app.py

import os
from pathlib import Path

import gradio as gr
from bs4 import BeautifulSoup
from huggingface_hub import WebhookPayload, WebhooksServer
from rich.console import Console
from rich.syntax import Syntax

from utilities.my_logger import setup_logger

proj_dir = Path(__name__).parent

SUBREDDIT = os.environ["SUBREDDIT"]
USERNAME = os.environ["USERNAME"]
DATASET_NAME = f"{USERNAME}/dataset-creator-reddit-{SUBREDDIT}"

FREQUENCY = os.environ.get("FREQUENCY", '').lower()
if FREQUENCY not in ["daily", "hourly"]:
    raise gr.Error("FREQUENCY environment variable must be 'daily' or 'hourly'")

WEBHOOK_SECRET = os.getenv("HF_WEBHOOK_SECRET", 'secret')

logger = setup_logger(__name__)


def log_file_to_html_string():
    log_file = "mylog.log"
    num_lines_visualize = 50

    console = Console(record=True, width=150, style="#272822")
    with open(log_file, "rt") as f:
        # Seek to the end of the file minus 300 lines
        # Read the last 300 lines of the file
        lines = f.readlines()
        lines = lines[-num_lines_visualize:]

        # Syntax-highlight the last 300 lines of the file using the Python lexer and Monokai style
        output = "".join(lines)
        syntax = Syntax(output, "python", theme="monokai", word_wrap=True)

    console.print(syntax);
    html_content = console.export_html(inline_styles=True)

    # Parse the HTML content using BeautifulSoup
    soup = BeautifulSoup(html_content, 'lxml')

    # Modify the <pre> tag
    pre_tag = soup.pre
    pre_tag['class'] = 'scrollable'
    del pre_tag['style']

    # Add your custom styles and the .scrollable CSS to the <style> tag
    style_tag = soup.style
    style_content = """
pre, code {
    background-color: #272822;
}
    .scrollable {
        font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace;
        height: 500px;
        overflow: auto;
    }
    """
    style_tag.append(style_content)

    return soup.prettify()


intro_md = f"""
# Reddit Dataset Creator
This is a reddit dataset creator which builds and updates [{DATASET_NAME}](https://huggingface.co/datasets/{DATASET_NAME}) 
which pulls from [/r/{SUBREDDIT}](http://www.reddit.com/r/{SUBREDDIT}). Check the dataset for more details. 

As shown in the below diagram this space pulls data from reddit via [PRAW](https://praw.readthedocs.io/en/stable/), processes it, and puts it in a corresponding dataset.
"""

how_to_md = f"""
# How to make your own space and dataset
1. Create a [reddit application](https://www.reddit.com/prefs/apps), use 'Script for personal use'
    - Redirect URI can be anything, I use 'http://www.example.com/unused/redirect/uri'
    - You need the `secret` and the `Client ID` from the reddit application.
    - `REDDIT_USER_AGENT` can be any descriptive string, probably any undescriptive string too.
2. Get your writable [huggingface token](https://huggingface.co/settings/tokens)
3. <a class="duplicate-button" style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/derek-thomas/dataset-creator-reddit-amitheasshole?duplicate=true"><img style="margin-top:0;margin-bottom:0" src="https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg" alt="Duplicate Space"></a>
and fill in the information
"""

how_does_it_work_md = f"""
# Core Components
There are 2 core components [main](main.py) and [app](app.py).
Main does a few things: 
- Pulls from a datasource 
- Updates a dataset on the hub
- Updates the README of the dataset
- Writes a local log file (inaccessible outside the spaces container)

App
- Visualizes the log file from Main

# Running it
This uses a docker space so that I can execute supervisor. Supervisor allows me to kick off 2 processes and manage the
log files. I use gradio for `app` and map that to the open port of huggingface spaces. 

The only communication between `app` and `main` is the log file.
"""

with gr.Blocks() as ui:
    with gr.Tab("Application"):
        gr.Markdown(intro_md)
        gr.Image(proj_dir / 'media' / 'reddit_scraper.drawio.png')
        gr.Markdown("# Logs")
        output = gr.HTML(log_file_to_html_string, every=1)
        ui.load(None,
                _js="""
        () => {
            document.body.classList.toggle('dark');
            document.querySelector('gradio-app').style.backgroundColor = 'var(--color-background-primary)'
        }
        """, )
    with gr.Tab("How to Create?"):
        gr.Markdown(how_to_md)
    with gr.Tab("How does it work?"):
        gr.Markdown(how_does_it_work_md)
    with gr.Tab("Hidden"):
        with gr.Column():
            input_text = gr.Textbox(label="Input Text")
            health_btn = gr.Button(value="Health")
        with gr.Column():
            output_text = gr.Textbox(label="Output Text")

app = WebhooksServer(ui=ui.queue(), webhook_secret=WEBHOOK_SECRET)


@app.add_webhook("/dataset_repo")
async def community(payload: WebhookPayload):
    if payload.event.scope.startswith("repo"):
        logger.info(f"Webhook received from {DATASET_NAME} indicating a repo {payload.event.action}")


if __name__ == '__main__':
    app.launch(server_name="0.0.0.0", show_error=True, server_port=7860)
    # ui.queue().launch(server_name="0.0.0.0", show_error=True, server_port=7860)