import streamlit as st
from requests_html import HTMLSession
import pandas as pd
import langchain as lc
import openai

st.title("Cybersecurity Vulnerability Scanner & AI Analyzer")

# URL input for scraping
url = st.text_input("Enter the target URL:")
if st.button("Scrape and Scan"):
    if url:
        st.write(f"Processing {url}...")

        # Initialize an HTML session
        session = HTMLSession()
        response = session.get(url)

        # Attempt to render JavaScript, if necessary
        if url:
        st.write(f"Processing {url}...")
        # Rest of the code...
    else:
    st.warning("Please enter a valid URL.")

        # Extract links, JavaScript files, and forms
        links = [link.attrs['href'] for link in response.html.find('a') if 'href' in link.attrs]
        js_files = [script.attrs['src'] for script in response.html.find('script') if 'src' in script.attrs]
        forms = [form.attrs.get('action', 'No action') for form in response.html.find('form')]

        # Display extracted data
        st.success("Scraping and scanning complete!")
        st.write("Links:", links)
        st.write("JavaScript Files:", js_files)
        st.write("Forms:", forms)
    else:
        st.warning("Please enter a valid URL.")

# AI-based Analysis
user_prompt = st.text_area("Enter an AI prompt for analysis:")
if st.button("Analyze with AI"):
    if user_prompt:
        # Initialize LangChain/OpenAI LLM for analysis
        llm = lc.LLMChain(llm=lc.OpenAI())
        full_prompt = f"{user_prompt}\nLinks:\n{links}\nJS Files:\n{js_files}\nForms:\n{forms}"
        ai_analysis = llm.run(full_prompt)
        st.write("AI Analysis:")
        st.write(ai_analysis)
    else:
        st.warning("Please provide an AI prompt for analysis.")