Building Your First AI Chatbot

In this guide, you'll learn how to create a simple AI chatbot. We'll show you three approaches: using OpenAI's GPT-4o, Anthropic's Claude, or running open source models locally with Ollama.

Choose Your Approach

Approach	Pros	Cons	Cost
OpenAI (GPT-4o)	Best-in-class quality, fast	Requires API key, usage costs	~$2.50/1M input tokens
Anthropic (Claude 3.5)	Excellent reasoning, longer context	Requires API key, usage costs	~$3/1M input tokens
Ollama (Local)	Free, private, no internet needed	Requires decent hardware	Free

What You'll Need

Node.js (version 20+) - Download here
A text editor (VS Code recommended)
For cloud options: An API key from your chosen provider
For local: A computer with 8GB+ RAM

Option A: Using OpenAI (GPT-4o)

Step 1: Set Up

mkdir my-chatbot && cd my-chatbot
npm init -y
npm install openai

Step 2: Create the Bot

Create bot.js:

import OpenAI from 'openai';
import readline from 'readline';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

const messages = [{ role: 'system', content: 'You are a helpful assistant.' }];

async function chat(userMessage) {
  messages.push({ role: 'user', content: userMessage });

  const response = await openai.chat.completions.create({
    model: 'gpt-4o', // Latest GPT-4 Omni model
    messages,
  });

  const reply = response.choices[0].message.content;
  messages.push({ role: 'assistant', content: reply });
  return reply;
}

// Interactive CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
});

console.log('GPT-4o Chatbot ready! Type "quit" to exit.\n');

function prompt() {
  rl.question('You: ', async (input) => {
    if (input.toLowerCase() === 'quit') {
      rl.close();
      return;
    }
    console.log('\nBot:', await chat(input), '\n');
    prompt();
  });
}

prompt();

Step 3: Run

export OPENAI_API_KEY=sk-your-key-here
node bot.js

Option B: Using Anthropic (Claude 3.5 Sonnet)

Step 1: Set Up

mkdir my-chatbot && cd my-chatbot
npm init -y
npm install @anthropic-ai/sdk

Step 2: Create the Bot

Create bot.js:

import Anthropic from '@anthropic-ai/sdk';
import readline from 'readline';

const anthropic = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
});

const messages = [];

async function chat(userMessage) {
  messages.push({ role: 'user', content: userMessage });

  const response = await anthropic.messages.create({
    model: 'claude-sonnet-4-20250514', // Latest Claude Sonnet
    max_tokens: 1024,
    system: 'You are a helpful assistant.',
    messages,
  });

  const reply = response.content[0].text;
  messages.push({ role: 'assistant', content: reply });
  return reply;
}

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
});

console.log('Claude 3.5 Chatbot ready! Type "quit" to exit.\n');

function prompt() {
  rl.question('You: ', async (input) => {
    if (input.toLowerCase() === 'quit') {
      rl.close();
      return;
    }
    console.log('\nBot:', await chat(input), '\n');
    prompt();
  });
}

prompt();

Step 3: Run

export ANTHROPIC_API_KEY=sk-ant-your-key-here
node bot.js

Option C: Using Ollama (Free, Local, Private)

Ollama lets you run powerful open source models like Llama 3.1 and Mistral locally.

Step 1: Install Ollama

# macOS/Linux
curl -fsSL https://ollama.com/install.sh | sh

# Or download from ollama.com for Windows

Step 2: Download a Model

# Llama 3.1 8B - Good balance of quality and speed
ollama pull llama3.1

# Or Mistral 7B - Fast and capable
ollama pull mistral

Step 3: Create the Bot

mkdir my-chatbot && cd my-chatbot
npm init -y
npm install ollama

Create bot.js:

import { Ollama } from 'ollama';
import readline from 'readline';

const ollama = new Ollama();
const messages = [];

async function chat(userMessage) {
  messages.push({ role: 'user', content: userMessage });

  const response = await ollama.chat({
    model: 'llama3.1', // or 'mistral'
    messages,
  });

  const reply = response.message.content;
  messages.push({ role: 'assistant', content: reply });
  return reply;
}

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
});

console.log('Llama 3.1 Chatbot ready! Type "quit" to exit.\n');

function prompt() {
  rl.question('You: ', async (input) => {
    if (input.toLowerCase() === 'quit') {
      rl.close();
      return;
    }
    console.log('\nBot:', await chat(input), '\n');
    prompt();
  });
}

prompt();

Step 4: Run

# Make sure Ollama is running first
ollama serve  # In another terminal

node bot.js

Comparing the Models

Model	Best For	Context Window	Notes
GPT-4o	General tasks, vision	128K tokens	Fastest GPT-4 variant
Claude 3.5 Sonnet	Coding, analysis	200K tokens	Excellent at reasoning
Llama 3.1 8B	Local/private use	128K tokens	Free, runs on consumer hardware
Mistral 7B	Fast local inference	32K tokens	Very efficient

Next Steps

Add a web interface - Use Next.js or Express
Add RAG - Give your bot custom knowledge
Try different models - Each has unique strengths
Add streaming - Show responses as they generate

See our Model Comparison Guide for detailed provider profiles.

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Building Your First AI Chatbot

Building Your First AI Chatbot

Choose Your Approach

What You'll Need

Option A: Using OpenAI (GPT-4o)

Step 1: Set Up

Step 2: Create the Bot

Step 3: Run

Option B: Using Anthropic (Claude 3.5 Sonnet)

Step 1: Set Up

Step 2: Create the Bot

Step 3: Run

Option C: Using Ollama (Free, Local, Private)

Step 1: Install Ollama

Step 2: Download a Model

Step 3: Create the Bot

Step 4: Run

Comparing the Models

Next Steps

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