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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import requests
import json
import time
import os
from datetime import datetime, timedelta
try:
import aiohttp
except ImportError:
aiohttp = None
from modules.config import Config
class KISClient:
"""
한국투자증권 (Korea Investment & Securities) REST API Client
"""
def __init__(self, is_virtual=None):
# Config에서 설정 로드
self.app_key = Config.KIS_APP_KEY
self.app_secret = Config.KIS_APP_SECRET
self.cano = Config.KIS_ACCOUNT[:8]
self.acnt_prdt_cd = Config.KIS_ACCOUNT[-2:] # "01" 등
# 가상/실전 모드 설정
if is_virtual is None:
self.is_virtual = Config.KIS_IS_VIRTUAL
else:
self.is_virtual = is_virtual
self.base_url = Config.KIS_BASE_URL
self.access_token = None
self.token_expired = None
self.last_req_time = 0
# 토큰 파일 경로 (영구 저장용)
self.token_file = os.path.join(Config.DATA_DIR, "kis_token.json")
self.load_token() # 초기화 시 토큰 로드 시도
def _safe_int(self, val):
"""안전한 int 변환"""
try:
if not val:
return 0
return int(str(val).strip())
except:
return 0
def _throttle(self):
"""API 요청 속도 제한 (초당 2회 이하로 제한)"""
# 모의투자는 Rate Limit이 매우 엄격함 (초당 2~3회 권장)
min_interval = 0.5 # 0.5초 대기 (초당 2회)
now = time.time()
elapsed = now - self.last_req_time
if elapsed < min_interval:
time.sleep(min_interval - elapsed)
self.last_req_time = time.time()
def load_token(self):
"""파일에서 토큰 로드"""
if os.path.exists(self.token_file):
try:
with open(self.token_file, "r", encoding="utf-8") as f:
data = json.load(f)
# 만료 시간 체크
expire_str = data.get("expired_at")
if expire_str:
expire_dt = datetime.strptime(expire_str, "%Y-%m-%d %H:%M:%S")
if datetime.now() < expire_dt:
self.access_token = data.get("access_token")
self.token_expired = expire_dt
print(f"📂 [KIS] Saved Token Loaded (Expires: {expire_str})")
except Exception as e:
print(f"⚠️ Failed to load token file: {e}")
def save_token(self):
"""토큰 파일 저장"""
if not self.access_token or not self.token_expired:
return
try:
data = {
"access_token": self.access_token,
"expired_at": self.token_expired.strftime("%Y-%m-%d %H:%M:%S")
}
with open(self.token_file, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2)
except Exception as e:
print(f"⚠️ Failed to save token file: {e}")
def _get_headers(self, tr_id=None):
"""공통 헤더 생성"""
headers = {
"Content-Type": "application/json; charset=utf-8",
"authorization": f"Bearer {self.access_token}",
"appkey": self.app_key,
"appsecret": self.app_secret,
}
if tr_id:
headers["tr_id"] = tr_id
return headers
def ensure_token(self, force=False):
"""접근 토큰 발급 (OAuth 2.0) 및 유효성 관리"""
# 토큰이 있고, 만료 시간이 아직 안 지났으면 재사용
if not force and self.access_token and self.token_expired:
if datetime.now() < self.token_expired:
return
# 앱키 확인
if not self.app_key or not self.app_secret:
print("❌ [KIS] App Key or Secret is missing!")
return
url = f"{self.base_url}/oauth2/tokenP"
payload = {
"grant_type": "client_credentials",
"appkey": self.app_key,
"appsecret": self.app_secret
}
try:
print(f"🔑 [KIS] 토큰 발급 요청: {url}")
res = requests.post(url, json=payload, timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
self.access_token = data.get('access_token')
# 만료 시간 설정
expires_in = int(data.get('expires_in', 86400))
self.token_expired = datetime.now() + timedelta(seconds=expires_in - 60)
# 파일 저장
self.save_token()
print(f"✅ [KIS] 토큰 발급 성공 (만료: {self.token_expired.strftime('%Y-%m-%d %H:%M:%S')})")
except Exception as e:
# 1분 제한 에러 핸들링 (EGW00133)
retry = False
if isinstance(e, requests.exceptions.RequestException) and e.response is not None:
err_text = e.response.text
print(f"📄 [KIS Error]: {err_text}")
if "EGW00133" in err_text:
print("⏳ [KIS] Rate Limit Hit (1 min). Waiting 65s...")
time.sleep(65) # 1분 대기
retry = True
if retry:
# 재귀 호출 (한 번만)
self.ensure_token()
return
print(f"❌ [KIS] 토큰 발급 실패: {e}")
self.access_token = None
raise e
def get_hash_key(self, datas):
"""주문 시 필요한 Hash Key 생성 (Koreainvestment header 특화)"""
url = f"{self.base_url}/uapi/hashkey"
headers = {
"content-type": "application/json; charset=utf-8",
"appkey": self.app_key,
"appsecret": self.app_secret
}
try:
res = requests.post(url, headers=headers, json=datas, timeout=Config.HTTP_TIMEOUT)
return res.json()["HASH"]
except Exception as e:
print(f"❌ Hash Key 생성 실패: {e}")
return None
def _request_api(self, method, endpoint, tr_id, params=None, data=None, use_hash=False):
"""API 요청 공통 핸들러 (토큰 만료 시 자동 갱신)"""
self._throttle()
self.ensure_token()
url = f"{self.base_url}/{endpoint}"
headers = self._get_headers(tr_id)
if use_hash and data:
hash_key = self.get_hash_key(data)
if hash_key:
headers["hashkey"] = hash_key
try:
if method == "GET":
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
else:
res = requests.post(url, headers=headers, json=data,
timeout=Config.HTTP_TIMEOUT)
# 토큰 만료 체크 (500 에러 or msg_cd 확인)
is_token_error = False
try:
# KIS는 토큰 만료 시 500을 주거나 200/403 등과 함께 msg_cd로 알려줌
if res.status_code == 500 or res.status_code == 401 or res.status_code == 403:
err_data = res.json()
# EGW00121: 유효하지 않은 토큰, EGW00123: 만료된 토큰
if err_data.get('msg_cd') in ['EGW00121', 'EGW00123']:
is_token_error = True
except:
pass
if is_token_error:
print("🔄 [KIS] Token expired (caught). Refreshing...")
