191 lines
5.5 KiB
Markdown
191 lines
5.5 KiB
Markdown
# Autonomous V2 Implementation Complete! ✅
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## What Changed
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### ✅ Files Modified
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1. **`utils/autonomous.py`** (previously `utils/autonomous_v2.py`)
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- Now the main autonomous system
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- Uses context-aware decision engine
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- Imports legacy functions from `autonomous_v1_legacy.py`
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2. **`utils/autonomous_v1_legacy.py`** (previously `utils/autonomous.py`)
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- Old autonomous system preserved as backup
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- Contains all the implementation functions (still used by V2)
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3. **`utils/autonomous_engine.py`** (NEW)
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- Core decision engine
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- Tracks context signals (messages, presence, activities)
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- Makes intelligent decisions without LLM calls
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- Mood-aware personality profiles
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4. **`bot.py`**
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- Added `initialize_v2_system()` call in `on_ready()`
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- Added `on_message_event()` hook to track every message
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- Added `on_presence_update()` event handler
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- Added `on_member_join()` event handler
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- Removed old autonomous reaction code (now handled by V2)
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5. **`server_manager.py`**
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- Updated `_run_autonomous_for_server()` to use V2 tick
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- Updated `_run_autonomous_reaction_for_server()` to use V2 tick
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- Removed conversation detection scheduler (now event-driven)
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6. **`utils/moods.py`**
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- Added `on_mood_change()` notifications in `rotate_server_mood()`
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- Added mood change notification in wake-up handler
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7. **`api.py`**
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- Added mood change notifications to all mood-setting endpoints
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- Updated `/servers/{guild_id}/mood`, `/servers/{guild_id}/mood/reset`, `/test/mood/{guild_id}`
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---
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## How It Works Now
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### Event-Driven Architecture
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**Before V1:**
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```
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Timer (every 15 min) → 10% random chance → Action
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```
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**After V2:**
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```
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Message arrives → Track context → Check thresholds → Intelligent decision → Action
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```
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### Context Tracking (No LLM!)
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Every message/event updates lightweight signals:
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- Message count (last 5 min, last hour)
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- Conversation momentum (0-1 scale)
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- User presence events (status changes, activities)
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- Time since last action
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- Current mood profile
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### Decision Logic
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Checks in priority order:
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1. **Join Conversation** - High momentum + social mood
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2. **Engage User** - Someone started interesting activity
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3. **FOMO Response** - Lots of messages without Miku
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4. **Break Silence** - Channel quiet + energetic mood
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5. **Share Tweet** - Quiet period + appropriate mood
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6. **React to Message** - Mood-based probability
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### Mood Influence
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Each mood has personality traits that affect decisions:
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- **Energy**: How quickly Miku breaks silence
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- **Sociability**: How easily she joins conversations
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- **Impulsiveness**: How quickly she reacts to events
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Examples:
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- **Bubbly** (0.9 energy, 0.95 sociability): Joins after 5 messages, breaks 30 min silence
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- **Shy** (0.4 energy, 0.2 sociability): Waits for 40+ messages, tolerates 50 min silence
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- **Asleep** (0.0 all): Does nothing at all
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---
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## Testing Checklist
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### ✅ Syntax Checks Passed
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- `autonomous_engine.py` ✅
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- `autonomous.py` ✅
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- `bot.py` ✅
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- `server_manager.py` ✅
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### 🔄 Runtime Testing Needed
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1. **Start the bot** - Check for initialization messages:
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```
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🚀 Initializing Autonomous V2 System...
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✅ Autonomous V2 System initialized
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```
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2. **Send some messages** - Watch for context tracking:
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```
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(No output expected - tracking is silent)
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```
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3. **Wait for autonomous action** - Look for V2 decisions:
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```
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🤖 [V2] Autonomous engine decided to: join_conversation for server 123456
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✅ [V2] Autonomous tick queued for server 123456
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```
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4. **Change mood via API** - Verify mood change notification:
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```
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🎭 API: Server mood set result: True
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(Should see mood notification to autonomous engine)
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```
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5. **Monitor reactions** - New messages should trigger real-time reaction checks:
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```
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🎯 [V2] Real-time reaction triggered for message from User
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```
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---
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## Rollback Plan (If Needed)
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If V2 causes issues:
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1. **Rename files back:**
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```bash
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cd /home/koko210Serve/docker/ollama-discord/bot/utils
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mv autonomous.py autonomous_v2_broken.py
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mv autonomous_v1_legacy.py autonomous.py
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```
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2. **Revert bot.py changes:**
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- Remove V2 imports and event handlers
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- Restore old autonomous reaction code
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3. **Revert server_manager.py:**
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- Change back to `miku_autonomous_tick_for_server`
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- Restore conversation detection scheduler
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4. **Restart bot**
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---
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## Performance Notes
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### Resource Usage
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- **Zero LLM calls for decisions** - Only simple math on tracked metrics
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- **Lightweight tracking** - No message content stored, just counts and timestamps
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- **Efficient** - Event-driven, only acts when contextually appropriate
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### Expected Behavior Changes
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- **More natural timing** - Won't interrupt active conversations
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- **Mood-consistent** - Bubbly Miku is chatty, shy Miku is reserved
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- **Better engagement** - Responds to user activities, not just timers
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- **Context-aware reactions** - More likely to react in active chats
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---
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## Next Steps
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1. **Monitor logs** for first 24 hours
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2. **Tune thresholds** if needed (in `autonomous_engine.py`)
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3. **Collect feedback** on behavior naturalness
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4. **Consider future enhancements:**
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- Topic detection
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- User affinity tracking
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- Time-of-day learning
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- Sentiment signals
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---
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## Documentation
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- **Decision Logic**: See `AUTONOMOUS_V2_DECISION_LOGIC.md` for detailed examples
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- **Comparison**: See `AUTONOMOUS_V2_COMPARISON.md` for V1 vs V2 diagrams
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- **Migration Guide**: See `AUTONOMOUS_V2_MIGRATION.md` for implementation details
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---
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🎉 **The V2 system is ready to roll!** Start the bot and watch Miku become truly autonomous!
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