import gradio as gr
import pandas as pd
from io import StringIO
import openai
import pytesseract



import os

import numpy as np
import time

# Set up OpenAI API key
from api_key import api_key
openai.api_key = os.environ["CHATGPT_API_KEY"]

Init_system_prompt = "You are an AI Assistant that tries to teach kids various subjects. You are given learning material and you task is to ask questions given the material and then you also grade answers and give feedback how to improve the answers"
system_message = {"role": "system", "content": Init_system_prompt}

import os
from PIL import Image

import pytesseract
#os.system("rm -f path.txt")
path = os.system("which tesseract >> path.txt")
with open("path.txt", 'r') as file:
    tesseract_path = file.read().replace('\n', '')


########### TAB 1 (UPLOAD) FUNCTIONS  #############################

def print_files(files):
    for file in files:
        print(file.__dir__())
        print(file.name)
        print(file.file)


def create_data(files):
    question_context = ''
    for file in files:
        if file.name.endswith('png') or file.name.endswith('.jpg'):
            try:
                question_context += (pytesseract.image_to_string(Image.open(file.name), lang='fin')) + '\n\n'
            except Exception as e:
                print(e)
                pass

    return question_context


########### TAB 2 (CHROMA + PLOT) FUNCTIONS  #############################

########### TAB 3 (CHAT) FUNCTIONS  #############################

def user(user_message, history):
        return "", history + [[user_message, None]]

def bot(history, messages_history, system_prompt, teksti_contexti, temperature, max_tokens, chatgpt_model):
    user_message = history[-1][0]

    bot_message, messages_history = ask_gpt(user_message, messages_history, system_prompt, teksti_contexti, temperature, max_tokens,chatgpt_model)
    messages_history += [{"role": "assistant", "content": bot_message}]
    history[-1][1] = bot_message
    time.sleep(0.2)
    return history, messages_history, str(messages_history)

def ask_gpt(message, messages_history, context, system_prompt, temperature, max_tokens, chatgpt_model):
    if len(messages_history) < 1:
        messages_history = [{"role": "system", "content": system_prompt}]
    messages_history += [{"role": "user", "content": context + '\n Please ask a question about the previous paragramph?'}]
    print(messages_history)
    response = openai.ChatCompletion.create(
        model=chatgpt_model,
        messages=messages_history,
        temperature=temperature,
        max_tokens=max_tokens
    )
    return response['choices'][0]['message']['content'], messages_history

def init_history(messages_history, system_prompt):
    messages_history = []
    messages_history += [{"role": "system", "content": system_prompt}]
    msg_log = gr.Textbox.update(value="Tähän tulee message history")
    system_prompt = gr.Textbox.update(value=system_prompt, label='Insert system message here')
    return messages_history, system_prompt, msg_log


############# INTERFACE ##########################
with gr.Blocks() as demo:
    gr.Markdown("ChatGPT demo with RAG using Chromadb")
    
    
    
    ############# TAB 1 ##########################
    with gr.Tab("Upload documents"):
        with gr.Row():
            files = gr.File(file_count='multiple', file_types=['image'], interactivate = True)
            gr.Markdown("")
            testi = gr.Button()
        
    ############# TAB 2 ##########################
    with gr.Tab("Create questions"):
        
        with gr.Row():
            gr.Markdown("")
        with gr.Row():
            create_context_btn = gr.Button()
            teksti_contexti = gr.Textbox(value='Tähän tulee konteksti', label='Dataframe columns')
    
    ############# TAB 3 ##########################

    with gr.Tab("Chat"):
        gr.Markdown("""<h1><center>ChatGPT 
        ChatBot with Gradio and OpenAI</center></h1>
        """)
        with gr.Row():
            system_prompt = gr.Textbox(value=Init_system_prompt, label='Insert system message here')
            chatgpt_model = gr.Dropdown(choices=["gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613"], value='gpt-3.5-turbo',label='ChatGPT model to use', interactive=True)
            temperature = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, value=0.0, label='temperature')
            max_tokens = gr.Slider(minimum=10, maximum=600, step=10, value=100, label='Max tokens')
        with gr.Row():
            chatbot = gr.Chatbot(label='ChatGPT Chat')
            state = gr.State([])
        with gr.Row():
            msg = gr.Textbox()
        with gr.Row():
            clear = gr.Button("Clear")
        with gr.Row():
            msg_log = gr.Textbox("Tähän tulee message history", label='Message history')
                    
        
    with gr.Accordion("Klikkaa avataksesi ohjeet"):
        gr.Markdown("Ohjeet tulee tänne")


    # TAB 1 (UPLOAD) Interactive elements:
    testi.click(print_files, [files])

    # TAB 2 (CHROMA + PLOT) Interactive elements:
    create_context_btn.click(create_data, files, teksti_contexti)


    # TAB 3 (CHAT) Interactive elements:
    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
        bot, [chatbot, state, system_prompt, teksti_contexti, temperature, max_tokens, chatgpt_model], [chatbot, state, msg_log]
    )
    clear.click(lambda: None, None, chatbot, queue=False).success(init_history, [state, system_prompt], [state, system_prompt, msg_log])


demo.launch(debug=True)