Document OCR web app

This tutorial shows you how to use Modal to deploy a fully serverless React + FastAPI application. We’re going to build a simple “Receipt Parser” web app that submits OCR transcription tasks to a separate Modal app defined in the Job Queue tutorial, polls until the task is completed, and displays the results. Try it out for yourself here.

Basic setup

Let’s get the imports out of the way and define an App.

from pathlib import Path

import fastapi
import fastapi.staticfiles
import modal

app = modal.App("example-doc-ocr-webapp")

Modal works with any ASGI or WSGI web framework. Here, we choose to use FastAPI.

web_app = fastapi.FastAPI()

Define endpoints

We need two endpoints: one to accept an image and submit it to the Modal job queue, and another to poll for the results of the job.

In parse, we’re going to submit tasks to the function defined in the Job Queue tutorial, so we import it first using Function.lookup.

We call .spawn() on the function handle we imported above to kick off our function without blocking on the results. spawn returns a unique ID for the function call, which we then use to poll for its result.

@web_app.post("/parse")
async def parse(request: fastapi.Request):
    parse_receipt = modal.Function.lookup(
        "example-doc-ocr-jobs", "parse_receipt"
    )

    form = await request.form()
    receipt = await form["receipt"].read()  # type: ignore
    call = parse_receipt.spawn(receipt)
    return {"call_id": call.object_id}

/result uses the provided call_id to instantiate a modal.FunctionCall object, and attempt to get its result. If the call hasn’t finished yet, we return a 202 status code, which indicates that the server is still working on the job.

@web_app.get("/result/{call_id}")
async def poll_results(call_id: str):
    function_call = modal.functions.FunctionCall.from_id(call_id)
    try:
        result = function_call.get(timeout=0)
    except TimeoutError:
        return fastapi.responses.JSONResponse(content="", status_code=202)

    return result

Now that we’ve defined our endpoints, we’re ready to host them on Modal. First, we specify our dependencies — here, a basic Debian Linux environment with FastAPI installed.

image = modal.Image.debian_slim(python_version="3.12").pip_install(
    "fastapi[standard]==0.115.4"
)

Then, we add the static files for our front-end. We’ve made a simple React app that hits the two endpoints defined above. To package these files with our app, we use add_local_dir with the local directory of the assets, and specify that we want them in the /assets directory inside our container (the remote_path). Then, we instruct FastAPI to serve this static file directory at our root path.

local_assets_path = Path(__file__).parent / "doc_ocr_frontend"
image = image.add_local_dir(local_assets_path, remote_path="/assets")


@app.function(image=image)
@modal.asgi_app()
def wrapper():
    web_app.mount(
        "/", fastapi.staticfiles.StaticFiles(directory="/assets", html=True)
    )
    return web_app

Running

While developing, you can run this as an ephemeral app by executing the command

modal serve doc_ocr_webapp.py

Modal watches all the mounted files and updates the app if anything changes. See these docs for more details.

Deploy

To deploy your application, run

modal deploy doc_ocr_webapp.py

That’s all!

If successful, this will print a URL for your app that you can navigate to in your browser 🎉 .