer', 'format' => 'int64', 'required' => false, 'maximum' => '99999999999999', 'minimum' => '1', 'example' => '1', 'title' => ''],
],
[
'name' => 'AutoPrediction',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'boolean',
- 'required' => false,
- 'example' => 'true',
- 'default' => 'true',
- ],
+ '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '',
- ],
+ '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'data:image/png;base64,xxxxx'."\n",
- ],
+ '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' => [
- 'type' => 'boolean',
- 'required' => false,
- 'default' => 'false',
- ],
+ 'schema' => ['description' => 'Set to `false` when providing a file URL in the `Content` parameter.<br>Set to `true` when providing Base64-encoded content in the `Body` parameter.<br>', 'type' => 'boolean', 'default' => 'false', 'required' => false, 'example' => 'false', 'title' => ''],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
- 'description' => 'Schema of Response',
+ 'description' => 'Response schema.',
'type' => 'object',
'properties' => [
- 'RequestId' => [
- 'title' => 'Id of the request',
- 'description' => 'Id of the request',
- 'type' => 'string',
- 'example' => '232B91A8-9938-5C10-B522-127D1E342A57',
- ],
- 'Code' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int32',
- 'example' => '200',
- ],
- 'Data' => [
- 'description' => '',
- 'type' => 'object',
- 'example' => '',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'success',
- ],
+ '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"
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+ .' ],'."\n"
+ .' "fieldWord": "班级：初二3班"'."\n"
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+ .' ],'."\n"
+ .' "specificType": "infoCustomeTableTemp",'."\n"
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+ .' "originalFileUrl": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D",'."\n"
+ .' "templateID": "269_2b6819527769749d962bf51d034b1820",'."\n"
+ .' "message": "",'."\n"
+ .' "classType": "template",'."\n"
+ .' "predictFile": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D"'."\n"
+ .'}', 'title' => ''],
+ 'Message' => ['description' => 'Returns `success` or an empty string on success, or an error message on failure.', 'type' => 'string', 'example' => 'success', 'title' => ''],
],
+ 'example' => '',
],
],
],
'errorCodes' => [
200 => [
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- 'errorMessage' => '模板预测超时',
- ],
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- 'errorMessage' => '模板预测失败',
- ],
- [
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- ],
- [
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- 'errorMessage' => '参数出错',
- ],
- [
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- 'errorMessage' => '没有权限',
- ],
- [
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- 'errorMessage' => '非法状态',
- ],
- [
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- 'errorMessage' => '服务不存在',
- ],
- [
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- 'errorMessage' => '未找到模板信息',
- ],
- [
- 'errorCode' => '16001',
- 'errorMessage' => '未找到可预测的模型',
- ],
- [
- 'errorCode' => '16004',
- 'errorMessage' => '指定的模型不存在',
- ],
- [
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- 'errorMessage' => '获取资源HTTP异常',
- ],
- [
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- ],
- [
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- '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' => '21004', 'errorMessage' => '模板提交失败', 'description' => ''],
+ ['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
+ ['errorCode' => '10002', 'errorMessage' => '没有权限', 'description' => ''],
+ ['errorCode' => '10003', 'errorMessage' => '非法状态', 'description' => ''],
+ ['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
+ ['errorCode' => '21018', 'errorMessage' => '未找到模板信息', 'description' => ''],
+ ['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', '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' => '22002', 'errorMessage' => 'ocr服务异常', 'description' => ''],
+ ['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
+ ['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
],
],
- 'staticInfo' => [
- 'returnType' => 'synchronous',
- ],
+ 'staticInfo' => ['returnType' => 'synchronous'],
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- ],
- 'CreateModelAsyncPredict' => [
- 'summary' => '文档自学习创建异步预测任务接口',
- 'methods' => [
- 'post',
+ 'title' => 'Classifier Service Prediction API '."\n",
+ 'requestParamsDescription' => 'Provide either the `content` or `body` field. 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'],
],
- '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' => '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' => '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'V1',
- ],
- ],
- [
- 'name' => 'BinaryToText',
- 'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'boolean',
- 'required' => false,
- 'example' => '',
- 'default' => 'false',
- ],
- ],
- [
'name' => 'Content',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- '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' => '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' => 'ModelId',
+ 'name' => 'ModelVersion',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int64',
- 'required' => false,
- 'maximum' => '9999999999999',
- 'minimum' => '1',
- 'example' => '123',
- ],
+ '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' => 'ServiceName',
