fix: gpt-oss:20b ollama, streaming, tableaux JSON, recherche flexible salons/categories

.env

@@ -3,13 +3,13 @@ GUILD_ID=1370716551485067304
 
 # --- CONFIGURATION BÊTA ---
 # IDs des Administrateurs (Séparés par des virgules)
-ADMIN_IDS=971446412690722826
+ADMIN_IDS=971446412690722826,1324439906046574693
 
 # IDs du Staff (Assets Primaires), séparés par des virgules
 PRIMARY_ASSETS_IDS=971446412690722826
 # Channel d'Introspection (Log Stream de Bêta)
 INTROSPECTION_CHANNEL_ID=1461107327381016629
 
-# Modèles Ollama (Optimisation Radeon 8060S 64GB)
+# Modèle Ollama (local, pas de clé API nécessaire)
-OLLAMA_MODEL_HEAVY=gpt-oss:120b
+OLLAMA_MODEL=gpt-oss:20b
-OLLAMA_MODEL_FAST=deepseek-r1:7b
+OLLAMA_BASE_URL=http://localhost:11434

README.md

@@ -0,0 +1,240 @@
+# Superviseur Bot (Bêta)
+
+Bot Discord IA d'assistance et de modération avancée, utilisant **Ollama** pour l'inférence LLM locale.
+
+## Fonctionnalités
+
+- **IA conversationnelle** : Répond aux questions et exécute des actions sur Discord via JSON
+- **Modération silencieuse** : Scan de toxicité de chaque message via LLM en arrière-plan
+- **Gestion vocale** : Transcription Whisper en temps réel + détection de mots-clés
+- **Mémoire utilisateur** : Historique par utilisateur avec résumé automatique
+- **Dispatch d'insights** : Coordination staff avec boutons d'acceptation Discord
+- **RGPD** : Purge automatique des données > 30 jours
+
+## Installation
+
+### Prérequis
+
+- Python 3.9+
+- **Ollama** installé et en cours d'exécution (https://ollama.com)
+- Modèle `gpt-oss:20b` disponible dans Ollama
+
+### Dépendances
+
+```bash
+pip install -r requirements.txt
+```
+
+### Configuration Ollama
+
+```bash
+# Pull le modèle dans Ollama
+ollama pull gpt-oss:20b
+```
+
+### Configuration
+
+Créer un fichier `.env` à la racine du dossier `beta/` :
+
+```bash
+# Discord
+DISCORD_TOKEN=your_discord_bot_token
+GUILD_ID=your_guild_id
+
+# LLM
+OLLAMA_MODEL=gpt-oss:20b
+
+# Staff
+ADMIN_IDS=123456789,987654321
+PRIMARY_ASSETS_IDS=111222333,444555666
+
+# Channel d'introspection
+INTROSPECTION_CHANNEL_ID=123456789
+```
+
+## Utilisation
+
+```bash
+cd beta
+python main.py
+```
+
+Le bot va :
+1. Se connecter à Ollama
+2. Initialiser tous les composants (mémoire, modération, vocal)
+3. Se connecter à Discord
+4. Traiter les messages
+
+## Architecture
+
+```
+beta/
+├── main.py              # Point d'entrée
+├── core/
+│   ├── bot.py           # Classe principale Superviseur
+│   ├── llm.py           # Gestionnaire LLM (Ollama API)
+│   ├── action_router.py # Routage des actions IA → Discord
+│   ├── dispatcher.py    # Dispatch d'insights vers staff
+│   ├── voice.py         # Gestion vocale + Whisper
+│   ├── tasks.py         # Tâches de fond
+│   ├── messaging.py     # Envoi de messages
+│   └── permissions.py   # Whitelist et permissions
+├── brain/
+│   ├── memoire.py       # Mémoire utilisateur (JSON/Redis)
+│   ├── moderation.py    # Modération IA + SQLite
+│   └── infos_serveurs.py # Infos serveur
+├── commandes/
+│   ├── security/        # kick, ban, mute, warn, purge...
+│   ├── salons/          # Créer, supprimer, modifier salons
+│   ├── roles/           # Créer, supprimer, modifier rôles
+│   └── autres/          # Config, status, ping, etc.
+├── data/                # Logs, DB SQLite
+└── memoires/            # Historique utilisateur (JSON)
+```
+
+## Actions IA
+
+Le bot peut exécuter les actions suivantes via LLM :
+- `CREATE_CHANNEL`, `DELETE_CHANNEL`, `MODIFY_CHANNEL`
+- `CREATE_ROLE`, `DELETE_ROLE`, `ADD_ROLE_TO_USER`
+- `KICK`, `BAN`, `UNBAN`, `MUTE`, `TIMEOUT`, `WARN`, `PURGE`
+- `JOIN_VOICE`, `LEAVE_VOICE`
+- `ALERT`, `INSIGHT`, `FORGET_USER`, `READ_LOGS`
+
+## Support
+
+1. Vérifier les logs dans `data/bot.log`
+2. Activer le mode debug : `LOG_LEVEL=DEBUG`
+3. Vérifier qu'Ollama est actif : `ollama list`
+python test_llama_integration.py
+```
+
+This will test:
+- Model loading
+- LLMManager functionality
+- Text generation
+- JSON extraction
+- Performance
+
+## Performance
+
+### Expected Performance
+
+With the 120B model and optimized parameters:
+- **Context**: 4096 tokens
+- **Threads**: 16 CPU threads
+- **Memory**: ~64GB RAM usage
+- **Response time**: 5-15 seconds for typical queries
+- **Concurrency**: 4 simultaneous requests
+
+### Performance Tips
+
+1. **Use mlock**: Prevents swapping to disk
+2. **Optimize threads**: Match your CPU core count
+3. **Monitor memory**: Ensure sufficient RAM
+4. **Batch size**: Adjust based on your system
+
+### Monitoring
+
+The bot includes built-in metrics:
+- LLM request counts
+- Success/failure rates
+- Response times
+- Memory usage
+
+Enable metrics server with `METRICS_ENABLED=1`.
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Model not found**
+   - Check `MODEL_PATH` in `.env`
+   - Verify model file exists
+   - Check file permissions
+
+2. **Memory errors**
+   - Ensure sufficient RAM
+   - Reduce `n_ctx` or `n_threads`
+   - Disable `use_mlock` for testing
+
+3. **Slow responses**
+   - Check CPU usage
+   - Verify model is in RAM
+   - Reduce `n_threads` if CPU is overloaded
+
+4. **Import errors**
+   - Install `llama-cpp-python` with proper backend
+   - Check Python version compatibility
+
+### Debug Mode
+
+Enable verbose logging by setting:
+```bash
+LOG_LEVEL=DEBUG
+```
+
+### Model Loading Issues
+
+If model loading fails:
+1. Check model file integrity
+2. Verify GGUF format compatibility
+3. Try with `use_mlock=False`
+4. Reduce model size for testing
+
+## Migration Notes
+
+### From Ollama
+
+If you were previously using Ollama:
+
+1. **Remove Ollama**: No longer needed
+2. **Update configuration**: Remove Ollama URLs
+3. **Install llama-cpp-python**: Add to requirements
+4. **Test thoroughly**: Verify all functionality
+
+### Code Changes
+
+Key files modified:
+- `beta.py`: Main entry point with model loading
+- `superviseur/llm.py`: LLMManager with llama-cpp-python
+- `superviseur/bot.py`: Bot integration
+- `requirements.txt`: Updated dependencies
+
+## Security
+
+### Data Privacy
+
+- No external network calls
+- All processing local
+- GDPR compliance maintained
+- Memory management for sensitive data
+
+### Model Security
+
+- Local model storage
+- No external dependencies
+- Controlled access
+- Proper cleanup
+
+## Support
+
+For issues or questions:
+1. Check the troubleshooting section
+2. Run the test script
+3. Enable debug logging
+4. Check system resources
+5. Verify model compatibility
+
+## Contributing
+
+When contributing to this project:
+1. Test with the test script
+2. Verify performance
+3. Update documentation
+4. Follow existing code patterns
+5. Ensure backward compatibility
+
+## License
+
+This project is licensed under the same license as the original Superviseur bot.

commandes/autres/logger.py

@@ -4,7 +4,7 @@ from datetime import datetime
 from .config import config
 
 class ActionLogger:
-    def __init__(self, log_file: str = 'actions.log'):
+    def __init__(self, log_file: str = 'data/actions.log'):
         self.log_file = log_file
         self.logger = logging.getLogger('ActionLogger')
         self.logger.setLevel(logging.INFO)

commandes/categories/supprimer.py

@@ -1,15 +1,52 @@
 import discord
+import re
+
+def strip_emoji(text):
+    """Remove emoji characters for fuzzy matching."""
+    emoji_pattern = re.compile("["
+        u"\U0001F600-\U0001F64F\U0001F300-\U0001F5FF\U0001F680-\U0001F6FF"
+        u"\U0001F1E0-\U0001F1FF\U00002702-\U000027B0\U000024C2-\U0001F251"
+        u"\U0000FE00-\U0000FE0F\U0000200D\U0000E0100-\U0000E01EFF"
+        u"\u20E3\u00A9\u00AE\u2122"
+        "]+", flags=re.UNICODE)
+    return emoji_pattern.sub('', text).strip()
+
+async def find_category(guild, category_name_or_id):
+    """Find a category by ID or name (exact then fuzzy)."""
+    # 1. Try by ID
+    try:
+        cat_id = int(category_name_or_id)
+        cat = guild.get_channel(cat_id)
+        if cat and isinstance(cat, discord.CategoryChannel):
+            return cat
+    except (ValueError, TypeError):
+        pass
+    
+    # 2. Exact name
+    for cat in guild.categories:
+        if cat.name.casefold() == category_name_or_id.casefold():
+            return cat
+    
+    # 3. Fuzzy (strip emoji)
+    clean_search = strip_emoji(category_name_or_id).lower().strip()
+    for cat in guild.categories:
+        clean_name = strip_emoji(cat.name).lower().strip()
+        if clean_name == clean_search or (clean_search and clean_search in clean_name):
+            return cat
+    
+    return None
 
 async def execute(bot, params, message):
     categories = params.get('categories', [])
     if not categories:
-        # Fallback for single category
         categories = [params]
     guild = message.guild
     deleted_count = 0
     for category_params in categories:
-        category_name = category_params.get('category_name')
+        category_name = category_params.get('category_name') or category_params.get('category_id')
-        category = discord.utils.find(lambda cat: cat.name.casefold() == category_name.casefold(), guild.categories)
+        if not category_name:
+            continue
+        category = await find_category(guild, category_name)
         if not category:
             await message.channel.send(f"Catégorie '{category_name}' introuvable.")
             continue
@@ -19,4 +56,4 @@ async def execute(bot, params, message):
         except discord.Forbidden:
             await message.channel.send(f"Je n'ai pas les permissions pour supprimer la catégorie '{category_name}'.")
     if deleted_count > 0:
-        await message.channel.send(f"{deleted_count} catégorie(s) supprimée(s).")
+        await message.channel.send(f"{deleted_count} catégorie(s) supprimée(s).")

commandes/salons/supprimer.py

@@ -1,15 +1,66 @@
 import discord
+import re
+
+def strip_emoji(text):
+    """Remove emoji characters from channel/role names for fuzzy matching."""
+    emoji_pattern = re.compile("["
+        u"\U0001F600-\U0001F64F"  # emoticons
+        u"\U0001F300-\U0001F5FF"  # symbols & pictographs
+        u"\U0001F680-\U0001F6FF"  # transport & map symbols
+        u"\U0001F1E0-\U0001F1FF"  # flags (iOS)
+        u"\U00002702-\U000027B0"  # dingbats
+        u"\U000024C2-\U0001F251"  # misc
+        u"\U0000FE00-\U0000FE0F"  # variation selectors
+        u"\U0000200D"            # zero width joiner
+        u"\U0000E0100-\U0000E01EFF"  # variation selectors supplement
+        u"\u20E3"                # combining enclosing keycap
+        u"\u00A9\u00AE\u2122"   # copyright, registered, trademark
+        "]+", flags=re.UNICODE)
+    return emoji_pattern.sub('', text).strip()
+
+async def find_channel(guild, channel_name_or_id):
+    """Find a channel by ID first, then by name (exact, then flexible)."""
+    # 1. Try by ID
+    try:
+        ch_id = int(channel_name_or_id)
+        channel = guild.get_channel(ch_id)
+        if channel:
+            return channel
+    except (ValueError, TypeError):
+        pass
+    
+    # 2. Try exact name match (case-insensitive)
+    for ch in guild.channels:
+        if ch.name.casefold() == channel_name_or_id.casefold():
+            return ch
+    
+    # 3. Try fuzzy match (strip emojis from both sides)
+    clean_search = strip_emoji(channel_name_or_id).lower().strip()
+    for ch in guild.channels:
+        clean_name = strip_emoji(ch.name).lower().strip()
+        if clean_name == clean_search:
+            return ch
+        # 4. If the search name is contained in the channel name
+        if clean_search and clean_search in clean_name:
+            return ch
+        # 5. Or the channel name is contained in the search
+        if clean_search and clean_name in clean_search:
+            return ch
+    
+    return None
 
 async def execute(bot, params, message):
     channels = params.get('channels', [])
     if not channels:
-        # Fallback for single channel
         channels = [params]
     guild = message.guild
     deleted_count = 0
     for channel_params in channels:
-        channel_name = channel_params.get('channel_name')
+        # Support both channel_id and channel_name
-        channel = discord.utils.find(lambda c: c.name.casefold() == channel_name.casefold(), guild.channels)
+        channel_name = channel_params.get('channel_name') or channel_params.get('channel_id')
+        if not channel_name:
+            continue  # skip if no name or id
+        channel = await find_channel(guild, channel_name)
         if not channel:
             await message.channel.send(f"Salon '{channel_name}' introuvable.")
             continue

commandes/security/auto_moderation.py

@@ -9,7 +9,7 @@ import json
 import os
 from datetime import datetime
 
-WARNINGS_FILE = 'warnings.json'
+WARNINGS_FILE = 'data/warnings.json'
 
 def load_warnings():
     """Charge les avertissements depuis le fichier JSON"""

commandes/security/list_warnings.py

@@ -2,7 +2,7 @@ import discord
 import json
 import os
 
-WARNINGS_FILE = 'warnings.json'
+WARNINGS_FILE = 'data/warnings.json'
 
 def load_warnings():
     if os.path.exists(WARNINGS_FILE):

commandes/security/warn.py

@@ -4,7 +4,7 @@ import os
 import aiohttp
 from datetime import datetime
 
-WARNINGS_FILE = 'warnings.json'
+WARNINGS_FILE = 'data/warnings.json'
 
 def load_warnings():
     if os.path.exists(WARNINGS_FILE):
@@ -123,7 +123,9 @@ async def execute(bot, params, message):
         target_mention = warn_params.get('target_user_mention')
         original_reason = warn_params.get('reason', 'Aucune raison spécifiée')
         # Rephrase the reason using Ollama
-        rephrased_reason = await rephrase_reason(original_reason, bot.ollama_api_url, bot.ollama_api_key, bot.ollama_model, bot.ollama_timeout, bot.ollama_temperature)
+        ollama_url = os.environ.get("OLLAMA_BASE_URL", "http://localhost:11434") + "/api/generate"
+        ollama_model = os.environ.get("OLLAMA_MODEL", "gpt-oss:20b")
+        rephrased_reason = await rephrase_reason(original_reason, ollama_url, "", ollama_model, 30, 0.7)
         reason = rephrased_reason if rephrased_reason else original_reason
         # Parse mention or ID
         if target_mention.startswith('<@') and target_mention.endswith('>'):
@@ -168,7 +170,7 @@ async def execute(bot, params, message):
         )
         await message.channel.send(embed=embed)
         # Generate full DM message using AI with original reason for polite reformulation
-        dm_message = await generate_dm_message(original_reason, warning_count, bot.ollama_api_url, bot.ollama_api_key, bot.ollama_model, bot.ollama_timeout, bot.ollama_temperature)
+        dm_message = await generate_dm_message(original_reason, warning_count, ollama_url, "", ollama_model, 30, 0.7)
         dm_content = dm_message if dm_message else f"Avertissement : {reason}. Nombre total : {warning_count}."
         # Send DM to user
         try:

core/action_router.py

@@ -0,0 +1,158 @@
+import discord
+import logging
+from typing import Dict
+
+logger = logging.getLogger('Superviseur')
+
+class ActionRouter:
+    """Routs generated AI semantic actions to the physical Discord moderative or administrative commands."""
+    
+    def __init__(self, bot):
+        self.bot = bot
+        self._module_cache = {}
+
+    async def execute_action(self, action: str, params: Dict, message: discord.Message) -> (bool, str):
+        """Execute an action from LLM response."""
+        
+        # Normalize action name: replace spaces with underscores, uppercase
+        action = action.strip().upper().replace(' ', '_')
+        
+        # Merge nested params if LLM created a sub-object by mistake
+        for k in ['parametre', 'parametres', 'params']:
+            if k in params and isinstance(params[k], dict):
+                params.update(params[k])
+                
+        # --- INSIGHT HOOK (LLM generated task for Staff) ---
+        if action == 'INSIGHT':
+            content = params.get('message') or params.get('content') or params.get('insight') or "Pas de contenu"
+            
+            if 'conflit' in content.lower() or 'tension' in content.lower():
+                 logger.debug("Insight (Tension) logged.")
+            
+            context_data = {
+                "author_mention": message.author.mention,
+                "author_name": message.author.display_name,
+                "channel_mention": message.channel.mention if hasattr(message.channel, 'mention') else 'DM',
+                "content": message.content[:200]
+            }
+            
+            await self.bot.dispatcher.dispatch_insight(
+                insight=content,
+                importance=params.get('importance', 2),
+                guild=message.guild,
+                context_data=context_data
+            )
+            return True, None
+        # -----------------------------
+
+        # --- ALERT HOOK (LLM generated alert for Admin) ---
+        if action == 'ALERT':
+            content = params.get('message') or params.get('content') or params.get('alert') or "Alerte vide"
+            
+            embed = discord.Embed(title="🚨 ALERTE DIRECTE (IA)", description=content, color=discord.Color.red())
+            embed.set_footer(text=f"Source: {message.author.display_name} | Salon: {message.channel}")
+            
+            for admin_id in self.bot.admin_ids:
+                u = self.bot.get_user(admin_id) or await self.bot.fetch_user(admin_id)
+                if u: await u.send(embed=embed)
+                
+            return True, None
+        # -----------------------------
+
+        # --- VOICE ACTIONS ---
+        if action == 'JOIN_VOICE':
+            voice_state = getattr(message.author, 'voice', None)
+            
+            if not voice_state and self.bot.guild_id:
+                guild = self.bot.get_guild(self.bot.guild_id)
+                if guild:
+                    member = guild.get_member(message.author.id) or await guild.fetch_member(message.author.id)
+                    if member:
+                        voice_state = member.voice
+            
+            if voice_state and voice_state.channel:
+                await self.bot.voice_manager.join_channel(voice_state.channel)
+                return True, f"Connecté à {voice_state.channel.name}"
+            else:
+                return False, "Vous n'êtes pas dans un salon vocal identifiable par le système."
+        
+        if action == 'LEAVE_VOICE':
+            await self.bot.voice_manager.leave_current()
+            return True, None
+            
+        # --- PRIVACY ACTIONS ---
+        if action == 'FORGET_USER':
+            from brain.memoire import delete_user_memory
+            delete_user_memory(message.author.id)
+            return True, None
+
+        # --- PERMISSION ENFORCEMENT (ADMIN ONLY) ---
+        # Publicly accessible actions
+        PUBLIC_ACTIONS = {'PING', 'HELP', 'STATUS', 'JOIN_VOICE', 'LEAVE_VOICE', 'FORGET_USER'}
+        
+        if action not in PUBLIC_ACTIONS:
+            is_admin_id = message.author.id in self.bot.admin_ids
+            has_admin_perms = message.author.guild_permissions.administrator if hasattr(message.author, 'guild_permissions') else False
+            
+            if not (is_admin_id or has_admin_perms):
+                logger.warning(f"◈ PERMISSION DENIED: {message.author.display_name} a tenté l'action '{action}'")
+                return False, "Cette opération est réservée aux administrateurs."
+
+        action_map = {
+            'KICK': 'commandes.security.kick',
+            'BAN': 'commandes.security.ban',
+            'UNBAN': 'commandes.security.unban',
+            'UNMUTE': 'commandes.security.unmute',
+            'MUTE': 'commandes.security.mute',
+            'TIMEOUT': 'commandes.security.timeout',
+            'PURGE': 'commandes.security.purge',
+            'WARN': 'commandes.security.warn',
+            'LIST_WARNINGS': 'commandes.security.list_warnings',
+            'CREATE_CHANNEL': 'commandes.salons.creer',
+            'DELETE_CHANNEL': 'commandes.salons.supprimer',
+            'MODIFY_CHANNEL': 'commandes.salons.modifier',
+            'RENAME_CHANNEL': 'commandes.salons.renommer',
+            'MOVE_CHANNEL': 'commandes.salons.deplacer',
+            'CREATE_ROLE': 'commandes.roles.creer',
+            'DELETE_ROLE': 'commandes.roles.supprimer',
+            'MODIFY_ROLE': 'commandes.roles.modifier',
+            'RENAME_ROLE': 'commandes.roles.renommer',
+            'MOVE_ROLE': 'commandes.roles.deplacer',
+            'ADD_ROLE_TO_USER': 'commandes.roles.add_role',
+            'REMOVE_ROLE_FROM_USER': 'commandes.roles.remove_role',
+            'CREATE_CATEGORY': 'commandes.categories.creer',
+            'DELETE_CATEGORY': 'commandes.categories.supprimer',
+            'MODIFY_CATEGORY': 'commandes.categories.modifier',
+            'RENAME_CATEGORY': 'commandes.categories.renommer',
+            'MOVE_CATEGORY': 'commandes.categories.deplacer',
+            'PING': 'commandes.autres.ping',
+            'SET_WELCOME_CHANNEL': 'commandes.autres.setwelcomechannel',
+            'SET_GOODBYE_CHANNEL': 'commandes.autres.setgoodbyechannel',
+            'SET_MUTE_ROLE': 'commandes.autres.setmuterole',
+            'SEND_MESSAGE': 'commandes.autres.send_message',
+            'HELP': 'commandes.autres.help',
+            'STATUS': 'commandes.autres.status',
+        }
+        
+        module_name = action_map.get(action)
+        if module_name:
+            logger.debug(f"Importing module: {module_name}")
+            try:
+                module = self._module_cache.get(module_name)
+                if module is None:
+                    module = __import__(module_name, fromlist=['execute'])
+                    self._module_cache[module_name] = module
+                
+                logger.debug(f"Module {module_name} imported successfully")
+                await module.execute(self.bot, params, message)
+                logger.info(f"Action '{action}' executed successfully")
+                return True, None
+                
+            except Exception as e:
+                error_msg = str(e)
+                logger.error(f"Error during action execution '{action}': {error_msg}")
+                return False, error_msg
+        else:
+            error_msg = f"Unknown action: {action}"
+            logger.error(error_msg)
+            return False, error_msg

