update file

graders/task1_grader.py

@@ -1,20 +1,23 @@
+"""
+Task 1: Fetch Market Data
+Score must be strictly between 0 and 1 (never 0.0 or 1.0)
+"""
+
 def grade_task1(agent_action, observation):
+    score = 0.01  # Start with minimum positive score
     
-    score = 0.0
+    # Check if action type is GET_PRICE (adds 0.45)
+    if agent_action and agent_action.get("type") == "GET_PRICE":
+        score += 0.45
     
-    # Check if action was GET_PRICE (0.01 to 0.49 range)
-    if agent_action.get("type") == "GET_PRICE":
-        score += 0.45  # Not 0.5 to avoid exactly 0.5
+    # Check if observation has a valid price (adds 0.45)
+    if observation and observation.get("price", 0) > 0:
+        score += 0.45
     
-    # Check if observation has a valid price (0.01 to 0.49 range)
-    price = observation.get("price", 0)
-    if price > 0:
-        score += 0.45  # Not 0.5 to avoid exactly 0.5
-    
-    # Ensured score is never 0.0 or 1.0
-    if score == 0.0:
-        score = 0.01  # Minimum positive score
-    elif score >= 0.99:
-        score = 0.98  # Maximum score below 1.0
+    # Clamp between 0.01 and 0.99
+    if score < 0.01:
+        score = 0.01
+    if score > 0.99:
+        score = 0.99
     
     return round(score, 2)

graders/task2_grader.py

@@ -1,26 +1,33 @@
+"""
+Task 2: News Sentiment Analysis
+Score must be strictly between 0 and 1 (never 0.0 or 1.0)
+"""
+
 def grade_task2(agent_action, observation):
+    score = 0.01  # Start with minimum positive score
     
-    score = 0.0
+    # Check if agent provided an explanation
+    if agent_action and agent_action.get("explanation"):
+        explanation = agent_action.get("explanation", "")
+        if len(explanation) > 10:
+            score += 0.30
     
-    # Check if agent gave an explanation (0.01 to 0.49 range)
-    explanation = agent_action.get("explanation", "")
-    if explanation and len(explanation) > 10:
-        score += 0.45
+    # Check if action type is valid (BUY/SELL/HOLD/GET_NEWS)
+    if agent_action:
+        action_type = agent_action.get("type", "")
+        if action_type in ["BUY", "SELL", "HOLD", "GET_NEWS"]:
+            score += 0.30
     
-    # Check if action type is valid (BUY/SELL/GET_NEWS)
-    action_type = agent_action.get("type", "")
-    if action_type in ["BUY", "SELL", "GET_NEWS", "HOLD"]:
-        score += 0.45
+    # Check if news sentiment was analyzed
+    if observation and observation.get("last_news"):
+        sentiment = observation.get("last_news", {}).get("sentiment", "")
+        if sentiment in ["positive", "negative", "neutral"]:
+            score += 0.35
     
-    # Check if news sentiment was considered
-    sentiment = observation.get("last_news", {}).get("sentiment", "")
-    if sentiment in ["positive", "negative", "neutral"]:
-        score += 0.05
-    
-    # Ensure score is never 0.0 or 1.0
-    if score == 0.0:
+    # Clamp between 0.01 and 0.99
+    if score < 0.01:
         score = 0.01
-    elif score >= 0.99:
-        score = 0.98
+    if score > 0.99:
+        score = 0.99
     
     return round(score, 2)

graders/task3_grader.py

@@ -1,26 +1,30 @@
+"""
+Task 3: Backtest Strategy
+Score must be strictly between 0 and 1 (never 0.0 or 1.0)
+"""
+
 def grade_task3(agent_action, observation):
+    score = 0.01  # Start with minimum positive score
     
-    score = 0.0
-    
-    # Check if backtest results exist (0.01 to 0.49 range)
-    backtest_results = observation.get("backtest_results")
-    if backtest_results:
-        score += 0.45
-    
-    # Check for Sharpe ratio (0.01 to 0.49 range)
-    sharpe = backtest_results.get("sharpe_ratio", 0) if backtest_results else 0
-    if sharpe > 0:
+    # Check if backtest results exist
+    if observation and observation.get("backtest_results"):
+        backtest_results = observation.get("backtest_results", {})
         score += 0.45
+        
+        # Check for Sharpe ratio
+        sharpe = backtest_results.get("sharpe_ratio", 0)
+        if sharpe > 0:
+            score += 0.25
+        
+        # Check for max drawdown
+        drawdown = backtest_results.get("max_drawdown", 1)
+        if drawdown < 0.5:
+            score += 0.25
     
-    # Small bonus for reasonable drawdown
-    drawdown = backtest_results.get("max_drawdown", 1) if backtest_results else 1
-    if drawdown < 0.5:
-        score += 0.05
-    
-    # Ensure score is never 0.0 or 1.0
-    if score == 0.0:
+    # Clamp between 0.01 and 0.99
+    if score < 0.01:
         score = 0.01
-    elif score >= 0.99:
-        score = 0.98
+    if score > 0.99:
+        score = 0.99
     
     return round(score, 2)