Skip to content

Use event notification to summarize PDF files on upload

Last reviewed: 2 months ago

In this tutorial, you will learn how to use event notifications to process a PDF file when it is uploaded to an R2 bucket. You will use Workers AI to summarize the PDF and store the summary as a text file in the same bucket.

Prerequisites

To continue, you will need:

Node.js version manager

Use a Node version manager like Volta or nvm to avoid permission issues and change Node.js versions. Wrangler, discussed later in this guide, requires a Node version of 16.17.0 or later.

1. Create a new project

You will create a new Worker project that will use Static Assets to serve the front-end of your application. A user can upload a PDF file using this front-end, which will then be processed by your Worker.

Create a new Worker project by running the following commands:

Terminal window
npm create cloudflare@latest -- pdf-summarizer

For setup, select the following options:

  • For What would you like to start with?, choose Hello World example.
  • For Which template would you like to use?, choose Hello World Worker.
  • For Which language do you want to use?, choose TypeScript.
  • For Do you want to use git for version control?, choose Yes.
  • For Do you want to deploy your application?, choose No (we will be making some changes before deploying).

Navigate to the pdf-summarizer directory:

cd pdf-summarizer

2. Create the front-end

Using Static Assets, you can serve the front-end of your application from your Worker. To use Static Assets, you need to add the required bindings to your wrangler.toml file.

[assets]
directory = "public"

Next, create a public directory and add an index.html file. The index.html file should contain the following HTML code:

Select to view the HTML code

<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>PDF Summarizer</title>
<style>
body {
font-family: Arial, sans-serif;
display: flex;
flex-direction: column;
min-height: 100vh;
margin: 0;
background-color: #fefefe;
}
.content {
flex: 1;
display: flex;
justify-content: center;
align-items: center;
}
.upload-container {
background-color: #f0f0f0;
padding: 20px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
}
.upload-button {
background-color: #4caf50;
color: white;
padding: 10px 15px;
border: none;
border-radius: 4px;
cursor: pointer;
font-size: 16px;
}
.upload-button:hover {
background-color: #45a049;
}
footer {
background-color: #f0f0f0;
color: white;
text-align: center;
padding: 10px;
width: 100%;
}
footer a {
color: #333;
text-decoration: none;
margin: 0 10px;
}
footer a:hover {
text-decoration: underline;
}
</style>
</head>
<body>
<div class="content">
<div class="upload-container">
<h2>Upload PDF File</h2>
<form id="uploadForm" onsubmit="return handleSubmit(event)">
<input
type="file"
id="pdfFile"
name="pdfFile"
accept=".pdf"
required
/>
<button type="submit" id="uploadButton" class="upload-button">
Upload
</button>
</form>
</div>
</div>
<footer>
<a
href="https://developers.cloudflare.com/r2/buckets/event-notifications/"
target="_blank"
>R2 Event Notification</a
>
<a
href="https://developers.cloudflare.com/queues/get-started/#3-create-a-queue"
target="_blank"
>Cloudflare Queues</a
>
<a href="https://developers.cloudflare.com/workers-ai/" target="_blank"
>Workers AI</a
>
<a
href="https://github.com/harshil1712/pdf-summarizer-r2-event-notification"
target="_blank"
>GitHub Repo</a
>
</footer>
<script>
handleSubmit = async (event) => {
event.preventDefault();
// Disable the upload button and show a loading message
const uploadButton = document.getElementById("uploadButton");
uploadButton.disabled = true;
uploadButton.textContent = "Uploading...";
// get form data
const formData = new FormData(event.target);
const file = formData.get("pdfFile");
if (file) {
// call /api/upload endpoint and send the file
await fetch("/api/upload", {
method: "POST",
body: formData,
});
event.target.reset();
} else {
console.log("No file selected");
}
uploadButton.disabled = false;
uploadButton.textContent = "Upload";
};
</script>
</body>
</html>

