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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):
# Fetch the secret prompt from environment variables
prompt = os.getenv("FLASHCARD_PROMPT")
response = openai.ChatCompletion.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": prompt},
{"role": "user", "content": content}
],
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)
# Save flashcards as a text file
file_path = "flashcards.txt"
with open(file_path, "w") as file:
file.write(f"Title: {title}\n\nFlashcards:\n{flashcards}")
return flashcards, file_path
# Gradio interface
def interface_fn(url):
flashcards, file_path = process_url(url)
return flashcards, file_path
iface = gr.Interface(
fn=interface_fn,
inputs=gr.Textbox(lines=2, placeholder="Enter URL here..."),
outputs=["text", gr.File(label="Download Flashcards")],
title="The Federal Flash Card Generator",
description="An application that helps students prepare for competitive exams like the UPSC, SSC, CLAT, MBA, etc. Enter a News Site URL to generate flashcards for exam preparation. Option to download the response as a text file."
)
# Launch the interface
if __name__ == "__main__":
iface.launch(share=False)
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