我正在使用LangChain库编写一个小型JavaScript应用程序。我有以下代码片段：

/* LangChain Imports */import { OpenAI } from "langchain/llms/openai";import { BufferMemory } from "langchain/memory";import { ConversationChain } from "langchain/chains";// ========================================================================================= //  // ============= Use LangChain to send request to OpenAi API =============================== //  // ========================================================================================= //  const openAILLMOptions = {    modelName: chatModel.value,    openAIApiKey: decryptedString,    temperature: parseFloat(temperatureValue.value),    topP: parseFloat(topP.value),    maxTokens: parseInt(maxTokens.value),    stop: stopSequences.value.length > 0 ? stopSequences.value : null,    streaming: true,};  const model = new OpenAI(openAILLMOptions);  const memory = new BufferMemory();  const chain = new ConversationChain({ llm: model, memory: memory });  try {    const response = await chain.call({ input: content.value, signal: signal }, undefined,      [        {          handleLLMNewToken(token) {            process.stdout.write(token);          },        },      ]    );// handle the response}

这不起作用（我尝试过使用TypeScript和不使用类型来处理token）。我查阅了各种论坛，它们要么是用Python实现流式传输，要么它们的解决方案与这个问题无关。总之，我可以通过LangChain的ConversationChain() API调用成功获取OpenAI的响应，但无法流式传输响应。有解决方案吗？

回答：

供参考，以下是我如何实现流式传输的：

const openAILLMOptions = {    modelName: chatModel.value,    cache: true,    openAIApiKey: openAIDecryptedString,    temperature: parseFloat(temperatureValue.value),    topP: parseFloat(topP.value),    maxTokens: parseInt(maxTokens.value),    stop: stopSequences.value.length > 0 ? stopSequences.value : null,    streaming: true,    verbose: true,  };const chat = new ChatOpenAI(openAILLMOptions);      const chatPrompt = ChatPromptTemplate.fromMessages([        [          "system",          systemPrompt.value,        ],        new MessagesPlaceholder("history"),        ["human", content.value],      ]);      const chain = new ConversationChain({        memory: new BufferMemory({ returnMessages: true, memoryKey: "history" }),        prompt: chatPrompt,        llm: chat,      });      await chain.call({        input: content.value,        signal: signal,        callbacks: [          {            handleLLMNewToken(token) {              aiResponse.value += token;            }          }        ]      });