University Chatbot is a web application that utilizes Google's Dialogflow API for natural language processing to handle user queries and generate responses. This project consists of a backend server built with Express.js and a frontend user interface built with React and Material-UI. Visit the Page

• Features
• Prerequisites
• Installation
• Getting Started
• API Endpoint

• Chat with a virtual assistant powered by Dialogflow.
• Send and receive messages in real-time.
• Like or dislike responses from the chatbot.

Before running the application, make sure you have the following installed on your system:

• Node.js
• Google Cloud account with Dialogflow API credentials

1. Clone the repository:

   In Git-Bash:

    $ git clone https://github.com/your-username/university-chatbot.git
    $ cd university-chatbot
   

2. Install frontend dependencies:

   In Git-Bash:

    $ cd ../Your respective Folder Name
    $ npm install
   

3. Install backend dependencies:

   In Git-Bash:

    $ cd ../Your respective Folder Name
    $ npm init
   

1)Set up Dialogflow:

• Create a Dialogflow agent in your Google Cloud account.
• Select or create a Cloud Platform project.
• Enable the Dialogflow API API.
• Set up authentication with a service account so you can access the API from your local workstation.
• Download the service account key JSON file and save it as key.json in the backend folder.

2)Create the backend server:

• Installing the client library:

  $ npm install @google-cloud/dialogflow
  

• Using the client library:

  const express = require("express");
  const app = express();
  const dialogflow = require("@google-cloud/dialogflow");
  const uuid = require("uuid");
  const Path = require("path");
  const cors = require("cors");
  
  app.use(express.json());
  app.use(cors());
  
  app.post("/api/chatbot", async (req, res) => {
    const { inputText } = req.body;
    console.log(inputText);
  
    try {
      const responseText = await runSample(
        (projectId = "your-project-id"),
        inputText
      );
      res.send(responseText);
    } catch (error) {
      console.error("Error processing user input:", error);
      res.status(500).send("Error processing user input");
    }
  });
  
  async function runSample(projectId, inputText) {
    const sessionId = uuid.v4();
  
    const sessionClient = new dialogflow.SessionsClient({
      keyFilename: Path.join(__dirname + "/key.json"),
    });
    const sessionPath = sessionClient.projectAgentSessionPath(
      projectId,
      sessionId
    );
  
    const request = {
      session: sessionPath,
      queryInput: {
        text: {
          // The query to send to the dialogflow agent
          text: inputText,
  
          languageCode: "en-US",
        },
      },
    };
  
    const responses = await sessionClient.detectIntent(request);
    // console.log("Detected intent");
    const result = responses[0].queryResult;
    // console.log(`  Query: ${result.queryText}`);
    // console.log(`  Response: ${result.fulfillmentText}`);
    if (result.intent) {
      // console.log(`  Intent: ${result.intent.displayName}`);
    } else {
      // console.log("  No intent matched.");
    }
    // console.log(result.fulfillmentText);
    return result.fulfillmentText;
  }
  
  const PORT = process.env.PORT || 3001;
  
  app.listen(PORT, () => {
    console.log(`Server is running in port ${PORT}`);
  });
  
  

• In Git-Bash:

   $ npm start
  

  • You can change the port by setting the PORT environment variable.

3)Run the frontend app:

• In Git-Bash:

  $ cd ../Your respective Folder Name
  $ npm start
  

  • The React app will run on port 3000 by default.

4)Access the application:

• Open your web browser
• And navigate to http://localhost:3000 to access the University Chatbot application.

POST http://localhost:3000/api/chatbot:

Send a POST request to the root endpoint with the following JSON payload:

     {
       "inputText": "User's query text goes here"
     }

The server will process the user's query using Dialogflow and return the chatbot's response as JSON.