Upload a file to the corpus

POST 
/v2/corpora/:corpus_key/upload_file

Upload files such as PDFs and Word Documents for automatic text extraction and metadata parsing. The request expects a multipart/form-data format containing the following parts:

• metadata - (Optional) Specifies a JSON object representing any additional metadata to be associated with the extracted document. For example, 'metadata={"key": "value"};type=application/json'
• chunking_strategy - (Optional) Specifies the chunking strategy for the platform to use. If you do not set this option, the platform uses the default strategy, which creates one chunk per sentence. For example, 'chunking_strategy={"type":"max_chars_chunking_strategy","max_chars_per_chunk":200};type=application/json'
• file - Specifies the file that you want to upload.
• filename - Specified as part of the file field with the file name that you want to associate with the uploaded file. For a curl example, use the following syntax: 'file=@/path/to/file/file.pdf;filename=desired_filename.pdf'

For more detailed information, see this File Upload API guide.

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 of which to upload the file.

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.

multipart/form-data

Body

Upload a file for the Vectara platform to attempt to parse and turn into a document within the corpus. The first part of the multipart request can contain any document metadata to attach to the parsed document. Only one document may be uploaded at a time.

metadata object

Arbitrary object that will be attached as document metadata to the extracted document.

property name* any

Arbitrary object that will be attached as document metadata to the extracted document.

chunking_strategy object

(Optional) Choose how to split documents into chunks during indexing. If you do not set a chunking strategy, the platform uses the default strategy which creates one chunk (docpart) per sentence.

oneOf

MaxCharsChunkingStrategy

type string

Default value: max_chars_chunking_strategy

When setting the type to max_chars_chunking_strategy, you can control the size of chunks (docparts).

max_chars_per_chunk int32required

Possible values: >= 100

Specifies the maximum number of characters per chunk.

The platform adds sentences to a chunk until the total number of characters exceeds the limit.

If a single sentence exceeds the limit, it splits the sentence across chunks. Note: This is the only case where the chunk may not contain a complete sentence.

filename string

Optional multipart section to override the filename.

file binaryrequired

Binary file contents. The file name of the file will be used as the document ID.

Responses

201

The extracted document has been parsed and added to the corpus.

application/json

Schema

Schema

id string

The document ID.

metadata object

The document metadata.

property name* any

The document metadata.

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.

Example (from schema)

{
  "id": "my-doc-id",
  "metadata": {},
  "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
  }
}

400

Upload file request was malformed.

application/json

Schema

Schema

field_errors object
The errors that relate to specific fields in the request.
property name* string
messages message[]
request_id string

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

Example (from schema)

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

403

Permissions do not allow uploading a file to 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 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"
}

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