오픈AI 컴플리션 스트림을 사용하여 Node.js와 Express.js로 시작하기

import express, { Request, Response } from 'express';
import cors from 'cors';
import { Configuration, OpenAIAPI } from 'openai';
// ...
app.post('/api/admin/testStream', async (req: Request, res: Response) => {
    const { password } = req.body;
    try {
        if (password !== process.env.ADMIN_PASSWORD) {
            res.send({ message: '잘못된 비밀번호입니다' });
            return;
        }
        const completion = await openai.createCompletion({
            model: 'text-davinci-003',
            prompt: '이것은 테스트입니다',
            stream: true,
        }, { responseType: 'stream' });
        completion.data.on('data', (chunk: any) => {
            console.log(chunk.toString());
        });
        res.send({ message: '스트림이 시작되었습니다' });
    } catch (err) {
        console.log(err);
        res.send(err);
    }
});
// ...

현재, 에러가 발생하고 있습니다.

타입 'CreateCompletionResponse'에는 'on' 속성이 존재하지 않습니다.ts(2339)

{ responseType: 'stream' }을 설정하더라도 그래도 발생합니다.

이 문제를 어떻게 해결하고 응답을 앞단으로 청크 단위로 보낼 수 있을까요? (저는 Socket.IO을 사용하고 있습니다.)

답변 1

import express, { Request, Response } from 'express';
import cors from 'cors';
import { Configuration, OpenAIAPI } from 'openai';
import http, { IncomingMessage } from 'http';
// ...
app.post('/api/admin/testStream', async (req: Request, res: Response) => {
    const { password } = req.body;
    try {
        if (password !== process.env.ADMIN_PASSWORD) {
            res.send({ message: '잘못된 비밀번호입니다' });
            return;
        }
        const completion = await openai.createChatCompletion({
            model: 'gpt-3.5-turbo',
            messages: [{ role: 'user', content: '미국은 언제 설립되었나요?' }],
            stream: true,
        }, { responseType: 'stream' });
        const stream = completion.data as unknown as IncomingMessage;
        stream.on('data', (chunk: Buffer) => {
            const payloads = chunk.toString().split(\n\n);
            for (const payload of payloads) {
                if (payload.includes('[DONE]')) return;
                if (payload.startsWith(data:)) {
                    const data = JSON.parse(payload.replace(data: , ));
                    try {
                        const chunk: undefined | string = data.choices[0].delta?.content;
                        if (chunk) {
                            console.log(chunk);
                        }
                    } catch (error) {
                        console.log(`JSON.parse와 ${payload}에서 오류가 발생했습니다.\n${error}`);
                    }
                }
            }
        });
        stream.on('end', () => {
            setTimeout(() => {
                console.log('\n스트림 완료');
                res.send({ message: '스트림 완료' });
            }, 10);
        });
        stream.on('error', (err: Error) => {
            console.log(err);
            res.send(err);
        });
    } catch (err) {
        console.log(err);
        res.send(err);
    }
});
// ...

더 많은 정보는 https://github.com/openai/openai-node/issues/18을(를) 방문하세요.

또한 Socket.IO 이벤트를 사용하여 메시지 청크를 보낼 수도 있었습니다!

그런데 이 앱을 더 자세히 보려는 사람들을 위해 다음 링크를 확인할 수 있습니다:

• 프론트엔드


• 백엔드

답변 2

Title: OpenAI Completion Stream: Boosting Node.js and Express.js Performance
Introduction:
In the rapidly evolving world of web development, OpenAI Completion Stream has emerged as a cutting-edge technology that brings significant benefits to Node.js and Express.js. This essay will delve into how the OpenAI Completion Stream assists in optimizing these technologies' performance, resulting in enhanced user experiences for developers and end-users alike. By harnessing the power of OpenAI's language model, developers can now seamlessly improve their SEO strategies and boost website performance effortlessly.
1. Understanding Node.js and Express.js:
Node.js is a runtime environment that allows developers to execute JavaScript code server-side, while Express.js is a powerful framework built on top of Node.js. Together, they provide developers with the ability to build robust and scalable web applications. However, optimizing their performance requires employing intelligent strategies, and OpenAI Completion Stream is here to help.
2. Leveraging OpenAI Completion Stream:
OpenAI Completion Stream enables developers to enhance the performance of Node.js and Express.js applications. By utilizing natural language processing algorithms, OpenAI enhances code completion, leading to efficient programming and increased productivity. Developers can write optimized and SEO-conscious code, ensuring their applications are easily discoverable by search engines.
3. Improving SEO Techniques:
SEO (Search Engine Optimization) plays a crucial role in driving organic traffic to websites. With OpenAI Completion Stream, developers can effortlessly create SEO-conscious content for their web applications. By suggesting relevant keywords, optimizing meta tags, and generating descriptive content, the language model assists developers in crafting web pages that rank well in search engine results pages (SERPs).
4. Real-time Performance Optimization:
To enhance website performance and user experience, developers often need to optimize their Node.js and Express.js applications. OpenAI Completion Stream provides real-time suggestions for performance optimization techniques. It advises on implementing caching mechanisms, reducing response times, and improving server-side rendering to ensure faster page loading. These optimization techniques help to decrease bounce rates, improve user engagement, and boost search engine rankings.
5. Streamlining Development Workflow:
OpenAI Completion Stream simplifies the development process by generating code snippets, templates, and solutions for common web development tasks. This resourcefulness allows developers to build applications faster and more efficiently. As a result, time-consuming tasks, such as creating routing systems, database integrations, and authentication mechanisms, can now be completed effortlessly, leaving developers with more time to focus on the core features of their applications.
6. Ensuring Scalability and Security:
As web applications grow in complexity, ensuring scalability and security becomes paramount. OpenAI Completion Stream guides developers in implementing effective load balancing, database scaling, and encryption techniques. This ensures that applications can handle high traffic volumes while protecting sensitive user data. Developers can rely on the language model to assist with the implementation of best practices and mitigate potential security vulnerabilities.
Conclusion:
OpenAI Completion Stream is transforming the way developers optimize and enhance Node.js and Express.js applications. With its language model's assistance, developers can effortlessly improve their SEO techniques, streamline workflow, improve performance, maintain scalability, and ensure robust security measures. Embracing the power of OpenAI Completion Stream helps developers pave the way for successful web applications that deliver remarkable user experiences and excel in the competitive online landscape.