Achieve streaming output like the ChatGPT mainframe
Moeki Kawakami
Posted on April 9, 2023
In this example, we use Langchain, but perhaps the original API alone can be used.
Welcome to LangChain | 🦜️🔗 Langchain
First, the server side.
import { ChatOpenAI } from "langchain/chat_models"
import { HumanChatMessage } from "langchain/schema"
import { CallbackManager } from "langchain/callbacks"
const api = (req, res, ctx) => {
if (req.method !== "POST") return
const input = req.body.input
const chat = new ChatOpenAI({
openAIApiKey: OPENAI_API_KEY,
streaming: true
callbackManager: CallbackManager.fromHandlers({
async handleLLMNewToken(token: string) {
res.write(token)
},
}),
})
await chat.call([new HumanChatMessage(input)])
res.end()
})
The point is to enable streaming with streaming: true
and write()
. This is called Writable streams in Node.js and is enabled for files and responses.
When all the Langchain processing is done, we terminate it with end()
.
Next is the client side.
const reply = async (input) => {
const decoder = new TextDecoder()
const res = await fetch(ENDPOINT, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
input,
}),
})
const reader = res?.body?.getReader()
let output = ""
while (true) {
if (reader) {
const { value, done } = await reader.read()
if (done) break
output += decoder.decode(value)
}
}
}
The point is getReader()
. Also, we need to decode it, so we put that process in.
💖 💪 🙅 🚩
Moeki Kawakami
Posted on April 9, 2023
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