Creating a chatbot for handling complex PDF and DOCX files can be a challenging task, but with the help of RAG (Retrieve, Analyze, Generate) methodology, we can make this process more manageable. In this tutorial, we will walk through the steps of building a chatbot that can read, analyze, and generate responses for complex PDF and DOCX files.
Step 1: Setting up the HTML structure
First, we need to create the HTML structure for our chatbot. We will use a simple form element to capture user input and display responses. Here’s an example of the HTML code:
<!DOCTYPE html>
<html>
<head>
<title>RAG Chatbot for Complex PDF and DOCX</title>
</head>
<body>
<h1>RAG Chatbot for Complex PDF and DOCX</h1>
<form id="chatbox">
<input type="text" id="userInput" placeholder="Type your query here...">
<button type="button" onclick="getResponse()">Submit</button>
</form>
<div id="responseArea"></div>
</body>
</html>In this code, we have a heading for the chatbot, a form element with an input field for user queries, and a button to submit the query. The responses will be displayed in the responseArea div.
Step 2: Adding JavaScript for interaction
Next, we need to add JavaScript code to handle user input and process responses. We will use a simple function to capture the user input and display a response. Here’s the JavaScript code:
<script>
function getResponse() {
var userInput = document.getElementById("userInput").value;
var responseArea = document.getElementById("responseArea");
// Logic for generating response based on user input
// Display the response in the responseArea
responseArea.innerHTML = "<p>Here is your response:</p><p>This is a sample response text.</p>";
}
</script>In this code, we capture the user input from the input field, generate a response based on the input (which we will implement later), and display the response in the responseArea div.
Step 3: Implement RAG methodology for handling PDF and DOCX files
Now, we need to implement the RAG methodology to handle complex PDF and DOCX files. This involves retrieving the file content, analyzing the content, and generating a response based on the analysis. We can use libraries like pdf.js for PDF files and mammoth.js for DOCX files.
For example, to retrieve and analyze a PDF file, we can use the pdf.js library. Here’s a simplified version of how to retrieve and analyze a PDF file:
<script src="https://cdnjs.cloudflare.com/ajax/libs/pdf.js/2.8.335/pdf.min.js"></script>
<script>
function analyzePDF(file) {
PDFJS.getDocument(file).then(function(pdf) {
pdf.getPage(1).then(function(page) {
page.getTextContent().then(function(textContent) {
var text = "";
textContent.items.forEach(function(item) {
text += item.str + " ";
});
// Generate response based on the extracted text
var response = "<p>Here is the content of the PDF:</p><p>" + text + "</p>";
displayResponse(response);
});
});
});
}
</script>Step 4: Displaying responses
Finally, we need to modify our getResponse function to display the response generated from the analysis of the PDF or DOCX file. Here’s the updated function:
<script>
function getResponse() {
var userInput = document.getElementById("userInput").value;
var responseArea = document.getElementById("responseArea");
// Replace this with logic to handle PDF or DOCX files
var file = "sample.pdf"; // Change this to the path of the PDF or DOCX file
analyzePDF(file);
}
function displayResponse(response) {
var responseArea = document.getElementById("responseArea");
responseArea.innerHTML = response;
}
</script>In this code, we call the analyzePDF function with the path to the PDF file, which will extract the text content from the file and generate a response. We then display the response using the displayResponse function.
That’s it! With these steps, you can create a chatbot using HTML tags that can handle complex PDF and DOCX files using the RAG methodology. Feel free to customize and expand on this tutorial to suit your specific needs.
Impressive 👏👌