Introducing Gradio 5.0
Read MoreIntroducing Gradio 5.0
Read MoreLet's work through an example of building a custom gradio component for displaying PDF files. This component will come in handy for showcasing document question answering models, which typically work on PDF input. This is a sneak preview of what our finished component will look like:
Make sure you have gradio 5.0 or higher installed as well as node 20+. As of the time of publication, the latest release is 4.1.1. Also, please read the Five Minute Tour of custom components and the Key Concepts guide before starting.
Navigate to a directory of your choosing and run the following command:
gradio cc create PDF
Tip: You should change the name of the component.
Some of the screenshots assume the component is called PDF
but the concepts are the same!
This will create a subdirectory called pdf
in your current working directory.
There are three main subdirectories in pdf
: frontend
, backend
, and demo
.
If you open pdf
in your code editor, it will look like this:
Tip:
For this demo we are not templating off a current gradio component. But you can see the list of available templates with `gradio cc show` and then pass the template name to the `--template` option, e.g. `gradio cc create
We're going to use the pdfjs javascript library to display the pdfs in the frontend. Let's start off by adding it to our frontend project's dependencies, as well as adding a couple of other projects we'll need.
From within the frontend
directory, run npm install @gradio/client @gradio/upload @gradio/icons @gradio/button
and npm install --save-dev pdfjs-dist@3.11.174
.
Also, let's uninstall the @zerodevx/svelte-json-view
dependency by running npm uninstall @zerodevx/svelte-json-view
.
The complete package.json
should look like this:
{
"name": "gradio_pdf",
"version": "0.2.0",
"description": "Gradio component for displaying PDFs",
"type": "module",
"author": "",
"license": "ISC",
"private": false,
"main_changeset": true,
"exports": {
".": "./Index.svelte",
"./example": "./Example.svelte",
"./package.json": "./package.json"
},
"devDependencies": {
"pdfjs-dist": "3.11.174"
},
"dependencies": {
"@gradio/atoms": "0.2.0",
"@gradio/statustracker": "0.3.0",
"@gradio/utils": "0.2.0",
"@gradio/client": "0.7.1",
"@gradio/upload": "0.3.2",
"@gradio/icons": "0.2.0",
"@gradio/button": "0.2.3",
"pdfjs-dist": "3.11.174"
}
}
Tip:
Running `npm install` will install the latest version of the package available. You can install a specific version with `npm install package@
Navigate to Index.svelte
and delete mentions of JSONView
import { JsonView } from "@zerodevx/svelte-json-view";
<JsonView json={value} />
Run the dev
command to launch the development server.
This will open the demo in demo/app.py
in an environment where changes to the frontend
and backend
directories will reflect instantaneously in the launched app.
After launching the dev server, you should see a link printed to your console that says Frontend Server (Go here): ...
.
You should see the following:
Its not impressive yet but we're ready to start coding!
We're going to start off by first writing the skeleton of our frontend and then adding the pdf rendering logic.
Add the following imports and expose the following properties to the top of your file in the <script>
tag.
You may get some warnings from your code editor that some props are not used.
That's ok.
import { tick } from "svelte";
import type { Gradio } from "@gradio/utils";
import { Block, BlockLabel } from "@gradio/atoms";
import { File } from "@gradio/icons";
import { StatusTracker } from "@gradio/statustracker";
import type { LoadingStatus } from "@gradio/statustracker";
import type { FileData } from "@gradio/client";
import { Upload, ModifyUpload } from "@gradio/upload";
export let elem_id = "";
export let elem_classes: string[] = [];
export let visible = true;
export let value: FileData | null = null;
export let container = true;
export let scale: number | null = null;
export let root: string;
export let height: number | null = 500;
export let label: string;
export let proxy_url: string;
export let min_width: number | undefined = undefined;
export let loading_status: LoadingStatus;
export let gradio: Gradio<{
change: never;
upload: never;
}>;
let _value = value;
let old_value = _value;
Tip: The `gradio`` object passed in here contains some metadata about the application as well as some utility methods. One of these utilities is a dispatch method. We want to dispatch change and upload events whenever our PDF is changed or updated. This line provides type hints that these are the only events we will be dispatching.
We want our frontend component to let users upload a PDF document if there isn't one already loaded.
