Update app.py

app.py

@@ -21,7 +21,7 @@ for module_name, pip_name in REQUIRED_PACKAGES.items():
         print(f"✅ {pip_name} установлен!")
 
 # ============================================
-# 👑 TOMIRIS SPACE 29 v2.0 — MACRO SURPRISE ENGINE (Async, Real FRED, Fixed CPI)
+# 👑 TOMIRIS SPACE 29 v2.1 — MACRO SURPRISE ENGINE (Hub-Connected)
 # ============================================
 import os, time, json, logging, asyncio
 from typing import Dict, Any, List, Optional
@@ -37,7 +37,7 @@ logger = logging.getLogger("Space29_MacroSurprise")
 
 # ================= КОНФИГУРАЦИЯ =================
 SYMBOLS = ["XAU/USD", "ETH/USD", "SOL/USD"]
-ARBITER_URL = os.getenv("SPACE18_URL", "https://tomiris-ai-name6-6.hf.space")
+HUB_URL = os.getenv("SPACE17_URL", "https://tomiris-ai-name5-5.hf.space")
 FRED_KEY = os.getenv("FRED_KEY", "faa11c8e2e4beee08c5b966e8b63a513")
 NEWSAPI_KEY = os.getenv("NEWSAPI_KEY", "948c7816beea47baa23b054592472d0e")
 
@@ -91,15 +91,12 @@ async def fetch_fred_series(series_id: str, months: int = 13) -> List[Dict]:
     return []
 
 def get_yoy_change(data: List[Dict], current_month: str) -> Optional[float]:
-    """Считает YoY изменение: текущее значение vs значение 12 месяцев назад (тот же месяц)."""
-    # Ищем записи с нужным месяцем
     current_val = None
     prev_val = None
     for item in data:
         date = item['date']
         if date == current_month:
             current_val = item['value']
-        # Тот же месяц, год назад (YYYY-1)
         year_ago = str(int(date[:4]) - 1) + date[4:]
         if date == year_ago and date[:7] == current_month[:7]:
             prev_val = item['value']
@@ -149,46 +146,41 @@ async def analyze_macro_surprises() -> Dict:
     today = datetime.now(timezone.utc)
     current_month_str = today.strftime("%Y-%m")
 
-    # Загружаем FRED параллельно
     cpi_data = await fetch_fred_series("CPIAUCSL", 13)
     core_cpi_data = await fetch_fred_series("CPILFESL", 13)
     unemp_data = await fetch_fred_series("UNRATE", 6)
-    nfp_data = await fetch_fred_series("PAYEMS", 3)       # Non-Farm Payrolls
-    gdp_data = await fetch_fred_series("GDP", 3)           # GDP (квартальный, но берём последний)
-    ism_data = await fetch_fred_series("NAPM", 3)          # ISM Manufacturing
-    retail_data = await fetch_fred_series("RSAFS", 3)      # Retail Sales
-    durable_data = await fetch_fred_series("DGORDER", 3)   # Durable Goods
+    nfp_data = await fetch_fred_series("PAYEMS", 3)
+    gdp_data = await fetch_fred_series("GDP", 3)
+    ism_data = await fetch_fred_series("NAPM", 3)
+    retail_data = await fetch_fred_series("RSAFS", 3)
+    durable_data = await fetch_fred_series("DGORDER", 3)
     fomc_surprise = await fetch_fomc_surprise()
 
     surprises = []
     total_score = 0.0
     weights = {"CPI_YOY": 0.30, "NFP": 0.25, "FOMC": 0.20, "ISM_MANUF": 0.10, "GDP_QOQ": 0.10, "RETAIL_SALES": 0.05}
 
-    # CPI YoY (корректный)
     cpi_yoy = get_yoy_change(cpi_data, current_month_str)
     if cpi_yoy is not None:
         s = calc_surprise(cpi_yoy, CONSENSUS["CPI_YOY"])
-        impact = s['impact'] * (1 if s['direction'] == 'NEGATIVE' else -0.5)  # высокая инфляция = риск-офф
+        impact = s['impact'] * (1 if s['direction'] == 'NEGATIVE' else -0.5)
         total_score += impact * weights["CPI_YOY"]
         surprises.append({"indicator": "CPI_YOY", "actual": round(cpi_yoy, 2), "consensus": CONSENSUS["CPI_YOY"], "surprise": s})
 
-    # NFP (последний месяц)
     if nfp_data:
-        nfp_actual = nfp_data[0]['value']  # абсолютное значение в тысячах
+        nfp_actual = nfp_data[0]['value']
         s = calc_surprise(nfp_actual, CONSENSUS["NFP"])
-        impact = s['impact'] * (1 if s['direction'] == 'POSITIVE' else -1)  # высокий NFP = риск-он
+        impact = s['impact'] * (1 if s['direction'] == 'POSITIVE' else -1)
         total_score += impact * weights["NFP"]
         surprises.append({"indicator": "NFP", "actual": int(nfp_actual), "consensus": CONSENSUS["NFP"], "surprise": s})
 
