app.py

import gradio as gr
import spacy
import requests
from bs4 import BeautifulSoup

# Load the pre-trained model
nlp = spacy.load("en_core_web_sm")

def extract_entities(url):
 # Step 1: Web scraping
 response = requests.get(url)
 soup = BeautifulSoup(response.text, 'html.parser')
 page_text = soup.get_text()

 # Apply the model to the text
 doc = nlp(page_text)

 # Extract entities and return as a formatted string
 results = "\n".join([f"{entity.text} ({entity.label_})" for entity in doc.ents])
 return results

iface = gr.Interface(fn=extract_entities, 
 inputs="textbox", 
 outputs="text",
 interpretation="default")

iface.launch()