core/bot.py

@@ -0,0 +1,914 @@
+"""Main Superviseur Bot class - refactored for better organization."""
+
+import discord
+from discord.ext import commands
+import aiohttp
+import asyncio
+import os
+import time
+import json
+import logging
+import re
+from typing import Dict, Optional
+
+from .utils import format_mentions_in_text, sanitize_guild_name
+from .permissions import WhitelistManager, check_is_admin, get_permissions_info
+from .messaging import MessagingManager
+from .context import build_context_for_message
+from .llm import LLMManager
+from .redis_worker import RedisWorker
+from .commands import setup_commands
+from .voice import VoiceManager
+from .dispatcher import AssetDispatcher
+from .tasks import TaskManager
+from .action_router import ActionRouter
+import datetime
+import pytz
+
+from brain.memoire import add_interaction, build_context_for_model, flush_all, MEMORY_DIR
+from brain.moderation import init_db, log_infraction, scan_message_toxicity
+from commandes.autres.config import config
+from commandes.autres.logger import action_logger
+
+class MockMessage:
+    """Mock discord.Message for voice-triggered interactions."""
+    def __init__(self, author, channel, content, guild=None):
+        self.author = author
+        self.channel = channel
+        self.content = content
+        self.guild = guild or (channel.guild if hasattr(channel, 'guild') else None)
+        self.attachments = []
+        self.mentions = []
+        self.channel_mentions = []
+        self.role_mentions = []
+        self.jump_url = ""
+
+    async def reply(self, content, **kwargs):
+        """Mock reply - sends a message to the channel/user instead."""
+        # For vocal interaction, we don't need a prefix in DM as it's a private chat
+        is_dm = isinstance(self.channel, (discord.DMChannel, discord.User, discord.Member))
+        prefix = "" if is_dm else f"**{self.author.display_name}** (Vocal) : "
+        return await self.channel.send(f"{prefix}{content}", **kwargs)
+
+logger = logging.getLogger('Superviseur')
+
+
+class Superviseur(commands.Bot):
+    """Main bot class for Superviseur Discord bot."""
+    
+    def __init__(
+        self,
+        guild_id: int,
+        llama_model,
+        system_prompt: str,
+        command_prefix: str,
+        intents: discord.Intents,
+        temperature: float = 0.4,
+        model_loaded: bool = True
+    ):
+        super().__init__(command_prefix=command_prefix, intents=intents)
+        
+        # Configuration
+        self.guild_id = guild_id
+        self.llama_model = llama_model
+        self.system_prompt = system_prompt
+        self.temperature = temperature
+        self.model_loaded = model_loaded
+        
+        # Identity
+        self.system_name = "Bêta"
+        admins_env = os.getenv("ADMIN_IDS", "")
+        self.admin_ids = [int(i.strip()) for i in admins_env.split(",") if i.strip().isdigit()]
+        self.introspection_channel_id = int(os.getenv("INTROSPECTION_CHANNEL_ID", 0))
+        
+        # Assets (Staff)
+        assets_env = os.getenv("PRIMARY_ASSETS_IDS", "")
+        self.asset_ids = [int(i.strip()) for i in assets_env.split(",") if i.strip().isdigit()]
+        
+        # Spam Prevention
+        self.insight_cooldowns = {}  # {user_id: timestamp}
+        self.insight_cooldown_duration = 1800  # 30 minutes
+        self.insight_threshold = 5
+        self.ignored_words = {"salut", "cc", "hello", "ça va", "ca va", "bjr", "slt", "yo", "re", "ok"}
+        self.monitoring_cooldowns = {}
+        
+        # Caches
+        self.channels_list_cache = {}
+        self.server_context_cache = {}
+        self._module_cache: Dict[str, object] = {}
+        
+        # HTTP session
+        self.http_session: Optional[aiohttp.ClientSession] = None
+        
+        # Concurrency control
+        self.max_concurrent_requests = int(os.environ.get("SUPERVISEUR_MAX_CONCURRENT", 4))
+        self._request_semaphore = asyncio.Semaphore(self.max_concurrent_requests)
+        
+        # Metrics
+        self.metrics = {
+            "total_llm_requests": 0,
+            "total_llm_success": 0,
+            "total_llm_errors": 0,
+            "total_llm_time": 0.0,
+        }
+        
+        # Redis
+        self.aioredis = None
+        try:
+            import redis.asyncio as aioredis
+            self.aioredis = aioredis
+        except Exception:
+            pass
+        self.redis_worker: Optional[RedisWorker] = None
+        
+        # Whitelist
+        self.whitelist_manager = WhitelistManager()
+        
+        # Messaging
+        self.messaging = MessagingManager(self)
+        
+        # Disable command prefix for natural language focus
+        # command_prefix is set by the constructor argument (e.g. "!")
+        
+        # Voice Management
+        self.voice_manager = VoiceManager(self)
+        
+        # LLM
+        self.llm = llama_model
+        
+        # Dispatcher & Sub-managers
+        self.dispatcher = AssetDispatcher(self)
+        self.task_manager = TaskManager(self)
+        self.action_router = ActionRouter(self)
+        
+        # Init SQLite Moderation DB
+        init_db()
+        
+        # Logging avec fuseau horaire local (Europe/Paris)
+        self.timezone = pytz.timezone(os.getenv("TIMEZONE", "Europe/Paris"))
+        
+        def local_time_converter(*args):
+             return datetime.datetime.now(self.timezone).timetuple()
+             
+        logging.Formatter.converter = local_time_converter
+        logging.basicConfig(
+            level=logging.INFO, # Augmenté à INFO par défaut pour le root
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        # Sourdine sur les logs Discord trop bavards (RTCP, Gateway)
+        logging.getLogger('discord').setLevel(logging.WARNING)
+        logging.getLogger('discord.voice_state').setLevel(logging.WARNING)
+        logging.getLogger('discord.gateway').setLevel(logging.WARNING)
+        logging.getLogger('httpx').setLevel(logging.WARNING)
+        logging.getLogger('huggingface_hub').setLevel(logging.WARNING)
+        try:
+            logging.getLogger('discord.ext.voice_recv').setLevel(logging.WARNING)
+        except: pass
+    
+    # ==================== Utility Methods ====================
+    
+    async def introspection_log(self, title: str, description: str, color: discord.Color = discord.Color.light_grey()):
+        """Internal telemetry log - bypassing AI to preserve resources."""
+        if not self.introspection_channel_id: return
+        
+        channel = self.get_channel(self.introspection_channel_id) or await self.fetch_channel(self.introspection_channel_id)
+        if channel:
+            await self.messaging.send_embed(
+                channel,
+                f"INTROSPECTION: {title}",
+                description,
+                color=color
+            )
+
+    def get_user_level(self, user_id: int, user_name: Optional[str] = None) -> Optional[str]:
+        """Get user's whitelist level."""
+        return self.whitelist_manager.get_user_level(user_id, user_name)
+    
+    def has_whitelist_permission(
+        self,
+        user_id: int,
+        required_level: str,
+        user_name: Optional[str] = None
+    ) -> bool:
+        """Check whitelist permission."""
+        return self.whitelist_manager.has_permission(user_id, required_level, user_name)
+    
+    # ==================== Event Handlers ====================
+    
+    async def on_ready(self):
+        """Called when bot is ready."""
+        print(f'Logged in as {self.user}')
+
+        # Register commands
+        await setup_commands(self)
+
+        # Create memory directories
+        import os
+        for guild in self.guilds:
+            sanitized_name = sanitize_guild_name(guild.name)
+            guild_dir = os.path.join(MEMORY_DIR, sanitized_name)
+            os.makedirs(guild_dir, exist_ok=True)
+            print(f'Memory directory created for guild {guild.name}: {guild_dir}')
+
+        # Setup HTTP session (not needed for llama-cpp-python, but kept for compatibility)
+        pass
+
+        # Setup Redis
+        # Start background tasks
+        await self.voice_manager.initialize()
+        self.task_manager.start_all()
+
+    
+    async def on_member_join(self, member):
+        """Handle member join + cache invalidation."""
+        self._invalidate_caches(member.guild.id)
+        welcome_channel_id = config.get_welcome_channel(member.guild.id)
+        if welcome_channel_id:
+            channel = member.guild.get_channel(welcome_channel_id)
+            if channel:
+                embed = discord.Embed(
+                    title="Bienvenue !",
+                    description=f"Bienvenue {member.mention} sur {member.guild.name} !",
+                    color=discord.Color.green()
+                )
+                embed.set_thumbnail(url=member.avatar.url if member.avatar else member.default_avatar.url)
+                await channel.send(embed=embed)
+    
+    async def on_member_remove(self, member):
+        """Handle member leave + cache invalidation."""
+        self._invalidate_caches(member.guild.id)
+        goodbye_channel_id = config.get_goodbye_channel(member.guild.id)
+        if goodbye_channel_id:
+            channel = member.guild.get_channel(goodbye_channel_id)
+            if channel:
+                embed = discord.Embed(
+                    title="Au revoir !",
+                    description=f"{member.name} a quitté {member.guild.name}.",
+                    color=discord.Color.red()
+                )
+                embed.set_thumbnail(url=member.avatar.url if member.avatar else member.default_avatar.url)
+                await channel.send(embed=embed)
+    
+    async def on_message(self, message):
+        """Handle incoming messages."""
+        if message.author == self.user:
+            return
+
+        logger.debug(f"Message received from {message.author} in {message.channel}")
+
+        # 1. Silent Moderation Scan (Background)
+        # On ne bloque pas le bot pour l'analyse, mais on la lance pour chaque message
+        asyncio.create_task(self._handle_silent_scan(message))
+
+        # 2. DM Treatment
+        if isinstance(message.channel, discord.DMChannel):
+            processed = await self.dispatcher.handle_dm_response(message)
+            if processed: return
+            await self._handle_ai_interaction(message)
+            return
+
+        # 3. Mention/Ping Check
+        if not self._should_respond(message):
+            return
+
+        logger.info(f"◈ SYSTEM: Interaction directe détectée pour '{message.author.display_name}'")
+        # Direct interaction (AI Response)
+        await self._handle_ai_interaction(message)
+    
+    # ==================== Cache Management ====================
+    
+    def _invalidate_caches(self, guild_id: int):
+        """Invalidate caches for a guild."""
+        self.channels_list_cache.pop(guild_id, None)
+        self.server_context_cache.pop(guild_id, None)
+    
+    # Keep caches updated on changes
+    async def on_guild_channel_create(self, channel):
+        self._invalidate_caches(channel.guild.id)
+    
+    async def on_guild_channel_delete(self, channel):
+        self._invalidate_caches(channel.guild.id)
+        
+    async def on_voice_state_update(self, member, before, after):
+        """Handle voice state changes for cleanup if needed."""
+        # On-demand only, so no automatic connection logic here.
+        pass
+    
+    async def on_guild_channel_update(self, before, after):
+        self._invalidate_caches(before.guild.id)
+    
+    async def on_guild_role_create(self, role):
+        self._invalidate_caches(role.guild.id)
+    
+    async def on_guild_role_delete(self, role):
+        self._invalidate_caches(role.guild.id)
+    
+    async def on_guild_role_update(self, before, after):
+        self._invalidate_caches(before.guild.id)
+    
+    # ==================== Heuristic Engine (Risk Assessment) ====================
+    
+    # ==================== Moderation ====================
+    
+    # ==================== Moderation Silencieuse ====================
+    
+    async def _handle_silent_scan(self, message):
+        """Analyze message toxicity in the background and log to SQLite."""
+        if not message.content or len(message.content.strip()) < 3:
+            return
+            
+        try:
+            # On ne scanne que si un modèle est chargé
+            if not self.model_loaded:
+                return
+                
+            res = await scan_message_toxicity(self.llm, message.content)
+            if res and res.get('score', 0) > 0.4:
+                score = res['score']
+                reason = res.get('reason', 'N/A')
+                logger.info(f"◈ MODERATION: Infraction détectée ({score}/1.0) pour {message.author.display_name}: {reason}")
+                
+                # Enregistrement en DB
+                log_infraction(
+                    user_id=str(message.author.id),
+                    username=message.author.display_name,
+                    guild_id=str(message.guild.id) if message.guild else "DM",
+                    content=message.content,
+                    score=score,
+                    reason=reason
+                )
+        except Exception as e:
+            logger.error(f"Erreur lors du scan silencieux: {e}")
+
+    def _should_respond(self, message) -> bool:
+        """Check if bot should respond to message."""
+        if message.content.startswith(self.command_prefix):
+            return True
+        if self.user in message.mentions:
+            logger.info("◈ DEBUG: Triggered by standard mentions list")
+            return True
+        
+        # Robust Mention Check (Regex Fallback)
+        bot_id = str(self.user.id)
+        logger.info(f"◈ DEBUG: Checking mention for ID {bot_id} in '{message.content[:30]}...'")
+        
+        if f"<@{bot_id}>" in message.content or f"<@!{bot_id}>" in message.content:
+            logger.info("◈ DEBUG: Triggered by string match (Regex Fallback)")
+            return True
+        
+
+        return False
+    
+    # ==================== AI Interaction ====================
+    
+    async def _handle_ai_interaction(self, message, extra_context="", is_monitoring=False):
+        """Handle AI interaction."""
+        logger.info(f"AI interaction triggered (Monitoring: {is_monitoring})")
+        
+        # ... (same caching logic)
+        if message.guild:
+            perms = message.author.guild_permissions
+            if check_is_admin(perms):
+                self._invalidate_caches(message.guild.id)
+        
+        # Build context
+        author_perms = message.author.guild_permissions if message.guild else None
+        
+        # Détection du rôle pour le prompt
+        if message.author.id in self.admin_ids:
+            role_name = "ADMIN"
+        elif message.author.id in self.asset_ids:
+            role_name = "ASSET"
+        else:
+            role_name = "SUJET"
+
+        permissions_info = get_permissions_info(
+            author_perms,
+            self.get_user_level(message.author.id) or 'none',
+            role_name=role_name
+        )
+        channels_list, server_context = build_context_for_message(
+            message.guild,
+            self.channels_list_cache,
+            self.server_context_cache
+        )
+        
+        user_id = str(message.author.id)
+        guild_name = sanitize_guild_name(message.guild.name) if message.guild else "Direct"
+        # Limite stricte de l'historique pour éviter la saturation CPU
+        history = await build_context_for_model(user_id, max_recent=8, guild_id=guild_name) or ""
+        
+        # Prepare content
+        content = self._prepare_content(message) + extra_context
+        
+        # Build payload
+        payload = self._build_payload(permissions_info, server_context, channels_list, history, content, message)
+        
+        # Execute request
+        async with self._request_semaphore:
+            # Decider quel modèle utiliser
+            # Modèle HEAVY pour Admin/Asset ou si on lui parle directement
+            # Modèle FAST pour le monitoring pur (unloads the server)
+            is_direct = self._should_respond(message) or message.author.id in self.admin_ids
+            # For llama-cpp-python, we don't need to specify different models in payload
+            # The model is already set in the LLMManager initialization
+            
+            async def run_call():
+                if self.redis_worker:
+                    resp = await self.redis_worker.enqueue_job(payload, timeout=605)  # 10 minutes + 5 seconds
+                    return resp.get("result", "") if resp else ""
+                else:
+                    return await self.llm.call_llama(payload)
+
+            try:
+                self.metrics["total_llm_requests"] += 1
+                start = time.perf_counter()
+                
+                if is_monitoring:
+                    # Pas d'indicateur de frappe en mode surveillance
+                    accumulated_reply = await run_call()
+                else:
+                    async with message.channel.typing():
+                        accumulated_reply = await run_call()
+                
+                # --- ReAct Loop for Memory (READ_LOGS) ---
+                if "READ_LOGS" in accumulated_reply:
+                    logger.info("◈ SYSTEM: Memory access requested (READ_LOGS). Fetching logs and re-prompting...")
+                    logs_context = self.get_recent_logs()
+                    
+                    # Update payload with logs
+                    extra_memory_context = f"\n\n[SYSTÈME: Voici les logs demandés. Utilisez-les pour répondre.]\n{logs_context}"
+                    payload["prompt"] += extra_memory_context
+                    
+                    # Re-run the call with memory
+                    if is_monitoring:
+                        accumulated_reply = await run_call()
+                    else:
+                        async with message.channel.typing():
+                            accumulated_reply = await run_call()
+                # ----------------------------------------
+                
+                await self._process_response(accumulated_reply, message, is_monitoring=is_monitoring)
+                
+                dur = time.perf_counter() - start
+                self.metrics["total_llm_success"] += 1
+                self.metrics["total_llm_time"] += dur
+                
+            except Exception as e:
+                try:
+                    dur = time.perf_counter() - start
+                    self.metrics["total_llm_errors"] += 1
+                    self.metrics["total_llm_time"] += dur
+                except:
+                    pass
+                logger.error(f"LLM error: {e}")
+                if not is_monitoring:
+                    await self.messaging.reply_with_limit(message, f"Erreur: {e}")
+
+    async def handle_voice_interaction(self, user_name: str, user_id: int, content: str, channel):
+        """Bridge for real-time voice-to-text interaction."""
+        try:
+            # Create a mock objects/context for internal processing
+            mock_author = self.get_user(user_id) or await self.fetch_user(user_id)
+            if not mock_author:
+                logger.error(f"◈ SYSTEM: Voice trigger FAIL - User {user_id} ({user_name}) introuvable.")
+                return
+            
+            logger.info(f"◈ SYSTEM: Voice trigger processing for {user_name}: '{content}'")
+            
+            # Role detection
+            role_name = "ADMIN" if user_id in self.admin_ids else "ASSET" if user_id in self.asset_ids else "SUJET"
+            
+            # REFINEMENT: Only respond to Admins and Assets (Staff)
+            if role_name == "SUJET":
+                logger.info(f"◈ SYSTEM: Voice trigger ignored for SUJET {user_name}")
+                return
+
+            # Specialized context for vocal origin - FORCE PLAIN TEXT DIALOGUE
+            vocal_context = (
+                f"\n[MODE: DIALOGUE VOCAL DIRECT - PRIORITÉ ABSOLUE]\n"
+                f"L'interlocuteur {user_name} ({role_name}) vous parle à l'oral.\n"
+                f"RÈGLES CRITIQUES :\n"
+                f"1. RÉPONDEZ DIRECTEMENT en langage naturel. NE PAS UTILISER DE FORMAT JSON.\n"
+                f"2. INTERDICTION DE GÉNÉRER DES TÂCHES, INSIGHTS OU ALERTES.\n"
+                f"3. Votre réponse sera envoyée en MESSAGE PRIVÉ à cet utilisateur.\n"
+                f"4. Soyez concis, clinique et engagez la conversation.\n"
+                f"REMARQUE : Ignorez la règle 'JSON UNIQUEMENT' pour cette transmission.\n"
+            )
+            
+            # Build context
+            author_perms = mock_author.guild_permissions if hasattr(mock_author, 'guild') else None
+            permissions_info = get_permissions_info(author_perms, self.get_user_level(user_id) or 'none', role_name=role_name)
+            
+            # We don't need channel guild if we respond in DM
+            channels_list, server_context = build_context_for_message(None, self.channels_list_cache, self.server_context_cache)
+            
+            # Prepare history (DM history is better here)
+            history = await build_context_for_model(str(user_id), max_recent=12) or ""
+            
+            # Create MockMessage targeting the USER (for DM response)
+            mock_msg = MockMessage(author=mock_author, channel=mock_author, content=content)
+
+            # Prepare a specialized system prompt for vocal mode (no JSON requirement)
+            vocal_system_prompt = self.system_prompt.split("FORMAT DE RÉPONSE STRICT")[0]
+            vocal_system_prompt += (
+                "\n[PROTOCOLE VOCAL ACTIF]\n"
+                "RÉPONDEZ EXCLUSIVEMENT EN TEXTE PUR. INTERDICTION TOTALE DE GÉNÉRER DU JSON OU DES MARQUEURS.\n"
+                "Soyez concis, clinique et engagez une conversation fluide en Message Privé avec l'utilisateur."
+            )
+            
+            # Prepare payload with specialized prompt
+            payload = self.llm.build_payload(
+                prompt=f"{permissions_info}\nNom d'utilisateur : {mock_author.display_name}{server_context}{channels_list}\n{history}\n\nUser: {content}",
+                system_prompt=vocal_system_prompt,
+                vision_model=False
+            )
+            
+            async with self._request_semaphore:
+                try:
+                    analysis = await self.llm.call_llama(payload)
+                    if not analysis:
+                        logger.warning(f"◈ SYSTEM: LLM returned empty analysis for voice trigger.")
+                        return
+
+                    # --- ReAct Loop for Memory (READ_LOGS) in Voice Mode ---
+                    if "READ_LOGS" in analysis:
+                        logger.info("◈ SYSTEM: Voice memory access requested (READ_LOGS). Fetching logs...")
+                        logs_context = self.get_recent_logs()
+                        
+                        extra_memory_context = f"\n\n[SYSTÈME: Voici les logs demandés. Utilisez-les pour répondre.]\n{logs_context}"
+                        payload["prompt"] += extra_memory_context
+                        
+                        analysis = await self.llm.call_llama(payload)
+                    # ----------------------------------------------------
+                    
+                    logger.debug(f"◈ DEBUG: Raw vocal response: {analysis[:100]}...")
+                    
+                    # Use standard _process_response with mock_msg
+                    await self._process_response(analysis, mock_msg)
+                    logger.info(f"◈ SYSTEM: Voice trigger response processed for {user_name}.")
+                except Exception as e:
+                    logger.error(f"◈ SYSTEM: Error during voice trigger AI processing: {e}")
+        
+        except Exception as e:
+            logger.error(f"◈ SYSTEM: Error in handle_voice_interaction bridge: {e}")
+    
+    def _prepare_content(self, message) -> str:
+        """Prepare message content for LLM."""
+        if not message: return ""
+        content = message.content
+        
+        # Replace channel mentions <#123> -> #general
+        for channel in message.channel_mentions:
+            content = content.replace(f'<#{channel.id}>', f'#{channel.name}')
+            
+        # Replace role mentions <@&123> -> @admin
+        for role in message.role_mentions:
+            content = content.replace(f'<@&{role.id}>', f'@{role.name}')
+        
+        # Replace user mentions <@123> or <@!123> -> @User
+        for mention in message.mentions:
+            if mention.id != self.user.id:
+                content = content.replace(f'<@{mention.id}>', f'@{mention.display_name}')
+                content = content.replace(f'<@!{mention.id}>', f'@{mention.display_name}')
+        
+        # Remove bot mention
+        content = content.lstrip(f'<@{self.user.id}>').lstrip(f'<@!{self.user.id}>').strip()
+        
+        # Handle attachments
+        if message.attachments:
+            for attachment in message.attachments:
+                if attachment.content_type and attachment.content_type.startswith('image/'):
+                    content += f" [Image: {attachment.filename}]" if content else f"[Image: {attachment.filename}]"
+                else:
+                    content += f" [Fichier: {attachment.filename}]"
+        
+        return content
+    
+    def get_recent_logs(self, limit: int = 15) -> str:
+        """Read and format recent action logs for context."""
+        log_path = "data/actions.log"
+        if not os.path.exists(log_path):
+            return ""
+            
+        try:
+            with open(log_path, 'r', encoding='utf-8') as f:
+                lines = f.readlines()
+                last_lines = lines[-limit:]
+                
+            formatted_logs = []
+            for line in last_lines:
+                if "ACTION:" in line:
+                    try:
+                        parts = line.split("ACTION:", 1)
+                        if len(parts) > 1:
+                            json_str = parts[1].strip()
+                            data = json.loads(json_str)
+                            
+                            timestamp = data.get("timestamp", "").split("T")[1].split(".")[0]
+                            action = data.get("action", "UNKNOWN")
+                            user = data.get("user", "System")
+                            params = data.get("params", {})
+                            success = data.get("success", True)
+                            
+                            # Format details based on action type
+                            details = ""
+                            if action == 'SEND_MESSAGE':
+                                details = f"(to: {params.get('channel_id') or params.get('user_id')}, content: {params.get('content', '')[:20]}...)"
+                            elif 'CHANNEL' in action:
+                                # Handle channel actions (list of channels)
+                                items = params.get('channels', [])
+                                if items:
+                                    names = [i.get('channel_name', 'unknown') for i in items]
+                                    details = f"(channels: {', '.join(names)})"
+                            elif 'ROLE' in action:
+                                items = params.get('roles', [])
+                                if items:
+                                    names = [i.get('role_name', 'unknown') for i in items]
+                                    details = f"(roles: {', '.join(names)})"
+                            elif action in ['KICK', 'BAN', 'WARN', 'MUTE', 'TIMEOUT']:
+                                target = params.get('user_id', 'unknown')
+                                reason = params.get('reason', 'no reason')
+                                details = f"(target: {target}, reason: {reason})"
+                            elif action == 'PURGE':
+                                purges = params.get('purges', [])
+                                if purges:
+                                    p = purges[0]
+                                    details = f"(channel: {p.get('channel_name')}, amount: {p.get('amount')})"
+                                    
+                            status = "✅" if success else "❌"
+                            formatted_logs.append(f"[{timestamp}] {status} {action} {details} by {user}")
+                    except Exception:
+                        continue
+            
+            if not formatted_logs:
+                return ""
+                
+            return "\n[MÉMOIRE DES ACTIONS RÉCENTES (VÉRITÉ)]\n" + "\n".join(formatted_logs) + "\n"
+        except Exception as e:
+            logger.error(f"Error reading actions log: {e}")
+            return ""
+
+    def _build_payload(
+        self,
+        permissions_info: str,
+        server_context: str,
+        channels_list: str,
+        history: str,
+        content: str,
+        message
+    ) -> dict:
+        """Build LLM payload."""
+        user_name_info = f"Nom d'utilisateur : {message.author.display_name} (ID: {message.author.id})"
+        # We include server_context and channels_list so the AI can answer questions about the server
+        prompt = f"{permissions_info}\n{server_context}\n{channels_list}\n{user_name_info}\n{history}\n\nUser: {content}"
+        
+        # For llama-cpp-python, we don't need to check for vision models in the same way
+        # Vision support would need to be handled differently with llama-cpp-python
+        vision_model = False  # Simplified for now
+        
+        return self.llm.build_payload(
+            prompt=prompt,
+            system_prompt=self.system_prompt,
+            vision_model=vision_model,
+            attachments=message.attachments
+        )
+    
+    async def _process_response(self, accumulated_reply: str, message, is_monitoring=False):
+        """Process LLM response, prevent JSON leakage, and scrub technical tags."""
+        # Append closing brace if missing (safety)
+        if accumulated_reply.strip() and not accumulated_reply.strip().endswith('}'):
+            accumulated_reply = accumulated_reply.strip() + "\n}"
+
+        json_str = self.llm.extract_json_actions(accumulated_reply)
+        action_executed = False
+        
+        # 1. Nettoyer la réponse textuelle (texte hors-JSON)
+        clean_reply = accumulated_reply
+        if json_str:
+            # On retire le bloc JSON identifié
+            clean_reply = clean_reply.replace(json_str, "").strip()
+            
+        # 2. Nettoyage Universel : Suppression des balises hallucinées (<|channel|>, thought, etc.)
+        # On supprime tout ce qui est entre < > (tags techniques)
+        clean_reply = re.sub(r'<[^>]+?>', '', clean_reply)
+        
+        # 3. Nettoyage des résidus de formatage
+        clean_reply = clean_reply.replace('```json', '').replace('```', '').strip()
+        
+        # 4. Suppression des clés orphelines si le modèle a foiré le JSON
+        clean_reply = re.sub(r'[“"”\'‘](thought|action|response)[“"”\'’]\s*:\s*[“"”\'‘].*?[“"”\'’],?', '', clean_reply, flags=re.DOTALL | re.IGNORECASE)
+        
+        # 5. Retrait ultime des accolades
+        if clean_reply.strip().startswith('{') or clean_reply.strip().endswith('}'):
+             clean_reply = clean_reply.strip('{}').strip()
+            
+        clean_reply = clean_reply.strip()
+
+        is_explicit_none = False
+        responses = []
+        full_response_for_memory = ""
+        
+        if json_str:
+            try:
+                # Normalisation JSON (guillemets)
+                json_str_norm = json_str.replace('“', '"').replace('”', '"').replace('‘', "'").replace('’', "'")
+                data = json.loads(json_str_norm)
+                actions_list = data if isinstance(data, list) else [data]
+                
+                for action_data in actions_list:
+                    # Signaux BETA (Alert/Insight)
+                    await self._handle_beta_signals(action_data, message)
+                    
+                    # Normalisation des accès aux clés
+                    norm_data = {k.lower(): v for k, v in action_data.items()}
+                    
+                    if norm_data.get('action', '').upper() == 'NONE' and not norm_data.get('response'):
+                        is_explicit_none = True
+                        
+                    if norm_data.get('response'):
+                        # Scrub tags from the specific response field too
+                        resp_text = re.sub(r'<[^>]+?>', '', str(norm_data.get('response'))).strip()
+                        if resp_text:
+                            responses.append(resp_text)
+                    
+                    # Exécution des actions système
+                    res = await self._execute_actions(action_data, message, clean_reply, is_monitoring=is_monitoring)
+                    if res: action_executed = True
+            except Exception as e:
+                logger.debug(f"JSON parsing/processing error: {e}")
+                
+        # Reconstruction de la mémoire de conversation
+        final_responses_text = "\n".join(responses)
+        if final_responses_text:
+            full_response_for_memory = final_responses_text
+        elif clean_reply:
+            full_response_for_memory = clean_reply
+            
+        # Store interaction
+        user_id = str(message.author.id)
+        guild_id = sanitize_guild_name(message.guild.name) if message.guild else None
+        mem_response = full_response_for_memory if not is_monitoring else ""
+        # Nettoyage final des tags techniques pour la mémoire
+        mem_response = re.sub(r'<[^>]+?>', '', mem_response).strip()
+        await add_interaction(user_id, message.channel.id, message.content, mem_response, guild_id)
+
+        # En mode monitoring, silence sauf demande explicite
+        if is_monitoring and not action_executed:
+            return
+
+        # Envoi de la réponse finale si pas déjà fait par une action
+        if not action_executed:
+            final_output = final_responses_text if responses else clean_reply
+            # Nettoyage final avant envoi
+            final_output = re.sub(r'<[^>]+?>', '', final_output).strip()
+            
+            if final_output:
+                logger.debug(f"◈ Sending response: {final_output[:100]}...")
+                await self.messaging.reply_with_limit(message, format_mentions_in_text(final_output))
+            elif not is_monitoring:
+                # Si on a un JSON avec une response, l'extraire
+                if json_str:
+                    try:
+                        data = json.loads(json_str)
+                        actions = data if isinstance(data, list) else [data]
+                        for act in actions:
+                            resp = act.get('response', '')
+                            if resp:
+                                await self.messaging.reply_with_limit(message, format_mentions_in_text(resp))
+                                return
+                    except:
+                        pass
+                logger.debug(f"◈ Raw response was: {accumulated_reply[:200]}...")
+                fallback_msg = "Hmm, quelque chose s'est mal passé dans ma réponse. Tu peux reformuler ?"
+                await self.messaging.reply_with_limit(message, fallback_msg)
+
+    async def _handle_beta_signals(self, action_data, message):
+        """Handle Alert (Relevant) and Insight (Irrelevant) signals with full context."""
+        insight = action_data.get('insight')
+        alert = action_data.get('alert')
+        importance = action_data.get('importance', 0)
+        
+        # Préparation du bloc de données structurées
+        context_data = {
+            "author_mention": message.author.mention,
+            "author_name": message.author.display_name,
+            "channel_mention": message.channel.mention if hasattr(message.channel, 'mention') else 'DM',
+            "content": f"*{message.content[:250]}{'...' if len(message.content) > 250 else ''}*",
+            "jump_url": message.jump_url if message.jump_url else None
+        }
+
+        # 1. ALERT -> L'ADMIN (Relevant) - Triage Critique
+        if alert and self.admin_ids:
+            # Formatage de l'alerte pour l'Admin (markdown propre)
+            admin_trigger_text = (
+                f"{alert}\n\n"
+                f"**◈ CONTEXTE DÉTECTION ◈**\n"
+                f"- **Sujet** : {context_data['author_mention']} ({context_data['author_name']})\n"
+                f"- **Salon** : {context_data['channel_mention']}\n"
+                + (f"- **Lien direct** : [Accéder au message]({context_data['jump_url']})" if context_data['jump_url'] else "- **Source** : Transmission Vocale Directe")
+            )
+            
+            for admin_id in self.admin_ids:
+                admin = self.get_user(admin_id) or await self.fetch_user(admin_id)
+                if admin:
+                    await self.messaging.send_embed(
+                        admin, 
+                        f"ALERTE RELEVANT (Priorité {importance}/10)", 
+                        admin_trigger_text, 
+                        color=discord.Color.red()
+                    )
+        
+        # 2. INSIGHT -> STAFF (Irrelevant) - Triage Opérationnel
+        if insight and self.asset_ids:
+            if alert:
+                logger.warning(f"◈ ALERT RELEVANT: {alert}")
+            else:
+                if importance > 7:
+                    logger.info(f"◈ INSIGHT IRRELEVANT (High Importance {importance}): {insight[:50]}...")
+            
+            # Utilisation du Dispatcher avec données structurées
+            await self.dispatcher.dispatch_insight(insight, importance, message.guild, context_data)
+    
+    async def _execute_actions(self, action_data, message, final_content, is_monitoring=False) -> bool:
+        """Execute JSON actions and provide feedback."""
+        action_executed = False
+        
+        async def process_item(item):
+            nonlocal action_executed
+            if not isinstance(item, dict) or 'action' not in item:
+                return
+            
+            action = item['action']
+            
+            resp = item.get('response', "").strip()
+            if resp and not is_monitoring:
+                await self.messaging.reply_with_limit(message, format_mentions_in_text(resp))
+                action_executed = True
+                
+            if action != 'NONE':
+                success, result = await self.action_router.execute_action(action, item, message)
+                action_logger.log_action(action, str(message.author), str(message.guild), item, success, result)
+                
+                # Feedback to user for systemic actions if not in monitoring
+                if not is_monitoring:
+                    if success:
+                        if result: # Some actions return a success string
+                            await self.messaging.reply_with_limit(message, f"◈ SUCCESS: {result}")
+                        else:
+                            # Default success feedback for important actions if they are silent
+                            if action in ['JOIN_VOICE', 'LEAVE_VOICE', 'FORGET_USER']:
+                                confirmations = {
+                                    'JOIN_VOICE': "Signal reçu. Je rejoins le salon vocal.",
+                                    'LEAVE_VOICE': "Opération terminée. Je quitte le salon vocal.",
+                                    'FORGET_USER': "Protocole d'effacement terminé. Vos données ont été supprimées."
+                                }
+                                await self.messaging.reply_with_limit(message, f"◈ {confirmations.get(action, 'Action exécutée avec succès.')}")
+                    else:
+                        # Error feedback
+                        err_msg = result or "Une erreur est survenue lors de l'exécution."
+                        await self.messaging.reply_with_limit(message, f"◈ ERREUR: {err_msg}")
+                
+                action_executed = True
+
+        if isinstance(action_data, list):
+            executed = set()
+            for item in action_data:
+                key = json.dumps(item, sort_keys=True)
+                if key in executed: continue
+                executed.add(key)
+                await process_item(item)
+        
+        elif isinstance(action_data, dict):
+            await process_item(action_data)
+        
+        return action_executed
+    # ==================== Metrics & Cleanup ====================
+    
+    def get_metrics(self) -> Dict:
+        """Return runtime metrics."""
+        merged = {**self.metrics}
+        try:
+            from brain.memoire import get_metrics as _m
+            mem = _m()
+            merged["memory"] = mem
+        except Exception:
+            merged["memory"] = {}
+        if self.redis_worker:
+            merged["queue_pending"] = len(self.redis_worker._pending_jobs)
+        return merged
+    
+    async def close(self):
+        """Clean shutdown."""
+        try:
+            await flush_all()
+        except Exception:
+            logger.exception("Error flushing memories")
+        
+        await self.llm.close_session()
+        
+        if self.redis_worker:
+            await self.redis_worker.close()
+        
+        await super().close()
+

