Creating Smart Chatbots Using NLP: A Complete Beginner’s Guide to Intelligent Conversational Agents

📗 Chapter 6: Deploying and Connecting Chatbots Across Platforms

🧠 Introduction

You’ve built an intelligent chatbot. It understands language, maintains context, and personalizes responses. But until it's deployed where users are — your website, WhatsApp, Slack, Facebook, or Alexa — it’s just potential.

Deployment is the final step that turns your chatbot into a real product.

This chapter covers:

• Web and mobile chatbot deployment
• Integration with messaging platforms like WhatsApp, Telegram, and Slack
• Hosting options: cloud vs on-prem
• Using APIs and webhooks for real-time updates
• Deployment with Rasa, Flask, and cloud providers
• Securing and monitoring your bot

Let’s ship it.

📘 Section 1: Choosing the Right Deployment Platform

📘 Section 2: Web Deployment (Using Flask + JavaScript)

💻 Backend: Flask (Python)

python

from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route("/bot", methods=["POST"])

def bot():

    user_message = request.json['message']

    reply = f"Echo: {user_message}"

    return jsonify({"response": reply})

if __name__ == "__main__":

    app.run(debug=True)

🌐 Frontend: HTML + JavaScript Widget

html

<input id="userInput" placeholder="Type a message..." />

<button onclick="sendMessage()">Send</button>

<div id="chatBox"></div>

<script>

async function sendMessage() {

  const msg = document.getElementById("userInput").value;

  const res = await fetch("/bot", {

    method: "POST",

    headers: { "Content-Type": "application/json" },

    body: JSON.stringify({ message: msg }),

  });

  const data = await res.json();

  document.getElementById("chatBox").innerHTML += `<p>You: ${msg}</p><p>Bot: ${data.response}</p>`;

}

</script>

📘 Section 3: WhatsApp Integration (Using Twilio)

✅ Requirements:

• Twilio Account
• Verified WhatsApp number
• Flask/Django webhook

💬 Sample Webhook

python

from flask import Flask, request

from twilio.twiml.messaging_response import MessagingResponse

app = Flask(__name__)

@app.route("/whatsapp", methods=["POST"])

def whatsapp_reply():

    incoming = request.form.get('Body')

    resp = MessagingResponse()

    reply = f"You said: {incoming}"

    resp.message(reply)

    return str(resp)

Configure Twilio to forward messages to /whatsapp webhook URL.

📘 Section 4: Telegram Bot Integration

📋 Steps:

1. Talk to @BotFather on Telegram
2. Get bot token
3. Set webhook using:

bash

https://api.telegram.org/bot<YOUR_TOKEN>/setWebhook?url=https://yourdomain.com/telegram

🧠 Flask Example

python

import requests

from flask import Flask, request

app = Flask(__name__)

TOKEN = "YOUR_TELEGRAM_BOT_TOKEN"

@app.route("/telegram", methods=["POST"])

def telegram():

    data = request.get_json()

    chat_id = data["message"]["chat"]["id"]

    msg = data["message"]["text"]

    send_url = f"https://api.telegram.org/bot{TOKEN}/sendMessage"

    requests.post(send_url, json={"chat_id": chat_id, "text": f"You said: {msg}"})

    return "OK"

📘 Section 5: Slack Bot Deployment

🧰 Steps:

• Create a Slack App in Slack API Console
• Enable Event Subscriptions
• Set a public URL for event handling
• Respond using Slack’s API

python

@app.route("/slack", methods=["POST"])

def slack_events():

    data = request.json

    if "challenge" in data:

        return jsonify({"challenge": data["challenge"]})

    user_message = data["event"]["text"]

    # Respond with Slack webhook or bot token here

    return "OK"

📘 Section 6: Rasa Chatbot Deployment

🔧 Hosting:

• Localhost (dev)
• Cloud: AWS EC2, Google Cloud, Heroku, DigitalOcean
• Docker-compose for scalable deployment

💬 Channels Supported:

• Facebook
• Slack
• Telegram
• Twilio (SMS & WhatsApp)
• Socket.io (for website widget)

📁 credentials.yml (Example)

yaml

telegram:

  access_token: "<TOKEN>"

  verify: "<BOT_USERNAME>"

  webhook_url: "<YOUR_HTTPS_ENDPOINT>/webhooks/telegram/webhook"

📘 Section 7: Cloud Hosting Options

📘 Section 8: Using Webhooks to Connect Chatbot and Backend

Webhooks allow your bot to:

• Fetch real-time data (e.g., order status, weather)
• Integrate with CRMs, APIs, or other services
• Store data in a database

Example: Get weather via API

python

import requests

def get_weather(city):

    key = "API_KEY"

    url = f"http://api.weatherapi.com/v1/current.json?key={key}&q={city}"

    res = requests.get(url).json()

    return f"{city} weather: {res['current']['temp_c']}°C"

📘 Section 9: Securing Your Chatbot

📘 Section 10: Monitoring and Analytics

Tools for analytics:

• Google Analytics (for web bots)
• Twilio Insights (for WhatsApp)
• Facebook Insights (for Messenger bots)
• Custom logging with Elastic Stack or Firebase

Track:

• Number of users
• Drop-off points
• Most asked intents
• Fallback rate
• Average session duration

✅ Chapter Summary Table