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authorZhineng Li <[email protected]>2026-02-13 10:54:11 +0800
committerZhineng Li <[email protected]>2026-02-13 10:54:11 +0800
commit7347bac4ab7e136157fc94777e6cf87ef9e08599 (patch)
tree0dec367dac6e152161a6f7cc0dba6ebbef1f34a2 /data/zh_cn/documentautoml/2022-12-29
downloadacs-metadata-full-7347bac4ab7e136157fc94777e6cf87ef9e08599.tar.gz
acs-metadata-full-7347bac4ab7e136157fc94777e6cf87ef9e08599.zip
first commitHEADv1.0.0+20260212main
Diffstat (limited to 'data/zh_cn/documentautoml/2022-12-29')
-rw-r--r--data/zh_cn/documentautoml/2022-12-29/api-docs.php4090
1 files changed, 4090 insertions, 0 deletions
diff --git a/data/zh_cn/documentautoml/2022-12-29/api-docs.php b/data/zh_cn/documentautoml/2022-12-29/api-docs.php
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--- /dev/null
+++ b/data/zh_cn/documentautoml/2022-12-29/api-docs.php
@@ -0,0 +1,4090 @@
+<?php return [
+ 'version' => '1.0',
+ 'info' => [
+ 'style' => 'RPC',
+ 'product' => 'documentAutoml',
+ 'version' => '2022-12-29',
+ ],
+ 'directories' => [
+ 'PredictTemplateModel',
+ 'PredictModel',
+ 'PredictClassifierModel',
+ 'CreateModelAsyncPredict',
+ 'GetModelAsyncPredict',
+ 'PredictPreTrainModel',
+ ],
+ 'components' => [
+ 'schemas' => [],
+ ],
+ 'apis' => [
+ 'PredictTemplateModel' => [
+ 'summary' => '模板服务预测目前包括两种类型：自定义KV模板和自定义表格模板。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'read',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'get',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'TaskId',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '任务ID',
+ 'type' => 'integer',
+ 'format' => 'int64',
+ 'required' => true,
+ 'example' => '1',
+ ],
+ ],
+ [
+ 'name' => 'Content',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '图片或pdf文件访问URL地址',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/demo.png',
+ ],
+ ],
+ [
+ 'name' => 'BinaryToText',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => 'content字段是图片URL时：false'."\n"
+ .'body为base64的内容时：true',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'false：表示content传入的是url'."\n"
+ .'true：表示body是直接传入图片进行base64的内容'."\n",
+ ],
+ ],
+ [
+ 'name' => 'Body',
+ 'in' => 'formData',
+ 'schema' => [
+ 'description' => '图片base64编码内容',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'data:image/png;base64,xxxxx',
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => 'F25FBAB4-665A-5D85-8AEF-39AE29F7D588',
+ ],
+ 'Data' => [
+ 'description' => '返回数据',
+ 'type' => 'object',
+ 'example' => '{'."\n"
+ .' "score": 0.9091,'."\n"
+ .' "data": ['."\n"
+ .' {'."\n"
+ .' "prob": 1,'."\n"
+ .' "fieldName": "姓名",'."\n"
+ .' "fieldWordRaw": "方大呆",'."\n"
+ .' "wordInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.9899999999999999,'."\n"
+ .' "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"
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+ .' {'."\n"
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+ .' },'."\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"
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+ .' },'."\n"
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+ .' {'."\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"
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+ .' {'."\n"
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+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 482,'."\n"
+ .' "y": 319'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 319'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "2"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 484,'."\n"
+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 499,'."\n"
+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 499,'."\n"
+ .' "y": 319'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 484,'."\n"
+ .' "y": 319'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "2"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 501,'."\n"
+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 516,'."\n"
+ .' "y": 302'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 516,'."\n"
+ .' "y": 319'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 501,'."\n"
