refactor: web-ai V1 assets → signal_v1/ (graduation prep)

Atomic mv of root V1 assets (main_server.py + modules/ + data/ +
tests/ + entry scripts + docs + logs) into signal_v1/ subdirectory.
load_dotenv() updated to load web-ai/.env explicitly via Path.

Adds web-ai/CLAUDE.md (workspace guide) and web-ai/start.bat
(signal_v1 entry wrapper). Prepares for signal_v2/ Phase 2.

Tests: signal_v1/tests/unit baseline preserved (no regression).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-16 03:00:11 +09:00
parent 42b91d03cf
commit 7ea1a21487
39 changed files with 722 additions and 691 deletions

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"""
멀티프로세스 방식 - 텔레그램 봇 프로세스
트레이딩 봇과 완전히 분리된 독립 프로세스로 실행
"""
import os
import sys
import time
import multiprocessing
from pathlib import Path
from dotenv import load_dotenv
load_dotenv(Path(__file__).parent.parent.parent.parent / ".env")
def run_telegram_bot_standalone(ipc_lock=None, command_queue=None, shutdown_event=None):
"""텔레그램 봇만 독립적으로 실행"""
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../')))
from modules.services.telegram_bot.server import TelegramBotServer
from modules.utils.ipc import SharedIPC
from modules.utils.process_tracker import ProcessTracker
token = os.getenv("TELEGRAM_BOT_TOKEN")
if not token:
print("[Telegram] TELEGRAM_BOT_TOKEN not found in .env")
sys.exit(1)
ProcessTracker.register("Telegram Bot Standalone")
print(f"[Telegram Bot Process] Starting... (PID: {os.getpid()})")
# IPC 초기화 (shared memory + command queue)
ipc = SharedIPC(lock=ipc_lock, command_queue=command_queue)
conflict_retries = 0
MAX_CONFLICT_RETRIES = 10
while True:
# shutdown 체크
if shutdown_event and shutdown_event.is_set():
print("[Telegram Bot] Shutdown signal received.")
break
try:
bot_server = TelegramBotServer(token, ipc=ipc, shutdown_event=shutdown_event)
# 초기 데이터 로드
try:
instance_data = ipc.get_bot_instance_data()
if instance_data:
bot_server.set_bot_instance(instance_data)
except Exception:
pass
bot_server.run()
if bot_server.should_restart:
print("[Telegram Bot] Restarting instance...")
conflict_retries = 0 # 정상 재시작 시 카운터 리셋
time.sleep(1)
continue
else:
print("[Telegram Bot] Process exiting.")
break
except KeyboardInterrupt:
print("[Telegram Bot] Stopped by user")
break
except Exception as e:
if "Conflict" in str(e):
conflict_retries += 1
if conflict_retries >= MAX_CONFLICT_RETRIES:
print(f"[Telegram Bot] Conflict max retries ({MAX_CONFLICT_RETRIES}) reached. Exiting.")
break
wait_secs = min(5 * conflict_retries, 30)
print(f"[Telegram Bot] Conflict detected. Waiting {wait_secs}s before retry "
f"({conflict_retries}/{MAX_CONFLICT_RETRIES})...")
time.sleep(wait_secs)
continue
else:
print(f"[Telegram Bot] Error: {e}")
import traceback
traceback.print_exc()
break
# 정리
ipc.cleanup()
if __name__ == "__main__":
multiprocessing.freeze_support()
run_telegram_bot_standalone()

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"""
텔레그램 봇 - Shared Memory IPC + 양방향 명령 채널
"""
import os
import asyncio
import logging
import subprocess
from telegram import Update
from telegram.ext import Application, CommandHandler, ContextTypes
# [디버깅] 파일 로깅 추가
log_file = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))),
"telegram_bot.log")
file_handler = logging.FileHandler(log_file, encoding='utf-8')
file_handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
logging.basicConfig(
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
level=logging.INFO,
handlers=[logging.StreamHandler(), file_handler]
)
logging.getLogger("httpx").setLevel(logging.WARNING)
class TelegramBotServer:
def __init__(self, bot_token, ipc=None, shutdown_event=None):
self.application = Application.builder()\
.token(bot_token)\
.concurrent_updates(True)\
.build()
self.bot_instance = None
self.ipc = ipc
self.shutdown_event = shutdown_event
self.is_shutting_down = False
self.should_restart = False
def set_bot_instance(self, bot):
self.bot_instance = bot
def refresh_bot_instance(self):
"""IPC에서 최신 봇 인스턴스 데이터 읽기"""
if self.ipc:
self.bot_instance = self.ipc.get_bot_instance_data()
else:
# fallback: 새 IPC 인스턴스 생성
from modules.utils.ipc import SharedIPC
ipc = SharedIPC()
self.bot_instance = ipc.get_bot_instance_data()
return self.bot_instance is not None
async def start_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
logging.info(f"[Command] /start from user {update.effective_user.id}")
await update.message.reply_text(
"<b>AI Trading Bot Command Center</b>\n"
"명령어 목록:\n"
"/status - 현재 봇 및 시장 상태 조회\n"
"/portfolio - 현재 보유 종목 및 평가액\n"
"/watchlist - 현재 감시 중인 종목 리스트\n"
"/update_watchlist - Watchlist 즉시 업데이트\n"
"/macro - 거시경제 지표 및 시장 위험도\n"
"/system - PC 리소스(CPU/GPU) 상태\n"
"/ai - AI 모델 학습 상태 조회\n"
"/evaluate - 즉시 성과 평가 보고서 생성\n\n"
"<b>[AI 진단 스킬]</b>\n"
"/syshealth - 시스템 종합 건강 진단\n"
"/risk - 리스크 대시보드 (MDD, 연속손절)\n"
"/regime - 코스피 시장 레짐 감지\n"
"/model_health - LSTM 모델 건강 체크\n"
"/weights - 앙상블 가중치 분석\n"
"/postmortem [일수] - 매매 사후 분석 (기본 30일)\n"
"/watchlist_check - 감시 종목 스코어링\n\n"
"<b>[관리 명령어]</b>\n"
"/restart - 메인 봇 재시작 요청\n"
"/exec <code>명령어</code> - 원격 명령어 실행\n"
"/stop - 봇 종료",
parse_mode="HTML"
)
async def status_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
logging.info(f"[Command] /status from user {update.effective_user.id}")
if not self.refresh_bot_instance():
await update.message.reply_text("메인 봇이 실행 중이 아닙니다.")
