app.py

import os
#import openai
import gradio as gr
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper, ServiceContext

#if you have OpenAI API key as an environment variable, enable the below
#openai.api_key = os.getenv("OPENAI_API_KEY")

#if you have OpenAI API key as a string, enable the below
#openai.api_key = "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"
#os.environ["OPENAI_API_KEY"] = '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'  
#os.environ["OPENAI_API_KEY"] = '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'  
os.environ["OPENAI_API_KEY"] = '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'

start_sequence = "\nAI:"
restart_sequence = "\nHuman: "

prompt = "The following is a conversation with an AI assistant. The assistant is helpful, creative, clever, and very friendly.\n\nHuman: "


def gradio_ask_ai(user_input):
    index = GPTSimpleVectorIndex.load_from_disk('index.json')
    query = user_input
    response = index.query(query)
    return response.response

def chatgpt_clone(input, history):
    history = history or []
    s = list(sum(history, ()))
    s.append(input)
    inp = ' '.join(s)
    #output = openai_create(inp) gradio_ask_ai
    
    output = gradio_ask_ai(inp)
    #print("out",type(output))
    history.append((input, output))
    return history, history

block = gr.Blocks()


with block:
    gr.Markdown("""<h1><center>Meshworks bot</center></h1>
    """)
    chatbot = gr.Chatbot()
    message = gr.Textbox(placeholder=prompt)
    state = gr.State()
    submit = gr.Button("Submit")
    submit.click(chatgpt_clone, inputs=[message, state], outputs=[chatbot, state])

block.launch()