Merge pull request #2 from VishwamAI/fix-workflow-issues-pr

Fix workflow issues pr

.github/workflows/ci.yml

@@ -11,15 +11,15 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python 3.8
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: 3.8
 
     - name: Cache dependencies
-      uses: actions/cache@v2
+      uses: actions/cache@v3
       with:
         path: ~/.cache/pip
         key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
@@ -31,38 +31,33 @@ jobs:
         python -m pip install --upgrade pip
         pip install -r requirements.txt
     
+    - name: Install flake8
+      run: pip install flake8
+
     - name: Run linting
-      run: |
-        pip install flake8
-        flake8 .
+      run: flake8 .
 
     - name: Run tests
       run: |
         pip install pytest pytest-cov
-        pytest --cov=your_module_name_here  # Replace with the actual module name
+        pytest --cov=src
     
     - name: Upload coverage results
       if: success()
-      uses: actions/upload-artifact@v2
+      uses: actions/upload-artifact@v3
       with:
         name: coverage-report
         path: coverage.xml
 
-  lint:
-    runs-on: ubuntu-latest
-
-    steps:
-    - uses: actions/checkout@v2
-
-    - name: Set up Python 3.8
-      uses: actions/setup-python@v2
-      with:
-        python-version: 3.8
-
-    - name: Install dependencies
+    - name: Debug information
       run: |
-        python -m pip install --upgrade pip
-        pip install flake8
-    
-    - name: Run linting
-      run: flake8 .
+        echo "Python version:"
+        python --version
+        echo "Pip version:"
+        pip --version
+        echo "Installed packages:"
+        pip list
+        echo "Current directory:"
+        pwd
+        echo "Directory contents:"
+        ls -R

src/agent_management.py

@@ -4,8 +4,10 @@
 from fetchai.ledger.api.token import TokenTxFactory
 
 import numpy as np
-from trading_environment import TradingEnvironment
-from moving_average_crossover_strategy import crossover_strategy
+import jax.numpy as jnp
+import tensorflow as tf
+from src.trading_environment import TradingEnvironment
+from moving_average_crossover_strategy import crossover_strategy_jax, crossover_strategy_tf
 
 class TradingAgent:
     def __init__(self, entity: Entity, ledger_api: LedgerApi, contract: Contract):
@@ -20,14 +22,21 @@ def make_decision(self, observation):
         # Extract relevant information from the observation
         balance, shares_held, short_ma, long_ma = observation
 
-        # Use the crossover strategy to generate a signal
-        prices = np.array([short_ma, long_ma])  # Use the moving averages as a proxy for prices
-        signal = crossover_strategy(prices, self.short_window, self.long_window)[-1]
+        # Use both JAX and TensorFlow crossover strategies to generate signals
+        price = self.environment.prices[self.environment.current_step]
+        prices_jax = jnp.array([price])
+        prices_tf = tf.constant([price])
 
-        # Convert signal to action
-        if signal == 1 and balance > 0:
+        signal_jax = crossover_strategy_jax(prices_jax, self.short_window, self.long_window)[-1]
+        signal_tf = crossover_strategy_tf(prices_tf, self.short_window, self.long_window)[-1].numpy()
+
+        # Combine signals (e.g., take the average)
+        combined_signal = (signal_jax + signal_tf) / 2
+
+        # Convert combined signal to action
+        if combined_signal > 0.5 and balance > 0:
             return 1  # Buy
-        elif signal == -1 and shares_held > 0:
+        elif combined_signal < -0.5 and shares_held > 0:
             return 2  # Sell
         else:
             return 0  # Hold
@@ -80,5 +89,6 @@ def main():
     agent = TradingAgent(entity, ledger_api, contract)
     agent.run()
 
+
 if __name__ == "__main__":
     main()

src/alpha_vantage_data_fetch.py

@@ -22,16 +22,16 @@ def fetch_daily_stock_data(symbol):
         'symbol': symbol,
         'apikey': API_KEY
     }
-    
+
     try:
         response = requests.get(BASE_URL, params=params)
         response.raise_for_status()  # Raise an exception for bad status codes
         data = response.json()
-        
+
         if 'Error Message' in data:
             logging.error(f"Error fetching data for {symbol}: {data['Error Message']}")
             return None
-        
+
         return data
     except requests.RequestException as e:
         logging.error(f"Request failed for {symbol}: {str(e)}")
@@ -51,7 +51,7 @@ def save_data_to_file(data, symbol):
 
 def main():
     symbols = ['AAPL', 'GOOGL', 'MSFT']  # Example stock symbols
-    
+
     for symbol in symbols:
         logging.info(f"Fetching data for {symbol}")
         data = fetch_daily_stock_data(symbol)
@@ -60,8 +60,9 @@ def main():
         else:
             logging.warning(f"No data fetched for {symbol}")
 
+
 if __name__ == "__main__":
     if not API_KEY:
         logging.error("Alpha Vantage API key not found. Please set the ALPHA_VANTAGE_API_KEY environment variable.")
     else:
-        main()
+        main()

src/moving_average_crossover_stratagy.py

@@ -79,5 +79,6 @@ def main():
 
     print(f"Final cumulative return: {cumulative_returns[-1]:.2f}")
 
+
 if __name__ == "__main__":
     main()

src/trading_environment.py

@@ -2,7 +2,7 @@
 import numpy as np
 import pandas as pd
 from gym import spaces
-from moving_average_crossover_strategy import moving_average, load_data
+from moving_average_crossover_strategy import moving_average_jax, load_data
 
 class TradingEnvironment(gym.Env):
     def __init__(self, csv_file_path, initial_balance=10000, transaction_fee=0.001):
@@ -29,11 +29,14 @@ def __init__(self, csv_file_path, initial_balance=10000, transaction_fee=0.001):
         self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(4,), dtype=np.float32)
 
     def _get_observation(self):
+        short_ma = moving_average_jax(self.prices[:self.current_step + 1], self.short_window)[-1]
+        long_ma = moving_average_jax(self.prices[:self.current_step + 1], self.long_window)[-1]
+
         obs = np.array([
             self.balance,
             self.shares_held,
-            moving_average(self.prices[:self.current_step+1], self.short_window)[-1],
-            moving_average(self.prices[:self.current_step+1], self.long_window)[-1]
+            short_ma if not np.isnan(short_ma) else self.prices[self.current_step],
+            long_ma if not np.isnan(long_ma) else self.prices[self.current_step]
         ])
         return obs
 

src/yahoo_finance_data_fetch.py

@@ -48,5 +48,6 @@ def main():
         else:
             logging.warning(f"No data fetched for {symbol}")
 
+
 if __name__ == "__main__":
     main()