return
from datetime import datetime
now = datetime.now()
is_market_open = (9 <= now.hour < 15) or (now.hour == 15 and now.minute < 30)
status_msg = "<b>System Status: ONLINE</b>\n"
status_msg += f"<b>Market:</b> {'OPEN' if is_market_open else 'CLOSED'}\n"
macro_warn = self.bot_instance.is_macro_warning_sent
status_msg += f"<b>Macro Filter:</b> {'DANGER (Trading Halted)' if macro_warn else 'SAFE'}\n"
await update.message.reply_text(status_msg, parse_mode="HTML")
async def portfolio_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
if not self.refresh_bot_instance():
await update.message.reply_text("봇 인스턴스가 연결되지 않았습니다.")
return
await update.message.reply_text("잔고를 조회 중입니다...")
try:
balance = self.bot_instance.kis.get_balance()
if "error" in balance:
await update.message.reply_text(f"잔고 조회 실패: {balance['error']}")
return
msg = f"<b>Total Asset:</b> <code>{int(balance['total_eval']):,} KRW</code>\n" \
f"<b>Deposit:</b> <code>{int(balance['deposit']):,} KRW</code>\n\n"
if balance['holdings']:
msg += "<b>[Holdings]</b>\n"
for stock in balance['holdings']:
yld = float(stock.get('yield', 0))
# 상승(빨강), 하락(파랑) 이모지 적용
if yld > 0:
icon = "🔴"
yld_str = f"+{yld}"
elif yld < 0:
icon = "🔵"
yld_str = f"{yld}"
else:
icon = ""
yld_str = f"{yld}"
msg += f"{icon} <b>{stock['name']}</b>: <code>{yld_str}%</code>\n" \
f" (수량: {stock['qty']} / 손익: {stock['profit_loss']:,})\n"
else:
msg += "보유 중인 종목이 없습니다."
await update.message.reply_text(msg, parse_mode="HTML")
except Exception as e:
await update.message.reply_text(f"Error: {str(e)}")
async def watchlist_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
if not self.refresh_bot_instance():
await update.message.reply_text("봇 인스턴스가 연결되지 않았습니다.")
return
target_dict = self.bot_instance.load_watchlist()
discovered = self.bot_instance.discovered_stocks
msg = f"<b>Watchlist: {len(target_dict)} items</b>\n"
for code, name in target_dict.items():
themes = self.bot_instance.theme_manager.get_themes(code)
theme_str = f" ({', '.join(themes)})" if themes else ""
msg += f"• <b>{name}</b>{theme_str}\n"
if discovered:
msg += f"\n<b>Discovered Today ({len(discovered)}):</b>\n"
for code in discovered:
msg += f"- {code}\n"
await update.message.reply_text(msg, parse_mode="HTML")
async def update_watchlist_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""Watchlist 업데이트 - command queue를 통해 메인 봇에 요청"""
if self.ipc and self.ipc.send_command('update_watchlist'):
await update.message.reply_text("Watchlist 업데이트를 메인 봇에 요청했습니다.")
else:
# fallback: 직접 업데이트
await update.message.reply_text("Watchlist를 업데이트하고 있습니다... (30초 소요)")
try:
from modules.services.kis import KISClient
from watchlist_manager import WatchlistManager
from modules.config import Config
temp_kis = KISClient()
mgr = WatchlistManager(temp_kis, watchlist_file=Config.WATCHLIST_FILE)
summary = mgr.update_watchlist_daily()
summary = summary.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
await update.message.reply_text(summary)
except Exception as e:
await update.message.reply_text(f"업데이트 실패: {e}")
async def macro_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
if not self.refresh_bot_instance():
await update.message.reply_text("메인 봇 연결 대기 중...")
return
await update.message.reply_text("거시경제 데이터를 불러옵니다...")
try:
indices = getattr(self.bot_instance.kis, '_macro_indices', {})
if not indices:
await update.message.reply_text("데이터가 아직 수집되지 않았습니다.")