+ 'name' => 'ModelId',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'pre_train_service',
- ],
+ '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' => 'ServiceVersion',
+ 'name' => 'BinaryToText',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'V1',
- ],
+ '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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'data:image/png;base64,xxxxx',
- ],
+ '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' => 'Schema of Response',
+ 'description' => 'The response data.',
'type' => 'object',
'properties' => [
- 'RequestId' => [
- 'title' => 'Id of the request',
- 'description' => 'Id of the request',
- 'type' => 'string',
- 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4',
- ],
- 'Code' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int32',
- 'example' => '200',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'success',
- ],
- 'Data' => [
- 'description' => '',
- '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' => '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 ',
- ],
- [
- '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',
+ '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'],
],
- '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"}]',
- ],
- 'GetModelAsyncPredict' => [
- 'summary' => '获取文档自学习异步模型预测结果',
- 'methods' => [
- 'post',
+ 'flowControl' => [
+ 'flowControlList' => [
+ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictModel'],
+ ],
],
- 'schemes' => [
- 'http',
- 'https',
+ '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' => [],
@@ -703,128 +2280,571 @@
],
'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' => '',
- 'type' => 'integer',
- 'format' => 'int64',
- 'required' => true,
- 'maximum' => '99999999999999',
- 'minimum' => '1',
- 'example' => '1',
- ],
+ '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' => 'Schema of Response',
+ 'description' => 'The response object.',
'type' => 'object',
'properties' => [
- 'RequestId' => [
- 'title' => 'Id of the request',
- 'description' => 'Id of the request',
- 'type' => 'string',
- 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4',
- ],
- 'Code' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int32',
- 'example' => '200',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'success',
- ],
- 'Data' => [
- 'description' => '',
- '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' => '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"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 180,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 168,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 180,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 192,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 192,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 180,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 195,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 209,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 209,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 195,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "1"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 211,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 223,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 223,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 211,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "7"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 224,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 236,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 236,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 224,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "2"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 237,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 249,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 249,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 237,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "7"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 253,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 270,'."\n"
+ .' "y": 224'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 270,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 253,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "name": "住址",'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 168,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 168,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "fieldWord": "xxxxxxxx"'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "specificType": "formuie-anti",'."\n"
+ .' "classType": "preDefinedServer",'."\n"
+ .' "predictFile": "https://xxxx"'."\n"
+ .' },'."\n"
+ .' "Code": 200'."\n"
+ .'}', 'title' => ''],
],
+ 'example' => '',
],
],
],
'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' => '模版预测失败', 'description' => ''],
+ ['errorCode' => '10001', 'errorMessage' => '参数出错', 'description' => ''],
+ ['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', 'description' => ''],
+ ['errorCode' => '13018', 'errorMessage' => '未找到模型信息', 'description' => ''],
+ ['errorCode' => '16004', 'errorMessage' => '指定模型不存在', 'description' => ''],
+ ['errorCode' => '23002', 'errorMessage' => '获取资源HTTP异常', 'description' => ''],
+ ['errorCode' => '11002', 'errorMessage' => '账号没有开通服务', 'description' => ''],
+ ['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
+ ['errorCode' => '50008', 'errorMessage' => '文件过大', 'description' => ''],