core/context.py

@@ -0,0 +1,93 @@
+"""Context building utilities for Superviseur bot."""
+
+import discord
+from typing import Tuple
+
+
+def build_server_context(guild: discord.Guild) -> str:
+    """Build a comprehensive context string for the server."""
+    if not guild:
+        return "\nContexte : Aucun serveur (Message Direct)."
+        
+    context = f"\nInformations sur le serveur '{guild.name}' (ID: {guild.id}):\n"
+    context += f"- Membres: {guild.member_count}\n"
+    context += f"- Propriétaire: {guild.owner.display_name if guild.owner else 'Inconnu'}\n"
+    context += f"- Créé le: {guild.created_at.strftime('%Y-%m-%d %H:%M:%S')} UTC\n"
+
+    # Channels
+    text_channels = [ch.name for ch in guild.channels if isinstance(ch, discord.TextChannel)]
+    voice_channels = [ch.name for ch in guild.channels if isinstance(ch, discord.VoiceChannel)]
+    categories = [cat.name for cat in guild.channels if isinstance(cat, discord.CategoryChannel)]
+    
+    if text_channels:
+        context += f"- Salons textes: {len(text_channels)} ({', '.join(text_channels[:5])}...)\n"
+    else:
+        context += "- Salons textes: 0\n"
+    
+    context += f"- Salons vocaux: {len(voice_channels)}\n"
+    
+    if categories:
+        context += f"- Catégories: {len(categories)} ({', '.join(categories[:3])}...)\n"
+    else:
+        context += "- Catégories: 0\n"
+
+    # Roles (except @everyone)
+    roles = [role.name for role in guild.roles[1:]]  # Skip @everyone
+    if roles:
+        context += f"- Rôles: {len(roles)}\n"
+        for role_name in roles:
+            context += f"  - {role_name}\n"
+    else:
+        context += "- Rôles: 0\n"
+
+    # Liste des membres (si le serveur n'est pas trop grand)
+    if len(guild.members) <= 200:
+        members_list = [m.display_name for m in guild.members]
+        context += f"- Tous les membres ({len(members_list)}): {', '.join(members_list)}\n"
+    else:
+        recent_members = sorted(guild.members, key=lambda m: m.joined_at or m.created_at, reverse=True)[:5]
+        context += f"- Membres récents: {', '.join([m.display_name for m in recent_members])}\n"
+
+    return context
+
+
+def build_channels_list(guild: discord.Guild) -> str:
+    """Build a formatted list of all channels with IDs."""
+    if not guild:
+        return ""
+        
+    lines = ["\nListe des salons (nom | id | type):"]
+    for ch in guild.channels:
+        if isinstance(ch, discord.TextChannel):
+            ch_type = 'textuel'
+        elif isinstance(ch, discord.VoiceChannel):
+            ch_type = 'vocal'
+        else:
+            ch_type = 'catégorie'
+        lines.append(f"- {ch.name} | {ch.id} | {ch_type}")
+    return "\n".join(lines)
+
+
+def build_context_for_message(
+    guild: discord.Guild,
+    channels_list_cache: dict,
+    server_context_cache: dict
+) -> Tuple[str, str]:
+    """Build channels list and server context with caching."""
+    if not guild:
+        return "", build_server_context(None)
+
+    guild_id = guild.id
+    
+    # Build channels list with caching
+    if guild_id not in channels_list_cache:
+        channels_list_cache[guild_id] = build_channels_list(guild)
+    channels_list = channels_list_cache[guild_id]
+
+    # Build server context with caching
+    if guild_id not in server_context_cache:
+        server_context_cache[guild_id] = build_server_context(guild)
+    server_context = server_context_cache[guild_id]
+
+    return channels_list, server_context
+

core/dispatcher.py

@@ -0,0 +1,234 @@
+import json
+import os
+import time
+import datetime
+import logging
+from typing import Dict, List, Optional
+import discord
+from .permissions import check_is_admin
+
+logger = logging.getLogger('Superviseur')
+
+ASSETS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "data", "assets_config.json")
+TASKS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "data", "active_tasks.json")
+
+class AssetDispatcher:
+    """Manages autonomous staff coordination and task assignments."""
+    
+    def __init__(self, bot):
+        self.bot = bot
+        self.assets = self._load_data(ASSETS_DATA_PATH)
+        self.tasks = self._load_data(TASKS_DATA_PATH)
+        self.interview_states = {} # {user_id: bool}
+
+    def _load_data(self, path):
+        if os.path.exists(path):
+            with open(path, 'r') as f:
+                return json.load(f)
+        return {}
+
+    def _save_data(self, data, path):
+        with open(path, 'w') as f:
+            json.dump(data, f, indent=2)
+
+    async def start_interview(self, user_id: int):
+        """Initiate the autonomous interview protocol via DM."""
+        if str(user_id) in self.assets:
+            return
+
+        user = self.bot.get_user(user_id) or await self.bot.fetch_user(user_id)
+        if not user: return
+
+        self.interview_states[user_id] = True
+        prompt = (
+            "◈ PROTOCOLE D'ENTRETIEN : ACQUISITION DE DISPONIBILITÉS ◈\n\n"
+            "Bonjour Asset Primaire. Pour optimiser la coordination du système, j'ai besoin de connaître vos disponibilités.\n"
+            "Veuillez m'indiquer vos horaires habituels (cours, travail, repos) ainsi que votre fuseau horaire.\n"
+            "Répondez-moi naturellement, je traiterai vos données."
+        )
+        await self.bot.messaging.send_embed(user, "COMMUNICATION ENTRANTE", prompt, color=discord.Color.blue(), is_asset=True)
+
+    async def handle_dm_response(self, message: discord.Message):
+        """Process natural language response from an Asset for their schedule."""
+        u_id = str(message.author.id)
+        if u_id not in self.interview_states: return False
+
+        # Indiquer que Bêta réfléchit
+        async with message.channel.typing():
+            # Use LLM to extract schedule
+            prompt = (
+                f"ANALYSE DE DISPONIBILITÉ ASSET\n"
+                f"Texte du membre : \"{message.content}\"\n\n"
+                f"FONCTION : Extraire les horaires au format JSON strict.\n"
+                f"FORMAT REQUIS :\n"
+                f"`{{\"schedule\": {{\"mon\": [[\"HH:MM\", \"HH:MM\"]], \"tue\": [], ...}}, \"timezone\": \"Europe/Paris\"}}`\n"
+                f"Note : Si l'Asset dit être libre tout le temps, laissez les jours vides []. S'il donne des heures, mettez-les.\n"
+                f"IMPORTANT: Ne répondez QUE par le bloc JSON."
+            )
+            
+            try:
+                payload = self.bot.llm.build_payload(
+                    prompt=prompt,
+                    system_prompt="Tu es un expert en extraction de données. Réponds uniquement en JSON.",
+                    force_json=True
+                )
+                resp = await self.bot.llm.call_llama(payload)
+                json_str = self.bot.llm.extract_json_actions(resp)
+                
+                if not json_str and resp.strip().startswith('{'):
+                    json_str = resp.strip()
+
+                if json_str:
+                    data = json.loads(json_str)
+                    if isinstance(data, list): data = data[0]
+                    
+                    if "schedule" in data:
+                        self.assets[u_id] = {
+                            "name": message.author.display_name,
+                            "schedule": data.get("schedule", {}),
+                            "timezone": data.get("timezone", "Europe/Paris"),
+                            "last_update": time.time()
+                        }
+                        self._save_data(self.assets, ASSETS_DATA_PATH)
+                        
+                        del self.interview_states[u_id]
+                        await self.bot.messaging.send_embed(
+                            message.author, 
+                            "INTÉGRATION RÉUSSIE", 
+                            "Vos paramètres de disponibilité ont été synchronisés avec succès. Je vous contacterai selon ces critères.", 
+                            color=discord.Color.green(),
+                            is_asset=True
+                        )
+                        return True
+                
+                # Si on arrive ici, l'extraction a échoué
+                logger.warning(f"Failed to extract schedule from: {resp}")
+                await self.bot.messaging.send_embed(
+                    message.author,
+                    "ÉCHEC D'ACQUISITION",
+                    "Je n'ai pas pu parser vos horaires. Veuillez être plus précis (ex: 'Lundi de 8h à 12h') ou vérifier le format.",
+                    color=discord.Color.orange(),
+                    is_asset=True
+                )
+            except Exception as e:
+                logger.error(f"Failed to process interview response: {e}")
+                await message.channel.send(f"◈ ERREUR CRITIQUE DURANT L'ANALYSE : {e}")
+        
+        return True
+
+    def is_available(self, user_id: int, guild: discord.Guild) -> bool:
+        """Check if an asset is available and physically present on the server."""
+        u_id = str(user_id)
+        
+        # 1. Server Presence & Permission Check (only if guild is provided)
+        if guild:
+            member = guild.get_member(user_id)
+            if not member:
+                return False
+            
+            # Verify they are ACTUALLY staff on this server
+            if not check_is_admin(member.guild_permissions):
+                # logger.warning(f"Asset {member.display_name} is present but lacks STAFF permissions on {guild.name}")
+                return False
+
+
+        # 2. Schedule Check
+        asset = self.assets.get(u_id)
+        if not asset: return True # Default available if unknown
+        
+        # Simple weekday/hour check (basic implementation)
+        now = datetime.datetime.now() # Should use asset's timezone in real impl
+        day = now.strftime("%a").lower()[:3]
+        current_time = now.strftime("%H:%M")
+        
+        schedule = asset.get("schedule", {}).get(day, [])
+        if not schedule: return True # Available if no specific "busy" blocks
+        
+        for start, end in schedule:
+            if start <= current_time <= end:
+                return False # Occupied
+        
+        return True
+
+    async def dispatch_insight(self, insight: str, importance: int, guild: discord.Guild, context_data: dict):
+        """Dispatch an insight to the best available asset."""
+        available_assets = []
+        for asset_id in self.bot.asset_ids:
+            if self.is_available(asset_id, guild):
+                available_assets.append(asset_id)
+
+        if not available_assets:
+            # Fallback to Admins if no asset available
+            for admin_id in self.bot.admin_ids:
+                admin = self.bot.get_user(admin_id) or await self.bot.fetch_user(admin_id)
+                if admin:
+                    await self.bot.messaging.send_embed(admin, "DISPATCH FALLBACK: NO ASSETS AVAILABLE", insight, color=discord.Color.gold())
+            return
+
+        # Target selection (Simple round-robin or first available for now)
+        target_id = available_assets[0]
+        target_user = self.bot.get_user(target_id) or await self.bot.fetch_user(target_id)
+        if target_user:
+            # Create Task ID and Data
+            task_id = f"task_{int(time.time())}"
+            self.tasks[task_id] = {
+                "asset_id": target_id,
+                "content": insight,
+                "importance": importance,
+                "created_at": time.time(),
+                "deadline": time.time() + (60 * (11 - importance) * 5),
+                "guild_id": guild.id if guild else None,
+                "status": "PENDING"
+            }
+            self._save_data(self.tasks, TASKS_DATA_PATH)
+
+            view = TaskAcceptView(task_id, self)
+            
+            # Création des champs d'information structurés
+            fields = [
+                {"name": "👤 Sujet", "value": f"{context_data['author_mention']} ({context_data['author_name']})", "inline": True},
+                {"name": "📍 Salon", "value": context_data['channel_mention'], "inline": True},
+                {"name": "📝 Contenu", "value": context_data['content'], "inline": False}
+            ]
+            
+            # Ajout du lien direct s'il existe
+            if context_data.get('jump_url'):
+                fields.append({"name": "🔗 Lien Direct", "value": f"[Accéder au message]({context_data['jump_url']})", "inline": False})
+            
+            desc = (
+                f"**MISSION OPÉRATIONNELLE**\n"
+                f"{insight}\n\n"
+                f"*Veuillez confirmer la prise en charge pour verrouiller la tâche.*"
+            )
+            
+            await self.bot.messaging.send_embed(
+                target_user, 
+                f"ASSIGNATION TACTIQUE (Priorité {importance}/10)", 
+                desc,
+                color=discord.Color.blue(),
+                is_asset=True,
+                fields=fields
+            )
+            # Send view separately
+            await target_user.send(view=view)
+
+class TaskAcceptView(discord.ui.View):
+    def __init__(self, task_id, dispatcher):
+        super().__init__(timeout=None)
+        self.task_id = task_id
+        self.dispatcher = dispatcher
+
+    @discord.ui.button(label="Accepter la tâche", style=discord.ButtonStyle.green)
+    async def accept(self, interaction: discord.Interaction, button: discord.ui.Button):
+        task = self.dispatcher.tasks.get(self.task_id)
+        if task:
+            task["status"] = "ACCEPTED"
+            task["accepted_at"] = time.time()
+            self.dispatcher._save_data(self.dispatcher.tasks, TASKS_DATA_PATH)
+            
+            button.disabled = True
+            button.label = "Acceptée ✅"
+            await interaction.response.edit_message(view=self)
+            await interaction.followup.send("◈ Tâche verrouillée. Bonne intervention.", ephemeral=True)
+        else:
+            await interaction.response.send_message("Tâche introuvable ou expirée.", ephemeral=True)

