telegram_bot.py

from langchain_openai import ChatOpenAI, OpenAIEmbeddings
import os
from dotenv import load_dotenv
from langchain.chains.combine_documents import create_stuff_documents_chain
from langchain_core.prompts import ChatPromptTemplate
from telegram import Update
from telegram.ext import Application, CommandHandler, MessageHandler, ContextTypes, filters

load_dotenv()

TELEGRAM_TOKEN = os.getenv('TELEGRAM_TOKEN')
USER_AGENT = os.environ.get('USER_AGENT')

from langchain_community.document_loaders import WebBaseLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.vectorstores.faiss import FAISS
from langchain.chains import create_retrieval_chain


def get_documents_from_web(url):
    loader = WebBaseLoader(url)
    docs = loader.load()

    splitter = RecursiveCharacterTextSplitter(
        chunk_size=200,
        chunk_overlap=20
    )

    splitDocs = splitter.split_documents(docs)
    return splitDocs


def create_db(docs):
    embedding = OpenAIEmbeddings()
    vectorStore = FAISS.from_documents(docs, embedding=embedding)
    return vectorStore


def create_chain(vectorStore):
    model = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.4)

    prompt = ChatPromptTemplate.from_template("""
    Answer the user's question:
    Context: {context}
    Question: {input}
    """)

    chain = create_stuff_documents_chain(llm=model, prompt=prompt)

    retriever = vectorStore.as_retriever()

    retriever_chain = create_retrieval_chain(retriever, chain)

    return retriever_chain


docs = get_documents_from_web("https://www.amazon.co.uk/gp/help/customer/display.html?nodeId=GKM69DUUYKQWKWX7")
vectorStore = create_db(docs)
chain = create_chain(vectorStore)


async def start(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    await update.message.reply_text(
        "Hi! I can help you with questions about the Amazon return policy."
        " How can I help you today?")


async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
    user_query = update.message.text
    response = chain.invoke({
        "input": user_query
    })
    await update.message.reply_text(response["answer"])

def main() -> None:

    application = Application.builder().token(TELEGRAM_TOKEN).build()

    application.add_handler(CommandHandler("start", start))

    application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))

    application.run_polling()


if __name__ == '__main__':
    main()