self.ensure_token(force=True)
headers = self._get_headers(tr_id)
if use_hash and data and "hashkey" in headers:
pass # Hash 재활용
if method == "GET":
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
else:
res = requests.post(url, headers=headers, json=data,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
return res.json()
except Exception as e:
print(f"❌ [KIS] API Request Failed: {url} | {e}")
if isinstance(e, requests.exceptions.RequestException) and e.response is not None:
print(f"📄 [KIS Error Body]: {e.response.text}")
raise e
def get_balance(self):
"""주식 잔고 조회"""
tr_id = "VTTC8434R" if self.is_virtual else "TTTC8434R"
endpoint = "uapi/domestic-stock/v1/trading/inquire-balance"
# 쿼리 파라미터
params = {
"CANO": self.cano,
"ACNT_PRDT_CD": self.acnt_prdt_cd,
"AFHR_FLPR_YN": "N",
"OFL_YN": "",
"INQR_DVSN": "02",
"UNPR_DVSN": "01",
"FUND_STTL_ICLD_YN": "N",
"FNCG_AMT_AUTO_RDPT_YN": "N",
"PRCS_DVSN": "00",
"CTX_AREA_FK100": "",
"CTX_AREA_NK100": ""
}
try:
data = self._request_api("GET", endpoint, tr_id, params=params)
# 응답 정리
if data['rt_cd'] != '0':
return {"error": data['msg1']}
holdings = []
for item in data['output1']:
if int(item['hldg_qty']) > 0:
holdings.append({
"code": item['pdno'],
"name": item['prdt_name'],
"qty": int(item['hldg_qty']),
"yield": float(item['evlu_pfls_rt']),
"purchase_price": float(item['pchs_avg_pric']), # 매입평균가
"current_price": float(item['prpr']), # 현재가
"profit_loss": int(item['evlu_pfls_amt']) # 평가손익
})
summary = data['output2'][0]
return {
"holdings": holdings,
"total_eval": int(summary['tot_evlu_amt']),
"deposit": int(summary['dnca_tot_amt']),
"today_buy_amt": int(summary.get('thdt_buy_amt', 0)), # 금일매수금액 (T+2 차감 전 당일 집행액)
}
except Exception as e:
return {"error": str(e)}
def order(self, ticker, qty, buy_sell, price=0, order_type="market"):
"""주문
buy_sell: 'BUY' or 'SELL'
order_type: 'market'(시장가), 'limit'(지정가), 'conditional'(조건부지정가)
price: 지정가일 때 주문 가격 (market이면 무시)
"""
self._throttle()
self.ensure_token()
# 모의투자/실전 TR ID 구분
if buy_sell == 'BUY':
tr_id = "VTTC0802U" if self.is_virtual else "TTTC0802U"
else:
tr_id = "VTTC0801U" if self.is_virtual else "TTTC0801U"
# 주문 구분 코드
# 00: 지정가, 01: 시장가, 03: 최유리지정가, 05: 장전시간외, 06: 장후시간외
if order_type == "limit" and price > 0:
ord_dvsn = "00"
ord_unpr = str(int(price))
order_type_str = f"지정가({price:,.0f})"
elif order_type == "conditional" and price > 0:
ord_dvsn = "03" # 최유리지정가
ord_unpr = str(int(price))
order_type_str = f"조건부({price:,.0f})"
else:
ord_dvsn = "01" # 시장가
ord_unpr = "0"
order_type_str = "시장가"
url = f"{self.base_url}/uapi/domestic-stock/v1/trading/order-cash"
datas = {
"CANO": self.cano,
"ACNT_PRDT_CD": self.acnt_prdt_cd,
"PDNO": ticker,
"ORD_DVSN": ord_dvsn,
"ORD_QTY": str(qty),
"ORD_UNPR": ord_unpr
}
headers = self._get_headers(tr_id=tr_id)
hash_key = self.get_hash_key(datas)
if hash_key:
headers["hashkey"] = hash_key
else:
print("⚠️ [KIS] Hash Key 생성 실패 (주문 전송 시도)")
try:
print(f"📤 [KIS] 주문 전송: {buy_sell} {ticker} {qty}ea ({order_type_str})")
res = requests.post(url, headers=headers, json=datas, timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
print(f"📥 [KIS] 주문 응답 코드(rt_cd): {data['rt_cd']}")
print(f"📥 [KIS] 주문 응답 메시지(msg1): {data['msg1']}")
if data['rt_cd'] != '0':
return {"status": False, "msg": data['msg1'], "rt_cd": data['rt_cd']}
return {"status": True, "msg": "주문 전송 완료", "order_no": data['output']['ODNO'], "rt_cd": data['rt_cd']}
except Exception as e:
return {"status": False, "msg": str(e), "rt_cd": "EXCEPTION"}
def get_current_price(self, ticker):
"""현재가 조회"""
self._throttle()
self.ensure_token()
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/inquire-price"
headers = self._get_headers(tr_id="FHKST01010100")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data['rt_cd'] != '0':
return None
return int(data['output']['stck_prpr']) # 현재가
except Exception as e:
print(f"❌ 현재가 조회 실패: {e}")
return None
def _get_daily_ohlcv_by_range(self, ticker, period="D", count=100):
"""기간별시세 API (FHKST03010100) - OHLCV 전체 반환
output2에서 stck_oprc, stck_hgpr, stck_lwpr, stck_clpr, acml_vol 파싱
"""
self._throttle()
self.ensure_token()
end_date = datetime.now().strftime("%Y%m%d")
start_date = (datetime.now() - timedelta(days=int(count * 1.6))).strftime("%Y%m%d")
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
headers = self._get_headers(tr_id="FHKST03010100")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_INPUT_DATE_1": start_date,
"FID_INPUT_DATE_2": end_date,
"FID_PERIOD_DIV_CODE": period,
"FID_ORG_ADJ_PRC": "1"
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data.get('rt_cd') != '0':
return None
output = data.get('output2', [])
if not output:
return None
opens, highs, lows, closes, volumes = [], [], [], [], []
