Update app.py

app.py

@@ -14,7 +14,7 @@ from collections import Counter
 
 
 # ─── Abuse Model ─────────────────────────────────────────────────
-model_name = "SamanthaStorm/tether-multilabel-v3"
+model_name = "SamanthaStorm/tether-multilabel-v4"
 model      = AutoModelForSequenceClassification.from_pretrained(model_name)
 tokenizer  = AutoTokenizer.from_pretrained(model_name, use_fast=False)
 
@@ -352,37 +352,68 @@ def analyze_single_message(text, thresholds):
     return abuse_score, threshold_labels, matched_scores, {"label": sentiment}, stage, darvo_score, tone_tag
 
 
-def generate_risk_snippet(abuse_score, top_label, hybrid_score, stage):
+def generate_risk_snippet(abuse_score, patterns, hybrid_score, stage):
     """
-    Generate risk assessment snippet based on abuse score and other factors
+    Enhanced risk assessment generator with more nuanced scoring and pattern analysis
+    
+    Parameters:
+    - abuse_score: float (0-100)
+    - patterns: list of detected abuse patterns
+    - hybrid_score: float (combined escalation/risk score)
+    - stage: int (1-4 representing relationship stages)
     """
-    risk_level = (
-        "Critical" if abuse_score >= 85 or hybrid_score >= 20 else
-        "High" if abuse_score >= 70 or hybrid_score >= 15 else
-        "Moderate" if abuse_score >= 50 or hybrid_score >= 10 else
-        "Low"
-    )
     
+    # Define risk thresholds with more granular levels
+    def get_risk_level(abuse_score, hybrid_score, patterns):
+        if abuse_score >= 85 or hybrid_score >= 20:
+            return "Critical"
+        elif abuse_score >= 70 or hybrid_score >= 15:
+            return "High"
+        elif abuse_score >= 50 or hybrid_score >= 10:
+            return "Moderate"
+        return "Low"
+
+    # Pattern severity weights
+    PATTERN_SEVERITY = {
+        "control": 3,
+        "gaslighting": 3,
+        "insults": 2,
+        "blame shifting": 2,
+        "guilt tripping": 2,
+        "dismissiveness": 1,
+        "projection": 1,
+        "contradictory statements": 1,
+        "obscure language": 1,
+        "recovery": 1
+    }
+
+    # Calculate weighted pattern severity
+    pattern_severity = sum(PATTERN_SEVERITY.get(p, 0) for p in patterns)
+    
+    # Get base risk level
+    risk_level = get_risk_level(abuse_score, hybrid_score, patterns)
+    
+    # Generate risk descriptions with more detailed context
     risk_descriptions = {
         "Critical": (
             "🚨 **Risk Level: Critical**\n"
-            "Multiple severe abuse patterns detected. This situation shows signs of "
-            "dangerous escalation and immediate intervention may be needed."
+            f"Multiple severe abuse patterns detected (Score: {abuse_score:.1f}%). "
+            "This situation shows signs of dangerous escalation and immediate intervention may be needed."
         ),
         "High": (
             "⚠️ **Risk Level: High**\n"
-            "Strong abuse patterns detected. This situation shows concerning "
-            "signs of manipulation and control."
+            f"Strong abuse patterns detected (Score: {abuse_score:.1f}%). "
+            "This situation shows concerning signs of manipulation and control."
         ),
         "Moderate": (
             "⚡ **Risk Level: Moderate**\n"
-            "Concerning patterns detected. While not severe, these behaviors "
-            "indicate unhealthy relationship dynamics."
+            f"Concerning patterns detected (Score: {abuse_score:.1f}%). "
+            "While not severe, these behaviors indicate unhealthy relationship dynamics."
         ),
         "Low": (
             "📝 **Risk Level: Low**\n"
-            "Minor concerning patterns detected. While present, the detected "
-            "behaviors are subtle or infrequent."
+            f"Minor concerning patterns detected (Score: {abuse_score:.1f}%). "
+            "While present, the detected behaviors are subtle or infrequent."
         )
     }
     
@@ -394,11 +425,28 @@ def generate_risk_snippet(abuse_score, top_label, hybrid_score, stage):
         4: "Surface calm may mask underlying issues."
     }
     
