72 lines
1.7 KiB
TypeScript
72 lines
1.7 KiB
TypeScript
import { kv } from '@vercel/kv'
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import { OpenAIStream, StreamingTextResponse } from 'ai-connector'
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import { Configuration, OpenAIApi } from 'openai-edge'
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import { auth } from '@/auth'
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import { nanoid } from '@/lib/utils'
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export const runtime = 'edge'
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const configuration = new Configuration({
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apiKey: process.env.OPENAI_API_KEY
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})
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const openai = new OpenAIApi(configuration)
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if (!process.env.OPENAI_API_KEY) {
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throw new Error('Missing env var from OpenAI')
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}
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export async function POST(req: Request) {
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const session = await auth()
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if (session == null) {
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return new Response('Unauthorized', { status: 401 })
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}
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const json = await req.json()
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const { messages } = json
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const res = await openai.createChatCompletion({
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model: 'gpt-3.5-turbo',
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messages,
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temperature: 0.7,
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top_p: 1,
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frequency_penalty: 1,
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max_tokens: 500,
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n: 1,
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stream: true
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})
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const stream = OpenAIStream(res, {
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async onCompletion(completion) {
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const title = json.messages[0].content.substring(0, 100)
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const userId = session?.user.id
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if (userId) {
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const id = json.id ?? nanoid()
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const createdAt = Date.now()
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const path = `/chat/${id}`
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const payload = {
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id,
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title,
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userId,
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createdAt,
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path,
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messages: [
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...messages,
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{
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content: completion,
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role: 'assistant'
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}
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]
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}
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await kv.hmset(`chat:${id}`, payload)
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await kv.zadd(`user:chat:${userId}`, {
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score: createdAt,
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member: `chat:${id}`
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})
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}
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}
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})
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return new StreamingTextResponse(stream)
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}
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