Update utils/model_inference.py

utils/model_inference.py

@@ -1,9 +1,20 @@
 import datetime
 import numpy as np
-from utils import fetch_forex_data, calculate_technical_indicators
+from utils.fetch_forex_data import fetch_forex_data
+from utils.calculate_technical_indicators import calculate_technical_indicators
 
-# Function to generate forex signals
 def generate_forex_signals(trading_capital, market_risk, timezone):
+    """
+    Generate forex trading signals based on technical indicators.
+
+    Args:
+        trading_capital (float): User's trading capital in USD.
+        market_risk (str): Risk level ("Low", "Medium", "High").
+        timezone (str): User's timezone (e.g., "UTC").
+
+    Returns:
+        dict: Dictionary containing the best signal and all generated signals.
+    """
     # Define the top 10 most popular currency pairs
     currency_pairs = [
         "EUR/USD", "GBP/USD", "USD/JPY", "AUD/USD", "USD/CAD",
@@ -16,14 +27,14 @@ def generate_forex_signals(trading_capital, market_risk, timezone):
         # Fetch historical data for the currency pair
         data = fetch_forex_data(pair, timeframe="15m")
 
-        # Calculate technical indicators (e.g., RSI, MACD, Bollinger Bands)
+        # Calculate technical indicators
         indicators = calculate_technical_indicators(data)
 
         # Generate trade signal
         entry_time = data.index[-1]
         exit_time = entry_time + datetime.timedelta(minutes=15)
 
-        roi = np.random.uniform(10, 20)  # Random ROI between 10% and 20% for alpha signals
+        roi = np.random.uniform(10, 20)  # Random ROI between 10% and 20%
         signal_strength = np.random.uniform(80, 100)  # Random signal strength (80%-100%)
 
         # Calculate Stop-Loss and Take-Profit levels based on risk