Phase 2: Fix triggers & dialogue — per-channel cooldowns, tension rebalance, user-message triggers

- Changed cooldown from global (ALL channels blocked) to per-channel dict keyed by channel_id
- Added conversation streak tracker: 3 near-miss interjection scores in a row force a dialogue trigger
- Expanded topic relevance keywords: added enthusiasm/vulnerability for Evil Miku, provocation/dismissal for Miku
- Lowered keyword divisor from /3.0 to /2.0 for higher base trigger scores
- Tension rebalance: added natural decay (-0.03/turn), reduced escalation weight (0.08->0.05), increased de-escalation weight (0.06->0.08)
- Reduced momentum multiplier (1.2->1.1) and intensity multiplier (1.3->1.2)
- Added spike cooldown: if last turn tension delta >0.15, next delta halved (prevents runaway spirals)
- Added user-message interjection check in bot.py on_message() (was only checking bot's own messages)
- Added random 15% argument trigger roll on user messages in normal message flow (was only from autonomous.py)

bot/bot.py

@@ -203,6 +203,32 @@ async def on_message(message):
         if is_persona_dialogue_active(message.channel.id):
             return
 
+    # Bipolar mode: check if the opposite persona should interject on user messages
+    # AND roll for random argument trigger (both non-blocking background tasks)
+    if not isinstance(message.channel, discord.DMChannel) and globals.BIPOLAR_MODE:
+        try:
+            from utils.persona_dialogue import check_for_interjection
+            from utils.bipolar_mode import maybe_trigger_argument, is_argument_in_progress as arg_in_progress
+            from utils.bipolar_mode import is_persona_dialogue_active as dialogue_active
+            from utils.task_tracker import create_tracked_task
+            
+            # Check interjection on user messages (opposite of current active persona)
+            if not message.author.bot or message.webhook_id:
+                current_persona = "evil" if globals.EVIL_MODE else "miku"
+                create_tracked_task(
+                    check_for_interjection(message, current_persona),
+                    task_name="interjection_check_user",
+                )
+            
+            # Roll random argument trigger chance (15%) on eligible messages
+            if not arg_in_progress(message.channel.id) and not dialogue_active(message.channel.id):
+                create_tracked_task(
+                    maybe_trigger_argument(message.channel, globals.client, "Triggered from conversation flow"),
+                    task_name="random_argument_trigger",
+                )
+        except Exception as e:
+            logger.error(f"Error in bipolar trigger checks: {e}")
+
     if message.content.strip().lower() == "miku, rape this nigga balls" and message.reference:
         async with message.channel.typing():
             # Get replied-to user

bot/utils/persona_dialogue.py

@@ -40,10 +40,15 @@ DIALOGUE_TIMEOUT = 900              # 15 minutes max dialogue duration
 ARGUMENT_TENSION_THRESHOLD = 0.75   # Tension level that triggers argument escalation
 
 # Initial trigger settings
-INTERJECTION_COOLDOWN_HARD = 180    # 3 minutes hard block
+INTERJECTION_COOLDOWN_HARD = 180    # 3 minutes hard block PER CHANNEL
-INTERJECTION_COOLDOWN_SOFT = 900    # 15 minutes for full recovery
+INTERJECTION_COOLDOWN_SOFT = 900    # 15 minutes for full recovery PER CHANNEL
 INTERJECTION_THRESHOLD = 0.5        # Score needed to trigger interjection
 
+# Conversation streak: if score is close but below threshold N times in a row,
+# force a dialogue trigger (catches extended conversations building toward something)
+STREAK_THRESHOLD = 3                # Number of near-miss messages before force trigger
+STREAK_MIN_SCORE = 0.3              # Minimum score to count as a "near miss"
+
 # ============================================================================
 # INTERJECTION SCORER (Initial Trigger Decision)
 # ============================================================================
@@ -60,6 +65,8 @@ class InterjectionScorer:
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
+            cls._instance._cooldowns = {}       # Per-channel cooldown timestamps
+            cls._instance._streaks = {}          # Per-channel near-miss streaks
         return cls._instance
     
     @property
@@ -94,8 +101,9 @@ class InterjectionScorer:
         if not self._passes_basic_filter(message):
             return False, "basic_filter_failed", 0.0
         
-        # Check cooldown
+        # Check per-channel cooldown
-        cooldown_mult = self._check_cooldown()
+        channel_id = message.channel.id
+        cooldown_mult = self._check_cooldown(channel_id)
         if cooldown_mult == 0.0:
             return False, "cooldown_active", 0.0
         
@@ -146,10 +154,17 @@ class InterjectionScorer:
         # Apply cooldown multiplier
         score *= cooldown_mult
         
+        # Check conversation streak (near-misses that build toward a trigger)
+        streak_triggered = self._check_streak(channel_id, score)
+        
         # Decision
-        should_interject = score >= INTERJECTION_THRESHOLD
+        should_interject = score >= INTERJECTION_THRESHOLD or streak_triggered
         reason_str = " | ".join(reasons) if reasons else "no_triggers"
         