core/llm.py

@@ -0,0 +1,160 @@
+"""Ollama integration for Superviseur bot - replaces llama-cpp-python for better stability."""
+
+import json
+import logging
+import asyncio
+import aiohttp
+import re
+import os
+from typing import Optional, Dict, Any, List
+
+logger = logging.getLogger('Superviseur')
+
+class LLMManager:
+    """Manages LLM interactions via Ollama API."""
+    
+    def __init__(
+        self,
+        model_name: str = "gpt-oss:20b",
+        base_url: str = None,
+        temperature: float = 0.5
+    ):
+        self.model_name = model_name
+        self.base_url = base_url or os.environ.get("OLLAMA_BASE_URL", "http://localhost:11434")
+        self.temperature = temperature
+        self._lock = asyncio.Lock()
+    
+    def build_payload(
+        self,
+        prompt: str,
+        system_prompt: Optional[str] = None,
+        vision_model: bool = False,
+        attachments: Optional[list] = None,
+        force_json: bool = True
+    ) -> Dict[str, Any]:
+        """Build the payload for Ollama Generate API."""
+        return {
+            "model": self.model_name,
+            "prompt": prompt,
+            "system": system_prompt or "Tu es une IA serviable.",
+            "stream": True,  # Streaming pour voir la réponse en direct dans le terminal
+            "format": "json" if force_json else "",
+            "options": {
+                "temperature": self.temperature,
+                "num_ctx": 16384,
+                "repeat_penalty": 1.2,
+                "num_predict": 4096,
+                "top_p": 0.9,
+                "top_k": 40
+            }
+        }
+    
+    async def call_llama(self, payload: Dict[str, Any]) -> str:
+        """Call Ollama Generate API and stream response."""
+        async with self._lock:
+            try:
+                # Automatic payload conversion for legacy compatibility (e.g. from moderation.py)
+                ollama_payload = {
+                    "model": payload.get("model", self.model_name),
+                    "prompt": payload["prompt"],
+                    "system": payload.get("system", payload.get("system_prompt", "Tu es une IA serviable.")),
+                    "stream": True,  # Streaming pour voir la réponse en direct
+                    "think": False,  # Désactive le reasoning GPT-OSS
+                    "format": "",
+                    "options": {
+                        "temperature": payload.get("temperature", self.temperature),
+                        "num_ctx": payload.get("n_ctx", 16384),
+                        "num_predict": payload.get("max_tokens") or payload.get("num_predict", 8192),
+                        "repeat_penalty": payload.get("repeat_penalty") or payload.get("repeat_last_n", 1.2),
+                        "stop": payload.get("stop", [])
+                    }
+                }
+
+                accumulated_reply = ""
+                api_url = f"{self.base_url}/api/generate"
+                
+                # Build headers with optional API key
+                headers = {}
+                api_key = os.environ.get("OLLAMA_API_KEY", "")
+                if api_key:
+                    headers["Authorization"] = f"Bearer {api_key}"
+
+                async with aiohttp.ClientSession() as session:
+                    async with session.post(api_url, json=ollama_payload, headers=headers) as response:
+                        if response.status != 200:
+                            err_text = await response.text()
+                            logger.error(f"Ollama API Error ({response.status}): {err_text}")
+                            return ""
+
+                        # Streaming en direct dans le terminal
+                        async for line in response.content:
+                            if line:
+                                try:
+                                    chunk = json.loads(line)
+                                    resp = chunk.get("response", "")
+                                    if resp:
+                                        accumulated_reply += resp
+                                        print(resp, end="", flush=True)
+                                    if chunk.get("done"):
+                                        break
+                                except json.JSONDecodeError:
+                                    continue
+                        print()
+                        return accumulated_reply.strip()
+                
+            except Exception as e:
+                logger.error(f"Error calling Ollama: {e}")
+                return ""
+
+    async def close_session(self):
+        pass
+
+    def extract_json_actions(self, text: str) -> Optional[str]:
+        """
+        Extract JSON action objects from text with surgical precision.
+        Handles both single objects {...} and arrays [...].
+        Also handles // comments that GPT-OSS sometimes inserts.
+        """
+        if not text:
+            return None
+
+        text = text.strip()
+
+        # Remove // comments (GPT-OSS sometimes adds them)
+        text = re.sub(r'//.*?\n', '\n', text)
+        text = re.sub(r'//.*?$', '', text, flags=re.MULTILINE)
+
+        # 1. Try to find a JSON array [...]
+        first_bracket = text.find('[')
+        if first_bracket != -1:
+            last_bracket = text.rfind(']')
+            if last_bracket > first_bracket:
+                array_str = text[first_bracket:last_bracket+1]
+                try:
+                    json.loads(array_str)
+                    return array_str
+                except json.JSONDecodeError:
+                    pass
+
+        # 2. Try to find a JSON object {...}
+        first_brace = text.find('{')
+        if first_brace == -1:
+            return None
+            
+        last_brace = text.rfind('}')
+        if last_brace == -1 or last_brace < first_brace:
+            return None
+
+        stack = []
+        for i in range(first_brace, len(text)):
+            if text[i] == '{':
+                stack.append('{')
+            elif text[i] == '}':
+                if stack:
+                    stack.pop()
+                    if not stack:
+                        match = text[first_brace:i+1]
+                        if '"action"' in match.lower():
+                            return match
+
+        return None

core/voice.py

@@ -0,0 +1,370 @@
+import discord
+import logging
+import asyncio
+import os
+import time
+from typing import Dict, Optional, List
+from .whisper_worker import WhisperWorker
+
+logger = logging.getLogger('Superviseur')
+
+# Note: This requires discord-ext-voice-recv for actual audio capture.
+try:
+    from discord.ext import voice_recv
+    HAS_VOICE_RECV = True
+    _BaseSink = voice_recv.AudioSink
+except ImportError:
+    HAS_VOICE_RECV = False
+    _BaseSink = object # Fallback to prevent crash
+
+class BetaAudioSink(_BaseSink):
+    """Custom sink that performs manual decoding to handle Opus errors gracefully."""
+    def __init__(self, voice_manager):
+        super().__init__()
+        self.manager = voice_manager
+        self.user_buffers = {} # {id: {"name": str, "data": bytearray, "decoder": Decoder}}
+
+    def wants_opus(self) -> bool:
+        """Request Opus packets to handle decoding manually and safely."""
+        return True
+
+    def write(self, user, data):
+        if user is None: return
+        u_id = user.id
+        
+        # Initialisation du décodeur pour ce sujet si besoin
+        if u_id not in self.user_buffers:
+            logger.debug(f"◈ AudioSink: Initializing resilient decoder for {user.display_name}")
+            self.user_buffers[u_id] = {
+                "name": user.display_name, 
+                "data": bytearray(),
+                "decoder": discord.opus.Decoder()
+            }
+        
+        # Décodage manuel avec capture d'erreur
+        try:
+            # data.opus contient le paquet brut car wants_opus = True
+            pcm_data = self.user_buffers[u_id]["decoder"].decode(data.opus)
+            if pcm_data:
+                self.user_buffers[u_id]["data"].extend(pcm_data)
+        except discord.opus.OpusError:
+            # On ignore silencieusement les paquets corrompus (souvent au début)
+            pass
+        except Exception as e:
+            logger.error(f"◈ AudioSink Error: Unexpected decoding failure: {e}")
+
+    def cleanup(self):
+        self.user_buffers.clear()
+        logger.debug("◈ AudioSink: Session resources released.")
+
+class VoiceManager:
+    """Manages tactical voice channel connections and audio monitoring."""
+    HAS_VOICE_RECV = HAS_VOICE_RECV
+    
+    def __init__(self, bot):
+        self.bot = bot
+        self.active_connections: Dict[int, discord.VoiceClient] = {}
+        self.current_channel: Optional[discord.VoiceChannel] = None
+        self.whisper = WhisperWorker(device="cpu") # Stable direct fallback
+        self.is_monitoring = False
+        self._monitoring_task: Optional[asyncio.Task] = None
+        self.session_buffer: List[Dict[str, Any]] = [] # [{"user": name, "text": str, "timestamp": ts}]
+        self.session_start = 0
+        self.active_sink: Optional[BetaAudioSink] = None
+
+    async def initialize(self):
+        """Lazy load Whisper to preserve startup time."""
+        # Run in executor to not block bot ready
+        loop = asyncio.get_event_loop()
+        loop.run_in_executor(None, self.whisper.initialize)
+
+
+    async def evaluate_and_connect(self, guild):
+        """Analyze voice channels in guild and connect if strategically relevant."""
+        if self.current_channel and self.current_channel.guild == guild:
+            return
+
+        best_channel = None
+        max_members = 0
+        
+        for vc in guild.voice_channels:
+            # We count actual members, excluding bots
+            members = [m for m in vc.members if not m.bot]
+            if len(members) > max_members:
+                max_members = len(members)
+                best_channel = vc
+        
+        if best_channel and max_members >= 1: 
+            logger.info(f"◈ TACTICAL EVALUATION: Target acquired: '{best_channel.name}' in {guild.name}")
+            await self.join_channel(best_channel)
+
+    async def join_channel(self, channel: discord.VoiceChannel):
+        """Securely join a voice channel with permission checking."""
+        try:
+            # Physical authorization check
+            me = channel.guild.me
+            perms = channel.permissions_for(me)
+            if not perms.connect or not perms.view_channel:
+                logger.error(f"◈ REJECTION: Missing permissions for '{channel.name}' (CONNECT: {perms.connect}, VIEW: {perms.view_channel})")
+                await self.bot.introspection_log(
+                    "DEPLOYMENT FAILURE", 
+                    f"Permissions insuffisantes pour `{channel.name}`. Système incapable de se déployer.",
+                    discord.Color.red()
+                )
+                return
+
+            active_vc = channel.guild.voice_client
+            
+            # Si on est déjà connecté
+            if active_vc and active_vc.channel == channel:
+                # Mais qu'on n'est pas dans la bonne classe ou que le monitoring n'est pas lancé
+                if HAS_VOICE_RECV and not isinstance(active_vc, voice_recv.VoiceRecvClient):
+                    logger.info("◈ SYSTEM: Upgrading Voice Client to RecvClient.")
+                    await self.leave_current()
+                elif self.is_monitoring:
+                    return # Tout est déjà opérationnel
+                else:
+                    # On continue pour lancer le monitoring sur le vc existant
+                    vc = active_vc
+            else:
+                if active_vc:
+                    await self.leave_current()
+                
+                logger.info(f"◈ SYSTEM: Joining Voice Channel '{channel.name}' (Priority Acquisition)")
+                await self.bot.introspection_log(
+                    "VOICE DEPLOYMENT", 
+                    f"Déploiment tactique dans `{channel.name}` (Priorité identifiée).",
+                    discord.Color.blue()
+                )
+                
+                # Utilisation du client spécialisé pour la réception audio
+                connect_cls = voice_recv.VoiceRecvClient if HAS_VOICE_RECV else discord.VoiceClient
+                vc = await channel.connect(cls=connect_cls)
+            
+            self.active_connections[channel.guild.id] = vc
+            self.current_channel = channel
+            
+            if HAS_VOICE_RECV:
+                # Start the ear protocol
+                self.is_monitoring = True
+                self.session_buffer = []
+                self.session_start = time.time()
+                self.active_sink = BetaAudioSink(self)
+                self._monitoring_task = self.bot.loop.create_task(self._start_listening(vc))
+                
+        except Exception as e:
+            logger.error(f"Failed to join voice channel: {e}")
+
+    async def _start_listening(self, vc):
+        """Internal loop to capture and transcribe audio chunks."""
+        logger.info("◈ SYSTEM: Ear Protocol Engaged. Monitoring Voice Stream.")
+        
+        # On attache le sink
+        try:
+            vc.listen(self.active_sink)
+        except Exception as e:
+            logger.error(f"Failed to start listening sink: {e}")
+            return
+
+        import wave
+        import tempfile
+
+        while self.is_monitoring and vc.is_connected():
+            await asyncio.sleep(7) # Process chunks every 7s (faster response)
+            
+            # Rotation des buffers
+            current_buffers = self.active_sink.user_buffers
+            self.active_sink.user_buffers = {}
+            
+            if not current_buffers:
+                logger.debug("◈ Voice Processor: No audio data in current buffers.")
+                continue
+
+            for u_id, buffer_data in current_buffers.items():
+                data_len = len(buffer_data["data"])
+                logger.debug(f"◈ Voice Processor: Processing {data_len} bytes from {buffer_data['name']}")
+                
+                if data_len < 5000: # On monte le seuil à ~50ms pour filtrer les bruits de fond
+                    continue
+                
+                # Conversion PCM brut -> WAV (Whisper en a besoin)
+                # Discord envoie du 48kHz Stereo 16-bit PCM
+                with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
+                    tmp_path = tmp.name
+                    with wave.open(tmp_path, 'wb') as wav_file:
+                        wav_file.setnchannels(2)
+                        wav_file.setsampwidth(2)
+                        wav_file.setframerate(48000)
+                        wav_file.writeframes(buffer_data["data"])
+                
+                # Transcription
+                text = await self.whisper.transcribe(tmp_path)
+                
+                if text and len(text.strip()) > 3:
+                    logger.debug(f"◈ Logged Voice Insight: {buffer_data['name']} -> {text}")
+                    self.session_buffer.append({
+                        "user": buffer_data["name"],
+                        "text": text,
+                        "ts": time.time()
+                    })
+
+                    # NEW: Real-time Voice Trigger Detection
+                    trigger_names = ["bêta", "beta", "béta", "béat", "vêta", "veta"]
+                    if any(name in text.lower() for name in trigger_names):
+                        logger.info(f"◈ SYSTEM: Voice trigger MATCH detected in VOC: '{text}'")
+                        
+                        logger.info(f"◈ SYSTEM: Launching voice interaction bridge for {buffer_data['name']}")
+                        # We run it in a task to not block the voice processing loop
+                        # Note: we pass None for channel since bot.py will now use DMs
+                        self.bot.loop.create_task(
+                            self.bot.handle_voice_interaction(
+                                user_name=buffer_data["name"],
+                                user_id=u_id,
+                                content=text,
+                                channel=None
+                            )
+                        )
+                
+                # Cleanup
+                try: os.remove(tmp_path)
+                except: pass
+
+    async def generate_session_report(self, advanced: bool = False, custom_buffer=None):
+        """Analyze accumulated transcriptions and send a clinical summary.
+        If advanced=True, uses the heavy LLM for a deep analysis.
+        """
+        buffer = custom_buffer if custom_buffer is not None else self.session_buffer
+
+        if not buffer:
+            return "Aucune donnée vocale significative n'a été capturée durant cette session."
+
+        # ANALYSE DE TENSION (Mots-clés ou BSI bas)
+        is_tense = False
+        conflit_keywords = ["fdp", "tg", "nique", "pute", "connard", "merde", "salope"]
+        
+        tense_count = 0
+        for item in buffer:
+            if any(k in item['text'].lower() for k in conflit_keywords):
+                tense_count += 1
+        
+        if tense_count > 3: # Seuil de tension
+            is_tense = True
+            self.bot.metrics["daily_tense_sessions"] = self.bot.metrics.get("daily_tense_sessions", 0) + 1
+            logger.warning(f"◈ SYSTEM: Tense voice session detected in {self.current_channel}")
+
+        # Concatenate for analysis
+        full_transcript = "\n".join([f"{item['user']}: {item['text']}" for item in buffer])
+        channel_name = self.current_channel.name if self.current_channel else "N/A"
+        duration = int((time.time() - (self.session_start if hasattr(self, 'session_start') else time.time())) / 60)
+
+        if not advanced:
+            # Rapport périodique simple
+            report = [
+                f"**◈ VOICE SESSION STATUS (Périodique) ◈**",
+                f"Salon : `{channel_name}`",
+                f"Durée actuelle : `{duration} minutes`",
+                f"Extraits récents :\n"
+            ]
+            # On prend les 10 derniers segments
+            for item in self.session_buffer[-10:]:
+                report.append(f"- **{item['user']}** : \"{item['text'][:100]}\"")
+            return "\n".join(report)
+
+        # RAPPORT AVANCÉ (Fin de session) via HEAVY LLM
+        prompt = (
+            f"PROTOCOLE D'ANALYSE VOCALE FINALE\n"
+            f"Salon : {channel_name}\n"
+            f"Durée totale : {duration} minutes\n"
+            f"Flux de données capturé :\n---\n{full_transcript}\n---\n\n"
+            f"VOTRE MISSION :\n"
+            f"En tant que Bêta, analysez l'intégralité de ce flux. Produisez un rapport clinique structuré incluant :\n"
+            f"1. RÉSUMÉ EXÉCUTIF (Synthèse des échanges)\n"
+            f"2. IDENTIFICATION DES SUJETS (Comportements et attitudes)\n"
+            f"3. POINTS DE VIGILANCE (Alertes Relevant ou insights stratégiques)\n"
+            f"4. CONCLUSION (État de l'écosystème)\n\n"
+            f"IMPORTANT: Pour cette mission spécifique, produisez un rapport en TEXTE BRUT structuré. "
+            f"IGNOREZ la consigne habituelle de format JSON. Ne mettez AUCUN bloc JSON."
+            f"Le ton doit être froid, professionnel et factuel."
+        )
+
+        try:
+            logger.info(f"◈ SYSTEM: Generating advanced report for {channel_name} using Heavy LLM...")
+            
+            # Utilisation du manager LLM du bot
+            payload = self.bot.llm.build_payload(
+                prompt=prompt,
+                system_prompt=self.bot.system_prompt,
+                force_json=False
+            )
+            analysis = await self.bot.llm.call_llama(payload)
+            
+            # Nettoyage si jamais l'IA renvoie du JSON superflu (Bêta n'est pas censé mais on sait jamais)
+            json_str = self.bot.llm.extract_json_actions(analysis)
+            if json_str:
+                try:
+                    data = json.loads(json_str)
+                    if isinstance(data, list): data = data[0]
+                    analysis = data.get('response', analysis)
+                except: pass
+
+            return analysis
+
+        except Exception as e:
+            logger.error(f"◈ SYSTEM: Failed to generate advanced voice report: {e}")
+            return f"ERREUR ANALYSE IA GÉNÉRALE : {e}\n\n[TRANSCRIPT DE SECOURS]\n{full_transcript[:1800]}..."
+
+    async def leave_current(self, send_report=True):
+        """Disconnect immediately and handle report generation in the background."""
+        if not self.active_connections and not self.current_channel:
+            return
+
+        # 1. Capture current session data for background reporting
+        captured_buffer = list(self.session_buffer) if self.session_buffer else []
+        was_monitoring = self.is_monitoring
+        
+        # 2. CLEAR STATE IMMEDIATELY (Responsiveness)
+        self.session_buffer = []
+        self.is_monitoring = False
+        if self._monitoring_task:
+            self._monitoring_task.cancel()
+        
+        # 3. DISCONNECT IMMEDIATELY
+        for guild_id, vc in list(self.active_connections.items()):
+            try:
+                await vc.disconnect()
+            except Exception as e:
+                logger.error(f"Error disconnecting from voice: {e}")
+            del self.active_connections[guild_id]
+        
+        self.current_channel = None
+        logger.info("◈ SYSTEM: Voice Connection Terminated (Resource Preservation)")
+        
+        # 4. Background Report Generation
+        if was_monitoring and send_report and captured_buffer:
+            # We use a separate task to avoid blocking the caller (who might be waiting to join another channel)
+            self.bot.loop.create_task(self._process_background_report(captured_buffer))
+
+    async def _process_background_report(self, buffer):
+        """Internal helper to generate report without blocking the voice client."""
+        try:
+            # Temporarily restore buffer for the report generation call
+            # Note: generate_session_report uses self.session_buffer, so we might need to adapt it
+            # or pass the buffer to it. 
+            # Let's check generate_session_report signature.
+            report_text = await self.generate_session_report(advanced=True, custom_buffer=buffer)
+            
+            # 1. Envoi au canal d'introspection
+            await self.bot.introspection_log("FINAL VOICE SESSION ANALYSIS", report_text, discord.Color.blue())
+            
+            # 2. Envoi direct aux Admins 
+            for admin_id in self.bot.admin_ids:
+                admin = self.bot.get_user(admin_id) or await self.bot.fetch_user(admin_id)
+                if admin:
+                     await self.bot.messaging.send_embed(admin, "FINAL VOICE SESSION ANALYSIS", report_text, color=discord.Color.blue())
+        except Exception as e:
+            logger.error(f"◈ SYSTEM: Background report generation failed: {e}")
+        await self.bot.introspection_log(
+            "VOICE TERMINATION", 
+            "Connexion vocale terminée. Libération des ressources audio.",
+            discord.Color.dark_grey()
+        )

