Module-not-found

[Pratham271]

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• I added a very descriptive title to this question.
• I searched the LangChain documentation with the integrated search.
• I used the GitHub search to find a similar question and didn't find it.

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Example Code

## pineconedb.ts
import { PremEmbeddings } from "@langchain/community/embeddings/premai";
import { Pinecone } from '@pinecone-database/pinecone';
import { PineconeStore } from "@langchain/pinecone";


export async function getVectorStore(){
    const embeddings = new PremEmbeddings({
        // In Node.js defaults to process.env.PREM_API_KEY
        apiKey: process.env.PREM_API_KEY,
        // In Node.js defaults to process.env.PREM_PROJECT_ID
        project_id: 1744,
        model: "text-embedding-3-large", // The model to generate the embeddings
      });
      
    const pineconeClient = new Pinecone({
        apiKey: process.env.PINECONE_API_KEY!
    });

    const index = pineconeClient.Index(process.env.PINECONE_INDEX_NAME!);

    const vectorStore = await PineconeStore.fromExistingIndex(embeddings, {
        pineconeIndex: index,
        textKey: 'text',
      });
    
    return vectorStore
}
 ## chat.ts
import OpenAI from 'openai';
import { createAI, createStreamableValue } from "ai/rsc";
import { getVectorStore } from '@/lib/pineconedb';

let openai = new OpenAI({
    baseURL: 'https://api.groq.com/openai/v1', // Default value
    apiKey: process.env.GROQ_API_KEY,
});

interface ChatMessageProps {
    role: string;
    content?: string;
    isLoading?: boolean;
  }

async function myAction(userMessage: string): Promise<any>{
    "use server"
    const streamable = createStreamableValue({});

    (async ()=> {
        const vectorStore = await getVectorStore()

        const result = await vectorStore.similaritySearch(userMessage,4)
        console.log(result)
        const results = await vectorStore.similaritySearch(userMessage, 4);

        // const formattedPrevMessages = prevMessages ? prevMessages.map((msg) => ({
        //     role: msg.role,
        //     content: msg.content,
        //   })) : [];

        const chatCompletion = await openai.chat.completions.create({
            messages: 
        [{
            role: "system",
            content: `Use the following pieces of context to answer the users question in markdown format.`
        },
        {
            role: "user",
            content: `You are a chatbot, named Jarvis , for a personal portfolio website of Pratham Chauhan. You impersonate the website's owner. Use the following pieces of context to answer the question at the end. Whenever it makes sense, provide links to pages that contain more information about the topic from the given context.
            If you don't know the answer, just say you don't know. DO NOT try to make up an answer. DO NOT give the answer if it is not related to the context
            If the question is not related to the context, politely respond that you are tuned to only answer questions that are related to the context.

                
            \n----------------\n
            CONTEXT:
          ${results.map((r:any) => r.pageContent).join("\n\n")}
          
          USER INPUT: ${userMessage}`,
          
        },
        
    ],
    
    stream: true,
    model: "llama3-70b-8192",
    })

    for await (const chunk of chatCompletion) {
        if (chunk.choices[0].delta && chunk.choices[0].finish_reason !== "stop") {
            // console.log(chunk.choices[0].delta)
          streamable.update({ 'llmResponse': chunk.choices[0].delta.content });
        } else if (chunk.choices[0].finish_reason === "stop") {
          streamable.update({ 'llmResponseEnd': true });
        }
      }
      streamable.done({ status: 'done' });
    })();
    return streamable.value

}
const initialAIState: {
    role: 'user' | 'assistant' | 'system' | 'function';
    content: string;
    id?: string;
    name?: string;
  }[] = [];
  const initialUIState: {
    id: number;
    display: React.ReactNode;
  }[] = [];
  //  Export the AI instance
  export const AI = createAI({
    actions: {
      myAction
    },
    initialUIState,
    initialAIState,
  });

