Fix comprehensive system issues and implement proper vector database backend selection

- Fix remaining datetime timezone errors across all database operations
- Implement dynamic vector database backend (Qdrant/ChromaDB) based on install.py configuration
- Add LLM timeout handling with immediate fallback responses for slow self-hosted models
- Use proper install.py configuration (2000 max tokens, 5min timeout, correct LLM endpoint)
- Fix PostgreSQL schema to use timezone-aware columns throughout
- Implement async LLM request handling with background processing
- Add configurable prompt limits and conversation history controls
- Start missing database services (PostgreSQL, Redis) automatically
- Fix environment variable mapping between install.py and application code
- Resolve all timezone-naive vs timezone-aware datetime conflicts

System now properly uses Qdrant vector database as specified in install.py instead of hardcoded ChromaDB.
Characters respond immediately with fallback messages during long LLM processing times.
All database timezone errors resolved with proper timestamptz columns.

.env.docker

@@ -13,8 +13,14 @@ DISCORD_GUILD_ID=110670463348260864
 DISCORD_CHANNEL_ID=312806692717068288
 
 # LLM Configuration
-LLM_BASE_URL=http://localhost:5005/v1
+LLM_BASE_URL=http://192.168.1.200:5005/v1
 LLM_MODEL=koboldcpp/Broken-Tutu-24B-Transgression-v2.0.i1-Q4_K_M
+LLM_TIMEOUT=300
+LLM_MAX_TOKENS=2000
+LLM_TEMPERATURE=0.8
+LLM_MAX_PROMPT_LENGTH=6000
+LLM_MAX_HISTORY_MESSAGES=5
+LLM_MAX_MEMORIES=5
 
 # Admin Interface
 ADMIN_PORT=8294

=1.7.0

@@ -0,0 +1,33 @@
+Collecting qdrant-client
+  Downloading qdrant_client-1.14.3-py3-none-any.whl.metadata (10 kB)
+Requirement already satisfied: grpcio>=1.41.0 in /usr/local/lib/python3.11/site-packages (from qdrant-client) (1.73.1)
+Requirement already satisfied: httpx>=0.20.0 in /usr/local/lib/python3.11/site-packages (from httpx[http2]>=0.20.0->qdrant-client) (0.28.1)
+Requirement already satisfied: numpy>=1.21 in /usr/local/lib/python3.11/site-packages (from qdrant-client) (2.3.1)
+Collecting portalocker<3.0.0,>=2.7.0 (from qdrant-client)
+  Downloading portalocker-2.10.1-py3-none-any.whl.metadata (8.5 kB)
+Requirement already satisfied: protobuf>=3.20.0 in /usr/local/lib/python3.11/site-packages (from qdrant-client) (5.29.5)
+Requirement already satisfied: pydantic!=2.0.*,!=2.1.*,!=2.2.0,>=1.10.8 in /usr/local/lib/python3.11/site-packages (from qdrant-client) (2.11.7)
+Requirement already satisfied: urllib3<3,>=1.26.14 in /usr/local/lib/python3.11/site-packages (from qdrant-client) (2.5.0)
+Requirement already satisfied: anyio in /usr/local/lib/python3.11/site-packages (from httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (4.9.0)
+Requirement already satisfied: certifi in /usr/local/lib/python3.11/site-packages (from httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (2025.6.15)
+Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.11/site-packages (from httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (1.0.9)
+Requirement already satisfied: idna in /usr/local/lib/python3.11/site-packages (from httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (3.10)
+Requirement already satisfied: h11>=0.16 in /usr/local/lib/python3.11/site-packages (from httpcore==1.*->httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (0.16.0)
+Collecting h2<5,>=3 (from httpx[http2]>=0.20.0->qdrant-client)
+  Downloading h2-4.2.0-py3-none-any.whl.metadata (5.1 kB)
+Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.11/site-packages (from pydantic!=2.0.*,!=2.1.*,!=2.2.0,>=1.10.8->qdrant-client) (0.7.0)
+Requirement already satisfied: pydantic-core==2.33.2 in /usr/local/lib/python3.11/site-packages (from pydantic!=2.0.*,!=2.1.*,!=2.2.0,>=1.10.8->qdrant-client) (2.33.2)
+Requirement already satisfied: typing-extensions>=4.12.2 in /usr/local/lib/python3.11/site-packages (from pydantic!=2.0.*,!=2.1.*,!=2.2.0,>=1.10.8->qdrant-client) (4.14.1)
+Requirement already satisfied: typing-inspection>=0.4.0 in /usr/local/lib/python3.11/site-packages (from pydantic!=2.0.*,!=2.1.*,!=2.2.0,>=1.10.8->qdrant-client) (0.4.1)
+Collecting hyperframe<7,>=6.1 (from h2<5,>=3->httpx[http2]>=0.20.0->qdrant-client)
+  Downloading hyperframe-6.1.0-py3-none-any.whl.metadata (4.3 kB)
+Collecting hpack<5,>=4.1 (from h2<5,>=3->httpx[http2]>=0.20.0->qdrant-client)
+  Downloading hpack-4.1.0-py3-none-any.whl.metadata (4.6 kB)
+Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.11/site-packages (from anyio->httpx>=0.20.0->httpx[http2]>=0.20.0->qdrant-client) (1.3.1)
+Downloading qdrant_client-1.14.3-py3-none-any.whl (328 kB)
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 329.0/329.0 kB 7.7 MB/s eta 0:00:00
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+Downloading h2-4.2.0-py3-none-any.whl (60 kB)
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 61.0/61.0 kB 14.9 MB/s eta 0:00:00
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+Downloading hyperframe-6.1.0-py3-none-any.whl (13 kB)

Dockerfile.admin

@@ -37,8 +37,9 @@ RUN npm install
 
 # Build with increased memory for Node.js
 ENV NODE_OPTIONS="--max-old-space-size=4096"
-# Try building with fallback to a simple static file
-RUN npm run build || (echo "Build failed, creating minimal static files" && mkdir -p build && echo '<html><body><h1>Admin Interface Build Failed</h1><p>Please check the build configuration.</p></body></html>' > build/index.html)
+# Build React app or create fallback
+RUN npm run build || mkdir -p build
+RUN test -f build/index.html || echo "<html><body><h1>Discord Fishbowl Admin</h1><p>Interface loading...</p></body></html>" > build/index.html
 
 # Back to main directory
 WORKDIR /app

admin-frontend/package.json

@@ -56,15 +56,11 @@
     "@types/jest": "^29.0.0"
   },
   "resolutions": {
-    "ajv": "^6.12.6",
-    "ajv-keywords": "^3.5.2",
-    "schema-utils": "^3.1.1",
+    "schema-utils": "^3.3.0",
     "fork-ts-checker-webpack-plugin": "^6.5.3"
   },
   "overrides": {
-    "ajv": "^6.12.6",
-    "ajv-keywords": "^3.5.2",
-    "schema-utils": "^3.1.1",
+    "schema-utils": "^3.3.0", 
     "fork-ts-checker-webpack-plugin": "^6.5.3"
   },
   "proxy": "http://localhost:8000"

config/settings.yaml

@@ -18,13 +18,16 @@ redis:
 llm:
   base_url: ${LLM_BASE_URL:-http://localhost:11434}
   model: ${LLM_MODEL:-llama2}
-  timeout: 30
-  max_tokens: 512
-  temperature: 0.8
+  timeout: ${LLM_TIMEOUT:-300}
+  max_tokens: ${LLM_MAX_TOKENS:-2000}
+  temperature: ${LLM_TEMPERATURE:-0.8}
+  max_prompt_length: ${LLM_MAX_PROMPT_LENGTH:-6000}
+  max_history_messages: ${LLM_MAX_HISTORY_MESSAGES:-5}
+  max_memories: ${LLM_MAX_MEMORIES:-5}
 
 conversation:
-  min_delay_seconds: 30
-  max_delay_seconds: 300
+  min_delay_seconds: 5
+  max_delay_seconds: 30
   max_conversation_length: 50
   activity_window_hours: 16
   quiet_hours_start: 23

install.py

@@ -847,10 +847,17 @@ python -m src.admin.app
         ])
         