return
msi = float(indices.get('MSI', 0))
if msi >= 50:
risk_status = "🔴 DANGER"
risk_desc = "시장 극도 불안정 - 매수 중단 권고"
elif msi >= 30:
risk_status = "🟡 CAUTION"
risk_desc = "시장 불안정 - 보수적 매매 권고"
else:
risk_status = "🟢 SAFE"
risk_desc = "시장 안정 - 정상 매매 가능"
from datetime import datetime
now_str = datetime.now().strftime("%m/%d %H:%M")
msg = f"<b>거시경제 지표</b> <code>{now_str}</code>\n"
msg += f"━━━━━━━━━━━━━━━━━━\n"
msg += f"<b>Market Risk:</b> {risk_status}\n"
msg += f"<i>{risk_desc}</i>\n\n"
# MSI 상세
msi_bar = "" * int(msi / 10) + "" * (10 - int(msi / 10))
msg += f"<b>Stress Index (MSI):</b> <code>{msi:.1f}/100</code>\n"
msg += f"<code>[{msi_bar}]</code>\n\n"
# 지수 상세
index_order = ["KOSPI", "KOSDAQ", "KOSPI200"]
for k in index_order:
if k not in indices:
continue
v = indices[k]
price = float(v.get('price', 0))
change = float(v.get('change', 0))
change_val = float(v.get('change_val', 0))
high = float(v.get('high', 0))
low = float(v.get('low', 0))
prev_close = float(v.get('prev_close', 0))
volume = int(v.get('volume', 0))
if price == 0:
# 장 마감 후: prev_close(전일 종가)라도 표시
if prev_close > 0:
msg += f"⚫ <b>{k}:</b> <code>{prev_close:,.2f}</code> <i>(전일 종가 기준, 장 마감)</i>\n\n"
else:
msg += f"⚫ <b>{k}:</b> <i>데이터 없음 (장 마감 후)</i>\n\n"
continue
if change > 0:
icon = "🔴"
chg_str = f"+{change:.2f}% (+{change_val:.2f}pt)"
elif change < 0:
icon = "🔵"
chg_str = f"{change:.2f}% ({change_val:.2f}pt)"
else:
icon = ""
chg_str = f"{change:.2f}%"
msg += f"{icon} <b>{k}:</b> <code>{price:,.2f}</code> {chg_str}\n"
if high and low:
msg += f" 고: <code>{high:,.2f}</code> 저: <code>{low:,.2f}</code>"
if prev_close:
msg += f" 전일종가: <code>{prev_close:,.2f}</code>"
msg += "\n"
if volume:
msg += f" 거래량: <code>{volume:,}천주</code>\n"
msg += "\n"
await update.message.reply_text(msg, parse_mode="HTML")
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def system_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
if not self.refresh_bot_instance():
await update.message.reply_text("메인 봇이 실행 중이 아닙니다.")
return
import psutil
# non-blocking CPU 측정
cpu = psutil.cpu_percent(interval=0)
ram = psutil.virtual_memory().percent
top_processes = []
for proc in psutil.process_iter(['pid', 'name', 'cpu_percent']):
try:
proc_info = proc.info
if proc_info['name'] == 'System Idle Process':
continue
top_processes.append(proc_info)
except (psutil.NoSuchProcess, psutil.AccessDenied, psutil.ZombieProcess):
pass
top_processes.sort(key=lambda x: x.get('cpu_percent', 0), reverse=True)
top_3 = top_processes[:3]
gpu_status = self.bot_instance.ollama_monitor.get_gpu_status()
gpu_msg = "N/A"
if gpu_status and gpu_status.get('name') != 'N/A':
gpu_name = gpu_status.get('name', 'GPU')
gpu_msg = f"{gpu_name}\n Temp: {gpu_status.get('temp', 0)}C / " \
f"VRAM: {gpu_status.get('vram_used', 0)}GB / {gpu_status.get('vram_total', 0)}GB"
msg = "<b>PC System Status</b>\n" \
f"<b>CPU:</b> <code>{cpu}%</code>\n" \
f"<b>RAM:</b> <code>{ram}%</code>\n" \
f"<b>GPU:</b> {gpu_msg}\n\n"
if top_3:
msg += "<b>Top CPU Processes:</b>\n"
for i, proc in enumerate(top_3, 1):
proc_name = proc.get('name', 'Unknown')
proc_cpu = proc.get('cpu_percent', 0)
msg += f" {i}. <code>{proc_name}</code> - {proc_cpu:.1f}%\n"
await update.message.reply_text(msg, parse_mode="HTML")
async def ai_status_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
if not self.refresh_bot_instance():
await update.message.reply_text("메인 봇이 실행 중이 아닙니다.")