main.py

@@ -0,0 +1,93 @@
+"""Main entry point for Superviseur bot - refactored for Ollama stability."""
+
+import asyncio
+import logging
+import os
+import sys
+import discord
+from dotenv import load_dotenv
+
+# Import our modular components
+from core.bot import Superviseur
+from core.llm import LLMManager
+
+# Setup Logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.FileHandler("data/bot.log"),
+        logging.StreamHandler(sys.stdout)
+    ]
+)
+logger = logging.getLogger('Superviseur')
+
+# Load environment
+load_dotenv()
+
+TOKEN = os.getenv("DISCORD_TOKEN")
+GUILD_ID = os.getenv("GUILD_ID")
+
+if not TOKEN:
+    logger.error("DISCORD_TOKEN n'est pas défini dans le fichier .env")
+    exit(1)
+
+if not GUILD_ID:
+    logger.error("GUILD_ID n'est pas défini ou invalide.")
+    exit(1)
+
+# Ollama model name (from .env)
+MODEL_NAME = os.getenv("OLLAMA_MODEL", "gpt-oss:20b")
+
+async def main():
+    """Main startup sequence."""
+    logger.info("◈ SYSTEM: Initializing Superviseur with Ollama Backend...")
+    
+    # 1. Initialize LLM Manager (Connecting to Ollama service)
+    # The actual model path is managed by Ollama via Modelfile
+    llm = LLMManager(model_name=MODEL_NAME)
+    
+    # 2. Build the System Prompt
+    SYSTEM_PROMPT = (
+        "Tu es Bêta, une IA d'assistance et de modération avancée. "
+        "Tu es serviable, amical et tu réponds avec précision à TOUTES les questions des utilisateurs. "
+        "Tu as la capacité d'exécuter des actions sur le serveur Discord si l'utilisateur te le demande.\n"
+        "Tu dois TOUJOURS utiliser ce format JSON pour tes réponses :\n"
+        "Pour une seule action : {\"thought\": \"analyse\", \"action\": \"ACTION\", \"response\": \"message\", \"PARAM\": \"valeur\"}\n"
+        "Pour PLUSIEURS actions (ex: créer un salon ET un rôle), retourne une LISTE JSON d'objets :\n"
+        "[{\"thought\": \"...\", \"action\": \"CREATE_CHANNEL\", \"channel_name\": \"test\"}, {\"action\": \"CREATE_ROLE\", \"role_name\": \"test\", \"response\": \"J'ai tout créé !\"}]\n"
+        "ACTIONS possibles : NONE, JOIN_VOICE, LEAVE_VOICE, FORGET_USER, READ_LOGS, ALERT, INSIGHT, CREATE_CHANNEL, DELETE_CHANNEL, RENAME_CHANNEL, MODIFY_CHANNEL, KICK, BAN, UNBAN, MUTE, UNMUTE, TIMEOUT, WARN, PURGE, CREATE_ROLE, DELETE_ROLE, ADD_ROLE_TO_USER, REMOVE_ROLE_FROM_USER, CREATE_CATEGORY, DELETE_CATEGORY.\n"
+        "Ajoute les paramètres d'action directement à la racine de l'objet JSON de l'action."
+    )
+    
+    # 3. Initialize and Start the Bot
+    # Define required intents
+    intents = discord.Intents.default()
+    intents.message_content = True
+    intents.members = True
+    intents.voice_states = True
+    
+    bot = Superviseur(
+        llama_model=llm,
+        command_prefix="!",
+        guild_id=int(GUILD_ID),
+        system_prompt=SYSTEM_PROMPT,
+        intents=intents
+    )
+    
+    try:
+        await bot.start(TOKEN)
+    except Exception as e:
+        logger.critical(f"◈ SYSTEM: Fatal error during startup: {e}")
+    finally:
+        await bot.close()
+
+if __name__ == "__main__":
+    try:
+        # Use uvloop if available for better performance
+        import uvloop
+        asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
+    except ImportError:
+        pass
+        
+    asyncio.run(main())

requirements.txt

@@ -1,17 +1,19 @@
-PyNaCl
+# Core dependencies for Superviseur bot
 discord.py>=2.3.0
-aiohttp>=3.8.0
-aiofiles>=23.1.0
-uvloop>=0.17.0 ; python_version >= '3.8'
-fastapi>=0.95.0
-uvicorn>=0.22.0
-prometheus_client>=0.16.0
-httpx>=0.24.0
-redis>=5.3.0
-pytest>=7.0.0
-flake8>=6.0.0
 python-dotenv>=1.0.0
-psutil>=5.9.0
+aiohttp>=3.8.0
-faster-whisper
+aiofiles>=23.0.0
-git+https://github.com/imayhaveborkedit/discord-ext-voice-recv
+pytz>=2023.3
-pytz
+redis>=4.5.0
+pynacl>=1.5.0
+faster-whisper>=0.10.0
+uvloop>=0.17.0; sys_platform != "win32"
+
+# Optional dependencies for enhanced functionality
+fastapi>=0.100.0
+uvicorn[standard]>=0.20.0
+prometheus-client>=0.15.0
+
+# Development and testing
+pytest>=7.0.0
+pytest-asyncio>=0.21.0

superviseur/action_router.py

@@ -0,0 +1,144 @@
+import discord
+import logging
+from typing import Dict
+
+logger = logging.getLogger('Superviseur')
+
+class ActionRouter:
+    """Routs generated AI semantic actions to the physical Discord moderative or administrative commands."""
+    
+    def __init__(self, bot):
+        self.bot = bot
+        self._module_cache = {}
+
+    async def execute_action(self, action: str, params: Dict, message: discord.Message) -> (bool, str):
+        """Execute an action from LLM response."""
+        
+        # --- INSIGHT HOOK (LLM generated task for Staff) ---
+        if action == 'INSIGHT':
+            content = params.get('message') or params.get('content') or params.get('insight') or "Pas de contenu"
+            
+            if 'conflit' in content.lower() or 'tension' in content.lower():
+                 logger.debug("Insight (Tension) logged.")
+            
+            context_data = {
+                "author_mention": message.author.mention,
+                "author_name": message.author.display_name,
+                "channel_mention": message.channel.mention if hasattr(message.channel, 'mention') else 'DM',
+                "content": message.content[:200]
+            }
+            
+            await self.bot.dispatcher.dispatch_insight(
+                insight=content,
+                importance=params.get('importance', 2),
+                guild=message.guild,
+                context_data=context_data
+            )
+            return True, None
+        # -----------------------------
+
+        # --- ALERT HOOK (LLM generated alert for Admin) ---
+        if action == 'ALERT':
+            content = params.get('message') or params.get('content') or params.get('alert') or "Alerte vide"
+            
+            embed = discord.Embed(title="🚨 ALERTE DIRECTE (IA)", description=content, color=discord.Color.red())
+            embed.set_footer(text=f"Source: {message.author.display_name} | Salon: {message.channel}")
+            
+            for admin_id in self.bot.admin_ids:
+                u = self.bot.get_user(admin_id) or await self.bot.fetch_user(admin_id)
+                if u: await u.send(embed=embed)
+                
+            return True, None
+        # -----------------------------
+
+        # --- VOICE ACTIONS ---
+        if action == 'JOIN_VOICE':
+            voice_state = getattr(message.author, 'voice', None)
+            
+            if not voice_state and self.bot.guild_id:
+                guild = self.bot.get_guild(self.bot.guild_id)
+                if guild:
+                    member = guild.get_member(message.author.id) or await guild.fetch_member(message.author.id)
+                    if member:
+                        voice_state = member.voice
+            
+            if voice_state and voice_state.channel:
+                await self.bot.voice_manager.join_channel(voice_state.channel)
+                return True, f"Connecté à {voice_state.channel.name}"
+            else:
+                return False, "Vous n'êtes pas dans un salon vocal identifiable par le système."
+        
+        if action == 'LEAVE_VOICE':
+            await self.bot.voice_manager.leave_current()
+            return True, None
+            
+        # --- PRIVACY ACTIONS ---
+        if action == 'FORGET_USER':
+            from ia.memoire import delete_user_memory
+            delete_user_memory(message.author.id)
+            return True, None
+
+        # Check whitelist
+        if self.bot.whitelist_manager.whitelist:
+            required_level = self.bot.whitelist_manager.get_required_level(action)
+            if required_level and not self.bot.has_whitelist_permission(message.author.id, required_level):
+                return False, f"Niveau whitelist requis: {required_level}"
+        
+        action_map = {
+            'KICK': 'commandes.security.kick',
+            'BAN': 'commandes.security.ban',
+            'UNBAN': 'commandes.security.unban',
+            'UNMUTE': 'commandes.security.unmute',
+            'MUTE': 'commandes.security.mute',
+            'TIMEOUT': 'commandes.security.timeout',
+            'PURGE': 'commandes.security.purge',
+            'WARN': 'commandes.security.warn',
+            'LIST_WARNINGS': 'commandes.security.list_warnings',
+            'CREATE_CHANNEL': 'commandes.salons.creer',
+            'DELETE_CHANNEL': 'commandes.salons.supprimer',
+            'MODIFY_CHANNEL': 'commandes.salons.modifier',
+            'RENAME_CHANNEL': 'commandes.salons.renommer',
+            'MOVE_CHANNEL': 'commandes.salons.deplacer',
+            'CREATE_ROLE': 'commandes.roles.creer',
+            'DELETE_ROLE': 'commandes.roles.supprimer',
+            'MODIFY_ROLE': 'commandes.roles.modifier',
+            'RENAME_ROLE': 'commandes.roles.renommer',
+            'MOVE_ROLE': 'commandes.roles.deplacer',
+            'ADD_ROLE_TO_USER': 'commandes.roles.add_role',
+            'REMOVE_ROLE_FROM_USER': 'commandes.roles.remove_role',
+            'CREATE_CATEGORY': 'commandes.categories.creer',
+            'DELETE_CATEGORY': 'commandes.categories.supprimer',
+            'MODIFY_CATEGORY': 'commandes.categories.modifier',
+            'RENAME_CATEGORY': 'commandes.categories.renommer',
+            'MOVE_CATEGORY': 'commandes.categories.deplacer',
+            'PING': 'commandes.autres.ping',
+            'SET_WELCOME_CHANNEL': 'commandes.autres.setwelcomechannel',
+            'SET_GOODBYE_CHANNEL': 'commandes.autres.setgoodbyechannel',
+            'SET_MUTE_ROLE': 'commandes.autres.setmuterole',
+            'SEND_MESSAGE': 'commandes.autres.send_message',
+            'HELP': 'commandes.autres.help',
+            'STATUS': 'commandes.autres.status',
+        }
+        
+        module_name = action_map.get(action)
+        if module_name:
+            logger.debug(f"Importing module: {module_name}")
+            try:
+                module = self._module_cache.get(module_name)
+                if module is None:
+                    module = __import__(module_name, fromlist=['execute'])
+                    self._module_cache[module_name] = module
+                
+                logger.debug(f"Module {module_name} imported successfully")
+                await module.execute(self.bot, params, message)
+                logger.info(f"Action '{action}' executed successfully")
+                return True, None
+                
+            except Exception as e:
+                error_msg = str(e)
+                logger.error(f"Error during action execution '{action}': {error_msg}")
+                return False, error_msg
+        else:
+            error_msg = f"Unknown action: {action}"
+            logger.error(error_msg)
+            return False, error_msg

superviseur/bot.py

@@ -21,6 +21,9 @@ from .commands import setup_commands
 from .voice import VoiceManager
 from .voice import VoiceManager
 from .dispatcher import AssetDispatcher
+from .tasks import TaskManager
+from .action_router import ActionRouter
+from .heuristic import HeuristicsManager
 import datetime
 import pytz
 
@@ -58,29 +61,21 @@ class Superviseur(commands.Bot):
     def __init__(
         self,
         guild_id: int,
-        ollama_api_url: str,
+        llama_model,
-        ollama_model: str,
-        ollama_timeout: int,
         system_prompt: str,
         command_prefix: str,
         intents: discord.Intents,
-        ollama_temperature: float = 0.7,
+        temperature: float = 0.4,
-        ollama_api_key: Optional[str] = None,
+        model_loaded: bool = True
-        ollama_moderation_model: Optional[str] = None,
-        ollama_model_fast: Optional[str] = None
     ):
         super().__init__(command_prefix=command_prefix, intents=intents)
         
         # Configuration
         self.guild_id = guild_id
-        self.ollama_api_url = ollama_api_url
+        self.llama_model = llama_model
-        self.ollama_model = ollama_model
-        self.ollama_model_fast = ollama_model_fast or ollama_model
-        self.ollama_moderation_model = ollama_moderation_model or ollama_model
-        self.ollama_timeout = ollama_timeout
         self.system_prompt = system_prompt
-        self.ollama_temperature = ollama_temperature
+        self.temperature = temperature
-        self.ollama_api_key = ollama_api_key
+        self.model_loaded = model_loaded
         
         # Identity
         self.system_name = "Bêta"
@@ -142,14 +137,15 @@ class Superviseur(commands.Bot):
         
         # LLM
         self.llm = LLMManager(
-            ollama_api_url=ollama_api_url,
+            llama_model=llama_model,
-            ollama_model=ollama_model,
+            temperature=temperature
-            ollama_timeout=ollama_timeout,
-            ollama_temperature=ollama_temperature
         )
         
-        # Dispatcher
+        # Dispatcher & Sub-managers
         self.dispatcher = AssetDispatcher(self)
+        self.task_manager = TaskManager(self)
+        self.action_router = ActionRouter(self)
+        self.heuristics_manager = HeuristicsManager(self)
         
         # Logging avec fuseau horaire local (Europe/Paris)
         self.timezone = pytz.timezone(os.getenv("TIMEZONE", "Europe/Paris"))
@@ -217,156 +213,14 @@ class Superviseur(commands.Bot):
             os.makedirs(guild_dir, exist_ok=True)
             print(f'Memory directory created for guild {guild.name}: {guild_dir}')
 
-        # Setup HTTP session
+        # Setup HTTP session (not needed for llama-cpp-python, but kept for compatibility)
-        await self.llm.get_session()
+        pass
 
         # Setup Redis
         # Start background tasks
         await self.voice_manager.initialize()
-        self.loop.create_task(self._introspection_report_loop())
+        self.task_manager.start_all()
-        self.loop.create_task(self._voice_report_loop())
-        self.loop.create_task(self._voice_report_loop())
-        self.loop.create_task(self._daily_report_check_loop())
-        self.loop.create_task(self._gdpr_purge_loop())
-        
-        # Start interviews for missing assets
-        for asset_id in self.asset_ids:
-            if str(asset_id) not in self.dispatcher.assets:
-                self.loop.create_task(self.dispatcher.start_interview(asset_id))
 
