textembedding-gecko

This documentation is valid for the following list of our models:

• textembedding-gecko-multilingual@001

• textembedding-gecko@001

• textembedding-gecko@003

Model Overview

A state-of-the-art text embedding model designed to convert textual data into numerical vector representations. It captures semantic meanings and relationships within the text, facilitating various natural language processing (NLP) tasks.

Setup your API Key

If you don’t have an API key for the Apilaplas API yet, feel free to use our Quickstart guide.

Submit a request

API Schema

post

Authorizations

Body

modelundefined · enumRequiredPossible values:

inputany ofRequired

string · min: 1Optional

or

string[] · min: 1Optional

dimensionsnumber | nullableOptional

auto_truncatebooleanOptionalDefault: true

task_typestring · enumOptionalPossible values:

titlestringOptional

encoding_formatstringOptional

Responses

201Success

post

HTTPcURLJavaScriptPython

POST /v1/embeddings HTTP/1.1
Host: api.apilaplas.com
Authorization: Bearer <YOUR_LAPLASAPI_KEY>
Content-Type: application/json
Accept: */*
Content-Length: 169

{
  "model": "textembedding-gecko-multilingual@001",
  "input": "text",
  "dimensions": 1,
  "auto_truncate": true,
  "task_type": "RETRIEVAL_QUERY",
  "title": "text",
  "encoding_format": "text"
}

201Success

No content