If it is loaded, we want to display it underneath a "clear" button that lets our users upload a new document.
We're going to use the Upload
and ModifyUpload
components that come with the @gradio/upload
package to do this.
Underneath the </script>
tag, delete all the current code and add the following:
<Block {visible} {elem_id} {elem_classes} {container} {scale} {min_width}>
{#if loading_status}
<StatusTracker
autoscroll={gradio.autoscroll}
i18n={gradio.i18n}
{...loading_status}
/>
{/if}
<BlockLabel
show_label={label !== null}
Icon={File}
float={value === null}
label={label || "File"}
/>
{#if _value}
<ModifyUpload i18n={gradio.i18n} absolute />
{:else}
<Upload
filetype={"application/pdf"}
file_count="single"
{root}
>
Upload your PDF
</Upload>
{/if}
</Block>
You should see the following when you navigate to your app after saving your current changes:
The Upload your PDF
text looks a bit small and barebones.
Lets customize it!
Create a new file called PdfUploadText.svelte
and copy the following code.
Its creating a new div to display our "upload text" with some custom styling.
Tip: Notice that we're leveraging Gradio core's existing css variables here: `var(--size-60)` and `var(--body-text-color-subdued)`. This allows our component to work nicely in light mode and dark mode, as well as with Gradio's built-in themes.
<script lang="ts">
import { Upload as UploadIcon } from "@gradio/icons";
export let hovered = false;
</script>
<div class="wrap">
<span class="icon-wrap" class:hovered><UploadIcon /> </span>
Drop PDF
<span class="or">- or -</span>
Click to Upload
</div>
<style>
.wrap {
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
min-height: var(--size-60);
color: var(--block-label-text-color);
line-height: var(--line-md);
height: 100%;
padding-top: var(--size-3);
}
.or {
color: var(--body-text-color-subdued);
display: flex;
}
.icon-wrap {
width: 30px;
margin-bottom: var(--spacing-lg);
}
@media (--screen-md) {
.wrap {
font-size: var(--text-lg);
}
}
.hovered {
color: var(--color-accent);
}
</style>
Now import PdfUploadText.svelte
in your <script>
and pass it to the Upload
component!
import PdfUploadText from "./PdfUploadText.svelte";
...
<Upload
filetype={"application/pdf"}
file_count="single"
{root}
>
<PdfUploadText />
</Upload>
After saving your code, the frontend should now look like this:
This is the most advanced javascript part. It took me a while to figure it out! Do not worry if you have trouble, the important thing is to not be discouraged 💪 Ask for help in the gradio discord if you need and ask for help.
With that out of the way, let's start off by importing pdfjs
and loading the code of the pdf worker from the mozilla cdn.
import pdfjsLib from "pdfjs-dist";
...
pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdn.bootcss.com/pdf.js/3.11.174/pdf.worker.js";
Also create the following variables:
let pdfDoc;
let numPages = 1;
let currentPage = 1;
let canvasRef;
Now, we will use pdfjs
to render a given page of the PDF onto an html
document.
Add the following code to Index.svelte
:
async function get_doc(value: FileData) {
const loadingTask = pdfjsLib.getDocument(value.url);
pdfDoc = await loadingTask.promise;
numPages = pdfDoc.numPages;
render_page();
}
function render_page() {
// Render a specific page of the PDF onto the canvas
pdfDoc.getPage(currentPage).then(page => {
const ctx = canvasRef.getContext('2d')
ctx.clearRect(0, 0, canvasRef.width, canvasRef.height);
let viewport = page.getViewport({ scale: 1 });
let scale = height / viewport.height;
viewport = page.getViewport({ scale: scale });
const renderContext = {
canvasContext: ctx,
viewport,
};
canvasRef.width = viewport.width;
canvasRef.height = viewport.height;
page.render(renderContext);
});
}
// If the value changes, render the PDF of the currentPage
$: if(JSON.stringify(old_value) != JSON.stringify(_value)) {
if (_value){
get_doc(_value);
}
old_value = _value;
gradio.dispatch("change");
}
Tip: The `$:` syntax in svelte is how you declare statements to be reactive. Whenever any of the inputs of the statement change, svelte will automatically re-run that statement.
