chatbot_api

New_APIs/ChatBot_API/README.md

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+# ChatBot API
+
+## Installation
+
+To use this program, you need to have Node.js installed. Then, install the required `express`,`fs` and `natural` libraries by running:
+
+```sh
+npm i express fs natural
+```
+
+## Method to use the API
+
+1. Run the index.mjs file using the following command:
+```sh
+    node index.mjs
+```
+
+OR
+
+```sh
+    nodemon index.mjs
+```
+
+2. Wait for a few seconds as the model get trained.
+
+3. When the server starts running you can use the ChatBot service.
+
+4. Endpoint - /chat
+
+POST - http://localhost:3000/chat
+
+Databody =>
+
+```bash
+
+{
+  "message":"Enter a message or chat for the ChatBot to answer"
+}
+
+```
+
+5. Example:
+
+```bash
+{
+  "message":"What's going in life"
+}
+
+{
+  "response": "Things have been interesting! How about you?"
+}
+
+```
+
+6. By adding more tags, patterns and responses the ChatBot becomes more and more advance and will be able to answer more and more complex messages.
+
+Contributed by - Satwik Mohan

New_APIs/ChatBot_API/index.mjs

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+import express, { json } from 'express';
+import { readFileSync } from 'fs';
+import pkg from 'natural';
+const { WordTokenizer, BayesClassifier } = pkg;
+const app = express();
+app.use(express.json());
+const PORT = process.env.PORT || 3000;
+
+console.log("Model Training begin");
+
+// Load intents
+const intents = JSON.parse(readFileSync('intents.json'));
+
+// Tokenizer and classifier
+const tokenizer = new WordTokenizer();
+const classifier = new BayesClassifier();
+
+// Train the classifier with the dataset
+intents.intents.forEach(intent => {
+  intent.patterns.forEach(pattern => {
+    classifier.addDocument(pattern, intent.tag);
+  });
+});
+
+classifier.train();
+
+// Function to get a random response
+function getRandomResponse(responses) {
+  const randomIndex = Math.floor(Math.random() * responses.length);
+  return responses[randomIndex];
+}
+
+app.post('/chat', (req, res) => {
+  const { message } = req.body;
+  if (!message) {
+    return res.status(400).json({ error: 'Message is required' });
+  }
+
+  const tokenizedMessage = tokenizer.tokenize(message.toLowerCase());
+  const classification = classifier.classify(tokenizedMessage.join(' '));
+
+  const intent = intents.intents.find(intent => intent.tag === classification);
+
+  if (intent) {
+    const response = getRandomResponse(intent.responses);
+    res.json({ response });
+  } else {
+    res.json({ response: "I'm sorry, I don't understand that." });
+  }
+});
+
+app.listen(PORT, () => {
+  console.log("Model Trained");
+  console.log(`Server is running on port ${PORT}`);
+});