+ .' "y": 319'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "2"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
+ .' "y": 301'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 518,'."\n"
+ .' "y": 301'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 518,'."\n"
+ .' "y": 320'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 206,'."\n"
+ .' "y": 320'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "fieldWord": "310101198610203222"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 1,'."\n"
+ .' "fieldName": "名族",'."\n"
+ .' "fieldWordRaw": "汉",'."\n"
+ .' "wordInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 112'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 112'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "汉",'."\n"
+ .' "charInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 112'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 112'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "汉"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 94'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 259,'."\n"
+ .' "y": 112'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 232,'."\n"
+ .' "y": 112'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "fieldWord": "汉"'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "specificType": "infoCustomeKvTemp",'."\n"
+ .' "width": 586,'."\n"
+ .' "angle": 0,'."\n"
+ .' "classType": "template",'."\n"
+ .' "height": 374,'."\n"
+ .' "predictFile": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/demo.png"'."\n"
+ .' }',
+ ],
+ 'Message' => [
+ 'description' => '返回消息',
+ 'type' => 'string',
+ 'example' => 'successful',
+ ],
+ 'Code' => [
+ 'description' => '状态码。说明 200表示成功。',
+ 'type' => 'string',
+ 'example' => '200',
+ ],
+ ],
+ ],
+ ],
+ ],
+ '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',
+ ],
+ ],
+ ],
+ 'staticInfo' => [
+ 'returnType' => 'synchronous',
+ ],
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\\"200\\"\\n}","type":"json"}]',
+ 'title' => '模板服务预测API',
+ 'requestParamsDescription' => 'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n"
+ ."\n"
+ .'pdf 限制20Mb 10页'."\n"
+ .'除长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。',
+ 'responseParamsDescription' => '```'."\n"
+ .'模板服务预测接口，返回Data字段解释说明：'."\n"
+ .'score 预测服务置信度 0-1 '."\n"
+ .'data. 算法返回的预测结果，数组格式'."\n"
+ .'prob 算法结果置信度 0-1 '."\n"
+ .'fieldName 抽取key'."\n"
+ .'fieldWord 抽取value'."\n"
+ .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点'."\n"
+ .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息'."\n"
+ .'specificType 算法类型（infoCustomeKvTemp:自定义KV 模板，infoCustomeTableTemp:自定义表格模板，ocr_infoExtractBill:信息抽取OCR识别，infoExtractBill:单据票证抽取，infoExtractDoc:长文档信息抽取 ）'."\n"
+ .'classType 模型预测服务、模板预测服务'."\n"
+ .'predictFile 预测文件地址（失效时间60分钟）'."\n"
+ .'```',
+ ],
+ 'PredictModel' => [
+ 'summary' => '模型预测分为三种类型：长文档信息抽取、单票据信息抽取、表格信息抽取。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'read',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'get',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'Content',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '图片或pdf文件访问URL地址',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png',
+ ],
+ ],
+ [
+ 'name' => 'ModelVersion',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '模型对应的版本号，如果不传入版本号表示默认用模型最新生效的版本。',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => '1',
+ ],
+ ],
+ [
+ 'name' => 'ModelId',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '模型ID。模型列表页模型ID',
+ 'type' => 'integer',
+ 'format' => 'int64',
+ 'required' => true,
+ 'maximum' => '9999999999999',
+ 'minimum' => '1',
+ 'example' => '123',
+ ],
+ ],
+ [
+ 'name' => 'BinaryToText',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => 'content字段是图片URL时：false'."\n"
+ .'body为base64的内容时：true',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'false：表示content传入的是url'."\n"
+ .'true：表示body是直接传入图片进行base64的内容',
+ 'default' => 'false',
+ ],
+ ],
+ [
+ 'name' => 'Body',
+ 'in' => 'formData',
+ 'schema' => [
+ 'description' => '图片base64编码内容',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'data:image/png;base64,xxxxx'."\n",