Now place the canvas
underneath the ModifyUpload
component:
<div class="pdf-canvas" style="height: {height}px">
<canvas bind:this={canvasRef}></canvas>
</div>
And add the following styles to the <style>
tag:
<style>
.pdf-canvas {
display: flex;
justify-content: center;
align-items: center;
}
</style>
Now for the fun part - actually rendering the PDF when the file is uploaded!
Add the following functions to the <script>
tag:
async function handle_clear() {
_value = null;
await tick();
gradio.dispatch("change");
}
async function handle_upload({detail}: CustomEvent<FileData>): Promise<void> {
value = detail;
await tick();
gradio.dispatch("change");
gradio.dispatch("upload");
}
Tip:
The `gradio.dispatch` method is actually what is triggering the `change` or `upload` events in the backend. For every event defined in the component's backend, we will explain how to do this in Step 9, there must be at least one `gradio.dispatch("
Now we will run these functions whenever the Upload
component uploads a file and whenever the ModifyUpload
component clears the current file. The <Upload>
component dispatches a load
event with a payload of type FileData
corresponding to the uploaded file. The on:load
syntax tells Svelte
to automatically run this function in response to the event.
<ModifyUpload i18n={gradio.i18n} on:clear={handle_clear} absolute />
...
<Upload
on:load={handle_upload}
filetype={"application/pdf"}
file_count="single"
{root}
>
<PdfUploadText/>
</Upload>
Congratulations! You have a working pdf uploader!
If a user uploads a PDF document with multiple pages, they will only be able to see the first one.
Let's add some buttons to help them navigate the page.
We will use the BaseButton
from @gradio/button
so that they look like regular Gradio buttons.
Import the BaseButton
and add the following functions that will render the next and previous page of the PDF.
import { BaseButton } from "@gradio/button";
...
function next_page() {
if (currentPage >= numPages) {
return;
}
currentPage++;
render_page();
}
function prev_page() {
if (currentPage == 1) {
return;
}
currentPage--;
render_page();
}
Now we will add them underneath the canvas in a separate <div>
...
<ModifyUpload i18n={gradio.i18n} on:clear={handle_clear} absolute />
<div class="pdf-canvas" style="height: {height}px">
<canvas bind:this={canvasRef}></canvas>
</div>
<div class="button-row">
<BaseButton on:click={prev_page}>
⬅️
</BaseButton>
<span class="page-count"> {currentPage} / {numPages} </span>
<BaseButton on:click={next_page}>
➡️
</BaseButton>
</div>
...
<style>
.button-row {
display: flex;
flex-direction: row;
width: 100%;
justify-content: center;
align-items: center;
}
.page-count {
margin: 0 10px;
font-family: var(--font-mono);
}
Congratulations! The frontend is almost complete 🎉
We're going to want users of our component to get a preview of the PDF if its used as an example
in a gr.Interface
or gr.Examples
.
To do so, we're going to add some of the pdf rendering logic in Index.svelte
to Example.svelte
.
<script lang="ts">
export let value: string;
export let type: "gallery" | "table";
export let selected = false;
import pdfjsLib from "pdfjs-dist";
pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdn.bootcss.com/pdf.js/3.11.174/pdf.worker.js";
let pdfDoc;
let canvasRef;
async function get_doc(url: string) {
const loadingTask = pdfjsLib.getDocument(url);
pdfDoc = await loadingTask.promise;
renderPage();
}
function renderPage() {
// Render a specific page of the PDF onto the canvas
pdfDoc.getPage(1).then(page => {
const ctx = canvasRef.getContext('2d')
ctx.clearRect(0, 0, canvasRef.width, canvasRef.height);
const viewport = page.getViewport({ scale: 0.2 });
const renderContext = {
canvasContext: ctx,
viewport
};
canvasRef.width = viewport.width;
canvasRef.height = viewport.height;
page.render(renderContext);
});
}
$: get_doc(value);
</script>
<div
class:table={type === "table"}
class:gallery={type === "gallery"}
class:selected
style="justify-content: center; align-items: center; display: flex; flex-direction: column;"
>
<canvas bind:this={canvasRef}></canvas>
</div>
<style>
.gallery {
padding: var(--size-1) var(--size-2);
}
</style>
Tip: Exercise for the reader - reduce the code duplication between `Index.svelte` and `Example.svelte` 😊
You will not be able to render examples until we make some changes to the backend code in the next step!
