| 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) |