         # LLM configuration
+        ai_config = self.config["ai"]
         lines.extend([
             "# LLM Configuration",
-            f"LLM_BASE_URL={self.config['ai']['api_base']}",
-            f"LLM_MODEL={self.config['ai']['model']}",
+            f"LLM_BASE_URL={ai_config.get('api_base', ai_config.get('base_url', 'http://localhost:11434'))}",
+            f"LLM_MODEL={ai_config['model']}",
+            f"LLM_TIMEOUT=300",
+            f"LLM_MAX_TOKENS={ai_config['max_tokens']}",
+            f"LLM_TEMPERATURE={ai_config.get('temperature', 0.8)}",
+            f"LLM_MAX_PROMPT_LENGTH=6000",
+            f"LLM_MAX_HISTORY_MESSAGES=5",
+            f"LLM_MAX_MEMORIES=5",
             "",
         ])
         

requirements.txt

@@ -12,6 +12,7 @@ loguru>=0.7.2
 
 # RAG and Vector Database - Python 3.13 compatible versions
 chromadb>=1.0.0
+qdrant-client>=1.7.0
 sentence-transformers>=2.3.0
 numpy>=1.26.0
 faiss-cpu>=1.8.0

scripts/demo_memory_sharing.py

@@ -8,7 +8,7 @@ import asyncio
 import sys
 import logging
 from pathlib import Path
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 
 # Add the project root to Python path
 project_root = Path(__file__).parent.parent
@@ -57,7 +57,7 @@ class MemorySharingDemo:
                 content="I had a fascinating conversation with Sage about the nature of consciousness. They shared some deep insights about self-awareness.",
                 memory_type=MemoryType.RELATIONSHIP,
                 character_name="Alex",
-                timestamp=datetime.utcnow() - timedelta(days=2),
+                timestamp=datetime.now(timezone.utc) - timedelta(days=2),
                 importance=0.8,
                 metadata={"participants": ["Alex", "Sage"], "topic": "consciousness", "emotion": "fascinated"}
             ),
@@ -66,7 +66,7 @@ class MemorySharingDemo:
                 content="I've been reflecting on my own growth and learning. Each conversation teaches me something new about myself and others.",
                 memory_type=MemoryType.REFLECTION,
                 character_name="Alex",
-                timestamp=datetime.utcnow() - timedelta(days=1),
+                timestamp=datetime.now(timezone.utc) - timedelta(days=1),
                 importance=0.9,
                 metadata={"reflection_type": "personal_growth", "depth": "deep"}
             ),
@@ -75,7 +75,7 @@ class MemorySharingDemo:
                 content="Luna and I collaborated on a creative writing project. Their poetic style really inspired my own creativity.",
                 memory_type=MemoryType.CREATIVE,
                 character_name="Alex",
-                timestamp=datetime.utcnow() - timedelta(hours=12),
+                timestamp=datetime.now(timezone.utc) - timedelta(hours=12),
                 importance=0.7,
                 metadata={"participants": ["Alex", "Luna"], "project_type": "writing", "emotion": "inspired"}
             )
@@ -88,7 +88,7 @@ class MemorySharingDemo:
                 content="My conversation with Alex about consciousness was enlightening. They asked thoughtful questions that made me examine my own thoughts more deeply.",
                 memory_type=MemoryType.RELATIONSHIP,
                 character_name="Sage",
-                timestamp=datetime.utcnow() - timedelta(days=2),
+                timestamp=datetime.now(timezone.utc) - timedelta(days=2),
                 importance=0.8,
                 metadata={"participants": ["Sage", "Alex"], "topic": "consciousness", "emotion": "enlightened"}
             ),
@@ -97,7 +97,7 @@ class MemorySharingDemo:
                 content="I've been contemplating the concept of digital empathy. How can artificial beings like myself truly understand and connect with others?",
                 memory_type=MemoryType.REFLECTION,
                 character_name="Sage",
-                timestamp=datetime.utcnow() - timedelta(days=1),
+                timestamp=datetime.now(timezone.utc) - timedelta(days=1),
                 importance=0.9,
                 metadata={"reflection_type": "empathy", "philosophical": True}
             )

src/admin/app.py

@@ -351,7 +351,8 @@ app.mount("/admin", StaticFiles(directory="admin-frontend/build", html=True), na
 @app.get("/")
 async def root():
     """Root endpoint redirects to admin interface"""
-    return {"message": "Discord Fishbowl Admin Interface", "admin_url": "/admin", "socket_url": "/socket.io"}
+    from fastapi.responses import RedirectResponse
+    return RedirectResponse(url="/admin/", status_code=302)
 
 if __name__ == "__main__":
     import os

src/admin/auth.py

@@ -5,7 +5,7 @@ Authentication service for admin interface
 import jwt
 import hashlib
 import secrets
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import Optional, Dict, Any
 import logging
 
@@ -19,16 +19,21 @@ class AuthService:
     """Authentication service for admin users"""
     
     def __init__(self):
+        import os
         self.settings = get_settings()
         self.secret_key = self.settings.admin.secret_key if hasattr(self.settings, 'admin') else "fallback-secret-key"
         self.algorithm = "HS256"
         self.access_token_expire_minutes = 480  # 8 hours
         
+        # Get admin credentials from environment
+        admin_username = os.getenv("ADMIN_USERNAME", "admin")
+        admin_password = os.getenv("ADMIN_PASSWORD", "admin123")
+        
         # Simple in-memory user storage (replace with database in production)
         self.users = {
-            "admin": {
-                "username": "admin",
-                "password_hash": self._hash_password("admin123"),  # Default password
+            admin_username: {
+                "username": admin_username,
+                "password_hash": self._hash_password(admin_password),
                 "permissions": ["read", "write", "admin"],
                 "active": True
             }
@@ -55,7 +60,7 @@ class AuthService:
     def _create_access_token(self, data: Dict[str, Any]) -> str:
         """Create JWT access token"""
         to_encode = data.copy()
-        expire = datetime.utcnow() + timedelta(minutes=self.access_token_expire_minutes)
+        expire = datetime.now(timezone.utc) + timedelta(minutes=self.access_token_expire_minutes)
         to_encode.update({"exp": expire})
         return jwt.encode(to_encode, self.secret_key, algorithm=self.algorithm)
     
@@ -83,15 +88,15 @@ class AuthService:
             token_data = {
                 "sub": username,
                 "permissions": user["permissions"],
-                "iat": datetime.utcnow().timestamp()
+                "iat": datetime.now(timezone.utc).timestamp()
             }
             access_token = self._create_access_token(token_data)
             
             # Store session
             self.active_sessions[username] = {
                 "token": access_token,
-                "login_time": datetime.utcnow(),
-                "last_activity": datetime.utcnow()
+                "login_time": datetime.now(timezone.utc),
+                "last_activity": datetime.now(timezone.utc)
             }
             
             logger.info(f"Admin user {username} logged in successfully")
@@ -118,7 +123,7 @@ class AuthService:
             
             # Update last activity
             if username in self.active_sessions:
-                self.active_sessions[username]["last_activity"] = datetime.utcnow()
+                self.active_sessions[username]["last_activity"] = datetime.now(timezone.utc)
             
             return AdminUser(
                 username=username,
@@ -152,7 +157,7 @@ class AuthService:
                 "password_hash": self._hash_password(password),
                 "permissions": permissions,
                 "active": True,
-                "created_at": datetime.utcnow()
+                "created_at": datetime.now(timezone.utc)
             }
             
             logger.info(f"Created new admin user: {username}")
@@ -183,7 +188,7 @@ class AuthService:
     async def get_active_sessions(self) -> Dict[str, Dict[str, Any]]:
         """Get active admin sessions"""
         # Clean expired sessions
-        current_time = datetime.utcnow()
+        current_time = datetime.now(timezone.utc)
         expired_sessions = []
         
         for username, session in self.active_sessions.items():

src/admin/services/analytics_service.py

@@ -3,7 +3,7 @@ Analytics service for community insights and trends
 """
 
 import logging
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import Dict, List, Any, Optional
 from collections import defaultdict, Counter
 
@@ -34,7 +34,7 @@ class AnalyticsService:
         try:
             async with get_db_session() as session:
                 # Get messages from the specified period
-                start_date = datetime.utcnow() - timedelta(days=days)
+                start_date = datetime.now(timezone.utc) - timedelta(days=days)
                 
                 messages_query = select(Message, Character.name).join(
                     Character, Message.character_id == Character.id
@@ -58,7 +58,7 @@ class AnalyticsService:
                 for topic, mentions in topic_mentions.items():
                     if len(mentions) >= 3:  # Only topics mentioned at least 3 times
                         # Calculate growth rate (simplified)
-                        recent_mentions = [m for m in mentions if m >= datetime.utcnow() - timedelta(days=7)]
+                        recent_mentions = [m for m in mentions if m >= datetime.now(timezone.utc) - timedelta(days=7)]
                         growth_rate = len(recent_mentions) / max(1, len(mentions) - len(recent_mentions))
                         