+        if streak_triggered and not should_interject:
+            reason_str = "streak_force_trigger"
+            logger.info(f"[Interjection] Streak force trigger in channel {channel_id} (score: {score:.2f})")
+        
         if should_interject:
             logger.info(f"{opposite_persona.upper()} WILL INTERJECT (score: {score:.2f})")
             logger.info(f"   Reasons: {reason_str}")
@@ -198,18 +213,22 @@ class InterjectionScorer:
         if opposite_persona == "evil":
             # Things Evil Miku can't resist commenting on
             TRIGGER_TOPICS = {
-                "optimism": ["happiness", "joy", "love", "kindness", "hope", "dreams", "wonderful", "amazing"],
+                "optimism": ["happiness", "joy", "love", "kindness", "hope", "dreams", "wonderful", "amazing", "blessed", "grateful"],
-                "morality": ["good", "should", "must", "right thing", "deserve", "fair", "justice"],
+                "morality": ["good", "should", "must", "right thing", "deserve", "fair", "justice", "the right", "better person"],
-                "weakness": ["scared", "nervous", "worried", "unsure", "help me", "don't know"],
+                "weakness": ["scared", "nervous", "worried", "unsure", "help me", "don't know", "confused", "lost", "lonely", "alone"],
-                "innocence": ["innocent", "pure", "sweet", "cute", "wholesome", "precious"],
+                "innocence": ["innocent", "pure", "sweet", "cute", "wholesome", "precious", "adorable"],
+                "enthusiasm": ["best day", "so excited", "can't wait", "so happy", "i love this", "this is great"],
+                "vulnerability": ["i think", "i feel", "maybe", "sometimes i wonder", "i wish", "i'm trying"],
             }
         else:
             # Things Miku can't ignore
             TRIGGER_TOPICS = {
-                "negativity": ["hate", "terrible", "awful", "worst", "horrible", "disgusting", "pathetic"],
+                "negativity": ["hate", "terrible", "awful", "worst", "horrible", "disgusting", "pathetic", "ugly", "boring", "annoying"],
-                "cruelty": ["deserve pain", "suffer", "worthless", "stupid", "idiot", "fool"],
+                "cruelty": ["deserve pain", "suffer", "worthless", "stupid", "idiot", "fool", "moron", "loser", "nobody"],
-                "hopelessness": ["no point", "meaningless", "nobody cares", "why bother", "give up"],
+                "hopelessness": ["no point", "meaningless", "nobody cares", "why bother", "give up", "what's the point", "don't care", "doesn't matter", "who cares"],
-                "evil_gloating": ["foolish", "naive", "weak", "inferior", "pathetic"],
+                "evil_gloating": ["foolish", "naive", "weak", "inferior", "pathetic", "beneath me", "waste of space"],
+                "provocation": ["fight me", "prove it", "make me", "i dare you", "try me", "you can't", "you won't"],
+                "dismissal": ["whatever", "shut up", "go away", "leave me alone", "not worth", "don't bother"],
             }
         
         total_matches = 0
@@ -217,7 +236,7 @@ class InterjectionScorer:
             matches = sum(1 for keyword in keywords if keyword in content_lower)
             total_matches += matches
         
-        return min(total_matches / 3.0, 1.0)
+        return min(total_matches / 2.0, 1.0)  # Lower divisor = higher base scores
     
     def _check_emotional_intensity(self, content: str) -> float:
         """Check emotional intensity using sentiment analysis"""
@@ -300,13 +319,11 @@ class InterjectionScorer:
         
         return min(score, 1.0)
     
-    def _check_cooldown(self) -> float:
+    def _check_cooldown(self, channel_id: int) -> float:
-        """Check cooldown and return multiplier (0.0 = blocked, 1.0 = full)"""
+        """Check per-channel cooldown and return multiplier (0.0 = blocked, 1.0 = full)"""
-        if not hasattr(globals, 'LAST_PERSONA_DIALOGUE_TIME'):
-            globals.LAST_PERSONA_DIALOGUE_TIME = 0
-        
         current_time = time.time()
-        time_since_last = current_time - globals.LAST_PERSONA_DIALOGUE_TIME
+        last_time = self._cooldowns.get(channel_id, 0)
+        time_since_last = current_time - last_time
         
