app.py

import gradio
import requests
from bs4 import BeautifulSoup
from transformers import pipeline

# Function to scrape information from a website
def scrape_website(prompt, website_link):
    response = requests.get(website_link)
    soup = BeautifulSoup(response.content, "html.parser")
    
    # Implement your web scraping logic here
    # Extract the desired information from the HTML
    
    scraped_info = "Scraped information from the website"
    return scraped_info

# Function to generate chatbot responses
def generate_chatbot_response(prompt):
    chatbot = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
    chatbot_response = chatbot(prompt, max_length=50, num_return_sequences=1)[0]["generated_text"]
    return chatbot_response

# Function to handle the web app logic
def web_app(prompt, website_link):
    scraped_info = scrape_website(prompt, website_link)
    chatbot_response = generate_chatbot_response(prompt)
    return {"Scraped Information": scraped_info, "Chatbot Response": chatbot_response}

# Create the Gradio interface
iface = gradio.Interface(
    fn=web_app,
    inputs=["text", "text"],
    outputs=["text", "text"],
    title="Web Scraping and Chatbot App",
    description="Enter a prompt and a website link to scrape information and generate a chatbot response."
)

# Run the Gradio app
iface.launch()