app.py

# Import librairies 
from pathlib import Path
import sys
import os 
import openai
import llama_index
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, LLMPredictor, PromptHelper, ServiceContext, GPTVectorStoreIndex, StorageContext, load_index_from_storage, download_loader,  GPTRAKEKeywordTableIndex
from llama_index.retrievers import VectorIndexRetriever
from langchain import OpenAI
from llama_index.node_parser import SimpleNodeParser
import gradio as gr
from llama_index.optimization.optimizer import SentenceEmbeddingOptimizer
from langchain.chat_models import ChatOpenAI
from llama_index.readers import Document
import io
from PyPDF2 import PdfReader
from azure.storage.filedatalake import DataLakeServiceClient
from llama_index.indices.vector_store.base import GPTVectorStoreIndex
from adlfs import AzureBlobFileSystem
import time 


header = """<center><b><p style=\"color: #E13C32; font-size: 36px;\">My Ardian Chatbot</p></b></center>
<i><p style=\"font-size: 16px; color: grey;\">Please make sure to formulate clear and precise questions and to add contextual information when possible. This will help the tool produce the most relevant response. Adopt an iterative approach and ask for more details or explanations when necessary.</br><i/></p>"""

footnote = "<p style=\"font-size: 16px; color: grey;\"> ⚠ The chatbot doesn't have a memory, it doesn't remember what it previously generated.</a></p>"

theme = gr.themes.Base(
  primary_hue="red",
  secondary_hue="gray",
  font=['FuturaTOT', '=', '36px']
)



def to_uppercase(text):
    return text.upper()

iface = gr.Interface(fn=to_uppercase, inputs="text", outputs="text")
iface.launch()