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4',
+ ],
+ 'Code' => [
+ 'description' => '请求结果状态，200为成功',
+ 'type' => 'integer',
+ 'format' => 'int32',
+ 'example' => '200',
+ ],
+ 'Message' => [
+ 'description' => '错误信息。',
+ 'type' => 'string',
+ 'example' => 'success',
+ ],
+ 'Data' => [
+ 'description' => '接口返回信息',
+ 'type' => 'object',
+ 'example' => '{'."\n"
+ .' "RequestId": "0C066DD3-F55D-18F7-8577-DE533E04054D",'."\n"
+ .' "Message": "",'."\n"
+ .' "Data": {'."\n"
+ .' "code": 200,'."\n"
+ .' "data": {'."\n"
+ .' "姓名": "xxx",'."\n"
+ .' "证号": "xxx",'."\n"
+ .' "性别": "女"'."\n"
+ .' },'."\n"
+ .' "specificType": "ocr_infoExtractBill",'."\n"
+ .' "originalFileUrl": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png",'."\n"
+ .' "message": "",'."\n"
+ .' "type": "卡证",'."\n"
+ .' "version": "1.0.9",'."\n"
+ .' "predictFile": "",'."\n"
+ .' "tim_img": "17",'."\n"
+ .' "score": 1.05,'."\n"
+ .' "wid": "1544",'."\n"
+ .' "hgt": "1054",'."\n"
+ .' "imageUrl": "",'."\n"
+ .' "angle": "0",'."\n"
+ .' "orig_hgt": "1054",'."\n"
+ .' "orig_wid": "1544",'."\n"
+ .' "tim_ocr": "97",'."\n"
+ .' "classType": "model",'."\n"
+ .' "info": ['."\n"
+ .' {'."\n"
+ .' "value_loc": "595,314,595,399,398,399,398,314",'."\n"
+ .' "key_prob": 1,'."\n"
+ .' "key_loc": "",'."\n"
+ .' "value_prob": 1,'."\n"
+ .' "value": "XXX",'."\n"
+ .' "key": "姓名"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "value_loc": "1256,234,1256,312,678,312,678,233",'."\n"
+ .' "key_prob": 1,'."\n"
+ .' "key_loc": "",'."\n"
+ .' "value_prob": 1,'."\n"
+ .' "value": "440305198305101408",'."\n"
+ .' "key": "证号"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "value_loc": "965,321,965,394,851,394,851,321",'."\n"
+ .' "key_prob": 1,'."\n"
+ .' "key_loc": "",'."\n"
+ .' "value_prob": 1,'."\n"
+ .' "value": "女",'."\n"
+ .' "key": "性别"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' },'."\n"
+ .' "Code": 200'."\n"
+ .'}',
+ ],
+ ],
+ ],
+ ],
+ ],
+ 'errorCodes' => [
+ 200 => [
+ [
+ 'errorCode' => '21002',
+ 'errorMessage' => '模板预测超时 ',
+ ],
+ [
+ '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',
+ ],
+ ],
+ ],
+ 'staticInfo' => [
+ 'returnType' => 'synchronous',
+ ],
+ 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": {\\n \\"RequestId\\": \\"0C066DD3-F55D-18F7-8577-DE533E04054D\\",\\n \\"Message\\": \\"\\",\\n \\"Data\\": {\\n \\"code\\": 200,\\n \\"data\\": {\\n \\"姓名\\": \\"xxx\\",\\n \\"证号\\": \\"xxx\\",\\n \\"性别\\": \\"女\\"\\n },\\n \\"specificType\\": \\"ocr_infoExtractBill\\",\\n \\"originalFileUrl\\": \\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png\\",\\n \\"message\\": \\"\\",\\n \\"type\\": \\"卡证\\",\\n \\"version\\": \\"1.0.9\\",\\n \\"predictFile\\": \\"\\",\\n \\"tim_img\\": \\"17\\",\\n \\"score\\": 1.05,\\n \\"wid\\": \\"1544\\",\\n \\"hgt\\": \\"1054\\",\\n \\"imageUrl\\": \\"\\",\\n \\"angle\\": \\"0\\",\\n \\"orig_hgt\\": \\"1054\\",\\n \\"orig_wid\\": \\"1544\\",\\n \\"tim_ocr\\": \\"97\\",\\n \\"classType\\": \\"model\\",\\n \\"info\\": [\\n {\\n \\"value_loc\\": \\"595,314,595,399,398,399,398,314\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"XXX\\",\\n \\"key\\": \\"姓名\\"\\n },\\n {\\n \\"value_loc\\": \\"1256,234,1256,312,678,312,678,233\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"440305198305101408\\",\\n \\"key\\": \\"证号\\"\\n },\\n {\\n \\"value_loc\\": \\"965,321,965,394,851,394,851,321\\",\\n \\"key_prob\\": 1,\\n \\"key_loc\\": \\"\\",\\n \\"value_prob\\": 1,\\n \\"value\\": \\"女\\",\\n \\"key\\": \\"性别\\"\\n }\\n ]\\n },\\n \\"Code\\": 200\\n }\\n}","type":"json"}]',
+ 'title' => '模型服务预测API',
+ 'requestParamsDescription' => 'BinaryToText为非必填项。'."\n"
+ ."\n"
+ .'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n"
+ ."\n"
+ .'pdf 限制20Mb 10页'."\n"
+ .'除了长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。',
+ 'responseParamsDescription' => '长文档信息抽取模型data返回字段解释说明：'."\n"
+ .'```json'."\n"
+ .'originalFileUrl 原始文件url'."\n"
+ .'predictFile 解析后用于预测的图片url集合'."\n"
+ .'data 具体预测结果'."\n"
+ .'angle 图片的角度，当NeedRotate为true时才会返回，0表示正向，90表示图片朝右，180朝下，270朝左'."\n"
+ .'content 识别出图片的文字块汇总'."\n"
