Create Document by Text

curl --request POST \
  --url https://{api_base_url}/datasets/{dataset_id}/document/create-by-text \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "text": "<string>",
  "doc_form": "text_model",
  "doc_language": "English",
  "embedding_model": "<string>",
  "embedding_model_provider": "<string>",
  "original_document_id": "<string>"
}
'

import requests

url = "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text"

payload = {
    "name": "<string>",
    "text": "<string>",
    "doc_form": "text_model",
    "doc_language": "English",
    "embedding_model": "<string>",
    "embedding_model_provider": "<string>",
    "original_document_id": "<string>"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    text: '<string>',
    doc_form: 'text_model',
    doc_language: 'English',
    embedding_model: '<string>',
    embedding_model_provider: '<string>',
    original_document_id: '<string>'
  })
};

fetch('https://{api_base_url}/datasets/{dataset_id}/document/create-by-text', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => '<string>',
    'text' => '<string>',
    'doc_form' => 'text_model',
    'doc_language' => 'English',
    'embedding_model' => '<string>',
    'embedding_model_provider' => '<string>',
    'original_document_id' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://{api_base_url}/datasets/{dataset_id}/document/create-by-text")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://{api_base_url}/datasets/{dataset_id}/document/create-by-text")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}"

response = http.request(request)
puts response.read_body

{
  "document": {
    "id": "a8e0e5b5-78c6-4130-a5ce-25feb0e0b4ac",
    "position": 1,
    "data_source_type": "upload_file",
    "data_source_info": {
      "upload_file_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
    },
    "data_source_detail_dict": {
      "upload_file": {
        "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
        "name": "guide.txt",
        "size": 2048,
        "extension": "txt",
        "mime_type": "text/plain",
        "created_by": "ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4",
        "created_at": 1741267200
      }
    },
    "dataset_process_rule_id": "e1f2a3b4-c5d6-7890-ef12-345678901234",
    "name": "guide.txt",
    "created_from": "api",
    "created_by": "ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4",
    "created_at": 1741267200,
    "tokens": 0,
    "indexing_status": "indexing",
    "error": null,
    "enabled": true,
    "disabled_at": null,
    "disabled_by": null,
    "archived": false,
    "display_status": "indexing",
    "word_count": 0,
    "hit_count": 0,
    "doc_form": "text_model",
    "doc_metadata": [],
    "summary_index_status": null,
    "need_summary": false
  },
  "batch": "20250306150245647595"
}

POST

datasets

{dataset_id}

document

create-by-text

Create Document by Text

curl --request POST \
  --url https://{api_base_url}/datasets/{dataset_id}/document/create-by-text \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "text": "<string>",
  "doc_form": "text_model",
  "doc_language": "English",
  "embedding_model": "<string>",
  "embedding_model_provider": "<string>",
  "original_document_id": "<string>"
}
'

import requests

url = "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text"

payload = {
    "name": "<string>",
    "text": "<string>",
    "doc_form": "text_model",
    "doc_language": "English",
    "embedding_model": "<string>",
    "embedding_model_provider": "<string>",
    "original_document_id": "<string>"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    text: '<string>',
    doc_form: 'text_model',
    doc_language: 'English',
    embedding_model: '<string>',
    embedding_model_provider: '<string>',
    original_document_id: '<string>'
  })
};

fetch('https://{api_base_url}/datasets/{dataset_id}/document/create-by-text', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => '<string>',
    'text' => '<string>',
    'doc_form' => 'text_model',
    'doc_language' => 'English',
    'embedding_model' => '<string>',
    'embedding_model_provider' => '<string>',
    'original_document_id' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://{api_base_url}/datasets/{dataset_id}/document/create-by-text"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://{api_base_url}/datasets/{dataset_id}/document/create-by-text")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://{api_base_url}/datasets/{dataset_id}/document/create-by-text")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"text\": \"<string>\",\n  \"doc_form\": \"text_model\",\n  \"doc_language\": \"English\",\n  \"embedding_model\": \"<string>\",\n  \"embedding_model_provider\": \"<string>\",\n  \"original_document_id\": \"<string>\"\n}"

response = http.request(request)
puts response.read_body

{
  "document": {
    "id": "a8e0e5b5-78c6-4130-a5ce-25feb0e0b4ac",
    "position": 1,
    "data_source_type": "upload_file",
    "data_source_info": {
      "upload_file_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
    },
    "data_source_detail_dict": {
      "upload_file": {
        "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
        "name": "guide.txt",
        "size": 2048,
        "extension": "txt",
        "mime_type": "text/plain",
        "created_by": "ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4",
        "created_at": 1741267200
      }
    },
    "dataset_process_rule_id": "e1f2a3b4-c5d6-7890-ef12-345678901234",
    "name": "guide.txt",
    "created_from": "api",
    "created_by": "ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4",
    "created_at": 1741267200,
    "tokens": 0,
    "indexing_status": "indexing",
    "error": null,
    "enabled": true,
    "disabled_at": null,
    "disabled_by": null,
    "archived": false,
    "display_status": "indexing",
    "word_count": 0,
    "hit_count": 0,
    "doc_form": "text_model",
    "doc_metadata": [],
    "summary_index_status": null,
    "need_summary": false
  },
  "batch": "20250306150245647595"
}

Authorizations

Authorization

string

header

required

Every request authenticates with an API key: Authorization: Bearer {API_KEY}. App endpoints take an app API key; knowledge endpoints take a knowledge base API key (Get Started).

Keep keys server-side; never embed them in client code. Requests with a missing or invalid key fail with HTTP 401 (unauthorized).

Path Parameters

dataset_id

string<uuid>

required

Knowledge base ID. From List Knowledge Bases.

Body

application/json

name

string

required

Document name.

text

string

required

Document text content.

indexing_technique

enum<string>

Required when adding the first document to a knowledge base. Subsequent documents inherit the knowledge base's indexing technique if omitted. high_quality uses embedding models for precise search; economy uses keyword-based indexing.

Available options:

high_quality,

economy

doc_form

enum<string>

default:text_model

text_model for standard text chunking, hierarchical_model for parent-child chunk structure, qa_model for question-answer pair extraction.

Available options:

text_model,

hierarchical_model,

qa_model

doc_language

string

default:English

Language of the document for processing optimization.

process_rule

object

Processing rules for chunking.

Show child attributes

retrieval_model

object

Controls how chunks are searched and ranked when querying this knowledge base.

Show child attributes

embedding_model

string

Embedding model name. Use the model field from Get Available Models with model_type=text-embedding.

embedding_model_provider

string

Embedding model provider. Use the provider field from Get Available Models with model_type=text-embedding.

original_document_id

string

Original document ID for versioning. Get it from List Documents.

Response

Document created successfully.

document

object

Show child attributes

batch

string

Batch ID for tracking indexing progress.

Retrieve Chunks from a Knowledge Base / Test Retrieval

Create Document by File

Guides

App APIs

Knowledge APIs

Create Document by Text

Authorizations

Path Parameters

Body

Response