Create Knowledge Base

curl --request POST \
  --url https://api.example.com/api/v1/knowledge-bases \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "Company Policies",
  "description": "Knowledge base containing all company policies and procedures",
  "document_language": "en",
  "chunking_strategy": "recursive",
  "vector_backend": "pinecone",
  "embedding_model": "text-embedding-3-large",
  "chunk_size": 512,
  "chunk_overlap": 50,
  "assistant_persona": "a customer-care voice assistant for Acme Bank"
}
'

import requests

url = "https://api.example.com/api/v1/knowledge-bases"

payload = {
    "name": "Company Policies",
    "description": "Knowledge base containing all company policies and procedures",
    "document_language": "en",
    "chunking_strategy": "recursive",
    "vector_backend": "pinecone",
    "embedding_model": "text-embedding-3-large",
    "chunk_size": 512,
    "chunk_overlap": 50,
    "assistant_persona": "a customer-care voice assistant for Acme Bank"
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'Company Policies',
    description: 'Knowledge base containing all company policies and procedures',
    document_language: 'en',
    chunking_strategy: 'recursive',
    vector_backend: 'pinecone',
    embedding_model: 'text-embedding-3-large',
    chunk_size: 512,
    chunk_overlap: 50,
    assistant_persona: 'a customer-care voice assistant for Acme Bank'
  })
};

fetch('https://api.example.com/api/v1/knowledge-bases', 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.example.com/api/v1/knowledge-bases",
  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' => 'Company Policies',
    'description' => 'Knowledge base containing all company policies and procedures',
    'document_language' => 'en',
    'chunking_strategy' => 'recursive',
    'vector_backend' => 'pinecone',
    'embedding_model' => 'text-embedding-3-large',
    'chunk_size' => 512,
    'chunk_overlap' => 50,
    'assistant_persona' => 'a customer-care voice assistant for Acme Bank'
  ]),
  CURLOPT_HTTPHEADER => [
    "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.example.com/api/v1/knowledge-bases"

	payload := strings.NewReader("{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}")

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

	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.example.com/api/v1/knowledge-bases")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/knowledge-bases")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}"

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

{
  "id": "<string>",
  "name": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "description": "<string>",
  "document_language": "en",
  "document_count": 0,
  "chunking_strategy": "recursive",
  "vector_backend": "pinecone",
  "embedding_model": "text-embedding-3-small",
  "chunk_size": 512,
  "chunk_overlap": 50,
  "assistant_persona": "<string>",
  "workspace_id": "<string>",
  "organization_id": "<string>",
  "user_id": "<string>"
}

{
  "error": "<string>",
  "message": "<string>"
}

{
  "error": "<string>",
  "message": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

{
  "error": "<string>",
  "message": "<string>"
}

POST

api

knowledge-bases

Create Knowledge Base

curl --request POST \
  --url https://api.example.com/api/v1/knowledge-bases \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "Company Policies",
  "description": "Knowledge base containing all company policies and procedures",
  "document_language": "en",
  "chunking_strategy": "recursive",
  "vector_backend": "pinecone",
  "embedding_model": "text-embedding-3-large",
  "chunk_size": 512,
  "chunk_overlap": 50,
  "assistant_persona": "a customer-care voice assistant for Acme Bank"
}
'

import requests

url = "https://api.example.com/api/v1/knowledge-bases"

payload = {
    "name": "Company Policies",
    "description": "Knowledge base containing all company policies and procedures",
    "document_language": "en",
    "chunking_strategy": "recursive",
    "vector_backend": "pinecone",
    "embedding_model": "text-embedding-3-large",
    "chunk_size": 512,
    "chunk_overlap": 50,
    "assistant_persona": "a customer-care voice assistant for Acme Bank"
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'Company Policies',
    description: 'Knowledge base containing all company policies and procedures',
    document_language: 'en',
    chunking_strategy: 'recursive',
    vector_backend: 'pinecone',
    embedding_model: 'text-embedding-3-large',
    chunk_size: 512,
    chunk_overlap: 50,
    assistant_persona: 'a customer-care voice assistant for Acme Bank'
  })
};

fetch('https://api.example.com/api/v1/knowledge-bases', 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.example.com/api/v1/knowledge-bases",
  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' => 'Company Policies',
    'description' => 'Knowledge base containing all company policies and procedures',
    'document_language' => 'en',
    'chunking_strategy' => 'recursive',
    'vector_backend' => 'pinecone',
    'embedding_model' => 'text-embedding-3-large',
    'chunk_size' => 512,
    'chunk_overlap' => 50,
    'assistant_persona' => 'a customer-care voice assistant for Acme Bank'
  ]),
  CURLOPT_HTTPHEADER => [
    "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.example.com/api/v1/knowledge-bases"

	payload := strings.NewReader("{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}")