for item in output:
try:
c = int(item.get('stck_clpr', 0) or 0)
o = int(item.get('stck_oprc', 0) or 0)
h = int(item.get('stck_hgpr', 0) or 0)
l = int(item.get('stck_lwpr', 0) or 0)
v = int(item.get('acml_vol', 0) or 0)
if c > 0:
opens.append(o if o > 0 else c)
highs.append(h if h > 0 else c)
lows.append(l if l > 0 else c)
closes.append(c)
volumes.append(v)
except (ValueError, TypeError):
pass
if not closes:
return None
# API는 최신순 → 과거→현재 순으로 변환
opens.reverse(); highs.reverse(); lows.reverse()
closes.reverse(); volumes.reverse()
result = {
'open': opens[-count:],
'high': highs[-count:],
'low': lows[-count:],
'close': closes[-count:],
'volume': volumes[-count:]
}
print(f"[KIS] {ticker} OHLCV: {len(result['close'])}개 ({start_date}~{end_date})")
return result
except Exception as e:
print(f"⚠️ [KIS] OHLCV 조회 실패 ({ticker}): {e}")
return None
def get_daily_ohlcv(self, ticker, period="D", count=100):
"""일별 OHLCV 시세 조회 (기술적 분석 + LSTM 7차원 입력용)
1차: 기간별시세 API OHLCV 파싱 (100일)
2차: 기존 close-only fallback
"""
ohlcv = self._get_daily_ohlcv_by_range(ticker, period, count)
if ohlcv and len(ohlcv['close']) >= 30:
return ohlcv
# fallback: close만 반환 (가짜 OHLCV)
print(f"[KIS] {ticker} OHLCV 실패 → close-only fallback")
prices = self._get_daily_price_by_range(ticker, period, count)
if not prices:
return None
return {
'open': prices, 'high': prices, 'low': prices,
'close': prices, 'volume': []
}
def _get_daily_price_by_range(self, ticker, period="D", count=100):
"""기간별시세 API (FHKST03010100) - 날짜 범위로 최대 100일 데이터 반환
inquire-daily-price(FHKST01010400)가 30일만 반환하는 한계 극복"""
self._throttle()
self.ensure_token()
end_date = datetime.now().strftime("%Y%m%d")
# 영업일 count개 확보를 위해 역일 1.6배 요청 (주말/공휴일 여유)
start_date = (datetime.now() - timedelta(days=int(count * 1.6))).strftime("%Y%m%d")
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
headers = self._get_headers(tr_id="FHKST03010100")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_INPUT_DATE_1": start_date,
"FID_INPUT_DATE_2": end_date,
"FID_PERIOD_DIV_CODE": period,
"FID_ORG_ADJ_PRC": "1"
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data.get('rt_cd') != '0':
return []
# 기간별시세는 output2에 배열로 반환
output = data.get('output2', [])
if not output:
return []
prices = []
for item in output:
clpr = item.get('stck_clpr', '')
if clpr and clpr != '0':
try:
prices.append(int(clpr))
except ValueError:
pass
prices.reverse() # API는 최신순 → 과거→현재 순으로 변환
result = prices[-count:]
print(f"[KIS] {ticker} 기간별시세: {len(result)}"
f"({start_date}~{end_date})")
return result
except Exception as e:
print(f"⚠️ [KIS] 기간별시세 조회 실패 ({ticker}): {e}")
return []
def get_daily_price(self, ticker, period="D", count=100):
"""일별 시세 조회 (기술적 분석 + LSTM용)
1차: 기간별시세 API (100일, LSTM 학습 가능)
2차: 구형 API fallback (30일)
"""
# 1차: 기간별시세 API (FHKST03010100) - 100일
prices = self._get_daily_price_by_range(ticker, period, count)
if prices and len(prices) >= 30:
return prices
# 2차: 구형 API fallback (FHKST01010400) - 30일
print(f"[KIS] {ticker} 기간별시세 실패 → 구형 API(30일) fallback")
self._throttle()
self.ensure_token()
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-price"
headers = self._get_headers(tr_id="FHKST01010400")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_PERIOD_DIV_CODE": period,
"FID_ORG_ADJ_PRC": "1"
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data.get('rt_cd') != '0':
return []
prices = [int(item['stck_clpr']) for item in data['output']
if item.get('stck_clpr')]
prices.reverse()
return prices
except Exception as e:
print(f"❌ 일별 시세 조회 실패 ({ticker}): {e}")
return []
def get_volume_rank(self, limit=5):
"""거래량 상위 종목 조회"""
self._throttle()
self.ensure_token()
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
headers = self._get_headers(tr_id="FHPST01710000")
params = {
"FID_COND_MRKT_DIV_CODE": "J", # 주식, ETF, ETN 전체
"FID_COND_SCR_RSLT_GD_CD": "20171", # 전체
"FID_INPUT_ISCD": "0000", # 전체
"FID_DIV_CLS_CODE": "0", # 0: 전체
"FID_BLNG_CLS_CODE": "0", # 0: 전체
"FID_TRGT_CLS_CODE": "111111111", # 필터링 조건 (이대로 두면 됨)
"FID_TRGT_EXCLS_CLS_CODE": "0000000000", # 제외 조건
"FID_INPUT_PRICE_1": "",
"FID_INPUT_PRICE_2": "",
"FID_VOL_CNT": "",
"FID_INPUT_DATE_1": ""
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data['rt_cd'] != '0':
return []
results = []
for item in data['output'][:limit]:
# 코드는 shtn_iscd, 이름은 hts_kor_isnm
results.append({
"code": item['mksc_shrn_iscd'],
"name": item['hts_kor_isnm'],
"volume": int(item['acml_vol']),
"price": int(item['stck_prpr'])
})
return results
except Exception as e:
print(f"❌ 거래량 순위 조회 실패: {e}")
return []
def buy_stock(self, ticker, qty):
return self.order(ticker, qty, 'BUY')
def get_current_index(self, ticker):
"""지수 현재가 조회 (업종/지수)
ticker: 0001 (KOSPI), 1001 (KOSDAQ), etc.
