import { AzureCosmosDBNoSQLConfig } from "../azure_cosmosdb_nosql.js";
import { BaseCache } from "@langchain/core/caches";
import { EmbeddingsInterface } from "@langchain/core/embeddings";
import { Generation } from "@langchain/core/outputs";

//#region src/caches/caches_nosql.d.ts
/**
 * Represents a Semantic Cache that uses CosmosDB NoSQL backend as the underlying
 * storage system.
 *
 * @example
 * ```typescript
 * const embeddings = new OpenAIEmbeddings();
 * const cache = new AzureCosmosDBNoSQLSemanticCache(embeddings, {
 *   databaseName: DATABASE_NAME,
 *   containerName: CONTAINER_NAME
 * });
 * const model = new ChatOpenAI({ model: "gpt-4o-mini", cache });
 *
 * // Invoke the model to perform an action
 * const response = await model.invoke("Do something random!");
 * console.log(response);
 * ```
 */
declare class AzureCosmosDBNoSQLSemanticCache extends BaseCache {
  private embeddings;
  private config;
  private similarityScoreThreshold;
  private cacheDict;
  private vectorDistanceFunction;
  constructor(embeddings: EmbeddingsInterface, dbConfig: AzureCosmosDBNoSQLConfig, similarityScoreThreshold?: number);
  private getLlmCache;
  /**
   * Retrieves data from the cache.
   *
   * @param prompt The prompt for lookup.
   * @param llmKey The LLM key used to construct the cache key.
   * @returns An array of Generations if found, null otherwise.
   */
  lookup(prompt: string, llmKey: string): Promise<any[] | null>;
  /**
   * Updates the cache with new data.
   *
   * @param prompt The prompt for update.
   * @param llmKey The LLM key used to construct the cache key.
   * @param value The value to be stored in the cache.
   */
  update(prompt: string, llmKey: string, returnValue: Generation[]): Promise<void>;
  /**
   * deletes the semantic cache for a given llmKey
   * @param llmKey
   */
  clear(llmKey: string): Promise<void>;
}
//#endregion
export { AzureCosmosDBNoSQLSemanticCache };
//# sourceMappingURL=caches_nosql.d.ts.map