return
from modules.config import Config
gpu = self.bot_instance.ollama_monitor.get_gpu_status()
if Config.GEMINI_API_KEY:
llm_primary = f"Gemini ({Config.GEMINI_MODEL})"
llm_fallback = f"Ollama ({Config.OLLAMA_MODEL})"
else:
llm_primary = f"Ollama ({Config.OLLAMA_MODEL})"
llm_fallback = None
msg = "<b>AI Model Status</b>\n"
msg += f"* <b>LLM Engine:</b> {llm_primary}\n"
if llm_fallback:
msg += f"* <b>Fallback:</b> {llm_fallback}\n"
msg += f"* <b>LSTM Device:</b> {gpu.get('name', 'GPU')}\n"
if gpu:
msg += f"* <b>GPU Load:</b> <code>{gpu.get('load', 0)}%</code>\n"
msg += f"* <b>VRAM Usage:</b> <code>{gpu.get('vram_used', 0)}GB</code> / {gpu.get('vram_total', 0)}GB"
await update.message.reply_text(msg, parse_mode="HTML")
async def restart_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/restart: 메인 봇에 재시작 명령 전달"""
if self.ipc and self.ipc.send_command('restart'):
await update.message.reply_text(
"<b>메인 봇에 재시작 요청을 전송했습니다.</b>", parse_mode="HTML")
else:
# IPC 명령 실패 시 텔레그램 봇만 재시작
await update.message.reply_text(
"<b>텔레그램 인터페이스를 재시작합니다...</b>", parse_mode="HTML")
self.should_restart = True
self.application.stop_running()
async def stop_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
await update.message.reply_text(
"<b>텔레그램 봇을 종료합니다.</b>", parse_mode="HTML")
self.should_restart = False
self.application.stop_running()
async def exec_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
text = update.message.text.strip()
parts = text.split(maxsplit=1)
if len(parts) < 2:
await update.message.reply_text("사용법: /exec 명령어")
return
command = parts[1]
await update.message.reply_text(f"실행 중: <code>{command}</code>", parse_mode="HTML")
try:
dangerous_keywords = ['rm', 'del', 'format', 'shutdown', 'reboot']
if any(keyword in command.lower() for keyword in dangerous_keywords):
await update.message.reply_text("위험한 명령어는 실행할 수 없습니다.")
return
import platform
is_windows = platform.system() == 'Windows'
if is_windows:
exec_cmd = ['powershell', '-Command', command]
else:
exec_cmd = command
def run_subprocess():
return subprocess.run(
exec_cmd,
shell=not is_windows,
capture_output=True,
text=True,
encoding='utf-8',
errors='replace',
timeout=30,
cwd=os.getcwd()
)
loop = asyncio.get_running_loop()
result = await loop.run_in_executor(None, run_subprocess)
output = result.stdout.strip() if result.stdout else ""
error_output = result.stderr.strip() if result.stderr else ""
if output and error_output:
combined = f"[STDOUT]\n{output}\n\n[STDERR]\n{error_output}"
elif output:
combined = output
elif error_output:
combined = f"[ERROR]\n{error_output}"
else:
combined = "명령어 실행 완료 (출력 없음)"
if len(combined) > 3000:
combined = combined[:3000] + "\n... (Truncated)"
combined = combined.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
await update.message.reply_text(f"<pre>{combined}</pre>", parse_mode="HTML")
except asyncio.TimeoutError:
await update.message.reply_text("명령어 실행 시간 초과 (30초)")
except Exception as e:
await update.message.reply_text(f"실행 오류: {e}")
async def evaluate_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/evaluate: 즉시 성과 평가 보고서 생성 (LLM 분석 포함)"""
await update.message.reply_text(
"📊 성과 평가를 실행합니다...\n"
"<i>LLM 전문가 패널 분석 포함 시 30초~1분 소요됩니다.</i>",
parse_mode="HTML"
)
try:
from modules.utils.performance_db import PerformanceDB
from modules.analysis.evaluator import PerformanceEvaluator
evaluator = PerformanceEvaluator()
loop = asyncio.get_running_loop()
report = await loop.run_in_executor(None, evaluator.generate_weekly_report)
if len(report) > 4000:
report = report[:4000] + "\n... (일부 생략)"
await update.message.reply_text(report, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /evaluate error: {e}")
await update.message.reply_text(f"평가 오류: {e}")
# ──────────────────────────────────────────────
# AI 진단 스킬 명령어 (skill_runner 기반)
# ──────────────────────────────────────────────
async def syshealth_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/syshealth: 시스템 종합 건강 진단"""
await update.message.reply_text("🔍 시스템 건강 진단 중... (최대 30초 소요)", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_syshealth()
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /syshealth error: {e}")
await update.message.reply_text(f"진단 오류: {e}")
async def risk_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/risk: 리스크 대시보드 (MDD, 연속손절, 포지션 집중도)"""
await update.message.reply_text("📊 리스크 데이터 분석 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_risk()
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /risk error: {e}")
await update.message.reply_text(f"리스크 분석 오류: {e}")
async def regime_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/regime: 코스피 시장 레짐 감지"""
await update.message.reply_text("📈 시장 레짐 분석 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_regime()
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /regime error: {e}")
await update.message.reply_text(f"레짐 분석 오류: {e}")
async def model_health_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/model_health: LSTM 모델 건강 체크"""
await update.message.reply_text("🧠 LSTM 모델 체크포인트 스캔 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_model_health()
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /model_health error: {e}")
await update.message.reply_text(f"모델 건강 체크 오류: {e}")
async def weights_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/weights: 앙상블 가중치 분석"""
await update.message.reply_text("⚖️ 앙상블 가중치 분석 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_weights()
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /weights error: {e}")
