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import gradio as gr
from gradio_chessboard import Chessboard
import chess
import chess.engine
import pandas as pd
import os
import uuid
from openai import OpenAI
import time
SYSTEM_KEY = os.getenv("OPENAI_API_KEY")
STOCKFISH_PATH = "/usr/games/stockfish"
def get_client(user_key):
key = user_key.strip() if user_key else SYSTEM_KEY
if not key: return None
return OpenAI(api_key=key)
def _load_lichess_openings(path_prefix="/app/data/lichess_openings/dist/"):
try:
files = [f"{path_prefix}{vol}.tsv" for vol in ("a", "b", "c", "d", "e")]
dfs = []
for fn in files:
if os.path.exists(fn):
df = pd.read_csv(fn, sep="\t", usecols=["eco", "name", "pgn", "uci", "epd"])
dfs.append(df)
if not dfs: return pd.DataFrame()
return pd.concat(dfs, ignore_index=True)
except:
return pd.DataFrame()
OPENINGS_DB = _load_lichess_openings()
def analyze_tactics(board):
fen = board.fen()
pins = []
turn = board.turn
for sq in chess.SQUARES:
piece = board.piece_at(sq)
if piece and piece.color == turn:
if board.is_pinned(turn, sq):
pins.append(chess.square_name(sq))
check = board.is_check()
values = {chess.PAWN: 1, chess.KNIGHT: 3, chess.BISHOP: 3, chess.ROOK: 5, chess.QUEEN: 9}
w_mat = sum(len(board.pieces(pt, chess.WHITE)) * val for pt, val in values.items())
b_mat = sum(len(board.pieces(pt, chess.BLACK)) * val for pt, val in values.items())
analysis = []
if check: analysis.append("KING IN CHECK.")
if pins: analysis.append(f"Pinned pieces at: {', '.join(pins)}.")
analysis.append(f"Material: White {w_mat} vs Black {b_mat}.")
return " ".join(analysis)
def tool_engine_analysis(board, time_limit=0.5):
if board.is_game_over(): return "GAME OVER", "NONE", "NONE"
if not os.path.exists(STOCKFISH_PATH): return "0", "Engine Missing", ""
try:
with chess.engine.SimpleEngine.popen_uci(STOCKFISH_PATH) as engine:
info = engine.analyse(board, chess.engine.Limit(time=time_limit))
score = info["score"].white()
if score.is_mate():
score_val = f"MATE IN {abs(score.mate())}"
else:
score_val = str(score.score())
best_move = info.get("pv", [None])[0]
if best_move:
origin = chess.square_name(best_move.from_square)
dest = chess.square_name(best_move.to_square)
move_uci = f"{origin} -> {dest}"
else:
move_uci = "NO MOVE"
return score_val, move_uci, move_uci
except:
return "N/A", "ANALYSIS ERROR", ""
def tool_ai_play(board, level):
levels = {
"Beginner": {"time": 0.01, "skill": 1, "depth": 1},
"Intermediate": {"time": 0.1, "skill": 8, "depth": 6},
"Advanced": {"time": 0.5, "skill": 15, "depth": 12},
"Grandmaster": {"time": 1.0, "skill": 20, "depth": 18}
}
config = levels.get(level, levels["Beginner"])
try:
with chess.engine.SimpleEngine.popen_uci(STOCKFISH_PATH) as engine:
engine.configure({"Skill Level": config["skill"]})
result = engine.play(board, chess.engine.Limit(time=config["time"], depth=config["depth"]))
return result.move
except:
return None
# --- AUDIO & TRANSCRIPTION ---
def generate_voice(client, text):
if not client or not text: return None
try:
response = client.audio.speech.create(
model="tts-1", voice="onyx", input=text, speed=1.15
)
unique = f"deepblue_{uuid.uuid4()}.mp3"
path = os.path.join("/tmp", unique)
with open(path, "wb") as f:
for chunk in response.iter_bytes():
f.write(chunk)
return path
except:
return None
def transcribe(client, audio_path):
if not client or not audio_path: return None
try:
with open(audio_path, "rb") as f:
t = client.audio.transcriptions.create(model="whisper-1", file=f, language="en")
return t.text
except:
return None
# --- AGENT BRAIN ---
SYSTEM_PROMPT = """
You are DEEP BLUE AI.
PROTOCOL:
1. **COMMAND**: State the optimal move coordinate (e.g., "e2 -> e4").
2. **LOGIC**: Explain WHY using the tactical data provided (e.g., "Pins the Knight," "Avoids Mate").
TONE: Robotic, High-Tech, Concise.
IF PLAYER WINS: "CHECKMATE. SYSTEM SHUTDOWN."
"""
def agent_reasoning(fen, user_api_key, mode="auto", user_audio=None):
client = get_client(user_api_key)
if not client:
return "⚠️ API KEY REQUIRED. Please enter your OpenAI Key in the right column.", None, "AUTH ERROR"
board = chess.Board(fen)
if board.is_game_over():
if board.is_checkmate():
msg = "CHECKMATE. GAME OVER."
msg += " HUMAN VICTORY." if board.turn == chess.BLACK else " SYSTEM VICTORY."
return msg, generate_voice(client, msg), "END"
return "DRAW.", None, "END"
# TOOLS
score, best_move_uci, arrow_visual = tool_engine_analysis(board)
opening = "Unknown"
if not OPENINGS_DB.empty:
match = OPENINGS_DB[OPENINGS_DB["epd"] == board.epd()]
if not match.empty: opening = match.iloc[0]['name']
tactics = analyze_tactics(board)
context = f"""
[SYSTEM TELEMETRY]
Turn: {'White' if board.turn == chess.WHITE else 'Black'}. Score: {score}. Opening: {opening}.