+ .'height 算法矫正图片后的高度'."\n"
+ .'width 算法矫正图片后的宽度'."\n"
+ .'orgHeight 原图的高度'."\n"
+ .'orgWidth 原图的宽度'."\n"
+ .'prism_wnum 识别的文字块的数量，prism_wordsInfo数组的大小'."\n"
+ .'```'."\n"
+ .'prism-wordsInfo文字块数组内的字段说明'."\n"
+ .'```json'."\n"
+ .'angle 文字块的角度，这个角度只影响width和height，当角度为-90、90、-270、270，width和height的值需要自行互换'."\n"
+ .'height 文字块的高度'."\n"
+ .'width 文字块的宽度'."\n"
+ .'pos 文字块的外矩形四个点的坐标按顺时针排列，左上、右上、右下、左下，当NeedRotate为true时，如果最外层的angle不为0，需要按照angle矫正图片后，坐标才准确'."\n"
+ .'word 文字块的文字'."\n"
+ .'tableId 当OutputTable为true并且该文字块在表格内则存在该字段，tableId表示表格的id'."\n"
+ .'tableCellId 当OutputTable为true并且该文字块在表格内则存在该字段，表示表格中单元格的id'."\n"
+ .'```'."\n"
+ .'charInfo单字信息'."\n"
+ .'```json'."\n"
+ .'word 单字文字'."\n"
+ .'x 单字左上角横坐标'."\n"
+ .'y 单字左上角纵坐标'."\n"
+ .'w 单字宽度'."\n"
+ .'h 单字高度'."\n"
+ .'```'."\n"
+ .'prism-tablesInfo表格数组内的字段说明'."\n"
+ .'```json'."\n"
+ .'tableId 表格id，和prism_wordsInfo信息中的tableId对应'."\n"
+ .'xCellSize 表格中横坐标单元格的数量'."\n"
+ .'yCellSize 表格中纵坐标单元格的数量'."\n"
+ .'```'."\n"
+ .'cellInfos单元格信息，包含单元格在整个表格中的空间拓扑关系'."\n"
+ .'```json'."\n"
+ .'tableCellId 表格中单元格id，和prism_wordsInfo信息中的tableCellId对应'."\n"
+ .'word 单元格中的文字'."\n"
+ .'xsc xStartCell缩写，表示横轴方向该单元格起始在第几个单元格，第一个单元格值为0'."\n"
+ .'xec xEndCell缩写，表示横轴方向该单元格结束在第几个单元格，第一个单元格值为0，如果xsc和xec都为0说明该文字在横轴方向占据了一个单元格并且在第一个单元格内'."\n"
+ .'ysc yStartCell缩写，表示纵轴方向该单元格起始在第几个单元格，第一个单元格值为0'."\n"
+ .'yec yEndCell缩写，表示纵轴方向该单元格结束在第几个单元格，第一个单元格值为0'."\n"
+ .'pos 单元格位置，按照单元格四个角的坐标顺时针排列，分别为左上XY坐标、右上XY坐标、右下XY坐标、左下XY坐标'."\n"
+ .'```',
+ ],
+ 'PredictClassifierModel' => [
+ 'summary' => '文档自学习分类器预测接口。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'read',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'get',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'ClassifierId',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '分类器ID',
+ 'type' => 'integer',
+ 'format' => 'int64',
+ 'required' => false,
+ 'maximum' => '99999999999999',
+ 'minimum' => '1',
+ 'example' => '1',
+ ],
+ ],
+ [
+ 'name' => 'AutoPrediction',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '是否开启自动预测，false：不开启， true：开启，默认开启',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'true',
+ 'default' => 'true',
+ ],
+ ],
+ [
+ 'name' => 'Content',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '图片或pdf文件可访问地址',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/table.png',
+ ],
+ ],
+ [
+ 'name' => 'Body',
+ 'in' => 'formData',
+ 'schema' => [
+ 'description' => '图片base64编码内容',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'data:image/png;base64,xxxxx'."\n",
+ ],
+ ],
+ [
+ 'name' => 'BinaryToText',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => 'content字段是图片URL时：false <br>body为base64的内容时：true',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'false',
+ 'default' => 'false',
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => '232B91A8-9938-5C10-B522-127D1E342A57',
+ ],
+ 'Code' => [
+ 'description' => '成功',
+ 'type' => 'integer',
+ 'format' => 'int32',
+ 'example' => '200',
+ ],
+ 'Data' => [
+ 'description' => '返回数据。',
+ 'type' => 'object',
+ 'example' => '{'."\n"
+ .' "score": 1,'."\n"
+ .' "classID": "269_2b6819527769749d962bf51d034b1820",'."\n"
+ .' "tables": ['."\n"
+ .' {'."\n"
+ .' "columns": ['."\n"
+ .' {'."\n"
+ .' "header_value": "姓名",'."\n"
+ .' "bodies": ['."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生1",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 99'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 99'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 123'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 123'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生1"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生2",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 123'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 123'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 146'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 146'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生2"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生3",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 146'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 