import streamlit as st
from model import GeneralModel
import os
import chess
import chess.engine
import stat
import re


def app():

    # Creating an object of prediction service
    pred = GeneralModel()
    api_key = st.sidebar.text_input("APIkey get it here https://beta.openai.com/account/api-keys", type="password")
    # Using the streamlit cache
    @st.cache
    def eval(fenstring):
        output = ""
        os.chmod("./stockfish_14_x64_popcnt",0o0777)
        engine = chess.engine.SimpleEngine.popen_uci("./stockfish_14_x64_popcnt")
        # Score: PovScore(Cp(+20), WHITE)
        board = chess.Board(fenstring)  
        info = engine.analyse(board, chess.engine.Limit(depth=20),multipv=3)
        # Score: PovScore(Mate(+1), WHITE)  
        engine.quit()
        evalstring = str(info)
        print (evalstring)
        #hacky way to parse best move, need to imprpve
        substrings = evalstring.split('Move.from_uci')

        # Extract the text between the single quotes using a regular expression
        match = re.search(r"'(.*?)'", substrings[1])
        topmove = match.group(1)

        print(topmove)
         # Create a list of lists, where each inner list contains the UCI strings for a single move
       
        stringprompt = 'Based on the chess board position at this fen string ' + fenstring + 'can you give an in depth analysis as to why ' + topmove + ' is the best move to play based on Material, Development, Center-control, King-safety and Pawn-structures if relevant. Also describe any tactics or ideas that we should be thinking about'

        
        return pred.model_prediction(input=stringprompt.strip() , api_key=api_key)
    def process_prompt(input):

        return pred.model_prediction(input=input.strip() , api_key=api_key)

    if api_key:

        # Setting up the Title
        st.title("Stockfish fen eval to GPT-3 top move explanation chess coach")

        # st.write("---")

        s_example = "r2qnrk1/1p1bbppp/p1np4/2p2p2/P1B1P3/2NP1NQ1/1PP3PP/R1B2RK1 w - - 0 12"
        input = st.text_area(
            "input a fen string and get a gpt 3.5 explanation of the top move",
            value=s_example,
            max_chars=1250,
            height=50,
        )

        if st.button("Submit"):
            with st.spinner(text="In progress"):
                report_text = eval(input)
                st.markdown(report_text)
    else:
        st.error("🔑 Please enter API Key")