Ingesting Documents

Ingest

documents

arrayRequired

An array of Document objects.

wait_for_complete

bool

A flag that will block until the ingest process is complete. Default is false.

batch_size

int

The size of each batch ingest request. Default is 10. Min is 1 and Max is 50.

upload_api

str

An endpoint that returns a presigned URL within a JSON dictionary with key URL. Default is the EyeLevel.ai file upload endpoint.

callback_url

str

An endpoint that will receive processing event updates as POST.

callback_data

str

A string that is returned, along with processing event updates, to the callback URL.

Document

bucketId

integerRequired

The bucketId of the bucket which this file will be ingested to.

filePath

stringRequired

The local file path or remote URL of the document being ingested by GroundX.

fileName

string

The name of the file being ingested.

fileType

enum

The type of document (one of the currently supported file types).

filter

object

A dictionary of key-value pairs that can be used to pre-filter documents prior to a search.

processLevel

enum

The amount of processing to perform on chunks (default ‘full’).

searchData

object

Custom metadata which can be used to influence GroundX’s search functionality. This data can be used to further hone GroundX search.

1	from groundx import Document, GroundX
2
3	client = GroundX(
4	api_key="YOUR_API_KEY",
5	)
6	client.ingest(
7	documents=[
8	Document(
9	bucket_id=1234,
10	file_name="my_file1.txt",
11	file_path="https://my.source.url.com/file1.txt",
12	file_type="txt",
13	),
14	Document(
15	bucket_id=1234,
16	file_name="my_file2.pdf",
17	file_path="/local/path/file2.pdf",
18	file_type="pdf",
19	filter={
20	permissions = {
21	roles = ["moderator","admin"]
22	},
23	# other metadata that can be used for pre-filtering of documents prior to search
24	},
25	search_data=dict(
26	key = "value",
27	),
28	)
29	],
30	)

1	from groundx import Document, GroundX
2
3	client = GroundX(
4	api_key="YOUR_API_KEY",
5	)
6	client.ingest(
7	documents=[
8	Document(
9	bucket_id=1234,
10	file_name="my_file1.txt",
11	file_path="https://my.source.url.com/file1.txt",
12	file_type="txt",
13	),
14	Document(
15	bucket_id=1234,
16	file_name="my_file2.pdf",
17	file_path="/local/path/file2.pdf",
18	file_type="pdf",
19	filter={
20	permissions = {
21	roles = ["moderator","admin"]
22	},
23	# other metadata that can be used for pre-filtering of documents prior to search
24	},
25	search_data=dict(
26	key = "value",
27	),
28	)
29	],
30	)