"""
endpoint = "uapi/domestic-stock/v1/quotations/inquire-index-price"
params = {
"FID_COND_MRKT_DIV_CODE": "U", # U: 업종/지수
"FID_INPUT_ISCD": ticker
}
try:
data = self._request_api("GET", endpoint, "FHKUP03500100", params=params)
if data['rt_cd'] != '0':
return None
o = data['output']
def _f(val): return float(val) if val else 0.0
def _i(val): return int(float(val)) if val else 0
return {
"price": _f(o.get('bstp_nmix_prpr')), # 현재지수
"change": _f(o.get('bstp_nmix_prdy_ctrt')), # 등락률(%)
"change_val": _f(o.get('bstp_nmix_prdy_vrss')), # 전일 대비 포인트
"high": _f(o.get('bstp_nmix_hgpr')), # 장중 고가
"low": _f(o.get('bstp_nmix_lwpr')), # 장중 저가
"prev_close": _f(o.get('prdy_nmix')), # 전일 종가
"volume": _i(o.get('acml_vol')), # 누적 거래량(천주)
"trade_value": _i(o.get('acml_tr_pbmn')), # 누적 거래대금(백만원)
}
except Exception as e:
print(f"❌ 지수 조회 실패({ticker}): {e}")
return None
def sell_stock(self, ticker, qty):
return self.order(ticker, qty, 'SELL')
def get_daily_index_price(self, ticker, period="D"):
"""지수 일별 시세 조회 (Market Stress Index용)"""
endpoint = "uapi/domestic-stock/v1/quotations/inquire-daily-indexchartprice"
# 날짜 계산 (최근 100일)
end_dt = datetime.now().strftime("%Y%m%d")
start_dt = (datetime.now() - timedelta(days=100)).strftime("%Y%m%d")
params = {
"FID_COND_MRKT_DIV_CODE": "U", # U: 업종/지수
"FID_INPUT_ISCD": ticker,
"FID_INPUT_DATE_1": start_dt, # 시작일
"FID_INPUT_DATE_2": end_dt, # 종료일
"FID_PERIOD_DIV_CODE": period,
"FID_ORG_ADJ_PRC": "0" # 수정주가 반영 여부
}
try:
data = self._request_api("GET", endpoint, "FHKUP03500200", params=params)
if data['rt_cd'] != '0':
return []
# output 리스트: [ {bstp_nmix_prpr: 지수, ...}, ... ]
prices = [float(item['bstp_nmix_prpr']) for item in data['output']]
prices.reverse() # 과거 -> 현재
return prices
except Exception as e:
print(f"❌ 지수 일별 시세 조회 실패({ticker}): {e}")
return []
def get_investor_trend(self, ticker):
"""종목별 투자자(외인/기관) 매매동향 조회"""
self._throttle()
self.ensure_token()
url = f"{self.base_url}/uapi/domestic-stock/v1/quotations/inquire-investor"
headers = self._get_headers(tr_id="FHKST01010900")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker
}
try:
res = requests.get(url, headers=headers, params=params,
timeout=Config.HTTP_TIMEOUT)
res.raise_for_status()
data = res.json()
if data['rt_cd'] != '0':
return None
trends = []
for item in data['output'][:5]:
trends.append({
"date": item['stck_bsop_date'],
"foreigner": self._safe_int(item.get('frgn_ntby_qty')),
"institutional": self._safe_int(item.get('orgn_ntby_qty')),
"price_change": float(item['prdy_vrss'])
})
return trends
except Exception as e:
print(f"[KIS] 투자자 동향 조회 실패({ticker}): {e}")
return None
class KISAsyncClient:
"""
비동기 KIS API 클라이언트
- aiohttp 기반 HTTP 호출
- 동기 KISClient의 토큰/설정을 공유
- 다중 종목 병렬 수집용
"""
def __init__(self, sync_client):
self.sync = sync_client
self.min_interval = 0.5 # 초당 2회 제한
async def _async_get(self, session, url, headers, params):
"""비동기 GET 요청"""
try:
timeout = aiohttp.ClientTimeout(total=Config.HTTP_TIMEOUT) if aiohttp else None
async with session.get(url, headers=headers, params=params,
timeout=timeout) as resp:
return await resp.json()
except Exception as e:
print(f"[KIS Async] Request failed: {e}")
return None
async def get_daily_price_async(self, ticker):
"""비동기 일별 시세 조회 (close only, 하위 호환)"""
import aiohttp
self.sync.ensure_token()
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-price"
headers = self.sync._get_headers(tr_id="FHKST01010400")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_PERIOD_DIV_CODE": "D",
"FID_ORG_ADJ_PRC": "1"
}
async with aiohttp.ClientSession() as session:
data = await self._async_get(session, url, headers, params)
if data and data.get('rt_cd') == '0':
prices = [int(item['stck_clpr']) for item in data['output']]
prices.reverse()
return prices
return []
async def get_daily_ohlcv_async(self, ticker, count=100):
"""비동기 OHLCV 조회 (기간별시세 API 사용)"""
import aiohttp
from datetime import datetime, timedelta
self.sync.ensure_token()
end_date = datetime.now().strftime("%Y%m%d")
start_date = (datetime.now() - timedelta(days=int(count * 1.6))).strftime("%Y%m%d")
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
headers = self.sync._get_headers(tr_id="FHKST03010100")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_INPUT_DATE_1": start_date,
"FID_INPUT_DATE_2": end_date,
"FID_PERIOD_DIV_CODE": "D",
"FID_ORG_ADJ_PRC": "1"
}
async with aiohttp.ClientSession() as session:
data = await self._async_get(session, url, headers, params)
if data and data.get('rt_cd') == '0':
output = data.get('output2', [])
opens, highs, lows, closes, volumes = [], [], [], [], []
for item in output:
try:
c = int(item.get('stck_clpr', 0) or 0)
if c > 0:
opens.append(int(item.get('stck_oprc', 0) or c))
highs.append(int(item.get('stck_hgpr', 0) or c))
lows.append(int(item.get('stck_lwpr', 0) or c))
closes.append(c)
volumes.append(int(item.get('acml_vol', 0) or 0))
except (ValueError, TypeError):
pass
if closes:
opens.reverse(); highs.reverse(); lows.reverse()
closes.reverse(); volumes.reverse()
return {
'open': opens[-count:], 'high': highs[-count:],
'low': lows[-count:], 'close': closes[-count:],
'volume': volumes[-count:]
}
return None
async def get_investor_trend_async(self, ticker):
"""비동기 투자자 동향 조회"""
import aiohttp
self.sync.ensure_token()
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-investor"
headers = self.sync._get_headers(tr_id="FHKST01010900")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker
}
async with aiohttp.ClientSession() as session:
data = await self._async_get(session, url, headers, params)
if data and data.get('rt_cd') == '0':
trends = []
for item in data['output'][:5]:
trends.append({
"date": item['stck_bsop_date'],
