import gradio as gr
import json 
import os
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import sys

from IPython.display import Markdown, display

def construct_index(directory_path):

    max_input_size = 4096

    num_outputs = 4096

    max_chunk_overlap = 20

    chunk_size_limit = 600


    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)


'''

import tkinter as tk
from llama_index import GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
from IPython.display import Markdown, display



# Define the GUI
class ChatBotGUI:
    def __init__(self, master):
        self.master = master
        master.title("Chat Bot")

        # Create a label and an entry for the question
        self.label = tk.Label(master, text="Ask me anything:")
        self.label.pack()

        self.entry = tk.Entry(master)
        self.entry.pack()

        # Create a button to submit the question
        self.button = tk.Button(master, text="Submit", command=self.submit_question)
        self.button.pack()

        # Create a text box to display the response
        self.textbox = tk.Text(master)
        self.textbox.pack()

    def submit_question(self):
        question = self.entry.get()
        response = ask_ai(question)
        self.textbox.insert(tk.END, "You: " + question + "\n")
        self.textbox.insert(tk.END, "Bot: " + response + "\n\n")
        self.entry.delete(0, tk.END)

# Create an instance of the GUI and start the main loop
root = tk.Tk()
chatbot_gui = ChatBotGUI(root)
root.mainloop()
'''


os.environ["OPENAI_API_KEY"] = "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"
construct_index("data")
def ask_ai(question,openai_api_key):
    
    if openai_api_key == "":
        os.environ["OPENAI_API_KEY"] = "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"
    else:
        os.environ["OPENAI_API_KEY"] = openai_api_key
        construct_index("data")


    
    index = GPTSimpleVectorIndex.load_from_disk('index.json')
    response = index.query(question, response_mode="compact")
    return response.response


api_key = gr.inputs.Textbox(label="Paste OPENAI API Key (Or left it blank to use default api)")
iface = gr.Interface(fn=ask_ai, inputs=["text", api_key], outputs="text", title="Chatbot")


iface.launch()