To view the front-end of your application, run the following command and navigate to the URL displayed in the terminal:

Terminal window
npm run dev
⛅️ wrangler 3.80.2
-------------------
⎔ Starting local server...
[wrangler:inf] Ready on http://localhost:8787
╭───────────────────────────╮
│ [b] open a browser │
│ [d] open devtools │
│ [l] turn off local mode │
│ [c] clear console │
│ [x] to exit │
╰───────────────────────────╯

When you open the URL in your browser, you will see that there is a file upload form. If you try uploading a file, you will notice that the file is not uploaded to the server. This is because the front-end is not connected to the back-end. In the next step, you will update your Worker that will handle the file upload.

3. Handle file upload

To handle the file upload, you will first need to add the R2 binding. In the wrangler.toml file, add the following code:

[[r2_buckets]]
binding = "MY_BUCKET"
bucket_name = "<R2_BUCKET_NAME>"

Replace <R2_BUCKET_NAME> with the name of your R2 bucket.

Next, update the src/index.ts file. The src/index.ts file should contain the following code:

src/index.ts
export default {
async fetch(request, env, ctx): Promise<Response> {
// Get the pathname from the request
const pathname = new URL(request.url).pathname;
if (pathname === "/api/upload" && request.method === "POST") {
// Get the file from the request
const formData = await request.formData();
const file = formData.get("pdfFile") as File;
// Upload the file to Cloudflare R2
const upload = await env.MY_BUCKET.put(file.name, file);
return new Response("File uploaded successfully", { status: 200 });
}
return new Response("incorrect route", { status: 404 });
},
} satisfies ExportedHandler<Env>;

The above code does the following:

  • Check if the request is a POST request to the /api/upload endpoint. If it is, it gets the file from the request and uploads it to Cloudflare R2 using the Workers API.
  • If the request is not a POST request to the /api/upload endpoint, it returns a 404 response.

Since the Worker code is written in TypeScript, you should run the following command to add the necessary type definitions. While this is not required, it will help you avoid errors.

Terminal window
npm run cf-typegen

You can restart the developer server to test the changes:

Terminal window
npm run dev

4. Create a queue

Event notifications capture changes to data in your R2 bucket. You will need to create a new queue pdf-summarize to receive notifications:

Terminal window
npx wrangler queues create pdf-summarizer

Add the binding to the wrangler.toml file:

[[queues.consumers]]
queue = "pdf-summarizer"

5. Handle event notifications

Now that you have a queue to receive event notifications, you need to update the Worker to handle the event notifications. You will need to add a Queue handler that will extract the textual content from the PDF, use Workers AI to summarize the content, and then save it in the R2 bucket.

Update the src/index.ts file to add the Queue handler:

src/index.ts
export default {
async fetch(request, env, ctx): Promise<Response> {
// No changes in the fetch handler
},
async queue(batch, env) {
for (let message of batch.messages) {
console.log(`Processing the file: ${message.body.object.key}`);
}
},
} satisfies ExportedHandler<Env>;

The above code does the following:

  • The queue handler is called when a new message is added to the queue. It loops through the messages in the batch and logs the name of the file.

For now the queue handler is not doing anything. In the next steps, you will update the queue handler to extract the textual content from the PDF, use Workers AI to summarize the content, and then add it to the bucket.

6. Extract the textual content from the PDF

To extract the textual content from the PDF, the Worker will use the unpdf library. The unpdf library provides utilities to work with PDF files.