-    # GDP (квартальный, берём последний)
     if gdp_data:
-        gdp_actual = gdp_data[0]['value']  # квартальное изменение в %
+        gdp_actual = gdp_data[0]['value']
         s = calc_surprise(gdp_actual, CONSENSUS["GDP_QOQ"])
         impact = s['impact'] * (1 if s['direction'] == 'POSITIVE' else -1)
         total_score += impact * weights["GDP_QOQ"]
         surprises.append({"indicator": "GDP_QOQ", "actual": round(gdp_actual, 2), "consensus": CONSENSUS["GDP_QOQ"], "surprise": s})
 
-    # ISM Manufacturing
     if ism_data:
         ism_actual = ism_data[0]['value']
         s = calc_surprise(ism_actual, CONSENSUS["ISM_MANUF"])
@@ -196,7 +188,6 @@ async def analyze_macro_surprises() -> Dict:
         total_score += impact * weights["ISM_MANUF"]
         surprises.append({"indicator": "ISM_MANUF", "actual": round(ism_actual, 2), "consensus": CONSENSUS["ISM_MANUF"], "surprise": s})
 
-    # Retail Sales
     if retail_data:
         retail_actual = retail_data[0]['value']
         s = calc_surprise(retail_actual, CONSENSUS["RETAIL_SALES"])
@@ -204,7 +195,6 @@ async def analyze_macro_surprises() -> Dict:
         total_score += impact * weights["RETAIL_SALES"]
         surprises.append({"indicator": "RETAIL_SALES", "actual": round(retail_actual, 2), "consensus": CONSENSUS["RETAIL_SALES"], "surprise": s})
 
-    # FOMC
     if fomc_surprise['impact'] != 0:
         total_score += fomc_surprise['impact'] * weights["FOMC"]
         surprises.append({"indicator": "FOMC", "signal": fomc_surprise['direction'], "impact": fomc_surprise['impact']})
@@ -223,7 +213,6 @@ async def analyze_macro_surprises() -> Dict:
         regime, direction = "NEUTRAL", "WAIT"
         confidence = 0.0
 
-    # Сохраняем историю
     SURPRISE_HISTORY.append({
         "timestamp": today.isoformat(),
         "surprise_index": round(surprise_index, 2),
@@ -241,12 +230,30 @@ async def analyze_macro_surprises() -> Dict:
         "total_score": round(total_score, 2)
     }
 
+# ================= ОТПРАВКА В HUB =================
+async def send_signal_to_hub(symbol: str, direction: str, confidence: float):
+    try:
+        await http_client.post(f"{HUB_URL}/signal", json={
+            "space": "space_29_macro_surprise",
+            "symbol": symbol,
+            "direction": direction,
+            "confidence": confidence,
+            "raw": json.dumps({"source": "space_29_macro_surprise"})
+        })
+        logger.info(f"📤 {symbol}: {direction} conf={confidence:.3f} отправлен в Hub")
+    except Exception as e:
+        logger.error(f"Ошибка отправки в Hub: {e}")
+
 # ================= ГЛАВНЫЙ СИГНАЛ =================
 async def get_macro_surprise_signal() -> Dict[str, Any]:
     start = time.time()
     analysis = await analyze_macro_surprises()
     latency = int((time.time() - start) * 1000)
 
+    # Отправка сигналов для всех трёх символов в Hub
+    for sym in SYMBOLS:
+        await send_signal_to_hub(sym, analysis['direction'], analysis['confidence'])
+
     result = {
         "space": "space_29_macro_surprise",
         "timestamp": int(time.time()),
@@ -255,22 +262,11 @@ async def get_macro_surprise_signal() -> Dict[str, Any]:
         "latency_ms": latency
     }
 
-    # Отправка в Arbiter
-    try:
-        await http_client.post(f"{ARBITER_URL}/log_signal", json={
-            "space": "space_29_macro_surprise",
-            "symbol": "XAU/USD",
-            "signal": result["signals"]["XAU/USD"],
-            "surprise_details": analysis
-        })
-    except:
-        pass
-
     logger.info(f"📈 Macro Surprise: Index={analysis['surprise_index']:.1f} Regime={analysis['market_regime']}")
     return result
 
 # ================= FASTAPI =================
-app = FastAPI(title="Tomiris Space 29 v2.0 — Macro Surprise Engine")
+app = FastAPI(title="Tomiris Space 29 v2.1 — Macro Surprise Engine (Hub)")
 
 @app.on_event("startup")
 async def startup(): pass
@@ -280,7 +276,7 @@ async def shutdown(): await http_client.aclose()
 
 @app.get("/health")
 async def health():
-    return {"status": "operational", "version": "2.0", "async": True, "no_mt5": True,
+    return {"status": "operational", "version": "2.1", "hub_connected": True,
             "indicators": list(CONSENSUS.keys()), "history_length": len(SURPRISE_HISTORY)}
 
 @app.get("/consilium")
@@ -303,4 +299,4 @@ if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)
 
-print("🚀 SPACE 29 v2.0 — MACRO SURPRISE ENGINE (REAL FRED, ASYNC) ЗАПУЩЕН!")
+print("🚀 SPACE 29 v2.1 — MACRO SURPRISE ENGINE (Hub-Connected) ЗАПУЩЕН!")