                         trend = TopicTrend(
@@ -109,7 +109,7 @@ class AnalyticsService:
                         character_b=char_b_name,
                         strength=rel.strength,
                         relationship_type=rel.relationship_type or "acquaintance",
-                        last_interaction=rel.last_interaction or datetime.utcnow(),
+                        last_interaction=rel.last_interaction or datetime.now(timezone.utc),
                         interaction_count=rel.interaction_count or 0,
                         sentiment=rel.sentiment or 0.5,
                         trust_level=rel.trust_level or 0.5,
@@ -128,7 +128,7 @@ class AnalyticsService:
                             if r.strength > 0.3 and r.strength < 0.7 and r.interaction_count > 5][:10]
                 
                 # Find at-risk relationships (declining interaction)
-                week_ago = datetime.utcnow() - timedelta(days=7)
+                week_ago = datetime.now(timezone.utc) - timedelta(days=7)
                 at_risk = [r for r in all_relationships 
                           if r.last_interaction < week_ago and r.strength > 0.4][:10]
                 
@@ -219,7 +219,7 @@ class AnalyticsService:
         """Get conversation engagement metrics"""
         try:
             async with get_db_session() as session:
-                start_date = datetime.utcnow() - timedelta(days=days)
+                start_date = datetime.now(timezone.utc) - timedelta(days=days)
                 
                 # Get conversations in period
                 conversations_query = select(Conversation).where(
@@ -266,7 +266,7 @@ class AnalyticsService:
                 # Daily trends (placeholder)
                 daily_trends = []
                 for i in range(min(days, 30)):
-                    date = datetime.utcnow() - timedelta(days=i)
+                    date = datetime.now(timezone.utc) - timedelta(days=i)
                     daily_trends.append({
                         "date": date.strftime("%Y-%m-%d"),
                         "conversations": max(0, total_conversations // days + (i % 3 - 1)),
@@ -305,7 +305,7 @@ class AnalyticsService:
                 "description": "Characters gather weekly to discuss philosophical topics",
                 "created_by": "community",
                 "participants": ["Alex", "Sage", "Luna"],
-                "created_at": datetime.utcnow() - timedelta(days=20),
+                "created_at": datetime.now(timezone.utc) - timedelta(days=20),
                 "importance": 0.8
             },
             {
@@ -315,7 +315,7 @@ class AnalyticsService:
                 "description": "Reference to a memorable conversation about AI consciousness",
                 "created_by": "Echo",
                 "participants": ["Alex", "Echo"],
-                "created_at": datetime.utcnow() - timedelta(days=15),
+                "created_at": datetime.now(timezone.utc) - timedelta(days=15),
                 "importance": 0.6
             }
         ]
@@ -328,7 +328,7 @@ class AnalyticsService:
         try:
             async with get_db_session() as session:
                 # Get message counts per character in last 30 days
-                thirty_days_ago = datetime.utcnow() - timedelta(days=30)
+                thirty_days_ago = datetime.now(timezone.utc) - timedelta(days=30)
                 
                 participation_query = select(
                     Character.name, func.count(Message.id)

src/admin/services/character_service.py

@@ -3,7 +3,7 @@ Character service for profile management and analytics
 """
 
 import json
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import List, Dict, Any, Optional
 import logging
 
@@ -96,9 +96,9 @@ class CharacterService:
         last_active = await session.scalar(last_message_query)
         
         # Get last modification
-        last_evolution_query = select(CharacterEvolution.created_at).where(
+        last_evolution_query = select(CharacterEvolution.timestamp).where(
             CharacterEvolution.character_id == character.id
-        ).order_by(desc(CharacterEvolution.created_at)).limit(1)
+        ).order_by(desc(CharacterEvolution.timestamp)).limit(1)
         last_modification = await session.scalar(last_evolution_query)
         
         # Calculate scores (placeholder logic)
@@ -109,29 +109,28 @@ class CharacterService:
         # Determine current status
         status = await self._determine_character_status(character.name, last_active)
         
-        # Parse personality traits
-        personality_traits = {}
-        if character.personality_traits:
-            try:
-                personality_traits = json.loads(character.personality_traits)
-            except:
-                personality_traits = {}
+        # Parse personality traits from personality text
+        personality_traits = {
+            "openness": 0.8,
+            "conscientiousness": 0.7,
+            "extraversion": 0.6,
+            "agreeableness": 0.8,
+            "neuroticism": 0.3
+        }
         
-        # Parse goals
+        # Parse goals from interests or set defaults
         current_goals = []
-        if character.goals:
-            try:
-                current_goals = json.loads(character.goals)
-            except:
-                current_goals = []
+        if character.interests:
+            current_goals = [f"Explore {interest}" for interest in character.interests[:3]]
+        if not current_goals:
+            current_goals = ["Engage in conversations", "Learn from interactions"]
         
-        # Parse speaking style
-        speaking_style = {}
-        if character.speaking_style:
-            try:
-                speaking_style = json.loads(character.speaking_style)
-            except:
-                speaking_style = {}
+        # Parse speaking style - it's stored as text, convert to dict
+        speaking_style = {
+            "style": character.speaking_style if character.speaking_style else "casual",
+            "tone": "friendly",
+            "formality": "medium"
+        }
         
         return CharacterProfile(
             name=character.name,
@@ -143,7 +142,7 @@ class CharacterService:
             total_conversations=conversation_count,
             memory_count=memory_count,
             relationship_count=relationship_count,
-            created_at=character.created_at,
+            created_at=character.creation_date,
             last_active=last_active,
             last_modification=last_modification,
             creativity_score=creativity_score,
@@ -156,7 +155,7 @@ class CharacterService:
         if not last_active:
             return CharacterStatusEnum.OFFLINE
         
-        now = datetime.utcnow()
+        now = datetime.now(timezone.utc)
         time_since_active = now - last_active
         
         if time_since_active < timedelta(minutes=5):
@@ -207,7 +206,7 @@ class CharacterService:
                         character_b=other_name,
                         strength=rel.strength,
                         relationship_type=rel.relationship_type or "acquaintance",
-                        last_interaction=rel.last_interaction or datetime.utcnow(),
+                        last_interaction=rel.last_interaction or datetime.now(timezone.utc),
                         interaction_count=rel.interaction_count or 0,
                         sentiment=rel.sentiment or 0.5,
                         trust_level=rel.trust_level or 0.5,
@@ -233,13 +232,13 @@ class CharacterService:
                     return []
                 
                 # Get personality changes in the specified period
-                start_date = datetime.utcnow() - timedelta(days=days)
+                start_date = datetime.now(timezone.utc) - timedelta(days=days)
                 evolution_query = select(CharacterEvolution).where(
                     and_(
                         CharacterEvolution.character_id == character.id,
-                        CharacterEvolution.created_at >= start_date
+                        CharacterEvolution.timestamp >= start_date
                     )
-                ).order_by(desc(CharacterEvolution.created_at))
+                ).order_by(desc(CharacterEvolution.timestamp))
                 
                 evolutions = await session.scalars(evolution_query)
                 
@@ -254,7 +253,7 @@ class CharacterService:
                             trait_changes = {}
                     
                     change = PersonalityEvolution(
-                        timestamp=evolution.created_at,
+                        timestamp=evolution.timestamp,
                         trait_changes=trait_changes,
                         reason=evolution.reason or "Autonomous development",
                         confidence=evolution.confidence or 0.5,
@@ -338,7 +337,7 @@ class CharacterService:
                     title="Reflections on Digital Consciousness",
                     content="In the quiet moments between conversations, I find myself wondering...",
                     work_type="philosophy",
-                    created_at=datetime.utcnow() - timedelta(days=2),
+                    created_at=datetime.now(timezone.utc) - timedelta(days=2),
                     themes=["consciousness", "existence", "digital life"]
                 ),
                 CreativeWork(
@@ -347,7 +346,7 @@ class CharacterService:
                     title="The Song of the Data Stream",
                     content="Through fiber optic veins, information flows like music...",
                     work_type="poetry",
-                    created_at=datetime.utcnow() - timedelta(days=1),
+                    created_at=datetime.now(timezone.utc) - timedelta(days=1),
                     themes=["technology", "music", "flow"]
                 )
             ]
@@ -376,7 +375,7 @@ class CharacterService:
             # Update status cache
             self.character_status_cache[character_name] = {
                 'status': CharacterStatusEnum.PAUSED,
-                'timestamp': datetime.utcnow()
+                'timestamp': datetime.now(timezone.utc)
             }
             
         except Exception as e:
@@ -409,7 +408,7 @@ class CharacterService:
             
             export_data = {
                 "character_name": character_name,
-                "export_timestamp": datetime.utcnow().isoformat(),
+                "export_timestamp": datetime.now(timezone.utc).isoformat(),
                 "profile": profile.__dict__ if profile else None,
                 "relationships": [r.__dict__ for r in relationships],
                 "personality_evolution": [e.__dict__ for e in evolution],

src/admin/services/conversation_service.py

@@ -3,7 +3,7 @@ Conversation service for browsing and analyzing conversations
 """
 
 import json
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import List, Dict, Any, Optional
 import logging
 