"foreigner": self.sync._safe_int(item.get('frgn_ntby_qty')),
"institutional": self.sync._safe_int(item.get('orgn_ntby_qty')),
"price_change": float(item['prdy_vrss'])
})
return trends
return None
async def get_daily_prices_batch(self, tickers):
"""여러 종목의 일별 시세(close only)를 병렬로 조회 (하위 호환)"""
import aiohttp
import asyncio
self.sync.ensure_token()
results = {}
async with aiohttp.ClientSession() as session:
tasks = []
for i, ticker in enumerate(tickers):
if i > 0:
await asyncio.sleep(self.min_interval)
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-price"
headers = self.sync._get_headers(tr_id="FHKST01010400")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_PERIOD_DIV_CODE": "D",
"FID_ORG_ADJ_PRC": "1"
}
tasks.append((ticker, self._async_get(session, url, headers, params)))
for ticker, task in tasks:
data = await task
if data and data.get('rt_cd') == '0':
prices = [int(item['stck_clpr']) for item in data['output']]
prices.reverse()
results[ticker] = prices
else:
results[ticker] = []
return results
async def get_daily_ohlcv_batch(self, tickers, count=100):
"""여러 종목의 OHLCV를 병렬로 조회 (기간별시세 API)"""
import aiohttp
import asyncio
from datetime import datetime, timedelta
self.sync.ensure_token()
results = {}
end_date = datetime.now().strftime("%Y%m%d")
start_date = (datetime.now() - timedelta(days=int(count * 1.6))).strftime("%Y%m%d")
async with aiohttp.ClientSession() as session:
tasks = []
for i, ticker in enumerate(tickers):
if i > 0:
await asyncio.sleep(self.min_interval)
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
headers = self.sync._get_headers(tr_id="FHKST03010100")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker,
"FID_INPUT_DATE_1": start_date,
"FID_INPUT_DATE_2": end_date,
"FID_PERIOD_DIV_CODE": "D",
"FID_ORG_ADJ_PRC": "1"
}
tasks.append((ticker, self._async_get(session, url, headers, params)))
for ticker, task in tasks:
data = await task
if data and data.get('rt_cd') == '0':
output = data.get('output2', [])
opens, highs, lows, closes, volumes = [], [], [], [], []
for item in output:
try:
c = int(item.get('stck_clpr', 0) or 0)
if c > 0:
opens.append(int(item.get('stck_oprc', 0) or c))
highs.append(int(item.get('stck_hgpr', 0) or c))
lows.append(int(item.get('stck_lwpr', 0) or c))
closes.append(c)
volumes.append(int(item.get('acml_vol', 0) or 0))
except (ValueError, TypeError):
pass
if closes:
opens.reverse(); highs.reverse(); lows.reverse()
closes.reverse(); volumes.reverse()
results[ticker] = {
'open': opens[-count:], 'high': highs[-count:],
'low': lows[-count:], 'close': closes[-count:],
'volume': volumes[-count:]
}
else:
results[ticker] = None
else:
results[ticker] = None
return results
async def get_investor_trends_batch(self, tickers):
"""여러 종목의 투자자 동향을 병렬로 조회"""
import aiohttp
import asyncio
self.sync.ensure_token()
results = {}
async with aiohttp.ClientSession() as session:
tasks = []
for i, ticker in enumerate(tickers):
if i > 0:
await asyncio.sleep(self.min_interval)
url = f"{self.sync.base_url}/uapi/domestic-stock/v1/quotations/inquire-investor"
headers = self.sync._get_headers(tr_id="FHKST01010900")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": ticker
}
tasks.append((ticker, self._async_get(session, url, headers, params)))
for ticker, task in tasks:
data = await task
if data and data.get('rt_cd') == '0':
trends = []
for item in data['output'][:5]:
trends.append({
"date": item['stck_bsop_date'],
"foreigner": self.sync._safe_int(item.get('frgn_ntby_qty')),
"institutional": self.sync._safe_int(item.get('orgn_ntby_qty')),
"price_change": float(item['prdy_vrss'])
})
results[ticker] = trends
else:
results[ticker] = None
return results

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"""
통합 LLM 클라이언트 — Gemini 2.5 Flash (Primary) + Ollama (Fallback)
설계 원칙:
- OllamaManager.request_inference(prompt) 와 동일한 인터페이스 유지
→ process.py, ai_council.py 코드 변경 최소화
- Gemini 실패(네트워크, Rate Limit) 시 자동으로 로컬 Ollama 폴백
- 15 RPM 제한 준수를 위한 자동 스로틀링
- VRAM 충돌 없음 (외부 API 호출이므로 LSTM 학습과 간섭 없음)
Rate Limit (Gemini 2.5 Flash 무료 티어):
- 15 RPM, 1,500 RPD (봇 필요량 ~240/일 → 여유 6배)
추가 패키지 불필요:
- requests (이미 설치됨) 기반 REST API 직접 호출
"""
import time
import requests
import json
from modules.config import Config
class GeminiLLMClient:
"""
Gemini API 클라이언트
사용법:
client = GeminiLLMClient()
result = client.request_inference(prompt) # str | None
"""
_GENERATE_URL = (
"https://generativelanguage.googleapis.com/v1beta/models"
"/{model}:generateContent?key={key}"
)
# 15 RPM → 최소 4초 간격 (여유 0.1초 추가)
_MIN_INTERVAL = 4.1
# 클래스 변수: 같은 프로세스 내 재생성 시에도 마지막 호출 시각 유지
# (워커 OOM 재시작 후 싱글톤 교체 시에도 스로틀 유효)
_class_last_call_ts: float = 0.0
def __init__(self):
self.api_key = Config.GEMINI_API_KEY
self.model = Config.GEMINI_MODEL
self._ollama = None # Ollama 폴백 (lazy init)
self._use_gemini = bool(self.api_key)
if self._use_gemini:
print(f"✅ [LLMClient] Primary: Gemini {self.model}")
else:
print("⚠️ [LLMClient] GEMINI_API_KEY 미설정 → Ollama 전용 모드")
# ── 내부 헬퍼 ────────────────────────────────────────────────────────────
def _throttle(self):
"""15 RPM 제한 준수 — 최소 호출 간격 강제 대기 (클래스 공유 타임스탬프)"""
elapsed = time.time() - GeminiLLMClient._class_last_call_ts
if elapsed < self._MIN_INTERVAL:
time.sleep(self._MIN_INTERVAL - elapsed)
def _call_gemini(self, prompt: str) -> str | None:
"""
Gemini REST API 단일 호출
설정:
- systemInstruction: JSON 전용 응답 강제
- thinkingBudget=0: 내부 추론 비활성 (속도 1.5초 / 토큰 절약)
- maxOutputTokens=512: 200은 thinking 소모로 잘리므로 여유 확보
"""
self._throttle()
url = self._GENERATE_URL.format(model=self.model, key=self.api_key)
payload = {
"system_instruction": {
"parts": [{"text": (
"You are a Korean stock market analyst. "
"Respond with valid JSON only. "
"No markdown, no code blocks, no explanations."
