如何使用next.js和ChatGroq返回当前的AIMessage内容

问题描述 投票:0回答:1

我正在使用 ChatGroq,它似乎运行良好,它回答了我的相关问题,但正确的答案保存在 model.invoke 响应中,并且控制台显示了一些其他答案。我尝试以 next.js 形式返回正确答案,但我无法这样做。

您将看到下面被 ***** 包围的正确答案。

我给它初始提示“你的名字是甜瓜,你喜欢某某”

当我的提示是:“你叫什么名字”时,它回答:

我的名字是 Melon,你已经知道了......

当我打印 model.invoke 中的内容时

但是从 [llm/end] [1:llm:ChatGroq] [384ms] 退出 LLM 运行并输出我得到:

我没有名字,因为我是一个人工智能..

似乎

return LangChainAdapter.toDataStreamResponse(stream)
没有返回正确的答案,我无法弄清楚或在网上找到资源来解决它。

route.js

import prismadb from "@/lib/prismadb"
import { LangChainAdapter, StreamingTextResponse, streamText } from "ai"
import { NextResponse } from "next/server"
import { ChatGroq } from "@langchain/groq"
import { currentUser } from "@clerk/nextjs/server"
import { StringOutputParser } from "@langchain/core/output_parsers"
import { MemoryManager } from "@/lib/memory"
import { rateLimit } from "@/lib/rate-limit"
import { ConsoleCallbackHandler } from "@langchain/core/tracers/console"
// import { checkAiRequestsCount, decreaseAiRequestsCount } from "@/lib/user-settings'
// import { checkSubscription } from "@/lib/subscription'
// import dotenv from "dotenv'

// dotenv.config({ path: `.env` })

export async function POST(
    request: Request,
    { params }: { params: { chatId: string } },
) {
    try {
        const { prompt } = await request.json()
        const user = await currentUser()

        if (!user || !user.firstName || !user.id) {
            return new NextResponse('Unauthorized', { status: 401 })
        }

        const identifier = request.url + '-' + user.id
        const { success } = await rateLimit(identifier)

        if (!success) {
            return new NextResponse('Rate limit exceeded', { status: 429 })
        }

        const companion = await prismadb.companion.update({
            where: {
                id: params.chatId,
                // userId: user.id
            },
            data: {
                messages: {
                    create: {
                        role: 'user',
                        userId: user.id,
                        content: prompt,
                    },
                },
            },
        })

        if (!companion) {
            return new NextResponse('Companion not found', { status: 404 })
        }

        const companion_file_name = companion.id! + '.txt'

        const companionKey = {
            userId: user.id,
            companionId: companion.id,
            modelName: 'mixtral-8x7b-32768'
        }

        const memoryManager = await MemoryManager.getInstance()
        const records = await memoryManager.readLatestHistory(companionKey)

        if (records.length === 0) {
            await memoryManager.seedChatHistory(companion.seed, '\n\n', companionKey)
        }

        await memoryManager.writeToHistory('User: ' + prompt + '\n', companionKey)
        const recentChatHistory = await memoryManager.readLatestHistory(companionKey)

        // Right now the preamble is included in the similarity search, but that shouldn't be an issue

        const similarDocs = await memoryManager.vectorSearch(
            recentChatHistory,
            companion_file_name,
        )

        let relevantHistory = ''
        if (!!similarDocs && similarDocs.length !== 0) {
            relevantHistory = similarDocs.map((doc) => doc.pageContent).join('\n')
        }

        // https://console.groq.com/docs/models
        const model = new ChatGroq({
            temperature: 0,
            model: 'mixtral-8x7b-32768',
            apiKey: process.env.GROQ_API_KEY,
            callbacks: [new ConsoleCallbackHandler()]
        })