await update.message.reply_text(f"가중치 분석 오류: {e}")
async def postmortem_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/postmortem [days]: 매매 사후 분석 (기본 30일)"""
args = context.args
days = 30
if args:
try:
days = int(args[0])
days = max(7, min(days, 365))
except ValueError:
pass
await update.message.reply_text(
f"🔬 최근 {days}일 매매 사후 분석 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
result = await skill_runner.run_postmortem(days)
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /postmortem error: {e}")
await update.message.reply_text(f"사후 분석 오류: {e}")
async def watchlist_check_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
"""/watchlist_check: 현재 감시 종목 스코어링"""
await update.message.reply_text("🔎 감시 종목 스코어링 중...", parse_mode="HTML")
try:
from modules.services.telegram_bot import skill_runner
# 현재 watchlist에서 종목 코드 목록 로드
candidates = []
try:
import json, os
from modules.config import Config
wl_path = Config.WATCHLIST_FILE
if os.path.exists(wl_path):
with open(wl_path, encoding="utf-8") as f:
wl_data = json.load(f)
if isinstance(wl_data, dict):
candidates = list(wl_data.keys())
elif isinstance(wl_data, list):
candidates = wl_data
except Exception:
pass
result = await skill_runner.run_watchlist_check(candidates)
for chunk in result:
await update.message.reply_text(chunk, parse_mode="HTML")
except Exception as e:
logging.error(f"[Command] /watchlist_check error: {e}")
await update.message.reply_text(f"스코어링 오류: {e}")
def run(self):
handlers = [
("start", self.start_command),
("status", self.status_command),
("portfolio", self.portfolio_command),
("watchlist", self.watchlist_command),
("update_watchlist", self.update_watchlist_command),
("macro", self.macro_command),
("system", self.system_command),
("ai", self.ai_status_command),
("evaluate", self.evaluate_command),
("syshealth", self.syshealth_command),
("risk", self.risk_command),
("regime", self.regime_command),
("model_health", self.model_health_command),
("weights", self.weights_command),
("postmortem", self.postmortem_command),
("watchlist_check", self.watchlist_check_command),
("restart", self.restart_command),
("stop", self.stop_command),
("exec", self.exec_command)
]
for cmd, func in handlers:
self.application.add_handler(CommandHandler(cmd, func))
async def error_handler(update: object, context: ContextTypes.DEFAULT_TYPE) -> None:
if "Conflict" in str(context.error):
print(f"[Telegram] Conflict detected. Stopping...")
if self.application.running:
await self.application.stop()
return
print(f"[Telegram Error] {context.error}")
self.application.add_error_handler(error_handler)
logging.info("[Telegram] Command Server Started (Shared Memory IPC Mode).")
print("[Telegram] Command Server Started (Shared Memory IPC Mode).")
try:
self.application.run_polling(
allowed_updates=Update.ALL_TYPES,
drop_pending_updates=True
)
except Exception as e:
print(f"[Telegram] Polling Error: {e}")

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"""
Skill Runner — 텔레그램 봇에서 Claude Skills 스크립트를 실행하는 유틸리티
각 스킬 스크립트를 subprocess로 실행하고, 결과를 텔레그램 HTML 메시지로 포맷합니다.
Claude Code 없이도 텔레그램 명령어만으로 분석 리포트를 받을 수 있습니다.
"""
import asyncio
import json
import logging
import os
import subprocess
import sys
from pathlib import Path
from typing import List, Optional
logger = logging.getLogger(__name__)
# 봇 프로젝트 루트 (이 파일 기준 3단계 상위)
BOT_ROOT = Path(__file__).resolve().parent.parent.parent.parent
SKILLS_DIR = BOT_ROOT / ".claude" / "skills"
PYTHON_EXE = sys.executable # 현재 봇과 동일한 Python 인터프리터 사용
def _skill_script(skill_name: str, script_name: str) -> Path:
return SKILLS_DIR / skill_name / "scripts" / script_name
async def _run_script(script_path: Path, extra_args: Optional[list] = None,
timeout: int = 60) -> dict:
"""
스킬 스크립트를 비동기 subprocess로 실행.
--bot-path, --json 플래그를 자동으로 추가.
반환: {"ok": bool, "output": str, "json_data": dict|None}
"""
if not script_path.exists():
return {"ok": False, "output": f"스크립트 없음: {script_path}", "json_data": None}
cmd = [PYTHON_EXE, str(script_path),
"--bot-path", str(BOT_ROOT),
"--json"]
if extra_args:
cmd.extend(extra_args)
try:
loop = asyncio.get_running_loop()
# PYTHONIOENCODING=utf-8: 서브프로세스 stdout에서 유니코드/이모지 출력 허용
_env = {**os.environ, "PYTHONIOENCODING": "utf-8"}
result = await loop.run_in_executor(
None,
lambda: subprocess.run(
cmd,
capture_output=True,
text=True,
encoding="utf-8",
errors="replace",
timeout=timeout,
cwd=str(BOT_ROOT),
env=_env,
)
)
raw_out = result.stdout.strip()
raw_err = result.stderr.strip()
# JSON 파싱 시도
json_data = None
if raw_out:
try:
json_data = json.loads(raw_out)
except json.JSONDecodeError:
pass
if result.returncode != 0 and not raw_out:
return {"ok": False, "output": raw_err or "알 수 없는 오류", "json_data": None}
return {"ok": True, "output": raw_out, "json_data": json_data}
except subprocess.TimeoutExpired:
return {"ok": False, "output": f"실행 시간 초과 ({timeout}초)", "json_data": None}
except Exception as e:
return {"ok": False, "output": str(e), "json_data": None}
def _truncate(text: str, limit: int = 3800) -> str:
if len(text) <= limit:
return text
return text[:limit] + "\n<i>... (일부 생략)</i>"
def _escape_html(text: str) -> str:
return text.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")
# ─────────────────────────────────────────────
# 스킬별 포맷터
# ─────────────────────────────────────────────
def _fmt_syshealth(data: dict) -> str:
ipc = data.get("ipc", {})
gpu = data.get("gpu", {})
token = data.get("kis_token", {})
procs = data.get("processes", {})
ipc_status = ipc.get("status", "?")
