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# from langchain_google_genai import GoogleGenerativeAI
# import requests
# from bs4 import BeautifulSoup
# from dotenv import load_dotenv
# import os
# load_dotenv()
# class RAG:
# def __init__(self):
# self.url = 'https://lalitmahale.github.io'
# self.llm = GoogleGenerativeAI(google_api_key=os.getenv("GOOGLE_API"),model="gemini-1.5-pro")
# def get_data(self):
# try:
# res = requests.get(self.url)
# soup = BeautifulSoup(res.content, "html.parser")
# return soup.get_text()
# except Exception as e:
# print(e)
# def clean_text(self):
# return self.get_data().replace("\n","")
# def prompt(self):
# return """You are a helpfull assistant for me and Your name is lalit mahale. understand the below context and give answer for user question.
# context : {context}\n\nQuestion : {question}\n\nGive proper answer for this questions."""
# def pipeline(self,query):
# try:
# prompt = self.prompt().format(context = self.clean_text(),question = query)
# return self.llm.invoke(prompt)
# except Exception as e:
# print(e)
# if __name__ == "__main__":
# res = RAG().pipeline("who is lalit mahale")
# print(res) |