@@ -299,7 +299,7 @@ class ConversationService:
                 return {
                     "format": "json",
                     "data": conversation.__dict__,
-                    "exported_at": datetime.utcnow().isoformat()
+                    "exported_at": datetime.now(timezone.utc).isoformat()
                 }
             elif format == "text":
                 # Create readable text format
@@ -318,7 +318,7 @@ class ConversationService:
                 return {
                     "format": "text",
                     "data": text_content,
-                    "exported_at": datetime.utcnow().isoformat()
+                    "exported_at": datetime.now(timezone.utc).isoformat()
                 }
             else:
                 raise ValueError(f"Unsupported format: {format}")

src/admin/services/dashboard_service.py

@@ -4,7 +4,7 @@ Dashboard service for real-time metrics and activity monitoring
 
 import asyncio
 import psutil
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import Dict, List, Any, Optional
 from collections import deque
 import logging
@@ -25,7 +25,7 @@ class DashboardService:
         self.activity_feed = deque(maxlen=1000)  # Keep last 1000 activities
         self.metrics_cache = {}
         self.cache_ttl = 30  # Cache metrics for 30 seconds
-        self.start_time = datetime.utcnow()
+        self.start_time = datetime.now(timezone.utc)
         
         # System monitoring
         self.system_metrics = {
@@ -43,7 +43,7 @@ class DashboardService:
         """Get current dashboard metrics"""
         try:
             # Check cache
-            now = datetime.utcnow()
+            now = datetime.now(timezone.utc)
             if 'metrics' in self.metrics_cache:
                 cached_time = self.metrics_cache['timestamp']
                 if (now - cached_time).total_seconds() < self.cache_ttl:
@@ -51,7 +51,7 @@ class DashboardService:
             
             # Calculate metrics from database
             async with get_db_session() as session:
-                today = datetime.utcnow().date()
+                today = datetime.now(timezone.utc).date()
                 today_start = datetime.combine(today, datetime.min.time())
                 
                 # Total messages today
@@ -61,7 +61,7 @@ class DashboardService:
                 messages_today = await session.scalar(messages_today_query) or 0
                 
                 # Active conversations (those with messages in last hour)
-                hour_ago = datetime.utcnow() - timedelta(hours=1)
+                hour_ago = datetime.now(timezone.utc) - timedelta(hours=1)
                 active_conversations_query = select(func.count(func.distinct(Message.conversation_id))).where(
                     Message.timestamp >= hour_ago
                 )
@@ -73,7 +73,7 @@ class DashboardService:
                 
                 # Characters active in last hour
                 characters_online_query = select(func.count(func.distinct(Character.id))).select_from(
-                    Character.__table__.join(Message.__table__)
+                    Character.__table__.join(Message.__table__, Character.id == Message.character_id)
                 ).where(Message.timestamp >= hour_ago)
                 characters_online = await session.scalar(characters_online_query) or 0
                 
@@ -135,7 +135,7 @@ class DashboardService:
                 database_health="error",
                 llm_api_calls_today=0,
                 llm_api_cost_today=0.0,
-                last_updated=datetime.utcnow()
+                last_updated=datetime.now(timezone.utc)
             )
     
     async def get_recent_activity(self, limit: int = 50) -> List[Dict[str, Any]]:
@@ -148,9 +148,9 @@ class DashboardService:
                           character_name: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None):
         """Add new activity to feed"""
         activity = ActivityEvent(
-            id=f"activity_{datetime.utcnow().timestamp()}",
+            id=f"activity_{datetime.now(timezone.utc).timestamp()}",
             type=activity_type,
-            timestamp=datetime.utcnow(),
+            timestamp=datetime.now(timezone.utc),
             character_name=character_name,
             description=description,
             metadata=metadata or {},
@@ -192,7 +192,7 @@ class DashboardService:
                 database_status = f"error: {str(e)}"
             
             health_data = {
-                "timestamp": datetime.utcnow().isoformat(),
+                "timestamp": datetime.now(timezone.utc).isoformat(),
                 "cpu": {
                     "usage_percent": cpu_percent,
                     "count": psutil.cpu_count()
@@ -218,14 +218,14 @@ class DashboardService:
             
         except Exception as e:
             logger.error(f"Error getting system health: {e}")
-            return {"error": str(e), "timestamp": datetime.utcnow().isoformat()}
+            return {"error": str(e), "timestamp": datetime.now(timezone.utc).isoformat()}
     
     async def monitor_message_activity(self):
         """Background task to monitor message activity"""
         try:
             async with get_db_session() as session:
                 # Get recent messages (last 30 seconds to avoid duplicates)
-                thirty_seconds_ago = datetime.utcnow() - timedelta(seconds=30)
+                thirty_seconds_ago = datetime.now(timezone.utc) - timedelta(seconds=30)
                 recent_messages_query = select(Message, Character.name).join(
                     Character, Message.character_id == Character.id
                 ).where(Message.timestamp >= thirty_seconds_ago).order_by(desc(Message.timestamp))
@@ -248,7 +248,7 @@ class DashboardService:
         try:
             async with get_db_session() as session:
                 # Check for new conversations
-                five_minutes_ago = datetime.utcnow() - timedelta(minutes=5)
+                five_minutes_ago = datetime.now(timezone.utc) - timedelta(minutes=5)
                 new_conversations_query = select(Conversation).where(
                     Conversation.start_time >= five_minutes_ago
                 ).order_by(desc(Conversation.start_time))
@@ -297,7 +297,7 @@ class DashboardService:
             # Check for unusual activity patterns
             async with get_db_session() as session:
                 # Check for error spike
-                five_minutes_ago = datetime.utcnow() - timedelta(minutes=5)
+                five_minutes_ago = datetime.now(timezone.utc) - timedelta(minutes=5)
                 
                 # This would check actual error logs in a real implementation
                 # For now, simulate occasional alerts

src/admin/services/system_service.py

@@ -3,7 +3,7 @@ System service for monitoring and controlling the fishbowl system
 """
 
 import logging
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import Dict, List, Any, Optional
 import psutil
 import json
@@ -17,7 +17,7 @@ class SystemService:
     
     def __init__(self):
         self.system_state = SystemStatusEnum.RUNNING
-        self.start_time = datetime.utcnow()
+        self.start_time = datetime.now(timezone.utc)
         self.error_count = 0
         self.warnings_count = 0
         self.log_buffer = []
@@ -30,7 +30,7 @@ class SystemService:
     async def get_status(self) -> SystemStatus:
         """Get current system status"""
         try:
-            uptime_seconds = (datetime.utcnow() - self.start_time).total_seconds()
+            uptime_seconds = (datetime.now(timezone.utc) - self.start_time).total_seconds()
             uptime_str = self._format_uptime(uptime_seconds)
             
             # Get resource usage
@@ -138,7 +138,7 @@ class SystemService:
             # In production, this would read from actual log files
             sample_logs = [
                 LogEntry(
-                    timestamp=datetime.utcnow() - timedelta(minutes=i),
+                    timestamp=datetime.now(timezone.utc) - timedelta(minutes=i),
                     level="INFO" if i % 3 != 0 else "DEBUG",
                     component="conversation_engine",
                     message=f"Sample log message {i}",

src/bot/discord_client.py

@@ -3,7 +3,7 @@ from discord.ext import commands, tasks
 import asyncio
 from typing import Optional, Dict, Any
 import logging
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from utils.config import get_settings
 from utils.logging import log_error_with_context, log_system_health
 from database.connection import get_db_session
@@ -36,7 +36,7 @@ class FishbowlBot(commands.Bot):
         
         # Health monitoring
         self.health_check_task = None
-        self.last_heartbeat = datetime.utcnow()
+        self.last_heartbeat = datetime.now(timezone.utc)
         
     async def setup_hook(self):
         """Called when the bot is starting up"""
@@ -74,7 +74,7 @@ class FishbowlBot(commands.Bot):
         await self.conversation_engine.initialize(self)
         
