Azure Cosmos DB NoSQL 语义缓存

import {
  AzureCosmosDBNoSQLConfig,
  AzureCosmosDBNoSQLSemanticCache,
} from "@langchain/azure-cosmosdb";
import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai";

const embeddings = new OpenAIEmbeddings();
const config: AzureCosmosDBNoSQLConfig = {
  databaseName: "<DATABASE_NAME>",
  containerName: "<CONTAINER_NAME>",
  // use endpoint to initiate client with managed identity
  connectionString: "<CONNECTION_STRING>",
};

/**
 * Sets the threshold similarity score for returning cached results based on vector distance.
 * Cached output is returned only if the similarity score meets or exceeds this threshold;
 * otherwise, a new result is generated. Default is 0.6, adjustable via the constructor
 * to suit various distance functions and use cases.
 * (see: https://aka.ms/CosmosVectorSearch).
 */

const similarityScoreThreshold = 0.5;
const cache = new AzureCosmosDBNoSQLSemanticCache(
  embeddings,
  config,
  similarityScoreThreshold
);

const model = new ChatOpenAI({ model: "gpt-4o-mini", cache });

// Invoke the model to perform an action
const response1 = await model.invoke("Do something random!");
console.log(response1);
/*
  AIMessage {
    content: "Sure! I'll generate a random number for you: 37",
    additional_kwargs: {}
  }
*/

const response2 = await model.invoke("Do something random!");
console.log(response2);
/*
  AIMessage {
    content: "Sure! I'll generate a random number for you: 37",
    additional_kwargs: {}
  }
*/