+ ['errorCode' => '50007', 'errorMessage' => '文件格式不支持', 'description' => ''],
+ ['errorCode' => '10005', 'errorMessage' => '服务不存在', 'description' => ''],
],
],
- 'staticInfo' => [
- 'returnType' => 'synchronous',
- ],
- 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"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"}]',
- ],
- 'PredictPreTrainModel' => [
- 'summary' => '文档自学习预训练模型预测接口',
- 'methods' => [
- 'post',
+ 'staticInfo' => ['returnType' => 'synchronous'],
+ 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"29413C69-11EF-15CB-BE20-70D318E2F4E9\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"RequestId\\": \\"29413C69-11EF-15CB-BE20-70D318E2F4E9\\",\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"score\\": 1,\\n \\"data\\": [\\n {\\n \\"prob\\": 0.9138551354408264,\\n \\"fieldWordRaw\\": \\"xx\\",\\n \\"wordInfo\\": [\\n {\\n \\"prob\\": 0.9138551354408264,\\n \\"pos\\": [\\n {\\n \\"x\\": 468,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 476,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 476,\\n \\"y\\": 153\\n },\\n {\\n \\"x\\": 468,\\n \\"y\\": 153\\n }\\n ],\\n \\"word\\": \\"xx\\",\\n \\"charInfo\\": [\\n {\\n \\"prob\\": 0.99,\\n \\"pos\\": [\\n {\\n \\"x\\": 468,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 471,\\n \\"y\\": 139\\n },\\n {\\n \\"x\\": 471,\\n \\"y\\": 153\\n },\\n {\\n \\"x\\": 468,\\n \\"y\\": 153\\n }\\n ],\\n \\"word\\": \\"x\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n 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+ 'title' => 'Preset Capability Service Prediction API ',
+ 'requestParamsDescription' => 'The `BinaryToText` parameter is optional.'."\n"
+ ."\n"
+ .'Provide the image content using either the `content` parameter for an image URL or the `body` parameter for base64-encoded image data. When using the `body` parameter, you must also set `BinaryToText` to `true`.',
+ 'responseParamsDescription' => 'The `Data` object returned by the template service prediction API contains the following fields:<br>'."\n"
+ .'`score`: The overall confidence score for the prediction, ranging from 0.0 to 1.0.<br>'."\n"
+ .'`data`: An array of detailed prediction results returned by the model.<br>'."\n"
+ .'`prob`: The confidence score for a specific extracted item, ranging from 0.0 to 1.0.<br>'."\n"
+ .'`name`: The name of the extracted field, which is the key in a key-value pair.<br>'."\n"
+ .'`fieldWord`: The value of the extracted field.<br>'."\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 }`.<br>'."\n"
+ .'`wordInfo`: Details of the extracted content, including the location of each character.<br>'."\n"
+ .'`specificType`: The algorithm type for the extraction. For example, `formuie-anti` indicates Universal Information Extraction (UIE).<br>'."\n"
+ .'`classType`: The service classification. For example, `preDefinedServer` indicates a pre-built capability.<br>'."\n"
+ .'`predictFile`: The prediction file URL, which expires in 60 minutes.<br><br><br><br><br><br><br><br><br><br>',
+ 'changeSet' => [],
+ 'flowControl' => [
+ 'flowControlList' => [
+ ['threshold' => '100', 'countWindow' => 1, 'regionId' => '*', 'api' => 'PredictPreTrainModel'],
+ ],
],
- 'schemes' => [
- 'http',
- 'https',
+ 'ramActions' => [
+ [
+ 'operationType' => 'get',
+ 'ramAction' => [
+ 'action' => 'documentautoml:PredictPreTrainModel',
+ 'authLevel' => 'operate',
+ 'actionConditions' => [],
+ 'resources' => [
+ ['validationType' => 'always', 'product' => 'DocumentAutoml', 'resourceType' => 'All Resource', 'arn' => '*'],
+ ],
+ ],
+ ],
],
+ ],
+ 'PredictTemplateModel' => [
+ 'summary' => 'Template service prediction supports custom KV templates and custom table templates.',
+ 'methods' => ['post'],
+ 'schemes' => ['http', 'https'],
'security' => [
[
'AK' => [],
@@ -832,159 +2852,1072 @@
],
'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' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '',
- ],
- ],
- [
- 'name' => 'ServiceVersion',
+ 'name' => 'TaskId',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'V1',
- ],
+ 'schema' => ['description' => 'The task ID.', 'type' => 'integer', 'format' => 'int64', 'required' => true, 'example' => '1', 'title' => ''],
],
[
- 'name' => 'ServiceName',
+ 'name' => 'Content',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => 'FormUIE',
- ],
+ '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/demo.png', 'title' => ''],
],
[
'name' => 'BinaryToText',
'in' => 'query',
- 'schema' => [
- 'description' => '',
- 'type' => 'boolean',
- 'required' => false,
- 'example' => 'false',
- 'default' => 'false',
- ],
+ 'schema' => ['description' => 'Set this parameter to `false` if the `Content` parameter specifies a URL. Set this parameter to `true` if the `Body` parameter contains base64-encoded content.', '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", 'title' => ''],
],
[
'name' => 'Body',
'in' => 'formData',
- 'schema' => [
- 'description' => '',
- 'type' => 'string',
- 'required' => false,
- 'example' => '',
- ],
+ 'schema' => ['description' => 'The base64-encoded content of the image or PDF file.', 'type' => 'string', 'required' => false, 'example' => 'data:image/png;base64,xxxxx', 'title' => ''],
],
],
'responses' => [
200 => [
'schema' => [
'title' => 'Schema of Response',
- 'description' => 'Schema of Response',
+ 'description' => 'The top-level response object.',
'type' => 'object',
