@genkit-ai/compat-oai/lib/embedder.js

Genkit AI framework plugin for OpenAI APIs.

"use strict";
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
  for (var name in all)
    __defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
  if (from && typeof from === "object" || typeof from === "function") {
    for (let key of __getOwnPropNames(from))
      if (!__hasOwnProp.call(to, key) && key !== except)
        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
  }
  return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
var embedder_exports = {};
__export(embedder_exports, {
  defineCompatOpenAIEmbedder: () => defineCompatOpenAIEmbedder
});
module.exports = __toCommonJS(embedder_exports);
function defineCompatOpenAIEmbedder(params) {
  const { ai, name, client, embedderRef } = params;
  const modelName = name.substring(name.indexOf("/") + 1);
  return ai.defineEmbedder(
    {
      name,
      configSchema: embedderRef?.configSchema,
      ...embedderRef?.info
    },
    async (input, options) => {
      const { encodingFormat: encoding_format, ...restOfConfig } = options;
      const embeddings = await client.embeddings.create({
        model: modelName,
        input: input.map((d) => d.text),
        encoding_format,
        ...restOfConfig
      });
      return {
        embeddings: embeddings.data.map((d) => ({ embedding: d.embedding }))
      };
    }
  );
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
  defineCompatOpenAIEmbedder
});
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