| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152 |
- // File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
- import { APIResource } from "../resource.mjs";
- import * as Core from "../core.mjs";
- export class Embeddings extends APIResource {
- /**
- * Creates an embedding vector representing the input text.
- *
- * @example
- * ```ts
- * const createEmbeddingResponse =
- * await client.embeddings.create({
- * input: 'The quick brown fox jumped over the lazy dog',
- * model: 'text-embedding-3-small',
- * });
- * ```
- */
- create(body, options) {
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
- // No encoding_format specified, defaulting to base64 for performance reasons
- // See https://github.com/openai/openai-node/pull/1312
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
- if (hasUserProvidedEncodingFormat) {
- Core.debug('Request', 'User defined encoding_format:', body.encoding_format);
- }
- const response = this._client.post('/embeddings', {
- body: {
- ...body,
- encoding_format: encoding_format,
- },
- ...options,
- });
- // if the user specified an encoding_format, return the response as-is
- if (hasUserProvidedEncodingFormat) {
- return response;
- }
- // in this stage, we are sure the user did not specify an encoding_format
- // and we defaulted to base64 for performance reasons
- // we are sure then that the response is base64 encoded, let's decode it
- // the returned result will be a float32 array since this is OpenAI API's default encoding
- Core.debug('response', 'Decoding base64 embeddings to float32 array');
- return response._thenUnwrap((response) => {
- if (response && response.data) {
- response.data.forEach((embeddingBase64Obj) => {
- const embeddingBase64Str = embeddingBase64Obj.embedding;
- embeddingBase64Obj.embedding = Core.toFloat32Array(embeddingBase64Str);
- });
- }
- return response;
- });
- }
- }
- //# sourceMappingURL=embeddings.mjs.map
|