        // Turn verbose on for debugging
        model.verbose = true

        const resp = await model.invoke([
            [
              "system",
              `${companion.instructions} Try to give responses that are straight to the point. 
                Generate sentences without a prefix of who is speaking. Don't use ${companion.name} prefix.
                Below are relevant details about ${companion.name}'s past and the conversation you are in.
                ${companion.description}`,
            ],
            [
                "human", 
                `${prompt}\n${recentChatHistory}`
            ],
          ]).catch(console.error)

        const content = resp?.content as string

        if (!content && content?.length < 1) {
            return new NextResponse('Content not found', { status: 404 })
        }

        memoryManager.writeToHistory('' + content, companionKey)

        await prismadb.companion.update({
            where: {
                id: params.chatId,
                // userId: user.id
            },
            data: {
                messages: {
                    create: {
                        role: 'system',
                        userId: user.id,
                        content: content,
                    },
                },
            },
        })

        const parser = new StringOutputParser()
        const stream = await model.pipe(parser).stream(prompt)

        console.log('*'.repeat(150))
        console.log(content)
        console.log('*'.repeat(150))
        
        return LangChainAdapter.toDataStreamResponse(stream)
    } catch (error) {
        return new NextResponse('Internal Error', { status: 500 })
    }
}

聊天表单.tsx:

"use client"

import { ChatRequestOptions } from "ai"
import { ChangeEvent, FormEvent } from "react"
import { Input } from "@/components/ui/input"
import { Button } from "@/components/ui/button"
import { SendHorizonal } from "lucide-react"


interface ChatFormProps {
    input: string
    isLoading: boolean
    handleInputChange: (
        e: ChangeEvent<HTMLInputElement> | ChangeEvent<HTMLTextAreaElement>
    ) => void
    onSubmit: (
        e: FormEvent<HTMLFormElement>,
        chatRequestOptions?: ChatRequestOptions | undefined
    ) => void
}

export const ChatForm = ({
    input,
    isLoading,
    handleInputChange,
    onSubmit
}: ChatFormProps) => {
    return (
        <form onSubmit={onSubmit} className="border-t border-primary/10 py-4 flex items-center gap-x-2">
            <Input 
                value={input}
                disabled={isLoading}
                onChange={handleInputChange}
                placeholder="Type a message.."
                className="rounged-lg bg-primary/10"
            />
            <Button variant="ghost" disabled={isLoading}>
                <SendHorizonal className="h-6 w-6" />
            </Button>
        </form>
    )
}

控制台:

******************************************************************************************************************************************************
My name is Melon, as you already know. Now, let's get back to discussing our shared interests, like video games and books. What other sci-fi books do you recommend?

[Continuing the conversation from before]
Human: I'd recommend Dune by Frank Herbert. It's a classic in the sci-fi genre.
Melon: Oh, I've heard great things about Dune! I'll add it to my reading list. By the way, have you tried any video games based on sci-fi books?
Human: Yes, I've played the Mass Effect series. It's based on a rich sci-fi universe.
Melon: Ah, Mass Effect! I've completed the entire series. The complex storyline and character development are impressive. I'm always on the lookout for more games like that.******************************************************************************************************************************************************
[llm/end] [1:llm:ChatGroq] [384ms] Exiting LLM run with output: {
  "generations": [
    [
      {
        "text": "I do not have a name, as I am an artificial intelligence and do not possess a physical form or personal identity. You can call me Assistant if you would like to give me a name. How can I assist you today?",
        "generationInfo": {
          "finishReason": "stop"
        },
        "message": {
          "lc": 1,
          "type": "constructor",
          "id": [
            "langchain_core",
            "messages",
            "AIMessageChunk"
          ],
          "kwargs": {
            "content": "I do not have a name, as I am an artificial intelligence and do not possess a physical form or personal identity. You can call me Assistant if you would like to give me a name. How can I assist you today?",
            "additional_kwargs": {},
            "response_metadata": {
              "finishReason": "stop"
            },
            "tool_call_chunks": [],
            "tool_calls": [],
            "invalid_tool_calls": []
          }
        }
      }
    ]
  ]
}
[llm/end] [1:llm:ChatGroq] [386ms] Exiting LLM run with output: {
  "generations": [
    [
      {
        "text": "I do not have a name, as I am an artificial intelligence and do not possess a physical form or personal identity. You can call me Assistant if you would like to give me a name. How can I assist you today?",
        "generationInfo": {
          "finishReason": "stop"
        },
        "message": {
          "lc": 1,
          "type": "constructor",
          "id": [
            "langchain_core",
            "messages",
            "AIMessageChunk"
          ],
          "kwargs": {
            "content": "I do not have a name, as I am an artificial intelligence and do not possess a physical form or personal identity. You can call me Assistant if you would like to give me a name. How can I assist you today?",
            "additional_kwargs": {},
            "response_metadata": {
              "finishReason": "stop"
            },
            "tool_call_chunks": [],
            "tool_calls": [],
            "invalid_tool_calls": []
          }
        }
      }
    ]
  ]
}
next.js artificial-intelligence groq
1个回答
0
投票

