Update app/schemas.py

app/schemas.py

@@ -1,47 +1,53 @@
-from typing import List, Literal, Optional
-from pydantic import BaseModel, Field
-
-SignalType = Literal["BUY", "SELL", "HOLD", "STRONG BUY", "STRONG SELL"]
-VolatilityLevel = Literal["Low", "Medium", "High"]
-
-class Candle(BaseModel):
-    date: str
-    price: float
-
-class ForecastPoint(BaseModel):
-    day: int
-    price: float
-    lower: float
-    upper: float
-
-class PredictionResponse(BaseModel):
-    ticker: str
-    currentPrice: float
-    targetPrice: float
-    predictedChange: float
-    signal: SignalType
-    rsi: float
-    macd: str
-    volatility: VolatilityLevel
-    historicalPrices: List[Candle]
-    predictedPrice: float
-    forecastData: List[ForecastPoint]
-
-class HistoryResponse(BaseModel):
-    ticker: str
-    historicalPrices: List[Candle]
-
-class ChartForecastPoint(BaseModel):
-    date: str
-    price: float
-    lower: float
-    upper: float
-
-class ChartForecastResponse(BaseModel):
-    ticker: str
-    points: List[ChartForecastPoint]
-
-class HealthResponse(BaseModel):
-    status: str
-    modelLoaded: bool
-    version: str = Field(default="1.0.0")
+from typing import List, Literal
+from pydantic import BaseModel, Field
+
+SignalType = Literal["BUY", "SELL", "HOLD", "STRONG BUY", "STRONG SELL"]
+VolatilityLevel = Literal["Low", "Medium", "High"]
+
+
+class Candle(BaseModel):
+    date: str
+    price: float
+
+
+class ForecastPoint(BaseModel):
+    day: int
+    price: float
+    changePct: float
+
+
+class PredictionResponse(BaseModel):
+    ticker: str
+    currentPrice: float
+    targetPrice: float
+    predictedChange: float
+    signal: SignalType
+    rsi: float
+    macd: str
+    volatility: VolatilityLevel
+    historicalPrices: List[Candle]
+    predictedPrice: float
+    forecastData: List[ForecastPoint]
+
+
+class HistoryResponse(BaseModel):
+    ticker: str
+    historicalPrices: List[Candle]
+
+
+class ChartForecastPoint(BaseModel):
+    date: str
+    price: float
+    lower: float
+    upper: float
+
+
+class ChartForecastResponse(BaseModel):
+    ticker: str
+    points: List[ChartForecastPoint]
+
+
+class HealthResponse(BaseModel):
+    status: str
+    modelLoaded: bool
+    version: str = Field(default="1.0.0")