)}]
},
"contents": [{"parts": [{"text": prompt}]}],
"generationConfig": {
"maxOutputTokens": 512, # 200→512 (thinking 비활성 후 실제 응답 공간 확보)
"temperature": 0.1, # 결정론적 출력
"thinkingConfig": {"thinkingBudget": 0}, # 내부 추론 끔 (속도↑, 토큰↓)
},
}
try:
resp = requests.post(url, json=payload, timeout=30)
GeminiLLMClient._class_last_call_ts = time.time()
# Rate Limit 초과
if resp.status_code == 429:
print("[LLMClient] Gemini Rate Limit (429) → Ollama 폴백")
return None
resp.raise_for_status()
data = resp.json()
# thinking 파트 제외, 실제 텍스트 파트만 결합
candidate = data.get("candidates", [{}])[0]
parts = candidate.get("content", {}).get("parts", [])
text = "".join(
p.get("text", "") for p in parts
if "text" in p and not p.get("thought")
).strip()
return text if text else None
except requests.exceptions.Timeout:
print("[LLMClient] Gemini Timeout (30s) → Ollama 폴백")
return None
except Exception as e:
print(f"[LLMClient] Gemini Error: {e} → Ollama 폴백")
return None
def _get_ollama(self):
"""Ollama 폴백 인스턴스 (lazy init — 필요할 때만 로드)"""
if self._ollama is None:
from modules.services.ollama import OllamaManager
self._ollama = OllamaManager()
# Ollama 실행 여부 사전 확인 (WinError 10061 조기 감지)
try:
requests.get(
f"{Config.OLLAMA_API_URL}/api/tags",
timeout=3,
)
except Exception:
print(
f"❌ [LLMClient] Ollama 미실행 (localhost:11434 연결 거부) — "
f"`ollama serve` 명령으로 Ollama를 시작하세요."
)
return self._ollama
# ── 공개 인터페이스 ───────────────────────────────────────────────────────
def request_inference(self, prompt: str, context_data=None) -> str | None:
"""
LLM 추론 요청 — OllamaManager.request_inference()와 동일한 시그니처
순서:
1) GEMINI_API_KEY 있음 → Gemini API 호출
2) Gemini 실패(에러/타임아웃/Rate Limit) → Ollama 로컬 폴백
3) GEMINI_API_KEY 없음 → 바로 Ollama 사용
"""
if self._use_gemini:
result = self._call_gemini(prompt)
if result is not None:
return result
# Gemini 실패 → Ollama 폴백
print("[LLMClient] Ollama 폴백 시도 중...")
return self._get_ollama().request_inference(prompt, context_data)
# ── OllamaManager 호환 메서드 (ai_council, evaluator 등에서 사용) ─────────
def check_vram(self) -> float:
"""VRAM 사용량 반환 (Ollama 측 정보, Gemini 호출 시엔 무관)"""
if self._ollama:
return self._ollama.check_vram()
return 0.0
def get_gpu_status(self) -> dict:
"""GPU 상태 반환 (OllamaManager 호환)"""
return self._get_ollama().get_gpu_status()
def unload_model(self):
"""Ollama 모델 언로드 (LSTM 학습 전 호출용, Gemini는 무작동)"""
if self._ollama:
try:
requests.post(
f"{Config.OLLAMA_API_URL}/api/generate",
json={"model": Config.OLLAMA_MODEL, "keep_alive": 0},
timeout=5,
)
except Exception:
pass
# ── 워커 프로세스 전역 싱글톤 ─────────────────────────────────────────────────
_llm_client: GeminiLLMClient | None = None
def get_llm_client() -> GeminiLLMClient:
"""
워커 프로세스 내 GeminiLLMClient 싱글톤 반환
process.py에서 기존 get_ollama() 대신 이 함수를 사용:
ollama = get_llm_client()
result = ollama.request_inference(prompt)
"""
global _llm_client
if _llm_client is None:
_llm_client = GeminiLLMClient()
return _llm_client

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import time
import requests
import xml.etree.ElementTree as ET
from typing import Optional
def _parse_items(root, max_items):
"""RSS item → [{title, url, pub_date, source}]"""
out = []
for item in root.findall(".//item")[:max_items]:
t = item.find("title")
l = item.find("link")
p = item.find("pubDate")
title = (t.text or "").strip() if t is not None else ""
url = (l.text or "").strip() if l is not None else ""
pub = (p.text or "").strip() if p is not None else ""
if not title:
continue
out.append({"title": title, "url": url, "pub_date": pub, "source": "Google News"})
return out
class NewsCollector:
"""동기 뉴스 수집 (Google News RSS)"""
@staticmethod
def get_market_news(query="주식 시장"):
url = f"https://news.google.com/rss/search?q={query}&hl=ko&gl=KR&ceid=KR:ko"
try:
resp = requests.get(url, timeout=5)
root = ET.fromstring(resp.content)
return _parse_items(root, 5)
except Exception as e:
print(f"[News] Collection failed: {e}")
return []
class AsyncNewsCollector:
"""비동기 뉴스 수집 + 5분 캐싱 + (옵션) 스냅샷 저장"""
def __init__(self, snapshot_store=None):
self._cache = None
self._cache_time = 0
self._cache_ttl = 300 # 5분
self._stock_cache = {} # {stock_name: (items, timestamp)}
self._snap = snapshot_store # NewsSnapshotStore | None
def _save_snapshot(self, items, query: str, ticker: Optional[str] = None):
if not self._snap or not items:
return
try:
self._snap.save_many(items, query=query, ticker=ticker)
except Exception as e:
print(f"[News] snapshot 저장 실패: {e}")
def get_market_news(self, query="주식 시장"):
"""동기 인터페이스 (하위 호환)"""
now = time.time()
if self._cache and (now - self._cache_time) < self._cache_ttl:
return self._cache
result = NewsCollector.get_market_news(query)
self._cache = result
self._cache_time = now
self._save_snapshot(result, query=query)
return result
async def get_market_news_async(self, query="주식 시장"):
"""비동기 뉴스 수집 (aiohttp + 캐싱)"""
now = time.time()
if self._cache and (now - self._cache_time) < self._cache_ttl:
return self._cache
try:
import aiohttp
url = f"https://news.google.com/rss/search?q={query}&hl=ko&gl=KR&ceid=KR:ko"
async with aiohttp.ClientSession() as session:
async with session.get(url, timeout=aiohttp.ClientTimeout(total=5)) as resp:
content = await resp.read()
root = ET.fromstring(content)
items = _parse_items(root, 5)
self._cache = items
self._cache_time = now
self._save_snapshot(items, query=query)
return items
except ImportError:
return self.get_market_news(query)
except Exception as e:
print(f"[News Async] Collection failed: {e}")
if self._cache:
return self._cache
return self.get_market_news(query)
async def get_stock_news_async(self, stock_name, max_items=3, ticker: Optional[str] = None):
"""종목별 뉴스 수집 (5분 캐싱)
stock_name: 종목 이름 (e.g. '삼성전자', 'SK하이닉스')
ticker: 스냅샷 저장 시 종목코드 (옵션)
"""
now = time.time()
cached = self._stock_cache.get(stock_name)
if cached and (now - cached[1]) < self._cache_ttl:
return cached[0]
try:
import aiohttp
import urllib.parse
query = urllib.parse.quote(f"{stock_name} 주가")
url = f"https://news.google.com/rss/search?q={query}&hl=ko&gl=KR&ceid=KR:ko"
async with aiohttp.ClientSession() as session:
async with session.get(url, timeout=aiohttp.ClientTimeout(total=5)) as resp:
content = await resp.read()
root = ET.fromstring(content)
items = _parse_items(root, max_items)
self._stock_cache[stock_name] = (items, now)
self._save_snapshot(items, query=f"{stock_name} 주가", ticker=ticker)
return items
except Exception as e:
print(f"[News] 종목 뉴스 수집 실패 ({stock_name}): {e}")
return []
def clear_stock_cache(self):
"""종목 뉴스 캐시 전체 초기화"""
self._stock_cache.clear()

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"""
뉴스 스냅샷 인프라 (v3.2)
목적:
- 수집한 뉴스를 SQLite에 타임스탬프와 함께 영구 저장
- 사후 감성 신호 재검증 (LLM 재호출 / 모델 비교) 가능하게
- 백테스트에서 '그 시점에 실제로 알 수 있던 뉴스'만 사용
스키마:
news_snapshots(
id INTEGER PK,
captured_at TEXT, # ISO8601 (KST) — 수집 시점
query TEXT, # 수집 쿼리 (예: '주식 시장', '삼성전자')
ticker TEXT, # 종목 코드 (종목 뉴스일 때, else NULL)
title TEXT,
url TEXT UNIQUE,
pub_date TEXT, # RSS pubDate 원본
source TEXT DEFAULT 'google_news'
)
sentiment_scores( # 야간 배치로 사후 생성
news_id INTEGER PK,
scored_at TEXT,
model TEXT,
sentiment REAL, # -1.0 ~ 1.0
confidence REAL,
raw_json TEXT,
FOREIGN KEY (news_id) REFERENCES news_snapshots(id)
)
순수 I/O 모듈 — 네트워크 의존성 없음 → unit 테스트 가능.
"""
import os
import sqlite3
from datetime import datetime, timezone, timedelta
from typing import Iterable, List, Optional, Dict
KST = timezone(timedelta(hours=9))
class NewsSnapshotStore:
"""
SQLite 기반 뉴스 스냅샷 저장소.
사용 예:
store = NewsSnapshotStore("data/news_snapshots.db")
store.save_many(items, query="삼성전자", ticker="005930")
rows = store.query_between(start, end, ticker="005930")
"""
def __init__(self, db_path: str):
self.db_path = db_path
os.makedirs(os.path.dirname(db_path) or ".", exist_ok=True)
self._init_schema()
# ──────────────────────────────────────────────
# 스키마
# ──────────────────────────────────────────────
def _connect(self) -> sqlite3.Connection:
conn = sqlite3.connect(self.db_path)
conn.row_factory = sqlite3.Row
return conn
def _init_schema(self):
with self._connect() as conn:
conn.executescript("""
CREATE TABLE IF NOT EXISTS news_snapshots (
id INTEGER PRIMARY KEY AUTOINCREMENT,
captured_at TEXT NOT NULL,
query TEXT NOT NULL,
ticker TEXT,
title TEXT NOT NULL,
url TEXT NOT NULL UNIQUE,
pub_date TEXT,
source TEXT DEFAULT 'google_news'
);
CREATE INDEX IF NOT EXISTS idx_news_captured
ON news_snapshots(captured_at);
CREATE INDEX IF NOT EXISTS idx_news_ticker
ON news_snapshots(ticker, captured_at);
CREATE TABLE IF NOT EXISTS sentiment_scores (
news_id INTEGER PRIMARY KEY,
scored_at TEXT NOT NULL,
model TEXT NOT NULL,
sentiment REAL NOT NULL,
confidence REAL NOT NULL,
raw_json TEXT,
FOREIGN KEY (news_id) REFERENCES news_snapshots(id)
);
""")
# ──────────────────────────────────────────────
# 쓰기
# ──────────────────────────────────────────────
def save_many(self, items: Iterable[Dict], query: str,
ticker: Optional[str] = None,
captured_at: Optional[datetime] = None) -> int:
"""
뉴스 다건 저장. URL 기준 중복 자동 무시.
Args:
items: [{"title": str, "url": str, "pub_date": str?}, ...]
Returns:
실제로 삽입된 행 수
"""
if captured_at is None:
captured_at = datetime.now(KST)
ts = captured_at.isoformat()
rows = []
for it in items:
title = (it.get("title") or "").strip()
url = (it.get("url") or "").strip()
if not title or not url:
continue
rows.append((ts, query, ticker, title, url, it.get("pub_date")))
if not rows:
return 0
with self._connect() as conn:
before = conn.total_changes
conn.executemany(
"INSERT OR IGNORE INTO news_snapshots "
"(captured_at, query, ticker, title, url, pub_date) "
"VALUES (?, ?, ?, ?, ?, ?)",
rows,
)
inserted = conn.total_changes - before
return inserted
def save_sentiment(self, news_id: int, model: str,
sentiment: float, confidence: float,
raw_json: str = "",
scored_at: Optional[datetime] = None) -> None:
if scored_at is None:
scored_at = datetime.now(KST)
with self._connect() as conn:
conn.execute(
"INSERT OR REPLACE INTO sentiment_scores "
"(news_id, scored_at, model, sentiment, confidence, raw_json) "
"VALUES (?, ?, ?, ?, ?, ?)",
(news_id, scored_at.isoformat(), model,
float(sentiment), float(confidence), raw_json),
)
# ──────────────────────────────────────────────
# 읽기
# ──────────────────────────────────────────────
def query_between(self, start: datetime, end: datetime,
ticker: Optional[str] = None,
query: Optional[str] = None) -> List[sqlite3.Row]:
"""특정 기간 내 수집된 뉴스 조회."""
sql = "SELECT * FROM news_snapshots WHERE captured_at >= ? AND captured_at < ?"
args = [start.isoformat(), end.isoformat()]
if ticker is not None:
sql += " AND ticker = ?"
args.append(ticker)
if query is not None:
sql += " AND query = ?"
args.append(query)
sql += " ORDER BY captured_at ASC"
with self._connect() as conn:
return list(conn.execute(sql, args))
def pending_sentiment(self, limit: int = 100) -> List[sqlite3.Row]:
"""아직 감성 점수가 없는 뉴스 반환 (야간 배치용)."""
