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import requests
from bs4 import BeautifulSoup
import openai
import gradio as gr
import os
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
# Function to scrape content from a URL
def scrape_content(url):
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
# Example of extracting title and body content - modify based on actual structure of the websites
title = soup.find('title').get_text()
paragraphs = soup.find_all('p')
content = '\n'.join([para.get_text() for para in paragraphs])
return title, content
# Function to create flashcards using OpenAI
def create_flashcards(content):
prompt = f"Create flashcards for UPSC exam preparation from the following content:\n\n{content}\n\n"
response = openai.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant for UPSC exam preparation that creates flash cards when a news URL is given as input,The flash card should include category that the topic belongs to on the front side along with a question framed and the back side content will be the answer to the question."},
{"role": "user", "content": prompt}
],
max_tokens=500,
temperature=0.7
)
flashcards = response.choices[0].message.content.strip()
return flashcards
# Function to process a single URL and generate flashcards
def process_url(url):
if not url:
return "No URL provided."
title, content = scrape_content(url)
flashcards = create_flashcards(content)
return f"Title: {title}\n\nFlashcards:\n{flashcards}"
# Gradio interface
iface = gr.Interface(
fn=process_url,
inputs=gr.Textbox(lines=2, placeholder="Enter URL here..."),
outputs="text",
title="UPSC Flashcard Generator",
description="Enter a News Site URL to generate flashcard for UPSC preparation."
)
# Launch the interface
if __name__ == "__main__":
iface.launch(share=True)
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