openagent-dev 0.2.1

Web apps in pure Python with all the flexibility and speed of nextjs.

⚙️ Installation

Open a terminal and run (Requires Python 3.7+):

pip install nextpy

🥳 Create your first app

Installing nextpy also installs the nextpy command line tool.

Test that the install was successful by creating a new project. (Replace my_app_name with your project name):

mkdir my_app_name
cd my_app_name
nextpy init

This command initializes a boilerplate app in your new directory.

You can run this app in development mode:

nextpy run

You should see your app running at http://localhost:3000.

Now you can modify the source code in my_app_name/my_app_name.py. Nextpy has fast refreshes so you can see your changes instantly when you save your code.

🫧 Example App

Let's go over an example: creating an image generation UI around DALL·E. For simplicity, we just call the OpenAI API, but you could replace this with an ML model run locally.

 

 

Here is the complete code to create this. This is all done in one Python file!

import nextpy as xt
import openai

openai.api_key = "YOUR_API_KEY"

class State(xt.State):
    """The app state."""
    prompt = ""
    image_url = ""
    processing = False
    complete = False

    def get_image(self):
        """Get the image from the prompt."""
        if self.prompt == "":
            return xt.window_alert("Prompt Empty")

        self.processing, self.complete = True, False
        yield
        response = openai.Image.create(prompt=self.prompt, n=1, size="1024x1024")
        self.image_url = response["data"][0]["url"]
        self.processing, self.complete = False, True
        

def index():
    return xt.center(
        xt.vstack(
            xt.heading("DALL·E"),
            xt.input(placeholder="Enter a prompt", on_blur=State.set_prompt),
            xt.button(
                "Generate Image",
                on_click=State.get_image,
                is_loading=State.processing,
                width="100%",
            ),
            xt.cond(
                State.complete,
                     xt.image(
                         src=State.image_url,
                         height="25em",
                         width="25em",
                    )
            ),
            padding="2em",
            shadow="lg",
            border_radius="lg",
        ),
        width="100%",
        height="100vh",
    )

# Add state and page to the app.
app = xt.App()
app.add_page(index, title="nextpy:DALL·E")
app.compile()

Let's break this down.

Nextpy UI

Let's start with the UI.

def index():
    return xt.center(
        ...
    )

This index function defines the frontend of the app.

We use different components such as center, vstack, input, and button to build the frontend. Components can be nested within each other to create complex layouts. And you can use keyword args to style them with the full power of CSS.

State

Nextpy represents your UI as a function of your state.

class State(xt.State):
    """The app state."""
    prompt = ""
    image_url = ""
    processing = False
    complete = False

The state defines all the variables (called vars) in an app that can change and the functions that change them.

Here the state is comprised of a prompt and image_url. There are also the booleans processing and complete to indicate when to show the circular progress and image.

Event Handlers

def get_image(self):
    """Get the image from the prompt."""
    if self.prompt == "":
        return xt.window_alert("Prompt Empty")

    self.processing, self.complete = True, False
    yield
    response = openai.Image.create(prompt=self.prompt, n=1, size="1024x1024")
    self.image_url = response["data"][0]["url"]
    self.processing, self.complete = False, True

Within the state, we define functions called event handlers that change the state vars. Event handlers are the way that we can modify the state in Nextpy. They can be called in response to user actions, such as clicking a button or typing in a text box. These actions are called events.

Our DALL·E. app has an event handler, get_image to which get this image from the OpenAI API. Using yield in the middle of an event handler will cause the UI to update. Otherwise the UI will update at the end of the event handler.

Routing

Finally, we define our app.

app = xt.App()

We add a page from the root of the app to the index component. We also add a title that will show up in the page preview/browser tab.

app.add_page(index, title="DALL-E")
app.compile()

You can create a multi-page app by adding more pages.