-    snippet = risk_descriptions[risk_level]
+    # Build output
+    output = risk_descriptions[risk_level]
     if stage in stage_context:
-        snippet += f"\n{stage_context[stage]}"
-        
-    return snippet
+        output += f"\n{stage_context[stage]}"
+    
+    # Add pattern analysis if patterns detected
+    if patterns:
+        output += "\n\n🔍 **Detected Patterns:**"
+        for pattern in patterns:
+            severity = PATTERN_SEVERITY.get(pattern, 0)
+            output += f"\n• {pattern.title()} (Severity: {'❗' * severity})"
+    
+    # Add safety recommendations based on risk level
+    if risk_level in ["Critical", "High"]:
+        output += "\n\n⚠️ **Safety Recommendations:**"
+        output += "\n• Consider reaching out to a domestic violence hotline"
+        output += "\n• Document all concerning interactions"
+        output += "\n• Have a safety plan in place"
+    
+    return output
+
+
 def generate_abuse_score_chart(dates, scores, patterns):
     """
     Generate a timeline chart of abuse scores
@@ -683,4 +731,100 @@ demo = gr.Interface(
 
 # This single call will start the server and block,
 # keeping the container alive on Spaces.
-demo.launch()
+demo.launch()
+
+def generate_risk_snippet(abuse_score, patterns, hybrid_score, stage):
+    """
+    Enhanced risk assessment generator with more nuanced scoring and pattern analysis
+    
+    Parameters:
+    - abuse_score: float (0-100)
+    - patterns: list of detected abuse patterns
+    - hybrid_score: float (combined escalation/risk score)
+    - stage: int (1-4 representing relationship stages)
+    """
+    
+    # Define risk thresholds with more granular levels
+    def get_risk_level(abuse_score, hybrid_score, patterns):
+        if abuse_score >= 85 or hybrid_score >= 20:
+            return "Critical"
+        elif abuse_score >= 70 or hybrid_score >= 15:
+            return "High"
+        elif abuse_score >= 50 or hybrid_score >= 10:
+            return "Moderate"
+        return "Low"
+
+    # Pattern severity weights
+    PATTERN_SEVERITY = {
+        "control": 3,
+        "gaslighting": 3,
+        "insults": 2,
+        "blame shifting": 2,
+        "guilt tripping": 2,
+        "dismissiveness": 1,
+        "projection": 1,
+        "contradictory statements": 1,
+        "obscure language": 1,
+        "recovery": 1
+    }
+
+    # Calculate weighted pattern severity
+    pattern_severity = sum(PATTERN_SEVERITY.get(p, 0) for p in patterns)
+    
+    # Get base risk level
+    risk_level = get_risk_level(abuse_score, hybrid_score, patterns)
+    
+    # Generate risk descriptions with more detailed context
+    risk_descriptions = {
+        "Critical": (
+            "🚨 **Risk Level: Critical**\n"
+            f"Multiple severe abuse patterns detected (Score: {abuse_score:.1f}%). "
+            "This situation shows signs of dangerous escalation and immediate intervention may be needed."
+        ),
+        "High": (
+            "⚠️ **Risk Level: High**\n"
+            f"Strong abuse patterns detected (Score: {abuse_score:.1f}%). "
+            "This situation shows concerning signs of manipulation and control."
+        ),
+        "Moderate": (
+            "⚡ **Risk Level: Moderate**\n"
+            f"Concerning patterns detected (Score: {abuse_score:.1f}%). "
+            "While not severe, these behaviors indicate unhealthy relationship dynamics."
+        ),
+        "Low": (
+            "📝 **Risk Level: Low**\n"
+            f"Minor concerning patterns detected (Score: {abuse_score:.1f}%). "
+            "While present, the detected behaviors are subtle or infrequent."
+        )
+    }
+    
+    # Add stage-specific context
+    stage_context = {
+        1: "Current patterns suggest a tension-building phase.",
+        2: "Messages show signs of active escalation.",
+        3: "Patterns indicate attempted reconciliation without real change.",
+        4: "Surface calm may mask underlying issues."
+    }
+    
+    # Build output
+    output = risk_descriptions[risk_level]
+    if stage in stage_context:
+        output += f"\n{stage_context[stage]}"
+    
+    # Add pattern analysis if patterns detected
+    if patterns:
+        output += "\n\n🔍 **Detected Patterns:**"
+        for pattern in patterns:
+            severity = PATTERN_SEVERITY.get(pattern, 0)
+            output += f"\n• {pattern.title()} (Severity: {'❗' * severity})"
+    
+    # Add safety recommendations based on risk level
+    if risk_level in ["Critical", "High"]:
+        output += "\n\n⚠️ **Safety Recommendations:**"
+        output += "\n• Consider reaching out to a domestic violence hotline"
+        output += "\n• Document all concerning interactions"
+        output += "\n• Have a safety plan in place"
+    
+    return output
+
+