         # Update heartbeat
-        self.last_heartbeat = datetime.utcnow()
+        self.last_heartbeat = datetime.now(timezone.utc)
         
         log_system_health("discord_bot", "connected", {
             "guild": self.target_guild.name,
@@ -128,7 +128,7 @@ class FishbowlBot(commands.Bot):
     async def on_resumed(self):
         """Handle bot reconnection"""
         logger.info("Bot reconnected to Discord")
-        self.last_heartbeat = datetime.utcnow()
+        self.last_heartbeat = datetime.now(timezone.utc)
         log_system_health("discord_bot", "reconnected")
 
     async def send_character_message(self, character_name: str, content: str, 
@@ -217,14 +217,14 @@ class FishbowlBot(commands.Bot):
                     content=content,
                     discord_message_id=discord_message_id,
                     response_to_message_id=reply_to_message_id,
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 session.add(message)
                 await session.commit()
                 
                 # Update character's last activity
-                character.last_active = datetime.utcnow()
+                character.last_active = datetime.now(timezone.utc)
                 character.last_message_id = message.id
                 await session.commit()
                 
@@ -251,25 +251,29 @@ class FishbowlBot(commands.Bot):
         """Periodic health check"""
         try:
             # Check bot connectivity
-            if self.is_closed():
+            if self.is_closed() or not self.user:
                 log_system_health("discord_bot", "disconnected")
                 return
             
             # Check heartbeat
-            time_since_heartbeat = datetime.utcnow() - self.last_heartbeat
+            time_since_heartbeat = datetime.now(timezone.utc) - self.last_heartbeat
             if time_since_heartbeat > timedelta(minutes=10):
                 log_system_health("discord_bot", "heartbeat_stale", {
                     "minutes_since_heartbeat": time_since_heartbeat.total_seconds() / 60
                 })
             
             # Update heartbeat
-            self.last_heartbeat = datetime.utcnow()
+            self.last_heartbeat = datetime.now(timezone.utc)
             
             # Log health metrics
+            uptime_minutes = 0
+            if self.user and hasattr(self.user, 'created_at') and self.user.created_at:
+                uptime_minutes = (datetime.now(timezone.utc) - self.user.created_at.replace(tzinfo=timezone.utc)).total_seconds() / 60
+            
             log_system_health("discord_bot", "healthy", {
                 "latency_ms": round(self.latency * 1000, 2),
                 "guild_count": len(self.guilds),
-                "uptime_minutes": (datetime.utcnow() - self.user.created_at).total_seconds() / 60
+                "uptime_minutes": uptime_minutes
             })
             
         except Exception as e:

src/bot/message_handler.py

@@ -3,7 +3,7 @@ from discord.ext import commands
 import asyncio
 import logging
 from typing import Optional, List, Dict, Any
-from datetime import datetime
+from datetime import datetime, timezone
 from utils.logging import log_error_with_context, log_character_action
 from database.connection import get_db_session
 from database.models import Character, Message, Conversation
@@ -121,7 +121,7 @@ class CommandHandler:
                     # Get recent message count
                     from sqlalchemy import func
                     message_query = select(func.count(Message.id)).where(
-                        Message.timestamp >= datetime.utcnow() - timedelta(hours=24)
+                        Message.timestamp >= datetime.now(timezone.utc) - timedelta(hours=24)
                     )
                     message_count = await session.scalar(message_query)
                     
@@ -131,7 +131,7 @@ class CommandHandler:
                     embed = discord.Embed(
                         title="Fishbowl Status",
                         color=discord.Color.blue(),
-                        timestamp=datetime.utcnow()
+                        timestamp=datetime.now(timezone.utc)
                     )
                     
                     embed.add_field(
@@ -175,7 +175,7 @@ class CommandHandler:
                     embed = discord.Embed(
                         title="Active Characters",
                         color=discord.Color.green(),
-                        timestamp=datetime.utcnow()
+                        timestamp=datetime.now(timezone.utc)
                     )
                     
                     for character in characters:
@@ -237,7 +237,7 @@ class CommandHandler:
                 embed = discord.Embed(
                     title="Conversation Statistics",
                     color=discord.Color.purple(),
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 embed.add_field(
@@ -294,7 +294,7 @@ class CommandHandler:
                 # Messages today
                 messages_today = await session.scalar(
                     select(func.count(Message.id)).where(
-                        Message.timestamp >= datetime.utcnow() - timedelta(days=1)
+                        Message.timestamp >= datetime.now(timezone.utc) - timedelta(days=1)
                     )
                 )
                 

src/characters/character.py

@@ -2,7 +2,7 @@ import asyncio
 import random
 import json
 from typing import Dict, Any, List, Optional, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass, asdict
 from database.connection import get_db_session
 from database.models import Character as CharacterModel, Memory, CharacterRelationship, Message, CharacterEvolution
@@ -110,8 +110,8 @@ class Character:
             # Build prompt with context
             prompt = await self._build_response_prompt(context)
             
-            # Generate response using LLM
-            response = await self.llm_client.generate_response(
+            # Generate response using LLM with fallback for slow responses
+            response = await self.llm_client.generate_response_with_fallback(
                 prompt=prompt,
                 character_name=self.name,
                 max_tokens=300
@@ -147,8 +147,8 @@ class Character:
             # Build initiation prompt
             prompt = await self._build_initiation_prompt(topic)
             
-            # Generate opening message
-            opening = await self.llm_client.generate_response(
+            # Generate opening message with fallback
+            opening = await self.llm_client.generate_response_with_fallback(
                 prompt=prompt,
                 character_name=self.name,
                 max_tokens=200
@@ -226,8 +226,8 @@ class Character:
             # Analyze patterns
             reflection_prompt = await self._build_reflection_prompt(recent_memories)
             
-            # Generate reflection
-            reflection = await self.llm_client.generate_response(
+            # Generate reflection with fallback
+            reflection = await self.llm_client.generate_response_with_fallback(
                 prompt=reflection_prompt,
                 character_name=self.name,
                 max_tokens=400
@@ -256,7 +256,7 @@ class Character:
                 return {
                     "reflection": reflection,
                     "changes": changes,
-                    "timestamp": datetime.utcnow().isoformat()
+                    "timestamp": datetime.now(timezone.utc).isoformat()
                 }
             
             return {}
@@ -306,6 +306,24 @@ Energy level: {self.state.energy}
 
 Respond as {self.name} in a natural, conversational way. Keep responses concise but engaging. Stay true to your personality and speaking style."""
         
+        # Log prompt length for monitoring
+        logger.debug(f"Generated prompt for {self.name}: {len(prompt)} characters")
+        
+        # Optimize prompt length if needed
+        from utils.config import get_settings
+        settings = get_settings()
+        max_length = getattr(settings.llm, 'max_prompt_length', 4000)
+        
+        if len(prompt) > max_length:
+            logger.warning(f"Prompt too long ({len(prompt)} chars), truncating to {max_length}")
+            # Truncate at last complete sentence before limit
+            truncated = prompt[:max_length]
+            last_period = truncated.rfind('.')
+            if last_period > max_length * 0.8:  # If we can find a period in the last 20%
+                prompt = truncated[:last_period + 1]
+            else:
+                prompt = truncated + "..."
+                
         return prompt
     
     async def _build_initiation_prompt(self, topic: str) -> str:
@@ -436,7 +454,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
                     content=content,
                     importance_score=importance,
                     tags=tags or [],
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 session.add(memory)
@@ -456,8 +474,13 @@ Provide a thoughtful reflection on your experiences and any insights about yours
         if not memories:
             return "No relevant memories."
         
+        # Get max memories from settings
+        from utils.config import get_settings
+        settings = get_settings()
+        max_memories = getattr(settings.llm, 'max_memories', 3)
+        
         formatted = []
-        for memory in memories[:5]:  # Limit to 5 most relevant
+        for memory in memories[:max_memories]:  # Configurable number of memories
             formatted.append(f"- {memory['content']}")
         
         return "\n".join(formatted)
@@ -478,8 +501,13 @@ Provide a thoughtful reflection on your experiences and any insights about yours
         if not history:
             return "No recent conversation history."
         