with self._connect() as conn:
return list(conn.execute(
"""SELECT n.* FROM news_snapshots n
LEFT JOIN sentiment_scores s ON s.news_id = n.id
WHERE s.news_id IS NULL
ORDER BY n.captured_at DESC
LIMIT ?""",
(limit,)
))
def stats(self) -> Dict:
"""DB 통계 (row 수, 감성 커버리지)."""
with self._connect() as conn:
total = conn.execute("SELECT COUNT(*) FROM news_snapshots").fetchone()[0]
scored = conn.execute("SELECT COUNT(*) FROM sentiment_scores").fetchone()[0]
return {
"total_news": total,
"scored": scored,
"pending": total - scored,
"coverage_pct": (scored / total * 100) if total else 0.0,
}

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import requests
import json
import psutil
try:
import pynvml
except ImportError:
pynvml = None
from modules.config import Config
class OllamaManager:
"""
Ollama API 세션 관리 및 메모리 누수 방지 래퍼
- GPU VRAM 사용량 모니터링
- keep_alive 파라미터를 통한 메모리 관리
"""
def __init__(self, model_name=None, base_url=None):
self.model_name = model_name or Config.OLLAMA_MODEL
self.base_url = base_url or Config.OLLAMA_API_URL
self.generate_url = f"{self.base_url}/api/generate"
self.gpu_available = False
try:
if pynvml:
pynvml.nvmlInit()
self.handle = pynvml.nvmlDeviceGetHandleByIndex(0) # 0번 GPU (5070 Ti)
self.gpu_available = True
print("✅ [OllamaManager] NVIDIA GPU Monitoring On")
else:
print("⚠️ [OllamaManager] 'nvidia-ml-py' not installed. GPU monitoring disabled.")
except Exception as e:
print(f"⚠️ [OllamaManager] GPU Init Failed: {e}")
def check_vram(self):
"""현재 GPU VRAM 사용량(GB) 반환"""
if not self.gpu_available:
return 0.0
try:
info = pynvml.nvmlDeviceGetMemoryInfo(self.handle)
used_gb = info.used / 1024**3
return used_gb
except Exception:
return 0.0
def get_gpu_status(self):
"""GPU 종합 상태 반환 (온도, 메모리, 사용률, 이름)"""
if not self.gpu_available:
return {"name": "N/A", "temp": 0, "vram_used": 0, "vram_total": 0, "load": 0}
try:
# GPU 이름
name = pynvml.nvmlDeviceGetName(self.handle)
if isinstance(name, bytes):
name = name.decode('utf-8')
# 온도
temp = pynvml.nvmlDeviceGetTemperature(self.handle, pynvml.NVML_TEMPERATURE_GPU)
# 메모리
mem_info = pynvml.nvmlDeviceGetMemoryInfo(self.handle)
vram_used = mem_info.used / 1024**3
vram_total = mem_info.total / 1024**3
# 사용률
util = pynvml.nvmlDeviceGetUtilizationRates(self.handle)
load = util.gpu
return {
"name": name,
"temp": temp,
"vram_used": round(vram_used, 1),
"vram_total": round(vram_total, 1),
"load": load
}
except Exception as e:
print(f"⚠️ GPU Status Check Failed: {e}")
return {"name": "N/A", "temp": 0, "vram_used": 0, "vram_total": 0, "load": 0}
def is_training_active(self):
"""LSTM 학습 중인지 확인 (GPU 메모리 충돌 방지)"""
try:
import torch
if torch.cuda.is_available():
# VRAM 사용량으로 학습 여부 추정
vram = self.check_vram()
return vram > Config.VRAM_WARNING_THRESHOLD
except Exception:
pass
return False
def request_inference(self, prompt, context_data=None):
"""
Ollama에 추론 요청
- LSTM 학습 중이면 대기 (GPU 메모리 충돌 방지)
"""
# LSTM 학습 중이면 최대 60초 대기
import time as _time
for _ in range(12):
if not self.is_training_active():
break
print("[Ollama] Waiting for LSTM training to finish...")
_time.sleep(5)
vram = self.check_vram()
if vram > Config.VRAM_WARNING_THRESHOLD:
print(f"[OllamaManager] High VRAM Usage ({vram:.1f}GB). Requesting unload.")
try:
# keep_alive=0으로 설정하여 모델 즉시 언로드
requests.post(self.generate_url,
json={"model": self.model_name, "keep_alive": 0}, timeout=5)
except Exception as e:
print(f"Warning: Failed to unload model: {e}")
payload = {
"model": self.model_name,
"prompt": prompt,
"stream": False,
"format": "json",
"options": {
"num_ctx": Config.OLLAMA_NUM_CTX, # 4096 (속도 2배)
"num_predict": Config.OLLAMA_NUM_PREDICT, # 응답 토큰 제한
"temperature": 0.1, # 더 결정론적 (JSON 파싱 안정성)
"num_gpu": 1,
"num_thread": Config.OLLAMA_NUM_THREAD # Config 설정값 (기본 8)
},
"keep_alive": "5m" # 5분 유지 (불필요한 VRAM 점유 줄임)
}
try:
response = requests.post(self.generate_url, json=payload, timeout=90) # 180→90초
response.raise_for_status()
return response.json().get('response')
except requests.exceptions.Timeout:
print(f"❌ Inference Timeout (90s): {self.model_name}")
return None
except Exception as e:
print(f"❌ Inference Error: {e}")
return None

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import requests
import os
import threading
from modules.config import Config
class TelegramMessenger:
def __init__(self, token=None, chat_id=None):
# 환경 변수에서 로드하거나 인자로 받음
self.token = token or Config.TELEGRAM_BOT_TOKEN
self.chat_id = chat_id or Config.TELEGRAM_CHAT_ID
if not self.token or not self.chat_id:
print("⚠️ [Telegram] Token or Chat ID not found.")
def send_message(self, message):
"""별도 스레드로 메시지를 전송하여 메인 루프 블로킹 방지"""
if not self.token or not self.chat_id:
return
def _send():
url = f"https://api.telegram.org/bot{self.token}/sendMessage"
payload = {
"chat_id": self.chat_id,
"text": message,
"parse_mode": "HTML"
}
try:
requests.post(url, json=payload, timeout=5)
except Exception as e:
print(f"⚠️ [Telegram] Error: {e}")
# 스레드 실행 (Fire-and-forget)
threading.Thread(target=_send, daemon=True).start()

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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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@@ -0,0 +1,463 @@
"""
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>")