# 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}` --- ## 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 --- ## 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 ``` --- ## Rollback Plan (If Needed) If V2 causes issues: 1. **Rename files back:** ```bash 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** --- ## 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 --- ## 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 --- ## 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 --- 🎉 **The V2 system is ready to roll!** Start the bot and watch Miku become truly autonomous!