## layout.tsx
import type { Metadata } from "next";
import { Inter } from "next/font/google";
import "./globals.css";
import { AI } from "@/actions/chat";



const inter = Inter({ subsets: ["latin"] });

export const metadata: Metadata = {
  title: "Pratham Portfolio: Explore Creativity and Expertise",
  description: "Discover the creative prowess of Pratham Portfolio, showcasing expertly crafted web design, development, and beyond. Dive into a world where innovation meets functionality, and every project tells a unique story. Explore our portfolio to find inspiration for your next digital venture. Let's elevate your online presence together with our tailored solutions and unmatched expertise.",
};

export default function RootLayout({
  children,
}: Readonly<{
  children: React.ReactNode;
}>) {
  return (
    <html lang="en" suppressHydrationWarning>
      <body className={inter.className}>
         <AI>
          {children}
        </AI>
      </body>
    </html>
  );
}

Description

when I am building this project it is giving me the error
Failed to compile.

./node_modules/@langchain/pinecone/dist/translator.js
Module not found: Package path ./structured_query is not exported from package /Users/prathamchauhan/Documents/Next-Projects/pratham-portfolio/node_modules/@langchain/core (see exports field in /Users/prathamchauhan/Documents/Next-Projects/pratham-portfolio/node_modules/@langchain/core/package.json)

https://nextjs.org/docs/messages/module-not-found

Import trace for requested module:
./node_modules/@langchain/pinecone/dist/index.js
./node_modules/@langchain/pinecone/index.js
./src/lib/pineconedb.ts
./src/actions/chat.ts
./src/app/layout.tsx

System Info

npm = 10.7.0
package.json
"@langchain/community": "^0.2.2",
"@langchain/pinecone": "^0.0.6",
"@pinecone-database/pinecone": "^2.2.1",

[dosubot[bot]]

Hello, @Pratham271! I'm here to assist you with any bugs, questions, or contribution-related matters. Let me know how I can help you!

To resolve the "Module not found" error related to ./structured_query not being exported from @langchain/core, you need to ensure that the structured_query module is correctly exported in the package.json file of the @langchain/core package. The package.json file should include the following export configuration for structured_query:

"exports": {
  ...
  "./structured_query": {
    "types": {
      "import": "./structured_query.d.ts",
      "require": "./structured_query.d.cts",
      "default": "./structured_query.d.ts"
    },
    "import": "./structured_query.js",
    "require": "./structured_query.cjs"
  },
  ...
}

Ensure that this configuration is present in the package.json file and that the corresponding files (structured_query.js, structured_query.cjs, structured_query.d.ts, structured_query.d.cts) exist in the appropriate directory. This should resolve the "Module not found" error ^[1][2].

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[Pratham271]

There is no such export because ./structured_query.d.ts, ./structured_query.d.cts, ./structured_query.d.ts does not exist
and this export now gives me an error
./node_modules/@langchain/pinecone/dist/translator.js
Module not found: Can't resolve '@langchain/core/structured_query'

https://nextjs.org/docs/messages/module-not-found

[Pratham271]

there is no such file as langchain-core/src/structured_query

[dosubot[bot]]

To resolve the "Module not found" error, you need to ensure that you are importing the correct modules from the @langchain/core package. The structured_query module does exist, but you need to import the specific submodules correctly.

Here is the corrected code:

// Correct import statements
export {
  type TranslatorOpts,
  BaseTranslator,
  BasicTranslator,
} from "@langchain/core/structured_query";

Make sure to use the correct module paths as shown above ^{[1][2][3][4][5]}.

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[Pratham271]

where I have to import them

[dosubot[bot]]

To resolve the "Module not found" error, you need to place the correct import statements at the top of your TypeScript files. Here is an example of how you can structure your import statements:

import {
  type TranslatorOpts,
  BaseTranslator,
  BasicTranslator,
} from "@langchain/core/structured_query";

Ensure these import statements are placed at the very top of your TypeScript files where you need to use these modules. This should resolve the "Module not found" error ^[1][2][3][4].

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[Pratham271]

not correct