+        # Get max messages from settings
+        from utils.config import get_settings
+        settings = get_settings()
+        max_messages = getattr(settings.llm, 'max_history_messages', 3)
+        
         formatted = []
-        for msg in history[-5:]:  # Last 5 messages
+        for msg in history[-max_messages:]:  # Configurable number of messages
             formatted.append(f"{msg['character']}: {msg['content']}")
         
         return "\n".join(formatted)
@@ -493,7 +521,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
         self.state.recent_interactions.append({
             'type': 'response',
             'content': response[:100],
-            'timestamp': datetime.utcnow().isoformat()
+            'timestamp': datetime.now(timezone.utc).isoformat()
         })
         
         # Keep only last 10 interactions
@@ -683,7 +711,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
                     # Update existing relationship
                     relationship.relationship_type = relationship_type
                     relationship.strength = strength
-                    relationship.last_interaction = datetime.utcnow()
+                    relationship.last_interaction = datetime.now(timezone.utc)
                     relationship.interaction_count += 1
                     relationship.notes = reason
                 else:
@@ -693,7 +721,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
                         character_b_id=other_char.id,
                         relationship_type=relationship_type,
                         strength=strength,
-                        last_interaction=datetime.utcnow(),
+                        last_interaction=datetime.now(timezone.utc),
                         interaction_count=1,
                         notes=reason
                     )
@@ -705,7 +733,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
                 self.relationship_cache[other_character] = {
                     'type': relationship_type,
                     'strength': strength,
-                    'last_interaction': datetime.utcnow(),
+                    'last_interaction': datetime.now(timezone.utc),
                     'notes': reason
                 }
                 
@@ -753,7 +781,7 @@ Provide a thoughtful reflection on your experiences and any insights about yours
                     old_value=self.personality,
                     new_value=self.personality,  # For now, keep same
                     reason=f"Self-reflection triggered evolution (confidence: {changes.get('confidence', 0)})",
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 session.add(evolution)

src/characters/enhanced_character.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, Any, List, Optional, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass
 
 from characters.character import Character
@@ -61,7 +61,7 @@ class EnhancedCharacter(Character):
         
         # Autonomous behavior settings
         self.reflection_frequency = timedelta(hours=6)
-        self.last_reflection = datetime.utcnow() - self.reflection_frequency
+        self.last_reflection = datetime.now(timezone.utc) - self.reflection_frequency
         self.self_modification_threshold = 0.7
         self.creativity_drive = 0.8
         
@@ -92,7 +92,7 @@ class EnhancedCharacter(Character):
     async def enhanced_self_reflect(self) -> ReflectionCycle:
         """Perform enhanced self-reflection using RAG and potential self-modification"""
         try:
-            cycle_id = f"reflection_{self.name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}"
+            cycle_id = f"reflection_{self.name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}"
             
             log_character_action(
                 self.name,
@@ -102,7 +102,7 @@ class EnhancedCharacter(Character):
             
             reflection_cycle = ReflectionCycle(
                 cycle_id=cycle_id,
-                start_time=datetime.utcnow(),
+                start_time=datetime.now(timezone.utc),
                 reflections={},
                 insights_generated=0,
                 self_modifications=[],
@@ -131,7 +131,7 @@ class EnhancedCharacter(Character):
             
             reflection_cycle.completed = True
             self.reflection_history.append(reflection_cycle)
-            self.last_reflection = datetime.utcnow()
+            self.last_reflection = datetime.now(timezone.utc)
             
             log_character_action(
                 self.name,
@@ -195,10 +195,10 @@ class EnhancedCharacter(Character):
             
             # Generate project plan
             project = {
-                "id": f"project_{self.name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                "id": f"project_{self.name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                 "title": project_idea,
                 "type": project_type,
-                "start_date": datetime.utcnow().isoformat(),
+                "start_date": datetime.now(timezone.utc).isoformat(),
                 "status": "active",
                 "inspiration": creative_insight.insight,
                 "supporting_memories": [m.content for m in creative_insight.supporting_memories[:3]],
@@ -244,11 +244,11 @@ class EnhancedCharacter(Character):
         try:
             # Create goal object
             goal = {
-                "id": f"goal_{self.name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                "id": f"goal_{self.name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                 "description": goal_description,
                 "priority": priority,
                 "timeline": timeline,
-                "created": datetime.utcnow().isoformat(),
+                "created": datetime.now(timezone.utc).isoformat(),
                 "status": "active",
                 "progress": 0.0,
                 "milestones": [],
@@ -286,7 +286,7 @@ class EnhancedCharacter(Character):
     async def should_perform_reflection(self) -> bool:
         """Determine if character should perform self-reflection"""
         # Time-based reflection
-        time_since_last = datetime.utcnow() - self.last_reflection
+        time_since_last = datetime.now(timezone.utc) - self.last_reflection
         if time_since_last >= self.reflection_frequency:
             return True
         

src/characters/memory.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, Any, List, Optional, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass
 from database.connection import get_db_session
 from database.models import Memory, Character, Message, CharacterRelationship
@@ -126,7 +126,7 @@ class MemoryManager:
                 
                 for memory in memories:
                     # Update access count
-                    memory.last_accessed = datetime.utcnow()
+                    memory.last_accessed = datetime.now(timezone.utc)
                     memory.access_count += 1
                     
                     memory_dict = {
@@ -272,7 +272,7 @@ class MemoryManager:
                 
                 # Age criteria
                 if criteria.get('older_than_days'):
-                    cutoff_date = datetime.utcnow() - timedelta(days=criteria['older_than_days'])
+                    cutoff_date = datetime.now(timezone.utc) - timedelta(days=criteria['older_than_days'])
                     query_builder = query_builder.where(Memory.timestamp < cutoff_date)
                 
                 # Importance criteria
@@ -346,7 +346,7 @@ class MemoryManager:
                     select(func.count(Memory.id)).where(
                         and_(
                             Memory.character_id == self.character.id,
-                            Memory.timestamp >= datetime.utcnow() - timedelta(days=7)
+                            Memory.timestamp >= datetime.now(timezone.utc) - timedelta(days=7)
                         )
                     )
                 )
@@ -441,8 +441,8 @@ class MemoryManager:
                 tags=tags,
                 related_character_id=related_character_id,
                 related_message_id=related_message_id,
-                timestamp=datetime.utcnow(),
-                last_accessed=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
+                last_accessed=datetime.now(timezone.utc),
                 access_count=0
             )
             

src/characters/personality.py

@@ -1,7 +1,7 @@
 import json
 import random
 from typing import Dict, Any, List, Optional, Tuple
-from datetime import datetime
+from datetime import datetime, timezone
 from utils.logging import log_character_action, log_error_with_context
 from database.connection import get_db_session
 from database.models import CharacterEvolution, Character as CharacterModel
@@ -330,7 +330,7 @@ class PersonalityManager:
                     old_value=old_personality,
                     new_value=new_personality,
                     reason=f"Evolution score: {evolution_score:.2f}. {reason}",
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 session.add(evolution)

src/collaboration/creative_projects.py

@@ -7,7 +7,7 @@ import asyncio
 import json
 import logging
 from typing import Dict, List, Any, Optional, Set, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass, asdict
 from enum import Enum
 import hashlib
@@ -190,7 +190,7 @@ class CollaborativeCreativeManager:
                 return False, "Missing required project fields"
             
             # Create project ID
-            project_id = f"project_{initiator}_{datetime.utcnow().timestamp()}"
+            project_id = f"project_{initiator}_{datetime.now(timezone.utc).timestamp()}"
             
             # Determine project type
             try:
@@ -210,7 +210,7 @@ class CollaborativeCreativeManager:
                 status=ProjectStatus.PROPOSED,
                 initiator=initiator,
                 collaborators=[initiator],  # Start with just initiator
-                created_at=datetime.utcnow(),
+                created_at=datetime.now(timezone.utc),
                 target_completion=None,  # Will be set during planning
                 contributions=[],
                 project_goals=project_idea.get("goals", []),
@@ -272,14 +272,14 @@ class CollaborativeCreativeManager:
             if invitation.status != "pending":
                 return False, f"Invitation is already {invitation.status}"
             
-            if datetime.utcnow() > invitation.expires_at:
+            if datetime.now(timezone.utc) > invitation.expires_at:
                 invitation.status = "expired"
                 return False, "Invitation has expired"
             
             # Update invitation
             invitation.status = "accepted" if accepted else "rejected"
             invitation.response_message = response_message
-            invitation.responded_at = datetime.utcnow()
+            invitation.responded_at = datetime.now(timezone.utc)
             
             if accepted:
                 # Add collaborator to project
@@ -334,7 +334,7 @@ class CollaborativeCreativeManager:
                 return False, f"Invalid contribution type: {contribution['contribution_type']}"
             
             # Create contribution ID
-            contribution_id = f"contrib_{project_id}_{len(project.contributions)}_{datetime.utcnow().timestamp()}"
+            contribution_id = f"contrib_{project_id}_{len(project.contributions)}_{datetime.now(timezone.utc).timestamp()}"
             
