Retrieve Document Index

Used to retrieve a Document Index given its ID or name.

X-API-KEYstring

API Key authentication via header

idstringRequired

Either the Document Index's ID or its unique name

mask_indexing_configbooleanOptional

Whether to mask the indexing configuration in the response

idstringformat: "uuid"

createdstringformat: "date-time"

labelstring<=150 characters

A human-readable label for the document index

namestring<=150 characters

A name that uniquely identifies this index within its workspace

indexing_configobject

statusenum

The current status of the document index

Allowed values:

1	import requests
2
3	url = "https://api.vellum.ai/v1/document-indexes/id"
4
5	headers = {"X-API-KEY": "<apiKey>"}
6
7	response = requests.get(url, headers=headers)
8
9	print(response.json())

1	{
2	"id": "string",
3	"created": "2024-01-15T09:30:00Z",
4	"label": "string",
5	"name": "string",
6	"indexing_config": {
7	"vectorizer": {
8	"config": {
9	"add_openai_api_key": true
10	},
11	"model_name": "text-embedding-3-small"
12	},
13	"chunking": {
14	"chunker_name": "reducto-chunker",
15	"chunker_config": {
16	"character_limit": 1000
17	}
18	}
19	},
20	"status": "ACTIVE"
21	}

1	import requests
2
3	url = "https://api.vellum.ai/v1/document-indexes/id"
4
5	headers = {"X-API-KEY": "<apiKey>"}
6
7	response = requests.get(url, headers=headers)
8
9	print(response.json())

1	{
2	"id": "string",
3	"created": "2024-01-15T09:30:00Z",
4	"label": "string",
5	"name": "string",
6	"indexing_config": {
7	"vectorizer": {
8	"config": {
9	"add_openai_api_key": true
10	},
11	"model_name": "text-embedding-3-small"
12	},
13	"chunking": {
14	"chunker_name": "reducto-chunker",
15	"chunker_config": {
16	"character_limit": 1000
17	}
18	}
19	},
20	"status": "ACTIVE"
21	}