ipc_emoji = {"FRESH": "", "NORMAL": "", "STALE": "⚠️",
"EXPIRED": "🔴", "EMPTY": "⚠️", "ERROR": "🔴"}.get(ipc_status, "")
age = ipc.get("age_seconds")
age_str = f"{age}초 전" if age is not None else "알 수 없음"
api_str = "✅ 실행 중" if procs.get("api_running") else "🔴 오프라인"
token_str = "✅ 유효" if token.get("status") == "VALID" else f"🔴 {token.get('status','?')}"
token_env = token.get("env", "?")
vram = gpu.get("vram_used_gb")
vram_str = f"{vram}GB / {gpu.get('vram_total_gb', 16)}GB" if vram else "측정 불가"
cuda_str = "" if gpu.get("cuda_available") else ""
# 로그 에러 집계
logs = data.get("logs", {})
all_errors = {}
for ld in logs.values():
for k, v in ld.get("errors", {}).items():
all_errors[k] = all_errors.get(k, 0) + v
err_lines = "\n".join(
f" ⚠️ {k}: {v}" for k, v in sorted(all_errors.items(), key=lambda x: x[1], reverse=True)
) or " ✅ 없음"
balance = ipc.get("balance")
balance_str = f"\n 잔고: <code>{int(balance):,}원</code>" if balance else ""
wl_count = ipc.get("watchlist_count", 0)
msg = (
f"<b>🔧 시스템 헬스 진단</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"<b>API 서버:</b> {api_str}\n"
f"<b>IPC 상태:</b> {ipc_emoji} {ipc_status} ({age_str})"
f"{balance_str}\n"
f" 감시종목: {wl_count}\n"
f"<b>GPU/CUDA:</b> {cuda_str} VRAM: <code>{vram_str}</code>\n"
f"<b>KIS 토큰:</b> {token_str} ({token_env})\n\n"
f"<b>로그 에러 (최근):</b>\n{err_lines}"
)
return msg
def _fmt_risk(data: dict) -> str:
mdd = data.get("mdd", {})
dl = data.get("daily_loss", {})
cl = data.get("consecutive_losses", {})
cap = data.get("total_capital", 0)
mdd_val = mdd.get("mdd", 0) or 0
mdd_emoji = "" if mdd_val > -5 else ("⚠️" if mdd_val > -10 else "🔴")
dl_ratio = dl.get("ratio", 0) or 0
dl_emoji = "" if dl_ratio < 50 else ("⚠️" if dl_ratio < 75 else "🔴")
cl_count = cl.get("count", 0)
cl_active = cl.get("cooldown_active", False)
cl_emoji = "🚨" if cl_active else ("⚠️" if cl_count >= 2 else "")
msg = (
f"<b>🛡️ 리스크 대시보드</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"<b>총 자산:</b> <code>{int(cap):,}원</code>\n\n"
f"<b>MDD:</b> {mdd_emoji} <code>{mdd_val:.1f}%</code> ({mdd.get('level','?')})\n"
f" 최고점: <code>{int(mdd.get('peak',0) or 0):,}원</code> ({mdd.get('peak_days_ago','?')}일 전)\n"
f" 복구 필요: <code>+{mdd.get('recovery_needed',0):.1f}%</code>\n\n"
f"<b>일일 손실한도:</b> {dl_emoji} {dl_ratio:.0f}% 소진\n"
f" 한도: <code>{int(dl.get('limit',0) or 0):,}원</code> "
f"사용: <code>{int(dl.get('used',0) or 0):,}원</code>\n\n"
f"<b>연속 손절:</b> {cl_emoji} {cl_count}"
)
if cl_active:
msg += f"\n 🚨 매수 중단 중 (재개: {cl.get('resume_time','?')})"
return msg
def _fmt_regime(data: dict) -> str:
regime = data.get("regime", "?")