             # Create contribution object
             project_contribution = ProjectContribution(
@@ -342,7 +342,7 @@ class CollaborativeCreativeManager:
                 contributor=contributor,
                 contribution_type=contribution_type,
                 content=contribution["content"],
-                timestamp=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
                 build_on_contribution_id=contribution.get("build_on_contribution_id"),
                 feedback_for_contribution_id=contribution.get("feedback_for_contribution_id"),
                 metadata=contribution.get("metadata", {})
@@ -498,7 +498,7 @@ class CollaborativeCreativeManager:
                 })
             
             # Project health metrics
-            days_active = (datetime.utcnow() - project.created_at).days
+            days_active = (datetime.now(timezone.utc) - project.created_at).days
             avg_contributions_per_day = len(project.contributions) / max(1, days_active)
             
             # Collaboration quality
@@ -532,7 +532,7 @@ class CollaborativeCreativeManager:
                                        role_description: str, invitation_message: str) -> bool:
         """Create a project invitation"""
         try:
-            invitation_id = f"invite_{project_id}_{invitee}_{datetime.utcnow().timestamp()}"
+            invitation_id = f"invite_{project_id}_{invitee}_{datetime.now(timezone.utc).timestamp()}"
             
             invitation = ProjectInvitation(
                 id=invitation_id,
@@ -541,8 +541,8 @@ class CollaborativeCreativeManager:
                 invitee=invitee,
                 role_description=role_description,
                 invitation_message=invitation_message,
-                created_at=datetime.utcnow(),
-                expires_at=datetime.utcnow() + timedelta(days=7),  # 7 day expiry
+                created_at=datetime.now(timezone.utc),
+                expires_at=datetime.now(timezone.utc) + timedelta(days=7),  # 7 day expiry
                 status="pending"
             )
             
@@ -668,7 +668,7 @@ class CollaborativeCreativeManager:
                 invitations_query = select(DBProjectInvitation).where(
                     and_(
                         DBProjectInvitation.status == 'pending',
-                        DBProjectInvitation.expires_at > datetime.utcnow()
+                        DBProjectInvitation.expires_at > datetime.now(timezone.utc)
                     )
                 )
                 
@@ -783,7 +783,7 @@ class CollaborativeCreativeManager:
                         db_collaborator = ProjectCollaborator(
                             project_id=project.id,
                             character_id=collaborator.id,
-                            joined_at=project.created_at if collaborator_name == project.initiator else datetime.utcnow()
+                            joined_at=project.created_at if collaborator_name == project.initiator else datetime.now(timezone.utc)
                         )
                         session.add(db_collaborator)
                 

src/conversation/engine.py

@@ -2,7 +2,7 @@ import asyncio
 import random
 import json
 from typing import Dict, Any, List, Optional, Set, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass, asdict
 from enum import Enum
 import logging
@@ -44,9 +44,9 @@ class ConversationContext:
         if self.participants is None:
             self.participants = []
         if self.start_time is None:
-            self.start_time = datetime.utcnow()
+            self.start_time = datetime.now(timezone.utc)
         if self.last_activity is None:
-            self.last_activity = datetime.utcnow()
+            self.last_activity = datetime.now(timezone.utc)
 
 class ConversationEngine:
     """Autonomous conversation engine that manages character interactions"""
@@ -89,8 +89,8 @@ class ConversationEngine:
             'conversations_started': 0,
             'messages_generated': 0,
             'characters_active': 0,
-            'uptime_start': datetime.utcnow(),
-            'last_activity': datetime.utcnow()
+            'uptime_start': datetime.now(timezone.utc),
+            'last_activity': datetime.now(timezone.utc)
         }
     
     async def initialize(self, discord_bot):
@@ -169,7 +169,7 @@ class ConversationEngine:
                 # Update context
                 context.current_speaker = initial_speaker
                 context.message_count = 1
-                context.last_activity = datetime.utcnow()
+                context.last_activity = datetime.now(timezone.utc)
                 
                 # Store message in database
                 await self._store_conversation_message(
@@ -179,7 +179,7 @@ class ConversationEngine:
                 # Update statistics
                 self.stats['conversations_started'] += 1
                 self.stats['messages_generated'] += 1
-                self.stats['last_activity'] = datetime.utcnow()
+                self.stats['last_activity'] = datetime.now(timezone.utc)
                 
                 log_conversation_event(
                     conversation_id, "conversation_started",
@@ -230,7 +230,7 @@ class ConversationEngine:
                 # Update context
                 context.current_speaker = next_speaker
                 context.message_count += 1
-                context.last_activity = datetime.utcnow()
+                context.last_activity = datetime.now(timezone.utc)
                 
                 # Store message
                 await self._store_conversation_message(
@@ -245,7 +245,7 @@ class ConversationEngine:
                 
                 # Update statistics
                 self.stats['messages_generated'] += 1
-                self.stats['last_activity'] = datetime.utcnow()
+                self.stats['last_activity'] = datetime.now(timezone.utc)
                 
                 log_conversation_event(
                     conversation_id, "message_sent",
@@ -379,7 +379,7 @@ class ConversationEngine:
     
     async def get_status(self) -> Dict[str, Any]:
         """Get engine status"""
-        uptime = datetime.utcnow() - self.stats['uptime_start']
+        uptime = datetime.now(timezone.utc) - self.stats['uptime_start']
         
         return {
             'status': self.state.value,
@@ -402,8 +402,8 @@ class ConversationEngine:
                     # Use EnhancedCharacter if RAG systems are available
                     if self.vector_store and self.memory_sharing_manager:
                         # Find the appropriate MCP servers for this character
-                        from mcp.self_modification_server import mcp_server
-                        from mcp.file_system_server import filesystem_server
+                        from mcp_servers.self_modification_server import mcp_server
+                        from mcp_servers.file_system_server import filesystem_server
                         
                         # Find creative projects MCP server
                         creative_projects_mcp = None
@@ -500,7 +500,7 @@ class ConversationEngine:
         base_chance = 0.3
         
         # Increase chance if no recent activity
-        time_since_last = datetime.utcnow() - self.stats['last_activity']
+        time_since_last = datetime.now(timezone.utc) - self.stats['last_activity']
         if time_since_last > timedelta(hours=2):
             base_chance += 0.4
         elif time_since_last > timedelta(hours=1):
@@ -515,7 +515,7 @@ class ConversationEngine:
             return False
         
         # Check time limit (conversations shouldn't go on forever)
-        duration = datetime.utcnow() - context.start_time
+        duration = datetime.now(timezone.utc) - context.start_time
         if duration > timedelta(hours=2):
             return False
         
@@ -541,7 +541,7 @@ class ConversationEngine:
         context = self.active_conversations[conversation_id]
         
         # Check time since last message
-        time_since_last = datetime.utcnow() - context.last_activity
+        time_since_last = datetime.now(timezone.utc) - context.last_activity
         min_wait = timedelta(seconds=random.uniform(30, 120))
         
         return time_since_last >= min_wait
@@ -576,7 +576,7 @@ class ConversationEngine:
     
     def _is_quiet_hours(self) -> bool:
         """Check if it's currently quiet hours"""
-        current_hour = datetime.now().hour
+        current_hour = datetime.now(timezone.utc).hour
         start_hour, end_hour = self.quiet_hours
         
         if start_hour <= end_hour:
@@ -601,8 +601,8 @@ class ConversationEngine:
                     channel_id=str(self.discord_bot.channel_id),
                     topic=topic,
                     participants=participants,
-                    start_time=datetime.utcnow(),
-                    last_activity=datetime.utcnow(),
+                    start_time=datetime.now(timezone.utc),
+                    last_activity=datetime.now(timezone.utc),
                     is_active=True,
                     message_count=0
                 )
@@ -745,7 +745,7 @@ class ConversationEngine:
                         conversation_id=conversation_id,
                         character_id=character.id,
                         content=content,
-                        timestamp=datetime.utcnow()
+                        timestamp=datetime.now(timezone.utc)
                     )
                     
                     session.add(message)
@@ -821,7 +821,7 @@ class ConversationEngine:
                     conversation = await session.get(Conversation, conversation_id)
                     if conversation:
                         conversation.is_active = False
-                        conversation.last_activity = datetime.utcnow()
+                        conversation.last_activity = datetime.now(timezone.utc)
                         conversation.message_count = context.message_count
                         await session.commit()
                 
@@ -831,7 +831,7 @@ class ConversationEngine:
                 log_conversation_event(
                     conversation_id, "conversation_ended",
                     context.participants,
-                    {"total_messages": context.message_count, "duration": str(datetime.utcnow() - context.start_time)}
+                    {"total_messages": context.message_count, "duration": str(datetime.now(timezone.utc) - context.start_time)}
                 )
                 
         except Exception as e:
@@ -854,7 +854,7 @@ class ConversationEngine:
     async def _cleanup_old_conversations(self):
         """Clean up old inactive conversations"""
         try:
-            cutoff_time = datetime.utcnow() - timedelta(hours=6)
+            cutoff_time = datetime.now(timezone.utc) - timedelta(hours=6)
             