Install the unpdf library by running the following command:

Terminal window
npm install unpdf

Update the src/index.ts file to import the required modules from the unpdf library:

src/index.ts
import { extractText, getDocumentProxy } from "unpdf";

Next, update the queue handler to extract the textual content from the PDF:

src/index.ts
async queue(batch, env) {
for(let message of batch.messages) {
console.log(`Processing file: ${message.body.object.key}`);
// Get the file from the R2 bucket
const file = await env.MY_BUCKET.get(message.body.object.key);
if (!file) {
console.error(`File not found: ${message.body.object.key}`);
continue;
}
// Extract the textual content from the PDF
const buffer = await file.arrayBuffer();
const document = await getDocumentProxy(new Uint8Array(buffer));
const {text} = await extractText(document, {mergePages: true});
console.log(`Extracted text: ${text.substring(0, 100)}...`);
}
}

The above code does the following:

  • The queue handler gets the file from the R2 bucket.
  • The queue handler extracts the textual content from the PDF using the unpdf library.
  • The queue handler logs the textual content.

7. Use Workers AI to summarize the content

To use Workers AI, you will need to add the Workers AI binding to the wrangler.toml file. The wrangler.toml file should contain the following code:

[ai]
binding = "AI"

Execute the following command to add the AI type definition:

Terminal window
npm run cf-typegen

Update the src/index.ts file to use Workers AI to summarize the content:

src/index.ts
async queue(batch, env) {
for(let message of batch.messages) {
// Extract the textual content from the PDF
const {text} = await extractText(document, {mergePages: true});
console.log(`Extracted text: ${text.substring(0, 100)}...`);
// Use Workers AI to summarize the content
const result: AiSummarizationOutput = await env.AI.run(
"@cf/facebook/bart-large-cnn",
{
input_text: text,
}
);
const summary = result.summary;
console.log(`Summary: ${summary.substring(0, 100)}...`);
}
}

The queue handler now uses Workers AI to summarize the content.

8. Add the summary to the R2 bucket

Now that you have the summary, you need to add it to the R2 bucket. Update the src/index.ts file to add the summary to the R2 bucket:

src/index.ts
async queue(batch, env) {
for(let message of batch.messages) {
// Extract the textual content from the PDF
// ...
// Use Workers AI to summarize the content
// ...
// Add the summary to the R2 bucket
const upload = await env.MY_BUCKET.put(`${message.body.object.key}-summary.txt`, summary, {
httpMetadata: {
contentType: 'text/plain',
},
});
console.log(`Summary added to the R2 bucket: ${upload.key}`);
}
}

The queue handler now adds the summary to the R2 bucket as a text file.

9. Enable event notifications

Your queue handler is ready to handle incoming event notification messages. You need to enable event notifications with the wrangler r2 bucket notification create command for your bucket. The following command creates an event notification for the object-create event type for the pdf suffix:

Terminal window
npx wrangler r2 bucket notification create <R2_BUCKET_NAME> --event-type object-create --queue pdf-summarizer --suffix "pdf"

Replace <R2_BUCKET_NAME> with the name of your R2 bucket.

An event notification is created for the pdf suffix. When a new file with the pdf suffix is uploaded to the R2 bucket, the pdf-summarizer queue is triggered.

10. Deploy your Worker

To deploy your Worker, run the wrangler deploy command:

Terminal window
npx wrangler deploy

In the output of the wrangler deploy command, copy the URL. This is the URL of your deployed application.

11. Test

To test the application, navigate to the URL of your deployed application and upload a PDF file. Alternatively, you can use the Cloudflare dashboard to upload a PDF file.

To view the logs, you can use the wrangler tail command.

Terminal window
npx wrangler tail

You will see the logs in your terminal. You can also navigate to the Cloudflare dashboard and view the logs in the Workers Logs section.

If you check your R2 bucket, you will see the summary file.

Conclusion

In this tutorial, you learned how to use R2 event notifications to process an object on upload. You created an application to upload a PDF file, and created a consumer Worker that creates a summary of the PDF file. You also learned how to use Workers AI to summarize the content of the PDF file, and upload the summary to the R2 bucket.

You can use the same approach to process other types of files, such as images, videos, and audio files. You can also use the same approach to process other types of events, such as object deletion, and object update.

If you want to view the code for this tutorial, you can find it on GitHub.