Building an E-Commerce Support Chatbot: Part 1 - Introduction and Setup

In this first article of our series, we'll lay the groundwork for building an intelligent e-commerce support chatbot using JavaScript technologies. Our chatbot will help customers get information about their orders without waiting for human support.

Technologies We'll Use

• LangChain.js – A framework for developing applications powered by language models
• Pinecone – A vector database for efficient similarity search
• React – For building our frontend user interface
• Node.js – For our backend server
• Database – We'll use MongoDB for storing our e-commerce data

Prerequisites

To follow along with this tutorial, you should have:

• Basic knowledge of JavaScript and Node.js
• Familiarity with React
• Node.js installed on your machine
• A code editor (VS Code recommended)
• npm or yarn for package management

---

Project Setup

Let's create our project structure:

mkdir ecommerce-chatbot
cd ecommerce-chatbot
mkdir backend frontend

Setting Up the Backend

First, let's initialize our backend:

cd backend
npm init -y

Now, let's install the required dependencies:

npm install @langchain/openai @langchain/pinecone @langchain/community @langchain/core express cors dotenv mongodb

---

Creating Our Basic Server

Let's create a simple Express server to get started:

// backend/server.js
const express = require('express');
const cors = require('cors');
require('dotenv').config();

const app = express();
const PORT = process.env.PORT || 5000;

// Middleware
app.use(cors());
app.use(express.json());

// Basic route
app.get('/api/health', (req, res) => {
  res.json({ status: 'ok', message: 'E-commerce Chatbot API is running' });
});

// Start server
app.listen(PORT, () => {
  console.log(`Server running on port ${PORT}`);
});

---

Setting Up Environment Variables

Create a .env file in your backend directory:

PORT=5000
OPENAI_API_KEY=your_openai_api_key
PINECONE_API_KEY=your_pinecone_api_key
PINECONE_ENVIRONMENT=your_pinecone_environment
MONGODB_URI=your_mongodb_connection_string

---

Setting Up LangChain

Let's create a basic LangChain configuration:

// backend/langchain/config.js
const { OpenAI } = require('@langchain/openai');
const { PineconeStore } = require('@langchain/pinecone');
const { PineconeClient } = require('@pinecone-database/pinecone');

// Initialize LLM
const initLLM = () => {
  return new OpenAI({
    openAIApiKey: process.env.OPENAI_API_KEY,
    temperature: 0.2,
    modelName: 'gpt-3.5-turbo',
  });
};

// Initialize Pinecone
const initPinecone = async () => {
  const client = new PineconeClient();
  await client.init({
    apiKey: process.env.PINECONE_API_KEY,
    environment: process.env.PINECONE_ENVIRONMENT,
  });
  return client;
};

module.exports = {
  initLLM,
  initPinecone,
};

---

Setting Up the Database Connection

// backend/database/connection.js
const { MongoClient } = require('mongodb');

let db = null;

async function connectToDatabase() {
  if (db) return db;

  try {
    const client = new MongoClient(process.env.MONGODB_URI);
    await client.connect();
    console.log('Connected to MongoDB');
    db = client.db('ecommerce');
    return db;
  } catch (error) {
    console.error('Database connection error:', error);
    process.exit(1);
  }
}

module.exports = { connectToDatabase };

---

Setting Up the Frontend

Now, let's initialize our React frontend:

cd ../frontend
npx create-react-app .

Install additional packages for the frontend:

npm install axios styled-components react-icons

---

Project Architecture Overview

Frontend (React)

• Chat interface for user interaction
• API calls to backend

Backend (Node.js/Express)

• API endpoints for chat functionality
• Integration with LangChain.js
• Connection to MongoDB for order data
• Integration with Pinecone for vector search

Next Steps

In Part 2, we'll:

• Set up MongoDB with sample order data
• Create the data schema
• Implement database operations for retrieving order information

Running the Application

Start the backend:

cd backend
node server.js

Start the frontend:

cd frontend
npm start

🚀 Stay tuned for Part 2!