146'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 169'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 169'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生3"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生4",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 169'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 169'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 191'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 191'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生4"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生5",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 191'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 191'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 215'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 215'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生5"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生6",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 215'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 215'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 238'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 238'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生6"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生7",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 238'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 238'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 261'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 261'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生7"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生8",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 261'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 261'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 283'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 283'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生8"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生9",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 283'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 283'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 187,'."\n"
+ .' "y": 307'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 307'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "value": "学生9"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0,'."\n"
+ .' "fieldWordRaw": "学生10",'."\n"
+ .' "wordInfo": [],'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 76,'."\n"
+ .' "y": 307'."\n"
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\\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/xxx/stage/upload/20230208/oss-uwGPIS8AsKcGRHfMRjvIrQVqN0uAxTgk.png?Expires=1675843535&OSSAccessKeyId=xxx&Signature=uPhg6JpDn47TgLt%2FI%2F7j4f%2FsFeA%3D\\"\\n },\\n \\"Message\\": \\"success\\"\\n}","type":"json"}]',
+ 'title' => '分类器服务预测API',
+ 'requestParamsDescription' => 'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n"
+ ."\n"
+ .'pdf限制20Mb，10页。'."\n"
+ .'除了长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。',
+ 'responseParamsDescription' => '分类器服务预测接口，返回Data字段解释说明：'."\n"
+ .'```json'."\n"
+ .'score 预测服务置信度 0-1'."\n"
+ .'data 算法返回的预测结果，数组格式 '."\n"
+ .'tables 表格区域预测结果'."\n"
+ .'prob 算法结果置信度 0-1 '."\n"
+ .'fieldName 抽取key '."\n"
+ .'fieldWord 抽取value '."\n"
+ .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点 '."\n"
+ .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息 '."\n"
+ .'specificType 算法类型（infoCustomeKvTemp:自定义KV 模板，infoCustomeTableTemp:自定义表格模板，ocr_infoExtractBill:信息抽取OCR识别，infoExtractBill:单据票证抽取，infoExtractDoc:长文档信息抽取 ）'."\n"
+ .'classType 模型预测服务、模板预测服务 '."\n"
+ .'predictFile 预测文件地址（失效时间60分钟）'."\n"
+ .'```',
+ ],
+ 'CreateModelAsyncPredict' => [
+ 'summary' => '文档自学习创建异步预测任务接口。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'write',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'create',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'ModelVersion',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '模型对应的版本号，如果不传入版本号表示默认用模型最新生效的版本。',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'V1',
+ ],
+ ],
+ [
