#for learning
import os
import openai
import gradio as gr

openai.api_key =  os.environ.get('O_APIKey')

#using a folder
from llama_index import VectorStoreIndex, SimpleDirectoryReader, SummaryIndex, download_loader
PDFReader = download_loader("PDFReader")
loader = PDFReader()

#loading options
# loader = SimpleDirectoryReader(input_files = ["pdf1","pdf2"])
# documents = loader.load_data()
# or
# documents = loader.load_data(file=['toolkit.pdf','pdf2','pdf3'])

documents = loader.load_data(file='toolkit.pdf')
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()

def reply(message, history):
  answer = str(query_engine.query(message))
  return answer

Conversing = gr.ChatInterface(reply, chatbot=gr.Chatbot(height=500), retry_btn=None,theme=gr.themes.Monochrome(),
                              title = 'E-Commerce And Digital Marketing Toolkit Q&A', undo_btn = None, clear_btn = None, css='footer {visibility: hidden}').launch()