Add new text document to a Vector Store

post

Create a new text document in a vector store.

Path parameters
vector-store-idstringRequired

The ID of the vector store.

Header parameters
x-api-keystringRequired

The API key for authentication.

Body
namestringOptional

The name of the document.

textstringOptional

The text content of the document.

Responses
201
Document created successfully.
application/json
post
POST /api/v1/vector-stores/{vector-store-id}/documents/create HTTP/1.1
Host: api.rememberizer.ai
x-api-key: text
Content-Type: application/json
Accept: */*
Content-Length: 29

{
  "name": "text",
  "text": "text"
}
201

Document created successfully.

{
  "id": 1,
  "name": "text",
  "type": "text",
  "vector_store": "text",
  "size": 1,
  "status": "text",
  "processing_status": "text",
  "indexed_on": "2025-06-26T10:55:09.123Z",
  "status_error_message": "text",
  "created": "2025-06-26T10:55:09.123Z",
  "modified": "2025-06-26T10:55:09.123Z"
}

Example Requests

curl -X POST \
  https://api.rememberizer.ai/api/v1/vector-stores/vs_abc123/documents/create \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Product Overview",
    "text": "Our product is an innovative solution for managing vector embeddings. It provides seamless integration with your existing systems and offers powerful semantic search capabilities."
  }'

Replace YOUR_API_KEY with your actual Vector Store API key and vs_abc123 with your Vector Store ID.

Path Parameters

Parameter
Type
Description

vector-store-id

string

Required. The ID of the vector store to add the document to.

Request Body

{
  "name": "Product Overview",
  "text": "Our product is an innovative solution for managing vector embeddings. It provides seamless integration with your existing systems and offers powerful semantic search capabilities."
}
Parameter
Type
Description

name

string

Required. The name of the document.

text

string

Required. The text content of the document.

Response Format

{
  "id": 1234,
  "name": "Product Overview",
  "type": "text/plain",
  "vector_store": "vs_abc123",
  "size": 173,
  "status": "processing",
  "processing_status": "queued",
  "indexed_on": null,
  "status_error_message": null,
  "created": "2023-06-15T10:15:00Z",
  "modified": "2023-06-15T10:15:00Z"
}

Authentication

This endpoint requires authentication using an API key in the x-api-key header.

Error Responses

Status Code
Description

400

Bad Request - Missing required fields or invalid format

401

Unauthorized - Invalid or missing API key

404

Not Found - Vector Store not found

500

Internal Server Error

This endpoint allows you to add text content directly to your vector store. It's particularly useful for storing information that might not exist in file format, such as product descriptions, knowledge base articles, or custom content. The text will be automatically processed into vector embeddings, making it searchable using semantic similarity.

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