Retrieve a document

GET 
https://api.vectara.io/v2/corpora/:corpus_key/documents/:document_id

Retrieve the content and metadata of a specific document, identified by its unique document_id from a specific corpus.

Request

Path Parameters

corpus_key CorpusKeyrequired

Possible values: <= 50 characters, Value must match regular expression [a-zA-Z0-9_\=\-]+$

The unique key identifying the corpus containing the document to retrieve.

document_id stringrequired

The document ID of the document to retrieve. This document_id must be percent encoded.

Header Parameters

Request-Timeout integer

Possible values: >= 1

The API will make a best effort to complete the request in the specified seconds or time out.

Request-Timeout-Millis integer

Possible values: >= 1

The API will make a best effort to complete the request in the specified milliseconds or time out.

Responses

200

Successfully retrieved the document.

application/json

Schema

Schema

id string

The document ID.

metadata object

The document metadata.

property name* any

The document metadata.

tables object[]
The tables that this document contains. Tables are not available when table extraction is not enabled.
Array [
id string
The unique ID of the table within the document.
title string
The title of the table.
data object
The data of the table.
headers array[]
The headers of the table.
rows array[]
The rows in the data.
description string
The description of the table.
]
parts object[]
Parts of the document that make up the document. However, parts are not available when retrieving a list of documents or when creating a document. This property is only available when retrieving a document by ID.
Array [
text stringrequired
The text of the document part.
metadata object
The metadata for a document part. These may be used in metadata filters at query time if filter attributes are configured on the corpus.
property name* any
The metadata for a document part. These may be used in metadata filters at query time if filter attributes are configured on the corpus.
context string
The context text for the document part.
custom_dimensions object
The custom dimensions as additional weights.
property name* double
]
storage_usage object

How much storage the document used. This information is currently not returned when retrieving the document, and only returned when indexing a document.

bytes_used int64

Number of bytes used by document counting towards maximum corpus size, and towards any billing plans.

metadata_bytes_used int64

Number of metadata bytes used by a document.

extraction_usage object

How much extraction quota the document used. This information is currently not returned when retrieving the document, and only returned when indexing a document.

table_extraction_used int64

The number of pages from the document that consumed the extraction quota.

Example (from schema)

{
  "id": "my-doc-id",
  "metadata": {},
  "tables": [
    {
      "id": "table_1",
      "title": "string",
      "data": {
        "headers": [
          [
            {
              "text_value": "string",
              "int_value": 0,
              "float_value": 0,
              "bool_value": true,
              "colspan": 0,
              "rowspan": 0
            }
          ]
        ],
        "rows": [
          [
            {
              "text_value": "string",
              "int_value": 0,
              "float_value": 0,
              "bool_value": true,
              "colspan": 0,
              "rowspan": 0
            }
          ]
        ]
      },
      "description": "string"
    }
  ],
  "parts": [
    {
      "text": "I'm a nice document part.",
      "metadata": {
        "nice_rank": 9000
      },
      "context": "string",
      "custom_dimensions": {}
    }
  ],
  "storage_usage": {
    "bytes_used": 0,
    "metadata_bytes_used": 0
  },
  "extraction_usage": {
    "table_extraction_used": 0
  }
}

403

Permissions do not allow retrieving a document from the corpus.

application/json

Schema

Schema

messages message[]

The messages describing why the error occurred.

request_id string

The ID of the request that can be used to help Vectara support debug what went wrong.

Example (from schema)

{
  "messages": [
    "Internal server error."
  ],
  "request_id": "string"
}

404

Corpus or document not found.

application/json

Schema

Schema

id string

The ID cannot be found.

messages message[]
request_id string

ID of the request that can be used to help Vectara support debug what went wrong.

Example (from schema)

{
  "id": "string",
  "messages": [
    "string"
  ],
  "request_id": "string"
}

Authorization: x-api-key

name: x-api-keytype: apiKeyin: header

• curl
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• csharp
• php
• java
• powershell

• CURL

curl -L -X GET 'https://api.vectara.io/v2/corpora/:corpus_key/documents/:document_id' \
-H 'Accept: application/json' \
-H 'x-api-key: <API_KEY_VALUE>'

Request Collapse all

Base URL

https://api.vectara.io

Auth

Security Scheme

ApiKeyAuthOAuth2

ApiKeyAuth

Parameters

corpus_key — pathrequired

document_id — pathrequired

Request-Timeout — header

Request-Timeout-Millis — header

ResponseClear

Click the Send API Request button above and see the response here!