+ 'name' => 'BinaryToText',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => 'content字段是图片URL时：false'."\n"
+ .'body为base64的内容时：true',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'false：表示content传入的是url'."\n"
+ .'true：表示body是直接传入图片进行base64的内容'."\n",
+ 'default' => 'false',
+ ],
+ ],
+ [
+ 'name' => 'Content',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '图片或pdf文件访问URL地址',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/1559855998794593/stage/upload/20230206/oss-hlfCRJ1SorSWs10MkqxK6YcL4OVAFSv4.png?Expires=1675665563&OSSAccessKeyId=XXXX&Signature=WLKghBc3zKzWJ3Td69%2B4C21jrbE%3D',
+ ],
+ ],
+ [
+ 'name' => 'ModelId',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '模型ID。模型列表页模型ID',
+ 'type' => 'integer',
+ 'format' => 'int64',
+ 'required' => false,
+ 'maximum' => '9999999999999',
+ 'minimum' => '1',
+ 'example' => '123',
+ ],
+ ],
+ [
+ 'name' => 'ServiceName',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '预训练服务名称',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'pre_train_service',
+ ],
+ ],
+ [
+ 'name' => 'ServiceVersion',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '预训练服务版本',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'V1',
+ ],
+ ],
+ [
+ 'name' => 'Body',
+ 'in' => 'formData',
+ 'schema' => [
+ 'description' => '图片base64编码内容',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'data:image/png;base64,xxxxx',
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4',
+ ],
+ 'Code' => [
+ 'description' => '请求结果状态，200为成功',
+ 'type' => 'integer',
+ 'format' => 'int32',
+ 'example' => '200',
+ ],
+ 'Message' => [
+ 'description' => '错误信息。',
+ 'type' => 'string',
+ 'example' => 'success',
+ ],
+ 'Data' => [
+ 'description' => '返回数据',
+ 'type' => 'string',
+ 'example' => '{'."\n"
+ .' "RequestId": "292D1584-134C-1221-B9BB-1B847C623D41",'."\n"
+ .' "Message": "",'."\n"
+ .' "Data": 1,'."\n"
+ .' "Code": 200'."\n"
+ .'}',
+ ],
+ ],
+ ],
+ ],
+ ],
+ 'errorCodes' => [
+ 200 => [
+ [
+ 'errorCode' => '21002',
+ 'errorMessage' => '模板预测超时 ',
+ ],
+ [
+ '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',
+ ],
+ ],
+ ],
+ 'staticInfo' => [
+ 'returnType' => 'synchronous',
+ ],
+ 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": \\"{\\\\n \\\\\\"RequestId\\\\\\": \\\\\\"292D1584-134C-1221-B9BB-1B847C623D41\\\\\\",\\\\n \\\\\\"Message\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"Data\\\\\\": 1,\\\\n \\\\\\"Code\\\\\\": 200\\\\n}\\"\\n}","type":"json"}]',
+ 'title' => '模型异步预测API',
+ 'requestParamsDescription' => 'BinaryToText为非必填项。'."\n"
+ ."\n"
+ .'content字段和body字段传参二选一，图片URL则content为图片访问地址。内容为base64编码则传参body，且BinaryToText传true。'."\n"
+ ."\n"
+ .'pdf 限制20Mb 10页'."\n"
+ .'除了长文档类型的模型预测以外，其他预测服务只会取第一页进行预测。',
+ 'responseParamsDescription' => 'Data字段为创建的异步任务ID，通过GetModelAsyncPredict获取结果',
+ ],
+ 'GetModelAsyncPredict' => [
+ 'summary' => '模型预测分为三种类型：长文档信息抽取、单票据信息抽取、表格信息抽取。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'read',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'get',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'AsyncPredictId',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '异步预测唯一ID，用于查询异步预测结果。',
+ 'type' => 'integer',
+ 'format' => 'int64',
+ 'required' => true,
+ 'maximum' => '99999999999999',
+ 'minimum' => '1',
+ 'example' => '1',
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => '3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4',
+ ],
+ 'Code' => [
+ 'description' => '请求结果状态，200为成功',
+ 'type' => 'integer',
+ 'format' => 'int32',
+ 'example' => '200',
+ ],
+ 'Message' => [
+ 'description' => '错误信息。',
+ 'type' => 'string',
+ 'example' => 'success',
+ ],
+ 'Data' => [
+ 'description' => '返回数据',
+ 'type' => 'string',
+ 'example' => '{'."\n"
+ .' "RequestId": "A9796F06-F1C4-1E89-8AFD-596583FF4B16",'."\n"
+ .' "Message": "",'."\n"
+ .' "Data": {'."\n"
+ .' "result": "https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/stage/data/XXXX/asyncPredict/713908/oss-933bbdf4-fa10-4c56-b6ab-9c85f32bbd0e.json?Expires=1991115127&OSSAccessKeyId=XXXX&Signature=5zYLY9yR%2B9Ok1WuRgHYdqtXHK10%3D",'."\n"
+ .' "asyncPredictId": 713908,'."\n"
+ .' "errorCode": 200,'."\n"
+ .' "errorMsg": "",'."\n"