'properties' => [
- 'RequestId' => [
- 'title' => 'Id of the request',
- 'description' => 'Id of the request',
- 'type' => 'string',
- 'example' => '29413C69-11EF-15CB-BE20-70D318E2F4E9',
- ],
- 'Code' => [
- 'description' => '',
- 'type' => 'integer',
- 'format' => 'int32',
- 'example' => '200',
- ],
- 'Message' => [
- 'description' => '',
- 'type' => 'string',
- 'example' => 'success',
- ],
- 'Data' => [
- 'description' => '',
- 'type' => 'object',
- 'example' => '',
- ],
+ 'RequestId' => ['title' => 'Id of the request', 'description' => 'The unique identifier for the request.', 'type' => 'string', 'example' => 'F25FBAB4-665A-5D85-8AEF-39AE29F7D588'],
+ 'Data' => ['description' => 'The returned business data.', '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"
+ .' "y": 112'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "男"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' }'."\n"
+ .' ],'."\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"
+ .' "fieldWord": "男"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 1,'."\n"
+ .' "fieldName": "身份证号",'."\n"
+ .' "fieldWordRaw": "310101********3222",'."\n"
+ .' "wordInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.9899999999999998,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
+ .' "y": 301'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 518,'."\n"
+ .' "y": 301'."\n"
+ .' },'."\n"
+ .' {'."\n"
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+ .' "y": 320'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
+ .' "y": 320'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "310101198610203222",'."\n"
+ .' "charInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
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+ .' },'."\n"
+ .' {'."\n"
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+ .' {'."\n"
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+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
+ .' "y": 319'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "3"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 223,'."\n"
+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
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+ .' "y": 302'."\n"
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+ .' {'."\n"
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+ .' {'."\n"
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+ .' ],'."\n"
+ .' "word": "1"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
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+ .' }', 'title' => ''],
+ 'Message' => ['description' => 'The returned status message.', 'type' => 'string', 'example' => 'successful', 'title' => ''],
+ 'Code' => ['description' => 'The status code for the request. A value of `200` indicates success.', 'type' => 'string', 'example' => '200', 'title' => ''],
],
+ 'example' => '',
],
],
],
'errorCodes' => [
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- ],
- [
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+ ['errorCode' => '21003', 'errorMessage' => '模板预测失败', 'description' => ''],
+ ['errorCode' => '21004', 'errorMessage' => '模板提交失败 ', 'description' => ''],
+ ['errorCode' => '10001', 'errorMessage' => '参数出错 ', 'description' => ''],
+ ['errorCode' => '10005', 'errorMessage' => '服务不存在 ', 'description' => ''],
+ ['errorCode' => '21018', 'errorMessage' => '未找到模板信息 ', 'description' => ''],
+ ['errorCode' => '16001', 'errorMessage' => '未找到可预测的模型', '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' => '22002', 'errorMessage' => 'ocr服务异常 ', 'description' => ''],
+ ['errorCode' => '11002', 'errorMessage' => '账号没有开通服务 ', 'description' => ''],
+ ['errorCode' => '19999', 'errorMessage' => '未知异常', 'description' => ''],
+ ],
+ ],
+ 'staticInfo' => ['returnType' => 'synchronous'],
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223,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 223,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 206,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"3\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 223,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 238,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 238,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 223,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"1\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 240,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 255,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 255,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 240,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"0\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 259,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 274,\\n \\"y\\": 302\\n },\\n {\\n \\"x\\": 274,\\n \\"y\\": 319\\n },\\n {\\n \\"x\\": 259,\\n \\"y\\": 319\\n }\\n ],\\n \\"word\\": \\"1\\"\\n },\\n {\\n \\"prob\\": 0.99,\\n \\"location\\": [\\n {\\n \\"x\\": 276,\\n \\"y\\": 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\\"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' => '*'],
+ ],
],
- [
- 'errorCode' => '19999',
- 'errorMessage' => '未知异常',
+ ],
+ ],
+ ],
+ ],
+ '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' => ''],
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+ ['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' => ''],
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generated by cgit v1.2.3 (git 2.46.0) at 2026-07-12 22:36:26 +0000