Vercel Alert: (Azure) Missing OpenAI API key

After successfully implementing the openAI API in my Next.js application using the langchain library, everything worked flawlessly on localhost. However, upon deploying to Vercel (ProVersion), I encountered an error:

Error: (Azure) OpenAI API key not found at new OpenAIChat (file:///var/task/node_modules/langchain/dist/llms/openai-chat.js:184:19) at new OpenAI (file:///var/task/node_modules/langchain/dist/llms/openai.js:54:20) at /var/task/.next/server/pages/api/tasks/ai.js:63:21 RequestId: 472c0bdb-dbbc-4cd4-95a3-1808d0b6a5ac Error: Runtime exited with error: exit status 1 Runtime.ExitError

This error points back to a section of code within the langchain node_module utilized in my application:

this.openAIApiKey =
            fields?.openAIApiKey ?? getEnvironmentVariable("OPENAI_API_KEY");
        this.azureOpenAIApiKey =
            fields?.azureOpenAIApiKey ??
                getEnvironmentVariable("AZURE_OPENAI_API_KEY");
        if (!this.azureOpenAIApiKey && !this.openAIApiKey) {
            throw new Error("(Azure) OpenAI API key not found");
        }

I had placed the OPENAI_API_KEY environmental variable (matching the one in my .env file) in Vercel:

vercel_environmental_variable

In my app, I defined the OPENAI_API_KEY in the .env file and accessed it in my backend as follows:

const apiKey = process.env.OPENAI_API_KEY;

const openAIModel = new OpenAI({
  modelName: "gpt-3.5-turbo",
  temperature: 0,
  maxTokens: 2000,
  openAIApiKey: apiKey,
});

Interestingly, I was able to both send and receive API requests locally without processing the OPENAI_API_KEY in the backend since the langchain module directly fetched it from my .env file:

const openAIModel = new OpenAI({
  modelName: "gpt-3.5-turbo",
  temperature: 0,
  maxTokens: 2000,
});

Further experimentation included switching the model to OpenAIChat, which worked just as well as the OpenAI model did locally. But again, the same error persisted when deployed to Vercel:

const openAIModel = new OpenAIChat({
  modelName: "gpt-3.5-turbo",
  temperature: 0,
  maxTokens: 2000,
});

Despite these configurations, the error continued to surface consistently. Any insights or suggestions would be greatly appreciated!

Thank you in advance! Nasti

Answer №1

While working with Langchain pinecone in a Node.js environment, I encountered a similar error specifically when using the OpenAIEmbeddings function. To resolve this issue, I implemented the following piece of code:

    import { OpenAIEmbeddings } from "@langchain/openai";

    const embeddingsArrays = await new OpenAIEmbeddings({
        openAIApiKey : process.env.OPEN_API_KEY
    }).embedDocuments(

Answer №2

After removing and re-adding the environmental variable in Vercel, redeploying the project resolved the issue successfully!

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