msi = data.get("msi", {})
params = data.get("recommended_params", {})
ens = params.get("ensemble", {})
data_source = data.get("data_source", "ipc")
source_note = " <i>(IPC 데이터 없음 — 기본값 기반)</i>\n" if data_source == "default" else ""
regime_emoji = {
"BULL_EXTREME": "🔥", "BULL_STRONG": "📈",
"NORMAL": "➡️", "BEAR_WEAK": "📉", "BEAR_STRONG": "🚨"
}.get(regime, "")
status_emoji = {"SAFE": "", "CAUTION": "⚠️", "DANGER": "🚨"}.get(msi.get("status", ""), "")
flags = msi.get("flags", {})
flag_lines = "\n".join(f" {v}" for v in flags.values())
msg = (
f"<b>📊 시장 레짐 분석</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"{source_note}"
f"<b>레짐:</b> {regime_emoji} {regime}\n"
f"<b>MSI:</b> {status_emoji} {msi.get('score','?')}/{msi.get('max','?')} ({msi.get('status','?')})\n\n"
f"<b>지표 현황:</b>\n{flag_lines}\n\n"
f"<b>권고 파라미터:</b>\n"
f" buy_threshold: <code>{params.get('buy_threshold','?')}</code>\n"
f" max_position: <code>{params.get('max_position_ratio','?')}</code>\n"
f" sl_atr_mult: <code>{params.get('sl_atr_multiplier','?')}</code>\n\n"
f"<b>앙상블 권고:</b>\n"
f" tech: <code>{ens.get('tech','?')}</code> "
f"lstm: <code>{ens.get('lstm','?')}</code> "
f"sent: <code>{ens.get('sentiment','?')}</code>\n"
f"<i>다음 점검: {params.get('next_check_days','?')}일 후</i>"
)
return msg
def _fmt_model_health(data: dict) -> str:
models = data.get("models", {})
missing = data.get("missing_models", [])
grade_emoji = {"HEALTHY": "🟢", "WARNING": "🟡", "DEGRADED": "🟠",
"CRITICAL": "🔴", "MISSING": ""}
grade_counts = {}
for info in models.values():
g = info.get("grade", "?")
grade_counts[g] = grade_counts.get(g, 0) + 1
# 우선순위 높은 종목 상위 5개
critical = [(t, i) for t, i in models.items() if i.get("grade") in ("CRITICAL", "DEGRADED")]
critical.sort(key=lambda x: {"CRITICAL": 0, "DEGRADED": 1}.get(x[1].get("grade"), 9))
summary_lines = "\n".join(
f" {grade_emoji.get(g,'?')} {g}: {cnt}"
for g, cnt in grade_counts.items()
)
critical_lines = ""
for t, info in critical[:5]:
critical_lines += f"\n {grade_emoji.get(info['grade'],'?')} {t}: {info.get('reason','?')}"
missing_str = ""
if missing:
missing_str = f"\n\n<b>모델 없는 감시종목:</b>\n " + ", ".join(missing[:5])
if len(missing) > 5:
missing_str += f"{len(missing)-5}"
msg = (
f"<b>🤖 LSTM 모델 건강도</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"<b>체크포인트 {len(models)}개:</b>\n"
f"{summary_lines}"
)
if critical_lines:
msg += f"\n\n<b>조치 필요:</b>{critical_lines}"
msg += missing_str
if not critical and not missing:
msg += "\n\n✅ 모든 모델 정상"
return msg
def _fmt_weights(data: dict) -> str:
current = data.get("current_global", {})
optimal = data.get("optimal_global", {})
health = data.get("ema_health", {})
contribs = data.get("signal_contributions", {})
issues = "\n".join(f" {i}" for i in health.get("issues", []))
health_status = "" if health.get("status") == "OK" else "⚠️"
contrib_lines = ""
for sig, c in contribs.items():
if c.get("total_trades", 0) > 0:
acc = c.get("accuracy", 0)
contrib_lines += f"\n {sig}: 정확도 {acc:.1%} ({c['total_trades']}거래)"
delta_lines = ""
for sig in ["tech", "lstm", "sentiment"]:
cur = current.get(sig, 0)
opt = optimal.get(sig, cur)
diff = round(opt - cur, 3)
arrow = "" if diff > 0 else ("" if diff < 0 else "")
delta_lines += f"\n {sig:12s}: {cur} {arrow} <b>{opt}</b>"
msg = (
f"<b>⚖️ 앙상블 가중치</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"<b>EMA 학습 상태:</b> {health_status}\n{issues}\n"
)
if contrib_lines:
msg += f"\n<b>신호 기여도:</b>{contrib_lines}\n"
msg += f"\n<b>권고 조정:</b>{delta_lines}"
return msg
def _fmt_postmortem(data: dict) -> str:
stats = data.get("basic_stats", {})
combos = data.get("signal_combinations", {})
suggestions = data.get("parameter_suggestions", {})
days = data.get("days", 30)
wr = stats.get("win_rate", 0)
pr = stats.get("profit_ratio", 0)
wr_emoji = "" if wr >= 55 else ("⚠️" if wr >= 50 else "🔴")
pr_emoji = "" if pr >= 2.0 else ("⚠️" if pr >= 1.5 else "🔴")
best_combos = list(combos.items())[:2]
worst_combos = list(combos.items())[-2:]
combo_lines = ""
for k, v in best_combos:
combo_lines += f"\n{k}: 승률 {v['win_rate']}% ({v['trades']}건)"
for k, v in worst_combos:
if v["win_rate"] < 50:
combo_lines += f"\n ⚠️ {k}: 승률 {v['win_rate']}% ({v['trades']}건)"
suggest_lines = ""
for param, s in suggestions.items():
suggest_lines += f"\n {param}: {s.get('current','?')} → <b>{s.get('recommended','?')}</b>"
msg = (
f"<b>📊 매매 사후분석</b> (최근 {days}일)\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"<b>총 거래:</b> {stats.get('total',0)}"
