Update app.py

app.py

@@ -16,7 +16,7 @@ SYMBOL = os.getenv("SYMBOL", "VN30F1M")
 RESOLUTION = os.getenv("RESOLUTION", "1")
 COUNTBACK = int(os.getenv("COUNTBACK", "330"))
 UPDATE_SECONDS = int(os.getenv("UPDATE_SECONDS", "10"))
-MIN_BARS = 120
+MIN_BARS = int(os.getenv("MIN_BARS", "50"))
 
 
 @dataclass
@@ -83,7 +83,7 @@ def build_features(data: Dict[str, List[float]]) -> pd.DataFrame:
 
 
 # ===== DATA FETCH =====
-def fetch_data(retries: int = 4) -> Optional[Dict[str, Any]]:
+def fetch_data(retries: int = 4, min_bars: int = MIN_BARS) -> Optional[Dict[str, Any]]:
     now = int(time.time())
     for i in range(retries):
         try:
@@ -103,8 +103,8 @@ def fetch_data(retries: int = 4) -> Optional[Dict[str, Any]]:
                 raise ValueError("Response missing OHLCV keys")
 
             n = len(data["c"])
-            if n < MIN_BARS:
-                raise ValueError(f"Not enough candles ({n}/{MIN_BARS})")
+            if n < min_bars:
+                raise ValueError(f"Not enough candles ({n}/{min_bars})")
 
             return data
         except Exception as exc:
@@ -120,9 +120,26 @@ def compute_signal(data: Dict[str, List[float]]) -> Dict[str, Any]:
     df = build_features(data)
     last = df.iloc[-1]
 
+    if len(df) < 50:
+        return {
+            "signal": "WAIT",
+            "price": float(last["close"]),
+            "confidence": 0.0,
+            "score": 0.0,
+            "reason": f"Warming up: need >=50 candles, got {len(df)}",
+            "risk": None,
+        }
+
     cols = ["ma20", "ma50", "zscore20", "rsi14", "mom10", "atr14", "volatility"]
     if last[cols].isna().any():
-        raise ValueError("Indicators not ready")
+        return {
+            "signal": "WAIT",
+            "price": float(last["close"]),
+            "confidence": 0.0,
+            "score": 0.0,
+            "reason": "Indicators not ready",
+            "risk": None,
+        }
 
     trend_score = 1 if last["close"] > last["ma20"] else -1
     structure_score = 1 if last["ma20"] > last["ma50"] else -1
@@ -179,7 +196,7 @@ def compute_signal(data: Dict[str, List[float]]) -> Dict[str, Any]:
 def update_loop() -> None:
     while True:
         try:
-            data = fetch_data()
+            data = fetch_data(min_bars=10)
             if data is None:
                 raise RuntimeError("Cannot fetch data from feed")
 
@@ -252,7 +269,7 @@ def signal() -> Dict[str, Any]:
 
 @app.get("/forecast")
 def forecast() -> Dict[str, Any]:
-    data = fetch_data()
+    data = fetch_data(min_bars=10)
     if data is None:
         raise HTTPException(status_code=503, detail="Data feed unavailable")
     return compute_signal(data)
@@ -260,7 +277,7 @@ def forecast() -> Dict[str, Any]:
 
 @app.get("/ohlc")
 def ohlc(limit: int = 200) -> List[Dict[str, Any]]:
-    data = fetch_data()
+    data = fetch_data(min_bars=1)
     if data is None:
         raise HTTPException(status_code=503, detail="Data feed unavailable")