@genkit-ai/vertexai/lib/index.js

Genkit AI framework plugin for Google Cloud Vertex AI APIs including Gemini APIs, Imagen, and more.

"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 src_exports = {};
__export(src_exports, {
  default: () => src_default,
  gemini: () => import_gemini.gemini,
  gemini10Pro: () => import_gemini.gemini10Pro,
  gemini15Flash: () => import_gemini.gemini15Flash,
  gemini15Pro: () => import_gemini.gemini15Pro,
  gemini20Flash: () => import_gemini.gemini20Flash,
  gemini20Flash001: () => import_gemini.gemini20Flash001,
  gemini20FlashLite: () => import_gemini.gemini20FlashLite,
  gemini20FlashLitePreview0205: () => import_gemini.gemini20FlashLitePreview0205,
  gemini20ProExp0205: () => import_gemini.gemini20ProExp0205,
  gemini25ProExp0325: () => import_gemini.gemini25ProExp0325,
  gemini25ProPreview0325: () => import_gemini.gemini25ProPreview0325,
  imagen2: () => import_imagen.imagen2,
  imagen3: () => import_imagen.imagen3,
  imagen3Fast: () => import_imagen.imagen3Fast,
  multimodalEmbedding001: () => import_embedder.multimodalEmbedding001,
  textEmbedding004: () => import_embedder.textEmbedding004,
  textEmbedding005: () => import_embedder.textEmbedding005,
  textEmbeddingGecko003: () => import_embedder.textEmbeddingGecko003,
  textEmbeddingGeckoMultilingual001: () => import_embedder.textEmbeddingGeckoMultilingual001,
  textMultilingualEmbedding002: () => import_embedder.textMultilingualEmbedding002,
  vertexAI: () => vertexAI
});
module.exports = __toCommonJS(src_exports);
var import_plugin = require("genkit/plugin");
var import_common = require("./common/index.js");
var import_embedder = require("./embedder.js");
var import_gemini = require("./gemini.js");
var import_imagen = require("./imagen.js");
/**
 * @license
 *
 * Copyright 2024 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
function vertexAI(options) {
  return (0, import_plugin.genkitPlugin)("vertexai", async (ai) => {
    const { projectId, location, vertexClientFactory, authClient } = await (0, import_common.getDerivedParams)(options);
    Object.keys(import_imagen.SUPPORTED_IMAGEN_MODELS).map(
      (name) => (0, import_imagen.imagenModel)(ai, name, authClient, { projectId, location })
    );
    Object.keys(import_gemini.SUPPORTED_GEMINI_MODELS).map(
      (name) => (0, import_gemini.defineGeminiKnownModel)(
        ai,
        name,
        vertexClientFactory,
        {
          projectId,
          location
        },
        options?.experimental_debugTraces
      )
    );
    if (options?.models) {
      for (const modelOrRef of options?.models) {
        const modelName = typeof modelOrRef === "string" ? modelOrRef : (
          // strip out the `vertexai/` prefix
          modelOrRef.name.split("/")[1]
        );
        const modelRef = typeof modelOrRef === "string" ? (0, import_gemini.gemini)(modelOrRef) : modelOrRef;
        (0, import_gemini.defineGeminiModel)({
          ai,
          modelName: modelRef.name,
          version: modelName,
          modelInfo: modelRef.info,
          vertexClientFactory,
          options: {
            projectId,
            location
          },
          debugTraces: options.experimental_debugTraces
        });
      }
    }
    Object.keys(import_embedder.SUPPORTED_EMBEDDER_MODELS).map(
      (name) => (0, import_embedder.defineVertexAIEmbedder)(ai, name, authClient, { projectId, location })
    );
  });
}
var src_default = vertexAI;
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
  gemini,
  gemini10Pro,
  gemini15Flash,
  gemini15Pro,
  gemini20Flash,
  gemini20Flash001,
  gemini20FlashLite,
  gemini20FlashLitePreview0205,
  gemini20ProExp0205,
  gemini25ProExp0325,
  gemini25ProPreview0325,
  imagen2,
  imagen3,
  imagen3Fast,
  multimodalEmbedding001,
  textEmbedding004,
  textEmbedding005,
  textEmbeddingGecko003,
  textEmbeddingGeckoMultilingual001,
  textMultilingualEmbedding002,
  vertexAI
});
//# sourceMappingURL=index.js.map