[TACTICS] {tactics}
[OPTIMAL PATH] Move: {best_move_uci}.
"""
if mode == "question" and user_audio:
q = transcribe(client, user_audio)
context += f"\n[USER INPUT]: {q}"
else:
context += "\nINSTRUCTION: Output move and tactical justification."
reply = "Computing..."
try:
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "system", "content": SYSTEM_PROMPT}, {"role": "user", "content": context}]
)
reply = response.choices[0].message.content
except Exception as e:
reply = f"API Error: {e}"
audio = generate_voice(client, reply)
return reply, audio, arrow_visual
# --- UI LOGIC ---
def update_log(new_advice, history_list):
if not new_advice or new_advice == "END": return history_list
history_list.insert(0, f"> {new_advice}")
return history_list
def format_log(history_list):
return "\n\n".join(history_list)
def game_cycle(fen, level, user_key, history_list):
board = chess.Board(fen)
if board.is_game_over():
text, audio, _ = agent_reasoning(fen, user_key)
return fen, text, audio, format_log(history_list), history_list
if board.turn == chess.BLACK:
ai_move = tool_ai_play(board, level)
if ai_move: board.push(ai_move)
text, audio, arrow = agent_reasoning(board.fen(), user_key, mode="auto")
new_hist = update_log(f"OPT: {arrow}", history_list)
return board.fen(), text, audio, format_log(new_hist), new_hist
return fen, "Awaiting Input...", None, format_log(history_list), history_list
def reset_game():
return chess.STARTING_FEN, "SYSTEM RESET.", None, "", []
def ask_agent(fen, user_key, audio, history_list):
text, aud, arrow = agent_reasoning(fen, user_key, mode="question", user_audio=audio)
return text, aud, format_log(history_list), history_list
# --- UI ---
css = """
body { background-color: #020617; color: #e2e8f0; }
.gradio-container { background-color: #020617 !important; border: none; }
#title { color: #0ea5e9; text-align: center; font-family: 'Courier New', monospace; font-size: 4em; font-weight: 800; text-shadow: 0 0 10px rgba(14, 165, 233, 0.5); }
#board { border: 3px solid #0ea5e9; box-shadow: 0 0 30px rgba(14, 165, 233, 0.1); }
button.primary { background-color: #0ea5e9 !important; color: black !important; font-weight: bold; border: none; }
button.secondary { background-color: #1e293b !important; color: #94a3b8 !important; border: 1px solid #334155; }
.feedback { background-color: #0f172a !important; color: #38bdf8 !important; border: 1px solid #1e293b; font-family: 'Consolas', 'Monaco', monospace; }
"""
with gr.Blocks(title="DEEP BLUE", css=css, theme=gr.themes.Base()) as demo:
gr.Markdown("# Coach Deep Blue", elem_id="title")
# API KEY INPUT
api_key_input = gr.Textbox(label="🔑 OpenAI API Key (Optional if System Key set)", placeholder="sk-...", type="password")
level = gr.Dropdown(["Beginner", "Intermediate", "Advanced", "Grandmaster"], value="Beginner", label="OPPONENT DIFFICULTY", interactive=True)
with gr.Row():
with gr.Column(scale=2):
board = Chessboard(elem_id="board", label="Battle Zone", value=chess.STARTING_FEN, game_mode=True, interactive=True)
with gr.Column(scale=1):
btn_reset = gr.Button("INITIALIZE NEW SEQUENCE", variant="secondary")
gr.Markdown("### 📟 SYSTEM OUTPUT")
coach_txt = gr.Textbox(label="Analysis", interactive=False, lines=3, elem_classes="feedback")
coach_audio = gr.Audio(label="Voice", autoplay=True, interactive=False, type="filepath", visible=True)
gr.Markdown("### 📜 STRATEGY LOG")
history_state = gr.State([])
history_display = gr.Textbox(label="Log", interactive=False, lines=6, max_lines=10, elem_classes="feedback")
gr.Markdown("### 🎤 HUMAN INTERFACE")
mic = gr.Audio(sources=["microphone"], type="filepath", show_label=False)
btn_ask = gr.Button("QUERY SYSTEM", variant="primary")
board.move(fn=game_cycle, inputs=[board, level, api_key_input, history_state], outputs=[board, coach_txt, coach_audio, history_display, history_state])
btn_reset.click(fn=reset_game, outputs=[board, coach_txt, coach_audio, history_display, history_state])
btn_ask.click(fn=ask_agent, inputs=[board, api_key_input, mic, history_state], outputs=[coach_txt, coach_audio, history_display, history_state])
mic.stop_recording(fn=ask_agent, inputs=[board, api_key_input, mic, history_state], outputs=[coach_txt, coach_audio, history_display, history_state])
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860, ssr_mode=False, allowed_paths=["/tmp"]) |