Update app.py

app.py

@@ -12,7 +12,7 @@ from torch.nn.functional import sigmoid
 from collections import Counter
 import logging
 import traceback
-import atexit
+
 
 # Set up logging
 logging.basicConfig(level=logging.DEBUG)
@@ -23,18 +23,6 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 logger.info(f"Using device: {device}")
 # Set up custom logging
 # Set up custom logging
-# Add cleanup function here
-def cleanup():
-    """Cleanup function to free memory"""
-    try:
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
-        logger.info("Cleanup completed")
-    except Exception as e:
-        logger.error(f"Error during cleanup: {e}")
-
-atexit.register(cleanup)
-
 class CustomFormatter(logging.Formatter):
     """Custom formatter with colors and better formatting"""
     grey = "\x1b[38;21m"
@@ -122,7 +110,7 @@ THRESHOLDS = {
 
 
 PATTERN_WEIGHTS = {
-    "recovery phase": 0.7,
+    "recovery": 0.7,
     "control": 1.4,
     "gaslighting": 1.3,
     "guilt tripping": 1.2,
@@ -341,32 +329,6 @@ def get_risk_stage(patterns, sentiment):
         logger.error(f"Error determining risk stage: {e}")
         return 1
 
-def detect_compound_threat(patterns):
-    """Helper function to standardize threat detection logic"""
-    pattern_set = set(p.lower() for p in patterns)
-    
-    # Expand primary threats to include more patterns
-    primary_threats = {"control", "insults", "blame shifting"}
-    
-    # Expand supporting risks to include more patterns
-    supporting_risks = {
-        "gaslighting", 
-        "dismissiveness", 
-        "blame shifting",
-        "guilt tripping",
-        "contradictory statements"
-    }
-    
-    has_primary = bool(primary_threats & pattern_set)
-    has_supporting = len(supporting_risks & pattern_set) >= 1  # Only need one supporting risk
-    
-    # Additional check for control + any other pattern
-    if "control" in pattern_set and len(pattern_set) > 1:
-        return True
-        
-    return has_primary and has_supporting
-
-
 @spaces.GPU
 def compute_abuse_score(matched_scores, sentiment):
     """Compute abuse score from matched patterns and sentiment"""
@@ -429,7 +391,7 @@ def analyze_single_message(text, thresholds):
             return 0.0, [], [], {"label": "none"}, 1, 0.0, None
 
         # Check for explicit abuse
-        explicit_abuse_words = ['fuck', 'bitch', 'shit', 'ass', 'dick', "make you regret it"]
+        explicit_abuse_words = ['fuck', 'bitch', 'shit', 'ass', 'dick']
         explicit_abuse = any(word in text.lower() for word in explicit_abuse_words)
         logger.debug(f"Explicit abuse detected: {explicit_abuse}")
         
@@ -458,43 +420,26 @@ def analyze_single_message(text, thresholds):
         if explicit_abuse:
             threshold_labels.append("insults")
             logger.debug("\nForced inclusion of 'insults' due to explicit abuse")
-
+            
         for label, score in sorted_predictions:
-            if label == "nonabusive":
-                continue  # Skip nonabusive label
             base_threshold = thresholds.get(label, 0.25)
             if explicit_abuse:
                 base_threshold *= 0.5
             if score > base_threshold:
                 if label not in threshold_labels:
                     threshold_labels.append(label)
+        
+        logger.debug("\nLabels that passed thresholds:", threshold_labels)
 
-        # Check for control pattern
-        control_score = raw_scores[LABELS.index("control")]
-        if control_score > 0.3 and "control" not in threshold_labels:  # Lower threshold for control
-            threshold_labels.append("control")
-            logger.debug("\nAdded control pattern due to high control score")
-
-        # Calculate matched scores (exclude nonabusive)
+        # Calculate matched scores
         matched_scores = []
         for label in threshold_labels:
-            if label == "nonabusive":
-                continue
             score = raw_scores[LABELS.index(label)]
             weight = PATTERN_WEIGHTS.get(label, 1.0)
             if explicit_abuse and label == "insults":
                 weight *= 1.5
             matched_scores.append((label, score, weight))
 
