AI Coach 백엔드 프록시 추가 및 trade 엔드포인트 인증 적용
- POST /api/stock/ai-coach: Anthropic API 프록시 (API 키 서버 보관) - trade/balance, trade/order: ADMIN_API_KEY 헤더 인증 추가 - print() → logging 모듈 전환 (stock-lab) - .env.example: ADMIN_API_KEY, ANTHROPIC_API_KEY, CORS_ALLOW_ORIGINS 추가 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -50,3 +50,12 @@ PGID=1000
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# Windows AI Server (NAS 입장에서 바라본 Windows PC IP)
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WINDOWS_AI_SERVER_URL=http://192.168.45.59:8000
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# Admin API Key (trade/order 등 민감 엔드포인트 보호, 미설정 시 인증 비활성화)
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ADMIN_API_KEY=
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# Anthropic API Key (AI Coach 프록시, 미설정 시 AI Coach 비활성화)
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ANTHROPIC_API_KEY=
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# CORS 허용 도메인 (콤마 구분)
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CORS_ALLOW_ORIGINS=https://gahusb.synology.me,http://localhost:3007,http://localhost:8080
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@@ -1,14 +1,18 @@
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import os
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import json
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import logging
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from datetime import date as date_type
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from typing import Optional
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from fastapi import FastAPI, Query
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from fastapi import FastAPI, Query, Header, Depends, HTTPException
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from fastapi.responses import JSONResponse
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from fastapi.middleware.cors import CORSMiddleware
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import requests
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from apscheduler.schedulers.background import BackgroundScheduler
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from pydantic import BaseModel
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(name)s] %(levelname)s %(message)s")
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logger = logging.getLogger("stock-lab")
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from .db import (
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init_db, save_articles, get_latest_articles,
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add_portfolio_item, get_all_portfolio, get_portfolio_item,
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@@ -37,6 +41,19 @@ scheduler = BackgroundScheduler(timezone=os.getenv("TZ", "Asia/Seoul"))
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# Windows AI Server URL (NAS .env에서 설정)
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WINDOWS_AI_SERVER_URL = os.getenv("WINDOWS_AI_SERVER_URL", "http://192.168.0.5:8000")
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# Admin API Key 인증
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ADMIN_API_KEY = os.getenv("ADMIN_API_KEY", "")
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def verify_admin(x_admin_key: str = Header(None)):
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"""admin/trade 엔드포인트 보호용 API 키 검증"""
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if not ADMIN_API_KEY:
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return # 키 미설정 시 인증 비활성화 (개발 환경)
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if x_admin_key != ADMIN_API_KEY:
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raise HTTPException(status_code=401, detail="Unauthorized")
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# Anthropic API 프록시용 키 (서버 측 보관)
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ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "")
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# 공휴일 목록 로드
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_HOLIDAYS_PATH = os.path.join(os.path.dirname(__file__), "holidays.json")
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try:
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@@ -124,53 +141,87 @@ def trigger_scrap():
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run_scraping_job()
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return {"ok": True}
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# --- Trading API (Windows Proxy) ---
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# --- Trading API (Windows Proxy, 인증 필요) ---
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@app.get("/api/trade/balance")
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@app.get("/api/trade/balance", dependencies=[Depends(verify_admin)])
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def get_balance():
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"""계좌 잔고 조회 (Windows AI Server Proxy)"""
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print(f"[Proxy] Requesting Balance from {WINDOWS_AI_SERVER_URL}...")
