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xenova / transformers.js

State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
https://huggingface.co/docs/transformers.js
Apache License 2.0
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Error while using the library in nextjs (app based route) #830

Open rr-jino-jose opened 1 week ago

rr-jino-jose commented 1 week ago

Question

Hello

I was going through the issues section to find out an solution for the issue i am facing.. I did tried some of the solutions provided by xenova but it seems like I am getting some wasm fallback error which I have no idea whats happening.. I doubt its on webpack but I wanted a clarity.

The error I see is like this while running npm run dev

 ✓ Compiled /api/openai in 1500ms (3656 modules)
TypeError: Cannot read properties of undefined (reading 'create')
    at constructSession (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:436:39)
    at async Promise.all (index 1)
    at async BertModel.from_pretrained (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:1007:20)
    at async AutoModel.from_pretrained (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:5026:20)
    at async Promise.all (index 1)
    at async loadItems (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/pipelines.js:2838:5)
    at async pipeline (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/pipelines.js:2790:21)
    at async HuggingFaceEmbedding.getExtractor (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/HuggingFaceEmbedding.js:37:30)
    at async HuggingFaceEmbedding.getTextEmbedding (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/HuggingFaceEmbedding.js:44:27)
    at async HuggingFaceEmbedding.getTextEmbeddings (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:30:31)
    at async batchEmbeddings (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:61:32)
    at async HuggingFaceEmbedding.getTextEmbeddingsBatch (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:40:16)
    at async HuggingFaceEmbedding.transform (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:44:28)
    at async VectorStoreIndex.getNodeEmbeddingResults (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:474:17)
    at async VectorStoreIndex.insertNodes (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:571:17)
    at async VectorStoreIndex.buildIndexFromNodes (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:486:9)
    at async VectorStoreIndex.init (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:436:13)
    at async VectorStoreIndex.fromDocuments (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:514:16)
    at async getOpenAIModelRequest (webpack-internal:///(rsc)/./src/actions/openai.ts:62:23)
    at async POST (webpack-internal:///(rsc)/./src/app/api/openai/route.ts:11:21)
    at async /Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:63809
    at async eU.execute (/Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:53964)
    at async eU.handle (/Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:65062)
    at async doRender (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1333:42)
    at async cacheEntry.responseCache.get.routeKind (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1555:28)
    at async DevServer.renderToResponseWithComponentsImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1463:28)
    at async DevServer.renderPageComponent (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1856:24)
    at async DevServer.renderToResponseImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1894:32)
    at async DevServer.pipeImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:911:25)
    at async NextNodeServer.handleCatchallRenderRequest (/opt/homebrew/lib/node_modules/next/dist/server/next-server.js:271:17)
    at async DevServer.handleRequestImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:807:17)
    at async /opt/homebrew/lib/node_modules/next/dist/server/dev/next-dev-server.js:331:20
    at async Span.traceAsyncFn (/opt/homebrew/lib/node_modules/next/dist/trace/trace.js:151:20)
    at async DevServer.handleRequest (/opt/homebrew/lib/node_modules/next/dist/server/dev/next-dev-server.js:328:24)
    at async invokeRender (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:163:21)
    at async handleRequest (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:342:24)
    at async requestHandlerImpl (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:366:13)
    at async Server.requestListener (/opt/homebrew/lib/node_modules/next/dist/server/lib/start-server.js:140:13)
Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback.
TypeError: Cannot read properties of undefined (reading 'create')
    at constructSession (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:446:39)
    at async Promise.all (index 1)
    at async BertModel.from_pretrained (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:1007:20)
    at async AutoModel.from_pretrained (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/models.js:5026:20)
    at async Promise.all (index 1)
    at async loadItems (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/pipelines.js:2838:5)
    at async pipeline (webpack-internal:///(rsc)/./node_modules/@xenova/transformers/src/pipelines.js:2790:21)
    at async HuggingFaceEmbedding.getExtractor (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/HuggingFaceEmbedding.js:37:30)
    at async HuggingFaceEmbedding.getTextEmbedding (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/HuggingFaceEmbedding.js:44:27)
    at async HuggingFaceEmbedding.getTextEmbeddings (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:30:31)
    at async batchEmbeddings (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:61:32)
    at async HuggingFaceEmbedding.getTextEmbeddingsBatch (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:40:16)
    at async HuggingFaceEmbedding.transform (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/embeddings/types.js:44:28)
    at async VectorStoreIndex.getNodeEmbeddingResults (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:474:17)
    at async VectorStoreIndex.insertNodes (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:571:17)
    at async VectorStoreIndex.buildIndexFromNodes (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:486:9)
    at async VectorStoreIndex.init (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:436:13)
    at async VectorStoreIndex.fromDocuments (webpack-internal:///(rsc)/./node_modules/llamaindex/dist/indices/vectorStore/index.js:514:16)
    at async getOpenAIModelRequest (webpack-internal:///(rsc)/./src/actions/openai.ts:62:23)
    at async POST (webpack-internal:///(rsc)/./src/app/api/openai/route.ts:11:21)
    at async /Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:63809
    at async eU.execute (/Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:53964)
    at async eU.handle (/Users/jino.jose/rakuten/git/rr-services-version-dashboard/node_modules/next/dist/compiled/next-server/app-route.runtime.dev.js:6:65062)
    at async doRender (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1333:42)
    at async cacheEntry.responseCache.get.routeKind (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1555:28)
    at async DevServer.renderToResponseWithComponentsImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1463:28)
    at async DevServer.renderPageComponent (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1856:24)
    at async DevServer.renderToResponseImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:1894:32)
    at async DevServer.pipeImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:911:25)
    at async NextNodeServer.handleCatchallRenderRequest (/opt/homebrew/lib/node_modules/next/dist/server/next-server.js:271:17)
    at async DevServer.handleRequestImpl (/opt/homebrew/lib/node_modules/next/dist/server/base-server.js:807:17)
    at async /opt/homebrew/lib/node_modules/next/dist/server/dev/next-dev-server.js:331:20
    at async Span.traceAsyncFn (/opt/homebrew/lib/node_modules/next/dist/trace/trace.js:151:20)
    at async DevServer.handleRequest (/opt/homebrew/lib/node_modules/next/dist/server/dev/next-dev-server.js:328:24)
    at async invokeRender (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:163:21)
    at async handleRequest (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:342:24)
    at async requestHandlerImpl (/opt/homebrew/lib/node_modules/next/dist/server/lib/router-server.js:366:13)
    at async Server.requestListener (/opt/homebrew/lib/node_modules/next/dist/server/lib/start-server.js:140:13)