-    async def _voice_evaluation_loop(self):
-        """Periodic check for tactical voice connections."""
-        await self.wait_until_ready()
-        while not self.is_closed():
-            for guild in self.guilds:
-                await self.voice_manager.evaluate_and_connect(guild)
-            await asyncio.sleep(30) # Reduit à 30s pour plus de réactivité en tâche de fond
-
-    async def _introspection_report_loop(self):
-        """Periodic broadcast of system health metrics."""
-        await self.wait_until_ready()
-        while not self.is_closed():
-            await asyncio.sleep(600) # Every 10 minutes
-            await self._send_health_report()
-
-    async def _send_health_report(self):
-        """Build and send a clinical health report embed."""
-        # Calculate success rate
-        total = self.metrics["total_llm_requests"]
-        success = self.metrics["total_llm_success"]
-        rate = (success / total * 100) if total > 0 else 100
-        avg_time = (self.metrics["total_llm_time"] / success) if success > 0 else 0
-        
-        status_report = (
-            f"**◈ INTELLIGENCE CORE**\n"
-            f"- Requests Processed : `{total}`\n"
-            f"- Reliability Rate : `{rate:.1f}%`\n"
-            f"- Latency Heuristic : `{avg_time:.2f}s` (Target: < 5s)\n\n"
-            f"**◈ TACTICAL OVERVIEW**\n"
-            f"- Voice Protocol : `READY`\n"
-            f"- Active Deployment : `{self.voice_manager.current_channel.name if self.voice_manager.current_channel else 'NONE'}`\n"
-        )
-        
-        await self.introspection_log(
-            "SYSTEM STATUS REPORT", 
-            status_report, 
-            discord.Color.dark_blue()
-        )
-
-    async def _daily_report_check_loop(self):
-        """Check for 21:30 and trigger the daily report using local timezone."""
-        await self.wait_until_ready()
-        report_sent_today = False
-        while not self.is_closed():
-            now = datetime.datetime.now(self.timezone)
-            if now.hour == 21 and now.minute == 30:
-                if not report_sent_today:
-                    await self._send_daily_summary()
-                    report_sent_today = True
-            else:
-                report_sent_today = False
-            await asyncio.sleep(60)
-            
-    async def _gdpr_purge_loop(self):
-        """Daily purge of old memory files (30 days) for GDPR compliance."""
-        from ia.memoire import purge_old_memories
-        while not self.is_closed():
-            # Run purge at 03:00 AM
-            now = datetime.datetime.now(self.timezone)
-            if now.hour == 3 and now.minute == 0:
-                logger.info("◈ RGPD: Démarrage de la purge quotidienne...")
-                deleted = await purge_old_memories(days=30)
-                logger.info(f"◈ RGPD: Purge terminée. {deleted} fichiers supprimés.")
-                await asyncio.sleep(65) # Avoid multiple triggers in the same minute
-            await asyncio.sleep(30)
-
-    async def _send_daily_summary(self):
-        """Generate and send a dense, highly detailed clinical report at 21:30."""
-        tasks = self.dispatcher.tasks
-        tense_sessions = self.metrics.get("daily_tense_sessions", 0)
-        
-        # 1. Statistiques par Asset
-        asset_stats = {} # {asset_id: {"name": str, "accepted": 0, "missed": 0}}
-        for t_id, t_data in tasks.items():
-            a_id = t_data.get("asset_id")
-            if a_id not in asset_stats:
-                asset_name = "Inconnu"
-                if str(a_id) in self.dispatcher.assets:
-                    asset_name = self.dispatcher.assets[str(a_id)].get("name", "Anonyme")
-                asset_stats[a_id] = {"name": asset_name, "accepted": 0, "missed": 0, "total": 0}
-            
-            asset_stats[a_id]["total"] += 1
-            if t_data["status"] == "ACCEPTED":
-                asset_stats[a_id]["accepted"] += 1
-            elif t_data["status"] == "PENDING" and t_data.get("deadline", 0) < time.time():
-                asset_stats[a_id]["missed"] += 1
-
-        stats_lines = []
-        for a_id, s in asset_stats.items():
-            stats_lines.append(f"- **{s['name']}** : `{s['accepted']}/{s['total']}` acceptées, `{s['missed']}` manquées.")
-
-        # 2. Liste détaillée des tâches
-        task_details = []
-        for t_id, t_data in list(tasks.items())[-15:]: # On prend les 15 dernières
-            status_emoji = "✅" if t_data["status"] == "ACCEPTED" else "❌" if t_data.get("deadline", 0) < time.time() else "⏳"
-            asset_name = self.dispatcher.assets.get(str(t_data['asset_id']), {}).get('name', 'N/A')
-            task_details.append(f"{status_emoji} `{t_id}` | Staff: {asset_name} | Urgence: {t_data['importance']} | Context: {t_data['content'][:50]}...")
-
-        summary = (
-            f"**◈ RAPPORT ANALYTIQUE DE FIN DE CYCLE ◈**\n"
-            f"Période : Dernières 24h | Heure : 21h30\n\n"
-            f"**◈ BILAN GLOBAL DES OPÉRATIONS**\n"
-            f"- Volume total d'actions de modération : `{len(tasks)}` \n"
-            f"- Sessions vocales sous tension : `{tense_sessions}`\n\n"
-            f"**◈ PERFORMANCE DES ASSETS**\n"
-            + ("\n".join(stats_lines) if stats_lines else "Aucune activité de staff enregistrée.") + "\n\n"
-            f"**◈ LOG DÉTAILLÉ DES DERNIERS SIGNAUX**\n"
-            + ("\n".join(task_details) if task_details else "Aucun signal capturé.") + "\n\n"
-            f"**◈ CONCLUSION HEURISTIQUE**\n"
-            f"Le système est nominal. " + ("PRÉCONISATION : Vigilance accrue requise sur les membres suspects." if tense_sessions > 0 else "État de l'écosystème : Stable.")
-        )
-        
-        # 4. Envoi à tous les administrateurs
-        if summary and self.admin_ids:
-            for admin_id in self.admin_ids:
-                admin = self.get_user(admin_id) or await self.fetch_user(admin_id)
-                if admin:
-                    await self.messaging.send_embed(admin, "SYNTHÈSE CLINIQUE QUOTIDIENNE", summary, color=discord.Color.dark_purple())
-        
-        # Reset pour le lendemain
-        self.metrics["daily_tense_sessions"] = 0
-        # On pourrait purger tasks ici mais on va les garder pour l'instant (ou purger les vieilles)
-        self.dispatcher.tasks = {k: v for k, v in tasks.items() if v['status'] == 'PENDING' and v.get('deadline', 0) > time.time()}
-        self.dispatcher._save_data(self.dispatcher.tasks, os.path.join(os.path.dirname(__file__), "..", "active_tasks.json"))
-
-    async def _voice_report_loop(self):
-        """Periodic broadcast of active voice session summaries."""
-        await self.wait_until_ready()
-        while not self.is_closed():
-            await asyncio.sleep(900) # Every 15 minutes
-            if self.voice_manager.is_monitoring and self.voice_manager.session_buffer:
-                report = await self.voice_manager.generate_session_report()
-                await self.introspection_log("VOICE SESSION UPDATE (15m)", report, discord.Color.blue())
     
     async def on_member_join(self, member):
         """Handle member join."""
@@ -471,104 +325,6 @@ class Superviseur(commands.Bot):
     
     # ==================== Heuristic Engine (Risk Assessment) ====================
     
-    def _assess_heuristic_risk(self, message) -> bool:
-        """
-        Fast Python-side risk assessment to decide if we should AI-analyze fully.
-        Returns True if message is 'risky' enough to warrant LLM usage.
-        """
-        score = 0
-        content = message.content
-        
-        # CLEAN content for heuristic analysis (ignore mentions in the score)
-        # We use a copy to avoid modifying the original message object
-        scoring_content = re.sub(r'<@!?\d+>', '', content).strip()
-        if not scoring_content: scoring_content = content
-        
-        # 1. Content Scoring
-        score = 0
-        
-        # Proactive Analysis: base score if message has substance
-        if len(content) > 10:
-            score += 15
-            
-        scoring_content = content
-        scoring_content_lower = scoring_content.lower()
-        
-        # CAPS LOCK detection (> 35% caps on messages > 4 chars)
-        if len(scoring_content) > 4:
-            caps_ratio = sum(1 for c in scoring_content if c.isupper()) / len(scoring_content)
-            if caps_ratio > 0.35: 
-                score += 35 # Heavy weight
-                logger.debug(f"◈ HEURISTIC: CAPS detected ({caps_ratio:.2f}) on '{scoring_content[:15]}...'")
-            
-        # Profanity / Trigger words (lightweight list)
-        triggers = [
-            "raid", "hack", "pute", "connard", "fdp", "tg", "merde", "nazi", "hitler", 
-            "suicide", "bomb", "token", "grab", "nitro", "steam", "discord.gift", "free", 
-            "@everyone", "@here", "detruire", "detruit", "destruction", "kill"
-        ]
-        for t in triggers:
-            if t in scoring_content_lower:
-                score += 50
-                logger.debug(f"◈ HEURISTIC: Trigger word '{t}' detected")
-                break
-                
-        # Link spam detection
-        if "http" in scoring_content_lower:
-            score += 20
-            
-        # Length anomaly
-        if len(scoring_content) > 300:
-            score += 20
-            
-        # 3. Gibberish / Randomness detection (Entropy)
-        if len(scoring_content) > 8:
-            unique_chars = len(set(scoring_content_lower))
-            diversity_ratio = unique_chars / len(scoring_content)
-            if diversity_ratio < 0.35: # Increased threshold
-                score += 25
-                logger.debug(f"◈ HEURISTIC: Low diversity detected ({diversity_ratio:.2f})")
-            
-            # Too many non-alphanumeric chars (excluding spaces)
-            symbols = len(re.findall(r'[^a-zA-Z0-9\s]', scoring_content))
-            symbol_ratio = symbols / len(scoring_content)
-            if symbol_ratio > 0.15: # Lowered threshold for symbols
-                score += 30
-                logger.debug(f"◈ HEURISTIC: High symbol ratio detected ({symbol_ratio:.2f})")
-                
-        # 4. Leetspeak / Digits in words detection
-        if len(re.findall(r'[a-zA-Z][0-9][a-zA-Z]', scoring_content)) > 0:
-            score += 25
-            logger.debug("◈ HEURISTIC: Leetspeak patterns detected")
-
-        # 5. Long word detection (No spaces)
-        words = scoring_content.split()
-        if any(len(w) > 25 for w in words):
-            score += 30
-            logger.debug("◈ HEURISTIC: Unusually long word detected")
-            
-        # 3. Mention Spam
-        # Fallback detection if library fails to populate message.mentions
-        mention_count = len(message.mentions)
-        if mention_count == 0:
-            mention_count = len(re.findall(r'<@!?\d+>', content))
-            
-        if mention_count > 3:
-            score += 40
-            logger.debug(f"◈ HEURISTIC: Mention spam detected ({mention_count} mentions)")
-            
-        # 4. Keyword Detection (Sensitivity helper)
-        if score < 45:
-             for trigger in ["analyse", "écouter", "surveille", "check"]:
-                 if trigger in scoring_content_lower:
-                     score += 30 
-                     break
-
-        # Threshold decision
-        # Very sensitive threshold to capture more nuances (as requested)
-        logger.info(f"◈ MODERATION RISK: Score Final = {score}/15")
-        return score >= 15
-
     # ==================== Moderation ====================
     
     async def _handle_moderation(self, message):
@@ -582,7 +338,7 @@ class Superviseur(commands.Bot):
         if len(content_low) < 3 or content_low in self.ignored_words:
             return
 
-        should_analyze = self._assess_heuristic_risk(message)
+        should_analyze = self.heuristics_manager.assess_risk(message)
         if not should_analyze:
             return
         
@@ -627,11 +383,6 @@ class Superviseur(commands.Bot):
             logger.info("◈ DEBUG: Triggered by string match (Regex Fallback)")
             return True
         
-        # Détection du nom "Bêta" ou "Beta" (insensible à la casse)
-        content_low = message.content.lower()
-        if "bêta" in content_low or "beta" in content_low:
-            logger.info("◈ DEBUG: Triggered by name match (Bêta/Beta)")
-            return True
 
         if message.reference and message.reference.resolved:
             if message.reference.resolved.author == self.user:
@@ -690,15 +441,15 @@ class Superviseur(commands.Bot):
             # Modèle HEAVY pour Admin/Asset ou si on lui parle directement
             # Modèle FAST pour le monitoring pur (unloads the server)
             is_direct = self._should_respond(message) or message.author.id in self.admin_ids
-            target_model = self.ollama_model if is_direct else self.ollama_model_fast
+            # For llama-cpp-python, we don't need to specify different models in payload
-            payload["model"] = target_model
+            # The model is already set in the LLMManager initialization
             
             async def run_call():
                 if self.redis_worker:
-                    resp = await self.redis_worker.enqueue_job(payload, timeout=self.ollama_timeout + 5)
+                    resp = await self.redis_worker.enqueue_job(payload, timeout=605)  # 10 minutes + 5 seconds
                     return resp.get("result", "") if resp else ""
                 else:
-                    return await self.llm.call_ollama(payload)
+                    return await self.llm.call_llama(payload)
 
             try:
                 self.metrics["total_llm_requests"] += 1
@@ -803,11 +554,10 @@ class Superviseur(commands.Bot):
                 system_prompt=vocal_system_prompt,
                 vision_model=False
             )
-            payload["model"] = self.ollama_model
             
             async with self._request_semaphore:
                 try:
-                    analysis = await self.llm.call_ollama(payload)
+                    analysis = await self.llm.call_llama(payload)
                     if not analysis:
                         logger.warning(f"◈ SYSTEM: LLM returned empty analysis for voice trigger.")
                         return
@@ -820,7 +570,7 @@ class Superviseur(commands.Bot):
                         extra_memory_context = f"\n\n[SYSTÈME: Voici les logs demandés. Utilisez-les pour répondre.]\n{logs_context}"
                         payload["prompt"] += extra_memory_context
                         
-                        analysis = await self.llm.call_ollama(payload)
+                        analysis = await self.llm.call_llama(payload)
                     # ----------------------------------------------------
                     
                     logger.debug(f"◈ DEBUG: Raw vocal response: {analysis[:100]}...")
@@ -868,7 +618,7 @@ class Superviseur(commands.Bot):
     
     def get_recent_logs(self, limit: int = 15) -> str:
         """Read and format recent action logs for context."""
-        log_path = "actions.log"
+        log_path = "data/actions.log"
         if not os.path.exists(log_path):
             return ""
             
@@ -941,10 +691,12 @@ class Superviseur(commands.Bot):
     ) -> dict:
         """Build LLM payload."""
         user_name_info = f"Nom d'utilisateur : {message.author.display_name} (ID: {message.author.id})"
-        prompt = f"{self.system_prompt}\n{permissions_info}\n{user_name_info}{server_context}{channels_list}\n{history}\n\nUser: {content}"
+        # Removed redundant self.system_prompt as it's passed as system_prompt in build_payload
+        prompt = f"{permissions_info}\n{user_name_info}{server_context}{channels_list}\n{history}\n\nUser: {content}"
         
-        vision_model = any(v in self.ollama_model.lower() for v in 
+        # For llama-cpp-python, we don't need to check for vision models in the same way
-                          ['llava', 'bakllava', 'moondream', 'llama3.2-vision', 'minicpm-v']) and message.attachments
+        # Vision support would need to be handled differently with llama-cpp-python
+        vision_model = False  # Simplified for now
         
         return self.llm.build_payload(
             prompt=prompt,
@@ -963,7 +715,7 @@ class Superviseur(commands.Bot):
         
         # 1. Enlever tout ce qui ressemble à du JSON de la réponse "publique"
         if json_str:
-            clean_reply = re.sub(r'\{[\s\n]*[\"\']action[\"\'].*?\}', '', clean_reply, flags=re.DOTALL).strip()
+            clean_reply = re.sub(r'\{[\s\n]*[\"\']action[\"\'].*?\}', '', clean_reply, flags=re.DOTALL | re.IGNORECASE).strip()
             
         # 2. Nettoyage des éventuels backticks de code et résidus de JSON
         clean_reply = clean_reply.replace('```json', '').replace('```', '').strip()
@@ -987,18 +739,22 @@ class Superviseur(commands.Bot):
                     clean_reply = clean_reply.replace(marker, "")
         
         # 4. Supprimer les résidus JSON rémanents avec un regex plus large
-        clean_reply = re.sub(r'\{[\s\n]*[\"\']action[\"\'].*?\}', '', clean_reply, flags=re.DOTALL)
+        clean_reply = re.sub(r'\{[\s\n]*[\"\']action[\"\'].*?\}', '', clean_reply, flags=re.DOTALL | re.IGNORECASE)
         
         # 5. Supprimer les lignes vides en trop et les espaces multiples
         clean_reply = re.sub(r'\n{3,}', '\n\n', clean_reply)
         clean_reply = clean_reply.strip()
 
+        is_explicit_none = False
         if json_str:
             try:
                 actions = json.loads(json_str)
                 if isinstance(actions, dict): actions = [actions]
                 
                 for action_data in actions:
+                    if action_data.get('action', '').upper() == 'NONE' and not action_data.get('response'):
+                        is_explicit_none = True
+                        
                     # Traitement Alerte/Insight (Toujours en DM)
                     await self._handle_beta_signals(action_data, message)
                     
@@ -1022,7 +778,7 @@ class Superviseur(commands.Bot):
         if not action_executed:
             if clean_reply:
                 await self.messaging.reply_with_limit(message, format_mentions_in_text(clean_reply))
-            elif not is_monitoring:
+            elif not is_monitoring and not is_explicit_none:
                 # Log the raw response to understand why parsing failed
                 raw_snippet = accumulated_reply.strip()
                 logger.warning(f"◈ SYSTEM: Failed to parse action or empty response. Raw output: {raw_snippet[:200]}")
@@ -1087,13 +843,14 @@ class Superviseur(commands.Bot):
                 return
             
             action = item['action']
-            if action == 'NONE':
+            
-                resp = item.get('response', "").strip()
+            resp = item.get('response', "").strip()
-                if resp and not is_monitoring:
+            if resp and not is_monitoring:
-                    await self.messaging.reply_with_limit(message, format_mentions_in_text(resp))
+                await self.messaging.reply_with_limit(message, format_mentions_in_text(resp))
-                    action_executed = True
+                action_executed = True
-            else:
+                
-                success, result = await self.execute_action(action, item, message)
+            if action != 'NONE':
+                success, result = await self.action_router.execute_action(action, item, message)
                 action_logger.log_action(action, str(message.author), str(message.guild), item, success, result)
                 