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

	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.example.com/api/v1/knowledge-bases")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/knowledge-bases")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"Company Policies\",\n  \"description\": \"Knowledge base containing all company policies and procedures\",\n  \"document_language\": \"en\",\n  \"chunking_strategy\": \"recursive\",\n  \"vector_backend\": \"pinecone\",\n  \"embedding_model\": \"text-embedding-3-large\",\n  \"chunk_size\": 512,\n  \"chunk_overlap\": 50,\n  \"assistant_persona\": \"a customer-care voice assistant for Acme Bank\"\n}"

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

{
  "id": "<string>",
  "name": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "description": "<string>",
  "document_language": "en",
  "document_count": 0,
  "chunking_strategy": "recursive",
  "vector_backend": "pinecone",
  "embedding_model": "text-embedding-3-small",
  "chunk_size": 512,
  "chunk_overlap": 50,
  "assistant_persona": "<string>",
  "workspace_id": "<string>",
  "organization_id": "<string>",
  "user_id": "<string>"
}

{
  "error": "<string>",
  "message": "<string>"
}

{
  "error": "<string>",
  "message": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

{
  "error": "<string>",
  "message": "<string>"
}

Body

application/json

Request body for creating a new knowledge base.

name

string

required

The name of the knowledge base. Should be unique within your organization and clearly identify its purpose.

Minimum string length: 1

description

string

required

A description of the knowledge base explaining its contents and purpose. AI agents read this to decide when the knowledge base is relevant.

document_language

string

default:en

Primary language of the material in this knowledge base. Deliberately a free-form string rather than an enum: an unrecognised value is accepted and stored rather than rejected.

chunking_strategy

enum<string>

default:recursive

How source material is split before embedding. Applied at index time, so it affects material ingested after it is set.

Available options:

fixed_size,

semantic,

sentence,

paragraph,

recursive

vector_backend

enum<string>

default:pinecone

Vector database backing this knowledge base's index.

Available options:

pinecone,

qdrant,

weaviate,

milvus,

pgvector

embedding_model

enum<string>

default:text-embedding-3-large

Embedding model used to vectorise chunks. Immutable: it is accepted here and never on update, because changing it would invalidate every vector already stored. Pick it up front.

Available options:

text-embedding-3-small,

text-embedding-3-large

chunk_size

integer

default:512

Target chunk size. Applied at index time; nothing already indexed is re-chunked.

Required range: 100 <= x <= 4096

chunk_overlap

integer

default:50

Overlap between consecutive chunks. Applied at index time.

Required range: 0 <= x <= 500

assistant_persona

string | null

A noun phrase rather than a sentence, describing how an assistant built on this knowledge base introduces itself - for example 'a customer-care voice assistant for Acme Bank'. Defaults to a value derived from the name, capped at 280 characters. Treated as identity-and-tone data in the user message, never as system instructions. It affects only answer generation, a capability this reference does not document, so no endpoint documented here is affected by setting it.

Maximum string length: 280

Response

Knowledge base created.

Response model for a knowledge base.

string

required

Unique identifier of the knowledge base.

name

string

required

The name of the knowledge base.

created_at

string<date-time>

required

UTC timestamp indicating when this knowledge base was created.

updated_at

string<date-time>

required

UTC timestamp indicating when this knowledge base was last modified.

description

string | null

Description of the knowledge base's purpose and contents.

document_language

string

default:en

Primary language of the material in this knowledge base.

document_count

integer

default:0

Number of documents stored in this knowledge base.

chunking_strategy

enum<string>

default:recursive

Chunking strategy currently in effect for new material.

Available options:

fixed_size,

semantic,

sentence,

paragraph,

recursive

vector_backend

enum<string>

default:pinecone

Vector database backing this knowledge base's index.

Available options:

pinecone,

qdrant,

weaviate,

milvus,

pgvector

embedding_model

enum<string>

default:text-embedding-3-small

Embedding model in use. Note the asymmetry with the create request, which defaults to text-embedding-3-large: this schema's default is text-embedding-3-small because knowledge bases created before the field existed are on small. Read the value off the response rather than assuming it.

Available options:

text-embedding-3-small,

text-embedding-3-large

chunk_size

integer

default:512

Target chunk size for new material.

chunk_overlap

integer

default:50

Overlap between consecutive chunks.

assistant_persona

string | null

How an assistant built on this knowledge base introduces itself.

status

enum<string> | null

Aggregate processing state of the knowledge base's documents.

Available options:

processing,

completed,

failed

workspace_id

string | null

Workspace this knowledge base belongs to.

organization_id

string | null

Organization this knowledge base belongs to, resolved from your token.

user_id

string | null

User this knowledge base belongs to, resolved from your token.

⌘I

API Reference

AI Agents v2

Built-in Tools

Custom Tools

Calls

Call Recording

Post-call Analysis

Phone Numbers

Knowledge Bases

Prompt Generation

Public Sharing

Webhook Subscriptions

API Keys

Create Knowledge Base

Body

Response