trend_agent.py

from indicators import calculate_ema

class TrendWatcherAgent:
    def run(self, df):
        # Sort by time (required by ta-lib)
        df = df.sort_index()

        # Calculate EMA20 and EMA50
        df = calculate_ema(df, 20)
        df = calculate_ema(df, 50)

        # Drop rows with NaN due to initial window
        df.dropna(subset=["ema_20", "ema_50"], inplace=True)

        # Get the latest row
        latest = df.iloc[-1]

        # Trend logic
        if latest["ema_20"] > latest["ema_50"]:
            return {"trend": "Uptrend", "confidence": 80}
        else:
            return {"trend": "Downtrend", "confidence": 70}