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@genkit-ai/vertexai

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

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"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 context_caching_exports = {}; __export(context_caching_exports, { handleCacheIfNeeded: () => handleCacheIfNeeded, handleContextCache: () => handleContextCache }); module.exports = __toCommonJS(context_caching_exports); var import_resources = require("@google-cloud/vertexai/build/src/resources"); var import_genkit = require("genkit"); var import_logging = require("genkit/logging"); var import_utils = require("./utils.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 * * https://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */ async function handleContextCache(apiClient, request, chatRequest, modelVersion, cacheConfigDetails) { const cachedContentsClient = new import_resources.CachedContents(apiClient); const { cachedContent, chatRequest: newChatRequest } = (0, import_utils.getContentForCache)( request, chatRequest, modelVersion, cacheConfigDetails ); cachedContent.model = modelVersion; const cacheKey = (0, import_utils.generateCacheKey)(cachedContent); cachedContent.displayName = cacheKey; let cache; try { cache = await (0, import_utils.lookupContextCache)(cachedContentsClient, cacheKey); import_logging.logger.debug(`Cache hit: ${cache ? "true" : "false"}`); } catch (error) { import_logging.logger.debug("No cache found, creating one."); } if (!cache) { try { const createParams = { ...cachedContent, // TODO: make this neater - idk why they chose to stringify the ttl... ttl: JSON.stringify((0, import_utils.calculateTTL)(cacheConfigDetails)) + "s" }; cache = await cachedContentsClient.create(createParams); import_logging.logger.debug(`Created new cache entry with key: ${cacheKey}`); } catch (cacheError) { import_logging.logger.error( `Failed to create cache with key ${cacheKey}: ${cacheError}` ); throw new import_genkit.GenkitError({ status: "INTERNAL", message: `Failed to create cache: ${cacheError}` }); } } if (!cache) { throw new import_genkit.GenkitError({ status: "INTERNAL", message: "Failed to use context cache feature" }); } newChatRequest.cachedContent = cache.name; return { cache, newChatRequest }; } async function handleCacheIfNeeded(apiClient, request, chatRequest, modelVersion, cacheConfigDetails) { if (!cacheConfigDetails || !(0, import_utils.validateContextCacheRequest)(request, modelVersion)) { return { chatRequest, cache: null }; } const { cache, newChatRequest } = await handleContextCache( apiClient, request, chatRequest, modelVersion, cacheConfigDetails ); return { chatRequest: newChatRequest, cache }; } // Annotate the CommonJS export names for ESM import in node: 0 && (module.exports = { handleCacheIfNeeded, handleContextCache }); //# sourceMappingURL=index.js.map