-        logger.debug("\n🧨 SINGLE-MESSAGE COMPOUND THREAT CHECK")
-        compound_threat_flag = detect_compound_threat([label for label, _, _ in matched_scores])
-        compound_threat_boost = compound_threat_flag
-
-        if compound_threat_flag:
-            logger.debug("⚠️ Compound high-risk patterns detected in single message.")
-        else:
-            logger.debug("✓ No compound threats detected in message.")
-      
         # Get sentiment
         sent_inputs = sentiment_tokenizer(text, return_tensors="pt", truncation=True, padding=True)
         sent_inputs = {k: v.to(device) for k, v in sent_inputs.items()}
@@ -507,25 +452,20 @@ def analyze_single_message(text, thresholds):
         abuse_score = compute_abuse_score(matched_scores, sentiment)
         if explicit_abuse:
             abuse_score = max(abuse_score, 70.0)
-        if compound_threat_boost:
-            abuse_score = max(abuse_score, 85.0)  # force high score if compound risk detected
-        if "control" in [label for label, _, _ in matched_scores]:
-            abuse_score = max(abuse_score, 70.0)  # Minimum score for control patterns
-            
+
         # Get DARVO score
         darvo_score = predict_darvo_score(text)
 
         # Get tone using emotion-based approach
         tone_tag = get_emotional_tone_tag(text, sentiment, threshold_labels, abuse_score)
-        
-        # Check for the specific combination
-        highest_pattern = max(matched_scores, key=lambda x: x[1])[0] if matched_scores else None
+         # Check for the specific combination
+        highest_pattern = max(matched_scores, key=lambda x: x[1])[0] if matched_scores else None  # Get highest pattern
         if sentiment == "supportive" and tone_tag == "neutral" and highest_pattern == "obscure language":
             logger.debug("Message classified as likely non-abusive (supportive, neutral, and obscure language). Returning low risk.")
             return 0.0, [], [], {"label": "supportive"}, 1, 0.0, "neutral"  # Return non-abusive values
 
         # Set stage
-        stage = 2 if explicit_abuse or abuse_score > 70 or compound_threat_boost else 1
+        stage = 2 if explicit_abuse or abuse_score > 70 else 1
         
         logger.debug("=== DEBUG END ===\n")
 
@@ -534,7 +474,6 @@ def analyze_single_message(text, thresholds):
     except Exception as e:
         logger.error(f"Error in analyze_single_message: {e}")
         return 0.0, [], [], {"label": "error"}, 1, 0.0, None
-
 def generate_abuse_score_chart(dates, scores, patterns):
     """Generate a timeline chart of abuse scores"""
     try:
@@ -725,22 +664,7 @@ def analyze_composite(msg1, msg2, msg3, *answers_and_none):
                     logger.debug(f"  • {severity} | {label}: {score:.3f} (weight: {weight})")
             else:
                 logger.debug("\n✓ No abuse patterns detected")
-             # Compound Threat Detection (across all active messages)
-            logger.debug("\n🧨 COMPOUND THREAT DETECTION")
-            logger.debug("=" * 50)
-
-            compound_threat_flag = any(
-                detect_compound_threat(result[0][1])  # patterns are in result[0][1]
-                for result in results
-            )
-
-            if compound_threat_flag:
-                logger.debug("⚠️ ALERT: Compound threat patterns detected across messages")
-                logger.debug("  • High-risk combination of primary and supporting patterns found")
-            else:
-                logger.debug("✓ No compound threats detected across messages")
 
-      
         # Extract scores and metadata
         abuse_scores = [r[0][0] for r in results]
         stages = [r[0][4] for r in results]
@@ -907,9 +831,6 @@ def analyze_composite(msg1, msg2, msg3, *answers_and_none):
             "Low"
         )
         logger.debug(f"\n⚠️ Final Escalation Risk: {escalation_risk}")
-        if compound_threat_flag:
-            escalation_risk = "Critical"
-            logger.debug("❗ Compound threat detected — overriding risk to CRITICAL.")
         # Generate Output Text
         logger.debug("\n📝 GENERATING OUTPUT")
         logger.debug("=" * 50)