miku-discord/readmes/AUTONOMOUS_V2_IMPLEMENTED.md

Autonomous V2 Implementation Complete! ✅

What Changed

✅ Files Modified

1. utils/autonomous.py (previously utils/autonomous_v2.py)

   • Now the main autonomous system
   • Uses context-aware decision engine
   • Imports legacy functions from autonomous_v1_legacy.py

2. utils/autonomous_v1_legacy.py (previously utils/autonomous.py)

   • Old autonomous system preserved as backup
   • Contains all the implementation functions (still used by V2)

3. utils/autonomous_engine.py (NEW)

   • Core decision engine
   • Tracks context signals (messages, presence, activities)
   • Makes intelligent decisions without LLM calls
   • Mood-aware personality profiles

4. bot.py

   • Added initialize_v2_system() call in on_ready()
   • Added on_message_event() hook to track every message
   • Added on_presence_update() event handler
   • Added on_member_join() event handler
   • Removed old autonomous reaction code (now handled by V2)

5. server_manager.py

   • Updated _run_autonomous_for_server() to use V2 tick
   • Updated _run_autonomous_reaction_for_server() to use V2 tick
   • Removed conversation detection scheduler (now event-driven)

6. utils/moods.py

   • Added on_mood_change() notifications in rotate_server_mood()
   • Added mood change notification in wake-up handler

7. api.py

   • Added mood change notifications to all mood-setting endpoints
   • Updated /servers/{guild_id}/mood, /servers/{guild_id}/mood/reset, /test/mood/{guild_id}

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How It Works Now

Event-Driven Architecture

Before V1:

Timer (every 15 min) → 10% random chance → Action

After V2:

Message arrives → Track context → Check thresholds → Intelligent decision → Action

Context Tracking (No LLM!)

Every message/event updates lightweight signals:

• Message count (last 5 min, last hour)
• Conversation momentum (0-1 scale)
• User presence events (status changes, activities)
• Time since last action
• Current mood profile

Decision Logic

Checks in priority order:

1. Join Conversation - High momentum + social mood
2. Engage User - Someone started interesting activity
3. FOMO Response - Lots of messages without Miku
4. Break Silence - Channel quiet + energetic mood
5. Share Tweet - Quiet period + appropriate mood
6. React to Message - Mood-based probability

Mood Influence

Each mood has personality traits that affect decisions:

• Energy: How quickly Miku breaks silence
• Sociability: How easily she joins conversations
• Impulsiveness: How quickly she reacts to events

Examples:

• Bubbly (0.9 energy, 0.95 sociability): Joins after 5 messages, breaks 30 min silence
• Shy (0.4 energy, 0.2 sociability): Waits for 40+ messages, tolerates 50 min silence
• Asleep (0.0 all): Does nothing at all

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Testing Checklist

✅ Syntax Checks Passed

• autonomous_engine.py ✅
• autonomous.py ✅
• bot.py ✅
• server_manager.py ✅

🔄 Runtime Testing Needed

1. Start the bot - Check for initialization messages:

   🚀 Initializing Autonomous V2 System...
   ✅ Autonomous V2 System initialized
   

2. Send some messages - Watch for context tracking:

   (No output expected - tracking is silent)
   

3. Wait for autonomous action - Look for V2 decisions:

   🤖 [V2] Autonomous engine decided to: join_conversation for server 123456
   ✅ [V2] Autonomous tick queued for server 123456
   

4. Change mood via API - Verify mood change notification:

   🎭 API: Server mood set result: True
   (Should see mood notification to autonomous engine)
   

5. Monitor reactions - New messages should trigger real-time reaction checks:

   🎯 [V2] Real-time reaction triggered for message from User
   

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Rollback Plan (If Needed)

If V2 causes issues:

1. Rename files back:

   cd /home/koko210Serve/docker/ollama-discord/bot/utils
   mv autonomous.py autonomous_v2_broken.py
   mv autonomous_v1_legacy.py autonomous.py
   

2. Revert bot.py changes:

   • Remove V2 imports and event handlers
   • Restore old autonomous reaction code

3. Revert server_manager.py:

   • Change back to miku_autonomous_tick_for_server
   • Restore conversation detection scheduler

4. Restart bot

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Performance Notes

Resource Usage

• Zero LLM calls for decisions - Only simple math on tracked metrics
• Lightweight tracking - No message content stored, just counts and timestamps
• Efficient - Event-driven, only acts when contextually appropriate

Expected Behavior Changes

• More natural timing - Won't interrupt active conversations
• Mood-consistent - Bubbly Miku is chatty, shy Miku is reserved
• Better engagement - Responds to user activities, not just timers
• Context-aware reactions - More likely to react in active chats

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Next Steps

1. Monitor logs for first 24 hours
2. Tune thresholds if needed (in autonomous_engine.py)
3. Collect feedback on behavior naturalness
4. Consider future enhancements:
   • Topic detection
   • User affinity tracking
   • Time-of-day learning
   • Sentiment signals

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Documentation

• Decision Logic: See AUTONOMOUS_V2_DECISION_LOGIC.md for detailed examples
• Comparison: See AUTONOMOUS_V2_COMPARISON.md for V1 vs V2 diagrams
• Migration Guide: See AUTONOMOUS_V2_MIGRATION.md for implementation details

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🎉 The V2 system is ready to roll! Start the bot and watch Miku become truly autonomous!