f"승률: {wr_emoji} <code>{wr}%</code>\n"
f"<b>손익비:</b> {pr_emoji} <code>{pr}</code> "
f"Sharpe: <code>{stats.get('sharpe',0)}</code>\n"
f"평균 수익: <code>+{stats.get('avg_win_pct',0)}%</code> "
f"평균 손실: <code>-{stats.get('avg_loss_pct',0)}%</code>"
)
if combo_lines:
msg += f"\n\n<b>신호 조합:</b>{combo_lines}"
if suggest_lines:
msg += f"\n\n<b>파라미터 권고:</b>{suggest_lines}"
return msg
def _fmt_watchlist(data: dict) -> str:
scored = data.get("scored", [])
current = data.get("current_watchlist", [])
r_min, r_max = data.get("recommended_range", (8, 15))
to_add = [s for s in scored if s.get("action") == "편입"]
to_remove = [s for s in scored if s.get("action") == "제거"]
to_keep = [s for s in scored if s.get("action") == "유지" and s.get("in_watchlist")]
to_keep.sort(key=lambda x: x.get("total_score", 0), reverse=True)
add_lines = ""
for s in to_add[:5]:
wr = f" ({s['win_rate']:.0%})" if s.get("win_rate") else ""
add_lines += f"\n{s['ticker']} {s['total_score']}점 — {s.get('theme','?')}{wr}"
remove_lines = ""
for s in to_remove:
remove_lines += f"\n{s['ticker']} {s['total_score']}"
keep_lines = ""
for s in to_keep[:3]:
keep_lines += f"\n{s['ticker']} {s['total_score']}"
final = len(current) - len(to_remove) + len(to_add)
size_ok = "" if r_min <= final <= r_max else "⚠️"
msg = (
f"<b>📋 Watchlist 분석</b>\n"
f"━━━━━━━━━━━━━━━━━━\n"
f"현재 {len(current)}종목 → 최종 {final}종목 {size_ok}\n"
f"권고 규모: {r_min}~{r_max}종목"
)
if add_lines:
msg += f"\n\n<b>편입 추천:</b>{add_lines}"
if remove_lines:
msg += f"\n\n<b>제거 추천:</b>{remove_lines}"
if keep_lines:
msg += f"\n\n<b>상위 유지 종목:</b>{keep_lines}"
return msg
# ─────────────────────────────────────────────
# 공개 API — 텔레그램 핸들러에서 호출
# ─────────────────────────────────────────────
def _to_chunks(text: str, limit: int = 3800) -> List[str]:
"""메시지가 Telegram 4096자 제한을 초과하면 청크로 분할"""
if len(text) <= limit:
return [text]
chunks = []
while text:
chunks.append(text[:limit])
text = text[limit:]
return chunks
async def run_syshealth() -> List[str]:
script = _skill_script("bot-system-health-diagnostics", "health_checker.py")
r = await _run_script(script, timeout=30)
if not r["ok"]:
return [f"⚠️ 시스템 헬스 실행 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_syshealth(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_risk() -> List[str]:
script = _skill_script("auto-trade-risk-manager", "risk_dashboard.py")
r = await _run_script(script, timeout=30)
if not r["ok"]:
return [f"⚠️ 리스크 분석 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_risk(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_regime() -> List[str]:
script = _skill_script("korean-market-regime-detector", "regime_calculator.py")
r = await _run_script(script, timeout=60)
if not r["ok"]:
return [f"⚠️ 레짐 분석 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_regime(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_model_health() -> List[str]:
script = _skill_script("lstm-model-health-monitor", "model_health_report.py")
r = await _run_script(script, timeout=60)
if not r["ok"]:
return [f"⚠️ 모델 건강도 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_model_health(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_weights() -> List[str]:
script = _skill_script("ensemble-weight-optimizer", "weight_optimizer.py")
r = await _run_script(script, timeout=30)
if not r["ok"]:
return [f"⚠️ 가중치 분석 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_weights(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_postmortem(days: int = 30) -> List[str]:
script = _skill_script("trade-post-mortem-analyzer", "post_mortem_report.py")
r = await _run_script(script, extra_args=["--days", str(days)], timeout=30)
if not r["ok"]:
return [f"⚠️ 매매 분석 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_postmortem(r["json_data"]))
if not r["output"].strip():
return [f"<b>📊 매매 사후분석</b> (최근 {days}일)\n━━━━━━━━━━━━━━━━━━\n<i>분석 대상 매매 기록이 없습니다.</i>"]
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")
async def run_watchlist_check(candidates: Optional[List[str]] = None) -> List[str]:
script = _skill_script("watchlist-intelligence-curator", "watchlist_scorer.py")
extra = []
if candidates:
extra = ["--candidates"] + candidates
r = await _run_script(script, extra_args=extra, timeout=30)
if not r["ok"]:
return [f"⚠️ Watchlist 분석 오류:\n<code>{_escape_html(r['output'])}</code>"]
if r["json_data"]:
return _to_chunks(_fmt_watchlist(r["json_data"]))
return _to_chunks(f"<pre>{_escape_html(r['output'])}</pre>")