+ .' "status": 2'."\n"
+ .' },'."\n"
+ .' "Code": 200'."\n"
+ .'}',
+ ],
+ ],
+ ],
+ ],
+ ],
+ 'errorCodes' => [
+ 200 => [
+ [
+ 'errorCode' => '21002',
+ 'errorMessage' => '模板预测超时',
+ ],
+ [
+ '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',
+ ],
+ ],
+ ],
+ 'staticInfo' => [
+ 'returnType' => 'synchronous',
+ ],
+ 'responseDemo' => '[{"errorExample":"","example":"{\\n \\"RequestId\\": \\"3EAC98E6-8DD6-511F-8764-DEE8B6EB6BB4\\",\\n \\"Code\\": 200,\\n \\"Message\\": \\"success\\",\\n \\"Data\\": \\"{\\\\n \\\\\\"RequestId\\\\\\": \\\\\\"A9796F06-F1C4-1E89-8AFD-596583FF4B16\\\\\\",\\\\n \\\\\\"Message\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"Data\\\\\\": {\\\\n \\\\\\"result\\\\\\": \\\\\\"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/3/stage/data/XXXX/asyncPredict/713908/oss-933bbdf4-fa10-4c56-b6ab-9c85f32bbd0e.json?Expires=1991115127&OSSAccessKeyId=XXXX&Signature=5zYLY9yR%2B9Ok1WuRgHYdqtXHK10%3D\\\\\\",\\\\n \\\\\\"asyncPredictId\\\\\\": 713908,\\\\n \\\\\\"errorCode\\\\\\": 200,\\\\n \\\\\\"errorMsg\\\\\\": \\\\\\"\\\\\\",\\\\n \\\\\\"status\\\\\\": 2\\\\n },\\\\n \\\\\\"Code\\\\\\": 200\\\\n}\\"\\n}","type":"json"}]',
+ 'title' => '获取模型异步预测结果API',
+ 'responseParamsDescription' => 'status 表示任务状态，0：未开始，1：异步任务运行中、 2：异步任务完成 、 3：异步任务运行失败。'."\n"
+ ."\n"
+ .'当status = 2 时，result为模型预测的结果URL。',
+ ],
+ 'PredictPreTrainModel' => [
+ 'summary' => '预置能力现有：UIE抽取，适用于通用智能预标注。',
+ 'methods' => [
+ 'post',
+ ],
+ 'schemes' => [
+ 'http',
+ 'https',
+ ],
+ 'security' => [
+ [
+ 'AK' => [],
+ ],
+ ],
+ 'operationType' => 'read',
+ 'deprecated' => false,
+ 'systemTags' => [
+ 'operationType' => 'get',
+ 'riskType' => 'none',
+ 'chargeType' => 'free',
+ ],
+ 'parameters' => [
+ [
+ 'name' => 'Content',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '预测内容，格式为JSON字符串。'."\n"
+ .'UIE抽取参数格式{"query":"xxx","schema":["字段1","字段2"]}, query对应图片URL，schema对应要抽取的字段数组',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => '{"query":"https://doc-automl-public.oss-cn-hangzhou.aliyuncs.com/demo/extractBill.png", "schema":["姓名", "住址"]}',
+ ],
+ ],
+ [
+ 'name' => 'ServiceVersion',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '预置能力服务版本，默认V1',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'V1',
+ ],
+ ],
+ [
+ 'name' => 'ServiceName',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => '预置能力服务名称，必填'."\n"
+ .'UIE抽取对应“FormUIE”',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => 'FormUIE',
+ ],
+ ],
+ [
+ 'name' => 'BinaryToText',
+ 'in' => 'query',
+ 'schema' => [
+ 'description' => 'content字段内容为图片URL时：false，'."\n"
+ .'body字段内容为图片base64时：true',
+ 'type' => 'boolean',
+ 'required' => false,
+ 'example' => 'false',
+ 'default' => 'false',
+ ],
+ ],
+ [
+ 'name' => 'Body',
+ 'in' => 'formData',
+ 'schema' => [
+ 'description' => '图片传递base64编码时的预测内容，格式为json字符串。'."\n"
+ .'UIE抽取参数格式{"query":"xxx","schema":["字段1","字段2"]}, query对应图片base64编码，schema对应要抽取的字段数组',
+ 'type' => 'string',
+ 'required' => false,
+ 'example' => '{"query":"data:image/png;base64,xxxxx","schema":["姓名", "住址"]}',
+ ],
+ ],
+ ],
+ 'responses' => [
+ 200 => [
+ 'schema' => [
+ 'title' => 'Schema of Response',
+ 'description' => 'Schema of Response',
+ 'type' => 'object',
+ 'properties' => [
+ 'RequestId' => [
+ 'title' => 'Id of the request',
+ 'description' => 'Id of the request',
+ 'type' => 'string',
+ 'example' => '29413C69-11EF-15CB-BE20-70D318E2F4E9',
+ ],
+ 'Code' => [
+ 'description' => '请求结果状态，200为成功',
+ 'type' => 'integer',
+ 'format' => 'int32',
+ 'example' => '200',
+ ],
+ 'Message' => [
+ 'description' => '错误信息',
+ 'type' => 'string',
+ 'example' => 'success',
+ ],
+ 'Data' => [
+ 'description' => '接口返回信息',
+ 'type' => 'object',
+ 'example' => '{'."\n"
+ .' "RequestId": "29413C69-11EF-15CB-BE20-70D318E2F4E9",'."\n"
+ .' "Message": "success",'."\n"
+ .' "Data": {'."\n"
+ .' "score": 1,'."\n"
+ .' "data": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.9138551354408264,'."\n"
+ .' "fieldWordRaw": "xx",'."\n"
+ .' "wordInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.9138551354408264,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 153'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 153'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "xx",'."\n"