And my code snippets looks like below:

src/action/openai.ts

"use server";
import { 
    OpenAI,  
    OpenAIAgent, 
    Settings, 
    VectorStoreIndex,
    QueryEngineTool
  } from "llamaindex";
import { HuggingFaceEmbedding } from "llamaindex/embeddings/HuggingFaceEmbedding";
import { SimpleDirectoryReader } from "llamaindex/readers/SimpleDirectoryReader";
import * as path from "path";
import * as fs from 'fs';

export async function getOpenAIModelRequest(query: string, knowledgeBase: any) {

    const knowledgeBaseJson = JSON.stringify(knowledgeBase, null, 2)

    try {
        // set LLM and the embedding model
    Settings.llm = new OpenAI({
      apiKey: process.env.NEXT_PUBLIC_OPENAI_KEY,
      model: "gpt-4o",
    })
    Settings.embedModel = new HuggingFaceEmbedding({
        modelType: "BAAI/bge-small-en-v1.5",
        quantized: false,

    })
    /*
    Set up logging so we can see the work in progress.
    Available events:
    llm-start
    llm-end
    agent-start
    agent-end
    llm-tool-call
    llm-tool-result
    //*/
    Settings.callbackManager.on("llm-tool-call", (event) => {
        console.log(event.detail.payload)
    })
    Settings.callbackManager.on("llm-tool-result", (event) => {
        console.log(event.detail.payload)
    })

    const currentDir = __dirname;
    const filePath = path.join(currentDir, 'knowledgeBase.json');

    try {
        fs.writeFileSync(filePath, knowledgeBaseJson);
        console.log(`File written successfully to ${filePath}`);
    } catch (err) {
        console.error('Error writing file:', err);
    }

    // load our data and create a query engine
    const reader = new SimpleDirectoryReader()
    const documents = await reader.loadData(currentDir)
    const index = await VectorStoreIndex.fromDocuments(documents)
    const retriever = await index.asRetriever()
    retriever.similarityTopK = 10
    const queryEngine = await index.asQueryEngine({
        retriever
    })
    console.log(4)

    // define the query engine as a tool
    const tools = [
        new QueryEngineTool({
            queryEngine: queryEngine,
            metadata: {
            name: "deployment_details_per_env",
            description: `This tool can answer detailed questions about deployments happened in various environments.`,
            },
        }),
    ]
    console.log(5)

    // create the agent
    const agent = new OpenAIAgent({tools})
    console.log(6)
    let response = await agent.chat({
        message: query,
    })
    console.log(6)
    return {
      message: response.response.message.content
    };
  }
    catch (err) {
        console.error(err)
        return {
            errors: "Error Calling OpenAI Model"
        }
    }

}

src/app/api/openai/route.ts

import {getOpenAIModelRequest } from "@/actions/openai";
import { NextRequest, NextResponse } from "next/server";

export async function POST(request: NextRequest) {
  const body = await request.json();
  const content = await getOpenAIModelRequest(body.query, body.query1);

  //if (content instanceof Error) {
  //  return NextResponse.json({ error: body.errors}, { status: 500 });
  //}
  return NextResponse.json(content, { status: 200 });
}

src/lib/model.ts

"use client";
export async function getAnswer(query: string, knowledgeBase: Record<string, any>[] | undefined) {
    const resp = await fetch(`/api/openai`, {method: "POST", body: JSON.stringify({query: query, query1: knowledgeBase})});
    const openAiResponse = await resp.json();
    return openAiResponse.message;

  }

next.config.mjs

import module from './package.json' with { type: "json" };

/** @type {import('next').NextConfig} */
const nextConfig = {
    experimental: {
        missingSuspenseWithCSRBailout: false,
        //serverComponentsExternalPackages: ['sharp', 'onnxruntime-node'],
    },
    env: {
        version: module.version
    },

    // Override the default webpack configuration
    webpack: (config) => {
      // Ignore node-specific modules when bundling for the browser
      // See https://webpack.js.org/configuration/resolve/#resolvealias
      config.resolve.alias = {
          ...config.resolve.alias,
          "sharp$": false,
          "onnxruntime-node$": false,
      }
      return config;
  },

};

export default nextConfig;

Any help is appreciated. Thanks.

xenova commented 4 days ago

Hi there 👋 Please take a look at one of the following next tutorials, which will help out: