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AI Document Table Data Extraction API

Artificial Intelligence#document#extraction#table
ApyHub
ApyHub
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Starting from 500 atoms
AI tier

About

This Utility API uses AI to recognize and extract essential information within tables in documents and images.
This API can analyse visual data to extract tabular information, offering versatility across various applications from optimizing data retrieval in documents to providing context-aware insights in augmented reality experiences.
The atoms cost is subjected to change depending on the size of the input file and the provider selected. The list of providers and the atoms cost for each provider is given below:
Provider (requested_service)Atoms
Azure500
ApyHub2000
Note: In order to test the API on API Playground, just click on "Show optional inputs" and enter the Authentication token for the provider before clicking on Send request. The output response structure and the result of the AI utility APIs depend on the service provider and it may vary depending on which service provider is selected.
Select API Endpoints
Input

API Playground

API Documentation

input file: output json
POST
https://api.apyhub.com/ai/document/extract/table/file

Request example

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curl --location --request POST 'https://api.apyhub.com/ai/document/extract/table/file' \
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--header 'apy-token: {{token}}' \
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--form 'file=@"sample.jpg"'
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--form 'requested_service="azure"'
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--form 'azure_key="your-azure-key"'
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--form 'azure_endpoint="your-azure-endpoint"'
Provider (requested_service)Atoms
Azure500
ApyHub2000
Method: POST
Content Type: multipart/form-data
Request Body
AttributeTypeMandatoryDescription
filefileYesthe source document file.
requested_serviceStringyesthe name of service provider. Supported providers are azure, apyhub. Defaults to apyhub
azure_keyStringyes (if azure is selected in requested_service)service key provided by azure
azure_endpointStringyes (if azure is selected in requested_service)the endpoint provided by azure
Size And Limits
requested_serviceSupport matrix and limitations
Apyhub* Supported formats (jpeg, jpg, png, tiff, heif, bmp, pdf, docx, xlsx, pptx ,html).
* Max document size 500 MB.
* Max number of pages (Analysis) 2000.
Azure* Supported formats (jpeg, jpg, png, tiff, heif, bmp, pdf, docx, xlsx, pptx ,html).
* Max document size 500 MB.
* Max number of pages (Analysis) 2000.
Sample Response
A successful request returns the extracted table data response in the output parameter specified. If the request fails, the response contains an error code and a message to help determine what went wrong.

HTTP Response Codes

The method may return one of the following HTTP status codes:
Status CodeDescription
200The request was successful.
400Invalid input - the file is corrupt or the supported inputs are not provided.
401Required authentication information is either missing or not valid for the resource.
500If any unexpected error occurs while processing the request.

Authentication

All API requests to ApyHub services need to be authenticated. Currently we support tokens or basic authentication mechanisms. You can generate and view your existing credentials from your workspace settings (on the left side of the navbar) and go to “API Keys".
Points to note:
  • Credential secrets are generated on the fly and are not stored in plain text, so on generating a credential please save the secrets somewhere safe.
  • Use the apy-token as the header parameter to pass the token.
  • Use the Authorization header to send the basic authentication credentials.

Error codes

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{
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  "error": {
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    "code": 105,
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    "message": "Invalid URL"
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  }
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}
To search for a specific error code, enter the code in the search box below. Alternatively, you can click on the button to view a complete list of all error codes.
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