+ .' "charInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 471,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 471,'."\n"
+ .' "y": 153'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 153'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 473,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 153'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 473,'."\n"
+ .' "y": 153'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' }'."\n"
+ .' ]'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "name": "姓名",'."\n"
+ .' "location": ['."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 139'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 476,'."\n"
+ .' "y": 153'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 468,'."\n"
+ .' "y": 153'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "fieldWord": "xx"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.9594210982322693,'."\n"
+ .' "fieldWordRaw": "xxxxxxxxxxx",'."\n"
+ .' "wordInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.9594210982322693,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 168,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 239'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 168,'."\n"
+ .' "y": 239'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "xxxxxxxxxxx",'."\n"
+ .' "charInfo": ['."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 366,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 383,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 383,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 366,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 384,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 401,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 401,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 384,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 402,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 414,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 414,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 402,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 418,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 427,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 427,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 418,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 429,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 438,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 438,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 429,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 439,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 448,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 448,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 439,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "prob": 0.99,'."\n"
+ .' "pos": ['."\n"
+ .' {'."\n"
+ .' "x": 450,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 164'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 467,'."\n"
+ .' "y": 179'."\n"
+ .' },'."\n"
+ .' {'."\n"
+ .' "x": 450,'."\n"
+ .' "y": 179'."\n"
+ .' }'."\n"
+ .' ],'."\n"
+ .' "word": "x"'."\n"
+ .' },'."\n"
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+ 'title' => '预置能力服务预测API',
+ 'requestParamsDescription' => 'BinaryToText为非必填项'."\n"
+ ."\n"
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+ 'responseParamsDescription' => '模板服务预测接口，返回Data字段解释说明：<br>'."\n"
+ .'score 预测服务置信度 0-1 <br>'."\n"
+ .'data. 算法返回的预测结果，数组格式<br>'."\n"
+ .'prob 算法结果置信度 0-1 <br>'."\n"
+ .'name 抽取key<br>'."\n"
+ .'fieldWord 抽取value<br>'."\n"
+ .'location 抽取结果坐标位置 { "x": 119,"y": 48 }表示页面坐标点<br>'."\n"
+ .'wordInfo 抽取内容详细信息，包括了每个字符的位置信息<br>'."\n"
+ .'specificType 算法类型（formuie-anti:UIE抽取）<br>'."\n"
+ .'classType preDefinedServer: 预置能力<br>'."\n"
+ .'predictFile 预测文件地址（失效时间60分钟）',
+ ],
+ ],
+ 'endpoints' => [
+ [
+ 'regionId' => 'cn-beijing',
+ 'endpoint' => 'documentautoml.cn-beijing.aliyuncs.com',
+ ],
+ ],
+];
generated by cgit v1.2.3 (git 2.46.0) at 2026-03-07 13:20:03 +0000