Update app.py

app.py

@@ -456,6 +456,11 @@ def analyze_single_message(text, thresholds):
 
         # 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  # 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 else 1
@@ -609,15 +614,34 @@ def analyze_composite(msg1, msg2, msg3, *answers_and_none):
         immediate_threats = [detect_threat_motifs(m, THREAT_MOTIFS) for m, _ in active]
         flat_threats = [t for sublist in immediate_threats for t in sublist]
         threat_risk = "Yes" if flat_threats else "No"
-        # Analyze each message
+                # Analyze each message
         logger.debug("\n🔍 INDIVIDUAL MESSAGE ANALYSIS")
         logger.debug("=" * 50)
         results = []
         for m, d in active:
             logger.debug(f"\n📝 ANALYZING {d}")
-            logger.debug("=" * 40)
+            logger.debug("-" * 40)  # Separator for each message
             result = analyze_single_message(m, THRESHOLDS.copy())
+
+            # Check for non-abusive classification and skip further analysis
+            if result[0] == 0.0 and result[1] == [] and result[3] == {"label": "supportive"} and result[4] == 1 and result[5] == 0.0 and result[6] == "neutral":
+                logger.debug(f"✓ {d} classified as non-abusive, skipping further analysis.")
+                # Option to include in final output (uncomment if needed):
+                # results.append(({"abuse_score": 0.0, "patterns": [], "sentiment": {"label": "supportive"}, "stage": 1, "darvo_score": 0.0, "tone": "neutral"}, d))
+                continue  # Skip to the next message
+
             results.append((result, d))
+            # Log the detailed results for the current message (if not skipped)
+            abuse_score, patterns, matched_scores, sentiment, stage, darvo_score, tone = result
+            logger.debug(f"\n📊 Results for {d}:")
+            logger.debug(f"  • Abuse Score: {abuse_score:.1f}%")
+            logger.debug(f"  • DARVO Score: {darvo_score:.3f}")
+            logger.debug(f"  • Risk Stage: {stage}")
+            logger.debug(f"  • Sentiment: {sentiment['label']}")
+            logger.debug(f"  • Tone: {tone}")
+            if patterns:
+                logger.debug("  • Patterns: " + ", ".join(patterns))
+
             
             # Unpack results for cleaner logging
             abuse_score, patterns, matched_scores, sentiment, stage, darvo_score, tone = result