import os
from langchain_community.document_loaders import AsyncHtmlLoader
from langchain_community.document_transformers import Html2TextTransformer
from langchain_groq import ChatGroq
import streamlit as st 
from dotenv import load_dotenv
from pathlib import Path

env_path = Path('.') / '.env'
load_dotenv(dotenv_path=env_path)

st.title("AI Sales Executive")
urls_input = st.text_area("Enter website URLs (comma-separated):")

if st.button("Submit"):
    if urls_input:
        urls = [url.strip() for url in urls_input.split(",")]
        loader = AsyncHtmlLoader(urls)
        docs = loader.load()

        html2text = Html2TextTransformer()
        docs_transformed = html2text.transform_documents(docs)

        llm = ChatGroq(
            model="llama3-8b-8192",
            temperature=0,
            max_tokens=None,
            timeout=None,
            max_retries=2,
        )


        prompt = """You are a senior sales executive tasked with demonstrating how your expert team of data scientists can significantly enhance this company's growth and optimize their existing products using AI/ML technologies. Provide detailed insights into the specific ways your team can contribute to the company's success, specifically tailored to the company's product and goals. Additionally, include a brief summary of the company based on the following website content:

Website content: {content}
"""
        content = """"""
        for doc in docs_transformed:
            content += doc.page_content + "\n\n"
        
        with st.spinner("Generating response..."):
            response = llm.invoke(prompt.format(content=content))
            st.write(response.content)