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logger.info(f"Requesting Balance from {WINDOWS_AI_SERVER_URL}")
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try:
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resp = requests.get(f"{WINDOWS_AI_SERVER_URL}/trade/balance", timeout=5)
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if resp.status_code != 200:
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print(f"[ProxyError] Balance Error: {resp.status_code} {resp.text}")
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logger.error(f"Balance Error: {resp.status_code}")
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return JSONResponse(status_code=resp.status_code, content=resp.json())
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print("[Proxy] Balance Success")
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return resp.json()
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except requests.JSONDecodeError:
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return JSONResponse(status_code=resp.status_code, content={"error": f"Upstream error {resp.status_code}"})
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except Exception as e:
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print(f"[ProxyError] Connection Failed: {e}")
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return JSONResponse(
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status_code=500,
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content={"error": "Connection Failed", "detail": str(e), "target": WINDOWS_AI_SERVER_URL}
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)
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logger.error(f"Balance Connection Failed: {e}")
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return JSONResponse(status_code=500, content={"error": "Connection Failed"})
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class OrderRequest(BaseModel):
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ticker: str # 종목 코드 (예: "005930")
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action: str # "BUY" or "SELL"
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quantity: int # 주문 수량
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price: int = 0 # 0이면 시장가
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reason: Optional[str] = "Manual Order" # 주문 사유 (AI 기록용)
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ticker: str
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action: str
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quantity: int
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price: int = 0
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reason: Optional[str] = "Manual Order"
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@app.post("/api/trade/order")
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@app.post("/api/trade/order", dependencies=[Depends(verify_admin)])
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def order_stock(req: OrderRequest):
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"""주식 매수/매도 주문 (Windows AI Server Proxy)"""
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print(f"[Proxy] Order Request: {req.dict()} to {WINDOWS_AI_SERVER_URL}...")
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logger.info(f"Order Request: {req.action} {req.ticker} x{req.quantity}")
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try:
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resp = requests.post(f"{WINDOWS_AI_SERVER_URL}/trade/order", json=req.dict(), timeout=10)
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if resp.status_code != 200:
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print(f"[ProxyError] Order Error: {resp.status_code} {resp.text}")
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logger.error(f"Order Error: {resp.status_code}")
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return JSONResponse(status_code=resp.status_code, content=resp.json())
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return resp.json()
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except requests.JSONDecodeError:
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return JSONResponse(status_code=resp.status_code, content={"error": f"Upstream error {resp.status_code}"})
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except Exception as e:
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print(f"[ProxyError] Order Connection Failed: {e}")
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return JSONResponse(
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status_code=500,
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content={"error": "Connection Failed", "detail": str(e), "target": WINDOWS_AI_SERVER_URL}
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logger.error(f"Order Connection Failed: {e}")
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return JSONResponse(status_code=500, content={"error": "Connection Failed"})
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# --- AI Coach 프록시 (API 키를 서버에 보관) ---
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class AiCoachRequest(BaseModel):
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model: str = "claude-haiku-4-5-20251001"
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prompt: str
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max_tokens: int = 1024
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@app.post("/api/stock/ai-coach")
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def ai_coach(req: AiCoachRequest):
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"""AI 포트폴리오 코치 — Anthropic API 프록시 (API 키 서버 보관)"""
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if not ANTHROPIC_API_KEY:
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raise HTTPException(503, "AI Coach not configured (ANTHROPIC_API_KEY missing)")
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allowed_models = {"claude-haiku-4-5-20251001", "claude-sonnet-4-6"}
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model = req.model if req.model in allowed_models else "claude-haiku-4-5-20251001"
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try:
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resp = requests.post(
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"https://api.anthropic.com/v1/messages",
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headers={
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"Content-Type": "application/json",
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"x-api-key": ANTHROPIC_API_KEY,
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"anthropic-version": "2023-06-01",
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},
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json={
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"model": model,
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"max_tokens": req.max_tokens,
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"messages": [{"role": "user", "content": req.prompt}],
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},
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timeout=30,
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)
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if resp.status_code != 200:
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logger.error(f"Anthropic API error: {resp.status_code}")
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return JSONResponse(status_code=resp.status_code, content={"error": "AI API error"})
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return resp.json()
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except requests.Timeout:
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return JSONResponse(status_code=504, content={"error": "AI API timeout"})
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except Exception as e:
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logger.error(f"AI Coach error: {e}")
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return JSONResponse(status_code=500, content={"error": "AI Coach failed"})
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