         if time_since_last < INTERJECTION_COOLDOWN_HARD:
             return 0.0
@@ -314,6 +331,35 @@ class InterjectionScorer:
             return (time_since_last - INTERJECTION_COOLDOWN_HARD) / (INTERJECTION_COOLDOWN_SOFT - INTERJECTION_COOLDOWN_HARD)
         else:
             return 1.0
+    
+    def _update_cooldown(self, channel_id: int):
+        """Mark a dialogue as having started in this channel"""
+        self._cooldowns[channel_id] = time.time()
+    
+    def _check_streak(self, channel_id: int, score: float) -> bool:
+        """Track near-miss interjection scores. After STREAK_THRESHOLD consecutive
+        near-misses, force a trigger to catch extended conversations building tension."""
+        if score >= INTERJECTION_THRESHOLD:
+            # Above threshold — reset streak (actual trigger handles it)
+            self._streaks[channel_id] = 0
+            return False
+        
+        if score < STREAK_MIN_SCORE:
+            # Too low — reset streak
+            self._streaks[channel_id] = 0
+            return False
+        
+        # Near miss — increment streak
+        current = self._streaks.get(channel_id, 0) + 1
+        self._streaks[channel_id] = current
+        
+        logger.debug(f"[Streak] Channel {channel_id}: {current}/{STREAK_THRESHOLD} near-misses (score: {score:.2f})")
+        
+        if current >= STREAK_THRESHOLD:
+            self._streaks[channel_id] = 0  # Reset after force trigger
+            return True
+        
+        return False
 
 
 # ============================================================================
@@ -370,7 +416,9 @@ class PersonaDialogue:
             "last_speaker": None,
         }
         self.active_dialogues[channel_id] = state
-        globals.LAST_PERSONA_DIALOGUE_TIME = time.time()
+        # Update per-channel cooldown via the scorer
+        scorer = get_interjection_scorer()
+        scorer._update_cooldown(channel_id)
         logger.info(f"Started persona dialogue in channel {channel_id}")
         return state
     
@@ -393,8 +441,8 @@ class PersonaDialogue:
         Returns delta to add to current tension score.
         """
         
-        # Sentiment analysis
+        # Natural tension decay — conversations cool off over time
-        base_delta = 0.0
+        base_delta = -0.03
         
         if self.sentiment_analyzer:
             try:
@@ -405,13 +453,13 @@ class PersonaDialogue:
                 if is_negative:
                     base_delta = sentiment_score * 0.15
                 else:
-                    base_delta = -sentiment_score * 0.05
+                    base_delta = -sentiment_score * 0.08  # Stronger cooling for positive
             except Exception as e:
                 logger.error(f"Sentiment analysis error in tension calc: {e}")
         
         text_lower = response_text.lower()
         
-        # Escalation patterns
+        # Escalation patterns (reduced weight: 0.05 per match)
         escalation_patterns = {
             "insult": ["idiot", "stupid", "pathetic", "fool", "naive", "worthless", "disgusting", "moron"],
             "dismissive": ["whatever", "don't care", "waste of time", "not worth", "beneath me", "boring"],
@@ -420,35 +468,43 @@ class PersonaDialogue:
             "challenge": ["prove it", "fight me", "make me", "i dare you", "try me"],
         }
         
-        # De-escalation patterns
+        # De-escalation patterns (increased weight: -0.08 per match)
         deescalation_patterns = {
             "concession": ["you're right", "fair point", "i suppose", "maybe you have", "good point"],
-            "softening": ["i understand", "let's calm", "didn't mean", "sorry", "apologize"],
+            "softening": ["i understand", "let's calm", "didn't mean", "sorry", "apologize", "i hear you"],
-            "deflection": ["anyway", "moving on", "whatever you say", "agree to disagree", "let's just"],
+            "deflection": ["anyway", "moving on", "whatever you say", "agree to disagree", "let's just", "maybe we should"],
         }
         
         # Check escalation
         for category, patterns in escalation_patterns.items():
             matches = sum(1 for p in patterns if p in text_lower)
             if matches > 0:
-                base_delta += matches * 0.08
+                base_delta += matches * 0.05  # Reduced from 0.08
         
         # Check de-escalation
         for category, patterns in deescalation_patterns.items():
             matches = sum(1 for p in patterns if p in text_lower)
             if matches > 0:
-                base_delta -= matches * 0.06
+                base_delta -= matches * 0.08  # Increased from 0.06
         
-        # Intensity multipliers
+        # Intensity multipliers (reduced)
         exclamation_count = response_text.count('!')
         caps_ratio = sum(1 for c in response_text if c.isupper()) / max(len(response_text), 1)
         
         if exclamation_count > 2 or caps_ratio > 0.3:
-            base_delta *= 1.3
+            base_delta *= 1.2  # Reduced from 1.3
         
-        # Momentum factor
+        # Momentum factor (reduced)
         if current_tension > 0.5:
-            base_delta *= 1.2
+            base_delta *= 1.1  # Reduced from 1.2
+        
+        # Spike cooldown: if last turn had a big spike, halve this delta
+        # (prevents runaway tension spirals from a single heated exchange)
+        if hasattr(self, '_last_tension_delta') and abs(self._last_tension_delta) > 0.15:
+            base_delta *= 0.5
+            logger.debug(f"[Tension] Spike cooldown active — delta halved to {base_delta:+.3f}")
+        
+        self._last_tension_delta = base_delta
         
         return base_delta