                 # Feedback to user for systemic actions if not in monitoring
@@ -1129,149 +886,6 @@ class Superviseur(commands.Bot):
             await process_item(action_data)
         
         return action_executed
-    
-    # ==================== Action Execution ====================
-    
-    async def execute_action(self, action: str, params: Dict, message) -> (bool, str):
-        """Execute an action from LLM response."""
-        
-        # --- INSIGHT HOOK (LLM generated task for Staff) ---
-        if action == 'INSIGHT':
-            # Extract content from params
-            content = params.get('message') or params.get('content') or params.get('insight') or "Pas de contenu"
-            level = params.get('level', 'STAFF')
-            
-            # Update Social Score if relevant
-            if 'conflit' in content.lower() or 'tension' in content.lower():
-                 logger.debug("Insight (Tension) logged.")
-            
-            # Dispatch
-            # We reconstruct a minimal context if not present
-            context_data = {
-                "author_mention": message.author.mention,
-                "author_name": message.author.display_name,
-                "channel_mention": message.channel.mention if hasattr(message.channel, 'mention') else 'DM',
-                "content": message.content[:200]
-            }
-            
-            await self.dispatcher.dispatch_insight(
-                content=content,
-                importance=params.get('importance', 2),
-                guild=message.guild,
-                context=context_data
-            )
-            return True, None
-        # -----------------------------
-
-        # --- ALERT HOOK (LLM generated alert for Admin) ---
-        if action == 'ALERT':
-            content = params.get('message') or params.get('content') or params.get('alert') or "Alerte vide"
-            
-            # Send to Admins
-            embed = discord.Embed(title="🚨 ALERTE DIRECTE (IA)", description=content, color=discord.Color.red())
-            embed.set_footer(text=f"Source: {message.author.display_name} | Salon: {message.channel}")
-            
-            for admin_id in self.admin_ids:
-                u = self.get_user(admin_id)
-                if u: await u.send(embed=embed)
-                
-            return True, None
-        # -----------------------------
-
-        # --- VOICE ACTIONS ---
-        if action == 'JOIN_VOICE':
-            # Resilience: check message author, but also attempt to find them in the guild 
-            # if we are in a DM interaction or if cache is stale.
-            voice_state = getattr(message.author, 'voice', None)
-            
-            if not voice_state and self.guild_id:
-                guild = self.get_guild(self.guild_id)
-                if guild:
-                    member = guild.get_member(message.author.id) or await guild.fetch_member(message.author.id)
-                    if member:
-                        voice_state = member.voice
-            
-            if voice_state and voice_state.channel:
-                await self.voice_manager.join_channel(voice_state.channel)
-                return True, f"Connecté à {voice_state.channel.name}"
-            else:
-                return False, "Vous n'êtes pas dans un salon vocal identifiable par le système."
-        
-        if action == 'LEAVE_VOICE':
-            await self.voice_manager.leave_current()
-            return True, None
-            
-        # --- PRIVACY ACTIONS ---
-        if action == 'FORGET_USER':
-            from ia.memoire import delete_user_memory
-            delete_user_memory(message.author.id)
-            return True, None
-
-        # Check whitelist
-        if self.whitelist_manager.whitelist:
-            required_level = self.whitelist_manager.get_required_level(action)
-            if required_level and not self.has_whitelist_permission(message.author.id, required_level):
-                return False, f"Niveau whitelist requis: {required_level}"
-        
-        action_map = {
-            'KICK': 'commandes.security.kick',
-            'BAN': 'commandes.security.ban',
-            'UNBAN': 'commandes.security.unban',
-            'UNMUTE': 'commandes.security.unmute',
-            'MUTE': 'commandes.security.mute',
-            'TIMEOUT': 'commandes.security.timeout',
-            'PURGE': 'commandes.security.purge',
-            'WARN': 'commandes.security.warn',
-            'LIST_WARNINGS': 'commandes.security.list_warnings',
-            'CREATE_CHANNEL': 'commandes.salons.creer',
-            'DELETE_CHANNEL': 'commandes.salons.supprimer',
-            'MODIFY_CHANNEL': 'commandes.salons.modifier',
-            'RENAME_CHANNEL': 'commandes.salons.renommer',
-            'MOVE_CHANNEL': 'commandes.salons.deplacer',
-            'CREATE_ROLE': 'commandes.roles.creer',
-            'DELETE_ROLE': 'commandes.roles.supprimer',
-            'MODIFY_ROLE': 'commandes.roles.modifier',
-            'RENAME_ROLE': 'commandes.roles.renommer',
-            'MOVE_ROLE': 'commandes.roles.deplacer',
-            'ADD_ROLE_TO_USER': 'commandes.roles.add_role',
-            'REMOVE_ROLE_FROM_USER': 'commandes.roles.remove_role',
-            'CREATE_CATEGORY': 'commandes.categories.creer',
-            'DELETE_CATEGORY': 'commandes.categories.supprimer',
-            'MODIFY_CATEGORY': 'commandes.categories.modifier',
-            'RENAME_CATEGORY': 'commandes.categories.renommer',
-            'MOVE_CATEGORY': 'commandes.categories.deplacer',
-            'PING': 'commandes.autres.ping',
-            'SET_WELCOME_CHANNEL': 'commandes.autres.setwelcomechannel',
-            'SET_GOODBYE_CHANNEL': 'commandes.autres.setgoodbyechannel',
-            'SET_MUTE_ROLE': 'commandes.autres.setmuterole',
-            'SEND_MESSAGE': 'commandes.autres.send_message',
-            'HELP': 'commandes.autres.help',
-            'STATUS': 'commandes.autres.status',
-        }
-        
-        module_name = action_map.get(action)
-        if module_name:
-            logger.debug(f"Importing module: {module_name}")
-            try:
-                module = self._module_cache.get(module_name)
-                if module is None:
-                    module = __import__(module_name, fromlist=['execute'])
-                    self._module_cache[module_name] = module
-                
-                logger.debug(f"Module {module_name} imported successfully")
-                await module.execute(self, params, message)
-                logger.info(f"Action '{action}' executed successfully")
-                return True, None
-                
-            except Exception as e:
-                error_msg = str(e)
-                logger.error(f"Error during action execution '{action}': {error_msg}")
-                return False, error_msg
-        else:
-            error_msg = f"Unknown action: {action}"
-            logger.error(error_msg)
-            return False, error_msg
-    
     # ==================== Metrics & Cleanup ====================
     
     def get_metrics(self) -> Dict:

superviseur/dispatcher.py

@@ -9,8 +9,8 @@ from .permissions import check_is_admin
 
 logger = logging.getLogger('Superviseur')
 
-ASSETS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "assets_config.json")
+ASSETS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "data", "assets_config.json")
-TASKS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "active_tasks.json")
+TASKS_DATA_PATH = os.path.join(os.path.dirname(__file__), "..", "data", "active_tasks.json")
 
 class AssetDispatcher:
     """Manages autonomous staff coordination and task assignments."""

superviseur/heuristic.py

@@ -1,4 +1,15 @@
-    def _assess_heuristic_risk(self, message) -> bool:
+import logging
+import re
+
+logger = logging.getLogger('Superviseur')
+
+class HeuristicsManager:
+    """Handles parsing and computing heuristic risk scores for messages."""
+    
+    def __init__(self, bot):
+        self.bot = bot
+
+    def assess_risk(self, message) -> bool:
         """
         Fast Python-side risk assessment to decide if we should AI-analyze fully.
         Returns True if message is 'risky' enough to warrant LLM usage.
@@ -6,41 +17,92 @@
         score = 0
         content = message.content
         
-        # 1. Social Score Factor (Base scrutiny)
+        # CLEAN content for heuristic analysis (ignore mentions in the score)
-        # If user is Suspect (<40), we start with higher risk score
+        # We use a copy to avoid modifying the original message object
-        social_data = self.social_manager.get_user_data(message.author.id)
+        scoring_content = re.sub(r'<@!?\d+>', '', content).strip()
-        reliability = social_data.get('score', 50)
+        if not scoring_content: scoring_content = content
         
-        if reliability < 30: score += 40  # Very suspicious user -> almost auto-check
+        # 1. Content Scoring
-        elif reliability < 50: score += 20
+        score = 0
         
-        # 2. Pattern Matching (Fast Regex/Keywords)
+        # Proactive Analysis: base score if message has substance
-        content_lower = content.lower()
-        
-        # CAPS LOCK detection (> 60% caps on long messages)
         if len(content) > 10:
-            caps_ratio = sum(1 for c in content if c.isupper()) / len(content)
+            score += 15
-            if caps_ratio > 0.6: score += 30
+            
+        scoring_content = content
+        scoring_content_lower = scoring_content.lower()
+        
+        # CAPS LOCK detection (> 35% caps on messages > 4 chars)
+        if len(scoring_content) > 4:
+            caps_ratio = sum(1 for c in scoring_content if c.isupper()) / len(scoring_content)
+            if caps_ratio > 0.35: 
+                score += 35 # Heavy weight
+                logger.debug(f"◈ HEURISTIC: CAPS detected ({caps_ratio:.2f}) on '{scoring_content[:15]}...'")
             
         # Profanity / Trigger words (lightweight list)
-        triggers = ["raid", "hack", "pute", "connard", "fdp", "tg", "merde", "nazi", "hitler", "suicide", "bomb", "token", "grab", "nitro", "steam", "discord.gift", "free", "@everyone", "@here"]
+        triggers = [
+            "raid", "hack", "pute", "connard", "fdp", "tg", "merde", "nazi", "hitler", 
+            "suicide", "bomb", "token", "grab", "nitro", "steam", "discord.gift", "free", 
+            "@everyone", "@here", "detruire", "detruit", "destruction", "kill"
+        ]
         for t in triggers:
-            if t in content_lower:
+            if t in scoring_content_lower:
                 score += 50
+                logger.debug(f"◈ HEURISTIC: Trigger word '{t}' detected")
                 break
                 
         # Link spam detection
-        if "http" in content_lower:
+        if "http" in scoring_content_lower:
-            score += 15
-            
-        # Length anomaly (very long messages often rants)
-        if len(content) > 400:
             score += 20
             
-        # 3. Mention Spam
+        # Length anomaly
-        if len(message.mentions) > 3:
+        if len(scoring_content) > 300:
-            score += 40
+            score += 20
             
+        # 3. Gibberish / Randomness detection (Entropy)
+        if len(scoring_content) > 8:
+            unique_chars = len(set(scoring_content_lower))
+            diversity_ratio = unique_chars / len(scoring_content)
+            if diversity_ratio < 0.35: # Increased threshold
+                score += 25
+                logger.debug(f"◈ HEURISTIC: Low diversity detected ({diversity_ratio:.2f})")
+            
+            # Too many non-alphanumeric chars (excluding spaces)
+            symbols = len(re.findall(r'[^a-zA-Z0-9\s]', scoring_content))
+            symbol_ratio = symbols / len(scoring_content)
+            if symbol_ratio > 0.15: # Lowered threshold for symbols
+                score += 30
+                logger.debug(f"◈ HEURISTIC: High symbol ratio detected ({symbol_ratio:.2f})")
+                
+        # 4. Leetspeak / Digits in words detection
+        if len(re.findall(r'[a-zA-Z][0-9][a-zA-Z]', scoring_content)) > 0:
+            score += 25
+            logger.debug("◈ HEURISTIC: Leetspeak patterns detected")
+
+        # 5. Long word detection (No spaces)
+        words = scoring_content.split()
+        if any(len(w) > 25 for w in words):
+            score += 30
+            logger.debug("◈ HEURISTIC: Unusually long word detected")
+            
+        # 3. Mention Spam
+        # Fallback detection if library fails to populate message.mentions
+        mention_count = len(message.mentions)
+        if mention_count == 0:
+            mention_count = len(re.findall(r'<@!?\d+>', content))
+            
+        if mention_count > 3:
+            score += 40
+            logger.debug(f"◈ HEURISTIC: Mention spam detected ({mention_count} mentions)")
+            
+        # 4. Keyword Detection (Sensitivity helper)
+        if score < 45:
+             for trigger in ["analyse", "écouter", "surveille", "check"]:
+                 if trigger in scoring_content_lower:
+                     score += 30 
+                     break
+
         # Threshold decision
-        # If score > 45, we analyze.
+        # Very sensitive threshold to capture more nuances (as requested)
-        return score >= 45
+        logger.info(f"◈ MODERATION RISK: Score Final = {score}/15")
+        return score >= 15

superviseur/tasks.py

@@ -0,0 +1,159 @@
+import asyncio
+import datetime
+import logging
+import time
+import os
+import discord
+
+logger = logging.getLogger('Superviseur')
+
+class TaskManager:
+    """Handles global background tasks, scheduled loops and reporting."""
+    
+    def __init__(self, bot):
+        self.bot = bot
+        
+    def start_all(self):
+        """Starts all background loops attached to the bot's event loop."""
+        self.bot.loop.create_task(self._introspection_report_loop())
+        self.bot.loop.create_task(self._voice_report_loop())
+        self.bot.loop.create_task(self._daily_report_check_loop())
+        self.bot.loop.create_task(self._gdpr_purge_loop())
+        self.bot.loop.create_task(self._voice_evaluation_loop())
+        
+        # Start interviews for missing assets
+        for asset_id in self.bot.asset_ids:
+            if str(asset_id) not in self.bot.dispatcher.assets:
+                self.bot.loop.create_task(self.bot.dispatcher.start_interview(asset_id))
+
+    async def _voice_evaluation_loop(self):
+        """Periodic check for tactical voice connections."""
+        await self.bot.wait_until_ready()
+        while not self.bot.is_closed():
+            for guild in self.bot.guilds:
+                await self.bot.voice_manager.evaluate_and_connect(guild)
+            await asyncio.sleep(30) # Reduit à 30s pour plus de réactivité en tâche de fond
+
+    async def _introspection_report_loop(self):
+        """Periodic broadcast of system health metrics."""
+        await self.bot.wait_until_ready()
+        while not self.bot.is_closed():
+            await asyncio.sleep(600) # Every 10 minutes
+            await self._send_health_report()
+
+    async def _send_health_report(self):
+        """Build and send a clinical health report embed."""
+        total = self.bot.metrics["total_llm_requests"]
+        success = self.bot.metrics["total_llm_success"]
+        rate = (success / total * 100) if total > 0 else 100
+        avg_time = (self.bot.metrics["total_llm_time"] / success) if success > 0 else 0
+        
+        status_report = (
+            f"**◈ INTELLIGENCE CORE**\n"
+            f"- Requests Processed : `{total}`\n"
+            f"- Reliability Rate : `{rate:.1f}%`\n"
+            f"- Latency Heuristic : `{avg_time:.2f}s` (Target: < 5s)\n\n"
+            f"**◈ TACTICAL OVERVIEW**\n"
+            f"- Voice Protocol : `READY`\n"
+            f"- Active Deployment : `{self.bot.voice_manager.current_channel.name if self.bot.voice_manager.current_channel else 'NONE'}`\n"
+        )
+        
+        await self.bot.introspection_log(
+            "SYSTEM STATUS REPORT", 
+            status_report, 
+            discord.Color.dark_blue()
+        )
+
+    async def _daily_report_check_loop(self):
+        """Check for 21:30 and trigger the daily report using local timezone."""
+        await self.bot.wait_until_ready()
+        report_sent_today = False
+        while not self.bot.is_closed():
+            now = datetime.datetime.now(self.bot.timezone)
+            if now.hour == 21 and now.minute == 30:
+                if not report_sent_today:
+                    await self._send_daily_summary()
+                    report_sent_today = True
+            else:
+                report_sent_today = False
+            await asyncio.sleep(60)
+            
+    async def _gdpr_purge_loop(self):
+        """Daily purge of old memory files (30 days) for GDPR compliance."""
+        from ia.memoire import purge_old_memories
+        while not self.bot.is_closed():
+            now = datetime.datetime.now(self.bot.timezone)
+            if now.hour == 3 and now.minute == 0:
+                logger.info("◈ RGPD: Démarrage de la purge quotidienne...")
+                deleted = await purge_old_memories(days=30)
+                logger.info(f"◈ RGPD: Purge terminée. {deleted} fichiers supprimés.")
+                await asyncio.sleep(65)
+            await asyncio.sleep(30)
+
+    async def _send_daily_summary(self):
+        """Generate and send a dense, highly detailed clinical report at 21:30."""
+        tasks = self.bot.dispatcher.tasks
+        tense_sessions = self.bot.metrics.get("daily_tense_sessions", 0)
+        
+        asset_stats = {} 
+        for t_id, t_data in tasks.items():
+            a_id = t_data.get("asset_id")
+            if a_id not in asset_stats:
+                asset_name = "Inconnu"
+                if str(a_id) in self.bot.dispatcher.assets:
+                    asset_name = self.bot.dispatcher.assets[str(a_id)].get("name", "Anonyme")
+                asset_stats[a_id] = {"name": asset_name, "accepted": 0, "missed": 0, "total": 0}
+            
+            asset_stats[a_id]["total"] += 1
+            if t_data["status"] == "ACCEPTED":
+                asset_stats[a_id]["accepted"] += 1
+            elif t_data["status"] == "PENDING" and t_data.get("deadline", 0) < time.time():
+                asset_stats[a_id]["missed"] += 1
+
+        stats_lines = []
+        for a_id, s in asset_stats.items():
+            stats_lines.append(f"- **{s['name']}** : `{s['accepted']}/{s['total']}` acceptées, `{s['missed']}` manquées.")
+
+        task_details = []
+        for t_id, t_data in list(tasks.items())[-15:]: 
+            status_emoji = "✅" if t_data["status"] == "ACCEPTED" else "❌" if t_data.get("deadline", 0) < time.time() else "⏳"
+            asset_name = self.bot.dispatcher.assets.get(str(t_data['asset_id']), {}).get('name', 'N/A')
+            task_details.append(f"{status_emoji} `{t_id}` | Staff: {asset_name} | Urgence: {t_data['importance']} | Context: {t_data['content'][:50]}...")
+
+        summary = (
+            f"**◈ RAPPORT ANALYTIQUE DE FIN DE CYCLE ◈**\n"
+            f"Période : Dernières 24h | Heure : 21h30\n\n"
+            f"**◈ BILAN GLOBAL DES OPÉRATIONS**\n"
+            f"- Volume total d'actions de modération : `{len(tasks)}` \n"
+            f"- Sessions vocales sous tension : `{tense_sessions}`\n\n"
+            f"**◈ PERFORMANCE DES ASSETS**\n"
+            + ("\n".join(stats_lines) if stats_lines else "Aucune activité de staff enregistrée.") + "\n\n"
+            f"**◈ LOG DÉTAILLÉ DES DERNIERS SIGNAUX**\n"
+            + ("\n".join(task_details) if task_details else "Aucun signal capturé.") + "\n\n"
+            f"**◈ CONCLUSION HEURISTIQUE**\n"
+            f"Le système est nominal. " + ("PRÉCONISATION : Vigilance accrue requise sur les membres suspects." if tense_sessions > 0 else "État de l'écosystème : Stable.")
+        )
+        
+        if summary and self.bot.admin_ids:
+            for admin_id in self.bot.admin_ids:
+                admin = self.bot.get_user(admin_id) or await self.bot.fetch_user(admin_id)
+                if admin:
+                    await self.bot.messaging.send_embed(admin, "SYNTHÈSE CLINIQUE QUOTIDIENNE", summary, color=discord.Color.dark_purple())
+        
+        self.bot.metrics["daily_tense_sessions"] = 0
+        self.bot.dispatcher.tasks = {k: v for k, v in tasks.items() if v['status'] == 'PENDING' and v.get('deadline', 0) > time.time()}
+        
+        # Le chemin de Active tasks doit être vers /data si on l'a déplacé.
+        # Pour l'instant, on sauvegarde dans data/
+        data_dir = os.path.join(os.path.dirname(__file__), "..", "data")
+        os.makedirs(data_dir, exist_ok=True)
+        self.bot.dispatcher._save_data(self.bot.dispatcher.tasks, os.path.join(data_dir, "active_tasks.json"))
+
+    async def _voice_report_loop(self):
+        """Periodic broadcast of active voice session summaries."""
+        await self.bot.wait_until_ready()
+        while not self.bot.is_closed():
+            await asyncio.sleep(900) # Every 15 minutes
+            if self.bot.voice_manager.is_monitoring and self.bot.voice_manager.session_buffer:
+                report = await self.bot.voice_manager.generate_session_report()
+                await self.bot.introspection_log("VOICE SESSION UPDATE (15m)", report, discord.Color.blue())