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| import streamlit as st | |
| from model import GeneralModel | |
| import os | |
| import chess | |
| import chess.engine | |
| import stat | |
| def app(): | |
| # Creating an object of prediction service | |
| pred = GeneralModel() | |
| api_key = st.sidebar.text_input("APIkey (current project not working)", type="password") | |
| # Using the streamlit 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() | |
| #parse info eventually but lets just do it all as a test | |
| evalstring = str(info) | |
| stringprompt = 'Based on the chess board position at this fen string ' + fenstring + 'can you give an in depth analysis as to why c3d5 is the best move to play ' | |
| 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 to GPT-3 strong move explination coach (currently not working)") | |
| # st.write("---") | |
| s_example = "I will input chess fen strings and you reply back with the top three moves I should do next and why I should do each move. you also should evaluate my opponents play r2qnrk1/1p1bbppp/p1np4/2p2p2/P1B1P3/2NP1NQ1/1PP3PP/R1B2RK1 w - - 0 12" | |
| input = st.text_area( | |
| "Use the example below or write your own text", | |
| 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") |