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In this guide, we will build a simple Node.js script that uses Nuabase to classify customer feedback.

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Prerequisites

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Step 1: Install the SDK

Install the nuabase package and zod for schema definition. 
npm install nuabase zod

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Step 2: Get your API Key

  1. Log in to the Nuabase Console.
  2. Navigate to API Keys.
  3. Create a new key and copy it.

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Step 3: Write your first function

Create a file named index.ts (or index.js): 
import { Nua } from 'nuabase';
import { z } from 'zod';

// Initialize with your API Key
const nua = new Nua({ apiKey: 'YOUR_NUABASE_API_KEY' });

// Define the output schema
const SentimentSchema = z.object({
  sentiment: z.enum(['Positive', 'Neutral', 'Negative']),
  confidence: z.number().min(0).max(1),
});

// Create the LLM function
const analyzeSentiment = nua.createFn({
  prompt: "Analyze the sentiment of the following text.",
  output: {
    name: "sentimentAnalysis",
    schema: SentimentSchema,
  },
});

async function main() {
  const text = "The product is great, but the shipping was delayed.";
  
  console.log("Analyzing...");
  const result = await analyzeSentiment(text);

  if (result.isSuccess) {
    console.log("Result:", result.data);
  } else {
    console.error("Error:", result.error);
  }
}

main();

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Step 4: Run it

Run the script using ts-node or node. 
npx ts-node index.ts
You should see an output similar to: 
{
  "sentiment": "Positive",
  "confidence": 0.8
}

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What just happened?

  1. You defined a Schema using Zod.
  2. You created a Function with a natural language prompt.
  3. Nuabase handled the prompt execution and guaranteed the output matched your schema.

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Next Steps

Now that you’ve seen the basics, learn how to integrate this into your actual application.

Frontend Integration

Securely call LLMs from your React/Vue/Web app.

Server Integration

Use Nuabase in your backend services.