JavaScript

import SGPClient from 'sgp';

const client = new SGPClient({
  apiKey: process.env['SGP_API_KEY'], // This is the default and can be omitted
});

const embeddingResponse = await client.models.embeddings.create('model_deployment_id', { texts: ['string'] });

console.log(embeddingResponse.embeddings);

{
  "embeddings": [
    [
      "<any>"
    ]
  ],
  "tokens_used": 0
}

Models

Generate text embedding

Description

Computes the text embeddings for text fragments using the model with the given model_deployment_id.

Details

Users can use this API to execute EMBEDDING type EGP model they have access to. To use this API, pass in the id of a model returned by the V3 Create Model API. An example text embedding request

{
    "texts": ["Please compute my embedding vector", "Another text fragment"]
}

POST

models

{model_deployment_id}

embeddings

JavaScript

import SGPClient from 'sgp';

const client = new SGPClient({
  apiKey: process.env['SGP_API_KEY'], // This is the default and can be omitted
});

const embeddingResponse = await client.models.embeddings.create('model_deployment_id', { texts: ['string'] });

console.log(embeddingResponse.embeddings);

{
  "embeddings": [
    [
      "<any>"
    ]
  ],
  "tokens_used": 0
}

Path Parameters

model_deployment_id

string

required

Body

application/json

Response

200

application/json

Successful Response

The response is of type object.

Poll Async Inference for result Generate reranking

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