Upload drift.py

engine/drift.py

@@ -31,15 +31,16 @@ def get_current_mode(state):
     trust = state.get("trust", 0.5)
     openness = state.get("openness", 0.5)
 
-    if anxiety > 0.8:
+    # Raised thresholds significantly to prevent premature crisis states
+    if anxiety > 0.85:  # Was 0.8 - now much harder to reach decompensating
         return "decompensating"
-    if anxiety > 0.6 and trust < 0.3:
+    if anxiety > 0.75 and trust < 0.25:  # Was 0.6 and 0.3 - much higher bar for triggered
         return "triggered"
-    if openness < 0.4 and trust < 0.5:
+    if openness < 0.3 and trust < 0.4:  # Was 0.4 and 0.5 - harder to be guarded
         return "guarded"
-    if trust > 0.6 and openness > 0.6:
+    if trust > 0.7 and openness > 0.7:  # Was 0.6 - higher bar for trusting too
         return "trusting"
-    if anxiety < 0.4 and openness > 0.5:
+    if anxiety < 0.3 and openness > 0.6:  # Was 0.4 and 0.5 - adjusted
         return "recovering"
     return state.get("mode", "baseline")
 
@@ -63,20 +64,21 @@ def calculate_state_change(state, student_response):
     advice_score = sum(1 for word in advice_words if word in response_lower)
     minimizing_score = sum(1 for word in minimizing if word in response_lower)
 
-    positive_impact = (validation_score * 0.05 + open_q_score * 0.04 + empathy_score * 0.03)
-    negative_impact = (advice_score * 0.08 + minimizing_score * 0.06)
+    # Reduced magnitude significantly - was causing too-fast emotional escalation
+    positive_impact = (validation_score * 0.02 + open_q_score * 0.015 + empathy_score * 0.01)  # Was 0.05, 0.04, 0.03
+    negative_impact = (advice_score * 0.03 + minimizing_score * 0.025)  # Was 0.08, 0.06
 
     changes = {
-        "trust": positive_impact * 0.8 - negative_impact * 0.5,
-        "anxiety": negative_impact * 0.5 - positive_impact * 0.3,
-        "openness": positive_impact * 0.4 - negative_impact * 0.2
+        "trust": positive_impact * 0.5 - negative_impact * 0.3,  # Was 0.8 and 0.5 - reduced multipliers
+        "anxiety": negative_impact * 0.3 - positive_impact * 0.2,  # Was 0.5 and 0.3 - reduced
+        "openness": positive_impact * 0.3 - negative_impact * 0.15  # Was 0.4 and 0.2 - reduced
     }
 
     word_count = len(student_response.split())
     if word_count < 5:
-        changes["trust"] -= 0.05
+        changes["trust"] -= 0.02  # Was 0.05 - reduced
     elif word_count > 100:
-        changes["anxiety"] += 0.05
+        changes["anxiety"] += 0.02  # Was 0.05 - reduced
 
     return changes