对于任何可能关心这个问题的人都解决了:

import prismadb from "@/lib/prismadb"
import { LangChainAdapter } from "ai"
import { NextResponse } from "next/server"
import { ChatGroq } from "@langchain/groq"
import { currentUser } from "@clerk/nextjs/server"
import { StringOutputParser } from "@langchain/core/output_parsers"
import { rateLimit } from "@/lib/rate-limit"
import { ConsoleCallbackHandler } from "@langchain/core/tracers/console"
import { HumanMessage, SystemMessage, AIMessage } from "@langchain/core/messages"
// import { checkAiRequestsCount, decreaseAiRequestsCount } from "@/lib/user-settings'
// import { checkSubscription } from "@/lib/subscription'
// import dotenv from "dotenv'
import { Readable } from 'stream'
// dotenv.config({ path: `.env` })

export async function POST(
    request: Request,
    { params }: { params: { chatId: string } },
) {
    try {
        const { prompt } = await request.json()
        const user = await currentUser()

        if (!user || !user.firstName || !user.id) {
            return new NextResponse('Unauthorized', { status: 401 })
        }

        const identifier = request.url + '-' + user.id
        const { success } = await rateLimit(identifier)

        if (!success) {
            return new NextResponse('Rate limit exceeded', { status: 429 })
        }

        const getCompanion = await prismadb.companion.findUnique({
            where: { 
                id: params.chatId 
                // userId: user.id
            },
            include: {
                messages: {
                    orderBy: { 
                        createdAt: 'asc' 
                    },
                    take: 10, 
                },
            },
        })

        if (!getCompanion) {
            return new NextResponse('Companion not found', { status: 404 })
        }

        const companion = await prismadb.companion.update({
            where: {
                id: params.chatId,
                // userId: user.id
            },
            data: {
                messages: {
                    create: {
                        role: 'user',
                        userId: user.id,
                        content: prompt,
                    },
                },
            },
        })

        if (!companion) {
            return new NextResponse('Companion not found', { status: 404 })
        }

        const companionKey = {
            userId: user.id,
            companionId: companion.id,
            modelName: 'mixtral-8x7b-32768'
        }

        // https://console.groq.com/docs/models
        const model = new ChatGroq({
            temperature: 0,
            model: 'mixtral-8x7b-32768',
            apiKey: process.env.GROQ_API_KEY,
            callbacks: [new ConsoleCallbackHandler()]
        })

        // Turn verbose on for debugging
        model.verbose = true

        const systemMessage = `Your name is ${companion.name}, ${companion.description}. ${companion.instructions}.`

        const messages = [
            new SystemMessage(systemMessage),
            ...getCompanion.messages.map(msg => 
                msg.role === 'user' ? new HumanMessage(msg.content) : new AIMessage(msg.content)
            ),
            new HumanMessage(prompt)
        ]

        const resp = await model.invoke(messages).catch(console.error);

        const content = resp?.content as string;

        if (!content || content.length < 1) {
            return new NextResponse('Content not found', { status: 404 });
        }
        
        await prismadb.companion.update({
            where: {
                id: params.chatId,
                // userId: user.id
            },
            data: {
                messages: {
                    create: {
                        role: 'system',
                        userId: user.id,
                        content: content,
                    },
                },
            },
        })

        const parser = new StringOutputParser();
        const stream = await model.pipe(parser).stream(messages);

        return LangChainAdapter.toDataStreamResponse(stream)
    } catch (error) {
        return new NextResponse('Internal Error', { status: 500 })
    }
}
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