The backend changes needed are smaller. We're almost done!
What we're going to do is:
change
and upload
events to our component.height
property to let users control the height of the PDF.data_model
of our component to be FileData
. This is so that Gradio can automatically cache and safely serve any files that are processed by our component.preprocess
method to return a string corresponding to the path of our uploaded PDF.postprocess
to turn a path to a PDF created in an event handler to a FileData
.When all is said an done, your component's backend code should look like this:
from __future__ import annotations
from typing import Any, Callable, TYPE_CHECKING
from gradio.components.base import Component
from gradio.data_classes import FileData
from gradio import processing_utils
if TYPE_CHECKING:
from gradio.components import Timer
class PDF(Component):
EVENTS = ["change", "upload"]
data_model = FileData
def __init__(self, value: Any = None, *,
height: int | None = None,
label: str | None = None, info: str | None = None,
show_label: bool | None = None,
container: bool = True,
scale: int | None = None,
min_width: int | None = None,
interactive: bool | None = None,
visible: bool = True,
elem_id: str | None = None,
elem_classes: list[str] | str | None = None,
render: bool = True,
load_fn: Callable[..., Any] | None = None,
every: Timer | float | None = None):
super().__init__(value, label=label, info=info,
show_label=show_label, container=container,
scale=scale, min_width=min_width,
interactive=interactive, visible=visible,
elem_id=elem_id, elem_classes=elem_classes,
render=render, load_fn=load_fn, every=every)
self.height = height
def preprocess(self, payload: FileData) -> str:
return payload.path
def postprocess(self, value: str | None) -> FileData:
if not value:
return None
return FileData(path=value)
def example_payload(self):
return "https://gradio-builds.s3.amazonaws.com/assets/pdf-guide/fw9.pdf"
def example_value(self):
return "https://gradio-builds.s3.amazonaws.com/assets/pdf-guide/fw9.pdf"
To test our backend code, let's add a more complex demo that performs Document Question and Answering with huggingface transformers.
In our demo
directory, create a requirements.txt
file with the following packages
torch
transformers
pdf2image
pytesseract
Tip: Remember to install these yourself and restart the dev server! You may need to install extra non-python dependencies for `pdf2image`. See [here](https://pypi.org/project/pdf2image/). Feel free to write your own demo if you have trouble.
import gradio as gr
from gradio_pdf import PDF
from pdf2image import convert_from_path
from transformers import pipeline
from pathlib import Path
dir_ = Path(__file__).parent
p = pipeline(
"document-question-answering",
model="impira/layoutlm-document-qa",
)
def qa(question: str, doc: str) -> str:
img = convert_from_path(doc)[0]
output = p(img, question)
return sorted(output, key=lambda x: x["score"], reverse=True)[0]['answer']
demo = gr.Interface(
qa,
[gr.Textbox(label="Question"), PDF(label="Document")],
gr.Textbox(),
)
demo.launch()
See our demo in action below!
Finally lets build our component with gradio cc build
and publish it with the gradio cc publish
command!
This will guide you through the process of uploading your component to PyPi and HuggingFace Spaces.
Tip: You may need to add the following lines to the `Dockerfile` of your HuggingFace Space.
RUN mkdir -p /tmp/cache/
RUN chmod a+rwx -R /tmp/cache/
RUN apt-get update && apt-get install -y poppler-utils tesseract-ocr
ENV TRANSFORMERS_CACHE=/tmp/cache/
In order to use our new component in any gradio 4.0 app, simply install it with pip, e.g. pip install gradio-pdf
. Then you can use it like the built-in gr.File()
component (except that it will only accept and display PDF files).
Here is a simple demo with the Blocks api:
import gradio as gr
from gradio_pdf import PDF
with gr.Blocks() as demo:
pdf = PDF(label="Upload a PDF", interactive=True)
name = gr.Textbox()
pdf.upload(lambda f: f, pdf, name)
demo.launch()
I hope you enjoyed this tutorial! The complete source code for our component is here. Please don't hesitate to reach out to the gradio community on the HuggingFace Discord if you get stuck.