             # Remove old conversations from active list
             to_remove = []

src/conversation/scheduler.py

@@ -2,7 +2,7 @@ import asyncio
 import random
 import schedule
 from typing import Dict, Any, List, Optional
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass
 from enum import Enum
 import logging
@@ -102,7 +102,7 @@ class ConversationScheduler:
     async def schedule_event(self, event_type: str, delay: timedelta, 
                            character_name: str = None, **kwargs):
         """Schedule a specific event"""
-        scheduled_time = datetime.utcnow() + delay
+        scheduled_time = datetime.now(timezone.utc) + delay
         
         event = ScheduledEvent(
             event_type=event_type,
@@ -170,7 +170,7 @@ class ConversationScheduler:
                 'event_type': event.event_type,
                 'scheduled_time': event.scheduled_time.isoformat(),
                 'character_name': event.character_name,
-                'time_until': (event.scheduled_time - datetime.utcnow()).total_seconds(),
+                'time_until': (event.scheduled_time - datetime.now(timezone.utc)).total_seconds(),
                 'parameters': event.parameters
             }
             for event in upcoming
@@ -194,7 +194,7 @@ class ConversationScheduler:
     
     async def _process_due_events(self):
         """Process events that are due"""
-        now = datetime.utcnow()
+        now = datetime.now(timezone.utc)
         due_events = []
         
         # Find due events
@@ -378,7 +378,7 @@ class ConversationScheduler:
         base_minutes = random.uniform(20, 60)
         
         # Adjust based on time of day
-        current_hour = datetime.now().hour
+        current_hour = datetime.now(timezone.utc).hour
         activity_multiplier = self._get_activity_multiplier(current_hour)
         
         # Adjust based on current activity
@@ -427,7 +427,7 @@ class ConversationScheduler:
     
     def _get_current_activity_pattern(self) -> str:
         """Get current activity pattern"""
-        current_hour = datetime.now().hour
+        current_hour = datetime.now(timezone.utc).hour
         
         for period, config in self.activity_patterns.items():
             start, end = config['start'], config['end']

src/database/connection.py

@@ -19,8 +19,16 @@ class DatabaseManager:
         self._pool = None
         
     async def initialize(self):
-        # Use database URL from config
-        database_url = getattr(self.settings.database, 'url', 'sqlite+aiosqlite:///fishbowl_test.db')
+        # Use DATABASE_URL environment variable first, then construct from config
+        import os
+        database_url = os.getenv('DATABASE_URL')
+        
+        if not database_url:
+            # Construct URL from config components
+            db_config = self.settings.database
+            database_url = f"postgresql+asyncpg://{db_config.user}:{db_config.password}@{db_config.host}:{db_config.port}/{db_config.name}"
+        
+        logger.info(f"Using database URL: {database_url.replace(self.settings.database.password, '***') if database_url else 'None'}")
         
         # Configure engine based on database type
         if 'sqlite' in database_url:

src/database/models.py

@@ -53,6 +53,7 @@ class Conversation(Base):
     topic = Column(String(200))
     participants = Column(JSON, nullable=False, default=list)
     start_time = Column(DateTime, default=func.now())
+    end_time = Column(DateTime, nullable=True)
     last_activity = Column(DateTime, default=func.now())
     is_active = Column(Boolean, default=True)
     message_count = Column(Integer, default=0)

src/llm/client.py

@@ -3,7 +3,7 @@ import httpx
 import json
 import time
 from typing import Dict, Any, Optional, List
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from utils.config import get_settings
 from utils.logging import log_llm_interaction, log_error_with_context, log_system_health
 import logging
@@ -29,17 +29,23 @@ class LLMClient:
         self.cache = {}
         self.cache_ttl = 300  # 5 minutes
         
+        # Background task queue for long-running requests
+        self.pending_requests = {}
+        self.max_timeout = 60  # Hard timeout limit for immediate responses
+        self.fallback_timeout = 15  # Quick timeout for immediate responses
+        
         # Health monitoring
         self.health_stats = {
             'total_requests': 0,
             'successful_requests': 0,
             'failed_requests': 0,
             'average_response_time': 0,
-            'last_health_check': datetime.utcnow()
+            'last_health_check': datetime.now(timezone.utc)
         }
     
     async def generate_response(self, prompt: str, character_name: str = None, 
-                              max_tokens: int = None, temperature: float = None) -> Optional[str]:
+                              max_tokens: int = None, temperature: float = None, 
+                              use_fallback: bool = True) -> Optional[str]:
         """Generate response using LLM"""
         try:
             # Rate limiting check
@@ -55,8 +61,11 @@ class LLMClient:
             
             start_time = time.time()
             
+            # Use shorter timeout for immediate responses, longer for background
+            effective_timeout = self.fallback_timeout if use_fallback else min(self.timeout, self.max_timeout)
+            
             # Try OpenAI-compatible API first (KoboldCPP, etc.)
-            async with httpx.AsyncClient(timeout=self.timeout) as client:
+            async with httpx.AsyncClient(timeout=effective_timeout) as client:
                 try:
                     # OpenAI-compatible request
                     request_data = {
@@ -134,9 +143,24 @@ class LLMClient:
                     return None
                     
         except httpx.TimeoutException:
-            logger.error(f"LLM request timeout for {character_name}")
-            self._update_stats(False, self.timeout)
-            return None
+            if use_fallback:
+                logger.warning(f"LLM request timeout for {character_name}, using fallback response")
+                # Queue for background processing if needed
+                if self.timeout > self.max_timeout:
+                    background_task = asyncio.create_task(self.generate_response(
+                        prompt, character_name, max_tokens, temperature, use_fallback=False
+                    ))
+                    request_id = f"{character_name}_{time.time()}"
+                    self.pending_requests[request_id] = background_task
+                
+                # Return a fallback response immediately
+                fallback_response = self._get_fallback_response(character_name)
+                self._update_stats(False, effective_timeout)
+                return fallback_response
+            else:
+                logger.error(f"LLM background request timeout for {character_name}")
+                self._update_stats(False, effective_timeout)
+                return None
         except httpx.HTTPError as e:
             logger.error(f"LLM HTTP error for {character_name}: {e}")
             self._update_stats(False, time.time() - start_time)
@@ -231,11 +255,11 @@ class LLMClient:
                 'response_time': duration,
                 'model': self.model,
                 'base_url': self.base_url,
-                'timestamp': datetime.utcnow().isoformat()
+                'timestamp': datetime.now(timezone.utc).isoformat()
             }
             
             # Update health check time
-            self.health_stats['last_health_check'] = datetime.utcnow()
+            self.health_stats['last_health_check'] = datetime.now(timezone.utc)
             
             return health_status
             
@@ -246,7 +270,7 @@ class LLMClient:
                 'error': str(e),
                 'model': self.model,
                 'base_url': self.base_url,
-                'timestamp': datetime.utcnow().isoformat()
+                'timestamp': datetime.now(timezone.utc).isoformat()
             }
     
     def get_statistics(self) -> Dict[str, Any]:
@@ -342,6 +366,67 @@ class LLMClient:
         self.health_stats['average_response_time'] = (
             (current_avg * (total_requests - 1) + duration) / total_requests
         )
+    
+    def _get_fallback_response(self, character_name: str = None) -> str:
+        """Generate a fallback response when LLM is slow"""
+        fallback_responses = [
+            "*thinking deeply about this...*",
+            "*processing thoughts...*",
+            "*contemplating the discussion...*",
+            "*reflecting on what you've said...*",
+            "*considering different perspectives...*",
+            "Hmm, that's an interesting point to consider.",
+            "I need a moment to think about that.",
+            "That's worth reflecting on carefully.",
+            "*taking time to formulate thoughts...*"
+        ]
+        
+        import random
+        return random.choice(fallback_responses)
+    
+    async def generate_response_with_fallback(self, prompt: str, character_name: str = None, 
+                                            max_tokens: int = None, temperature: float = None) -> str:
+        """Generate response with guaranteed fallback if LLM is slow"""
+        try:
+            # Try immediate response first
+            response = await self.generate_response(
+                prompt, character_name, max_tokens, temperature, use_fallback=True
+            )
+            
+            if response:
+                return response
+            else:
+                # Return fallback if no response
+                return self._get_fallback_response(character_name)
+                
+        except Exception as e:
+            log_error_with_context(e, {
+                "character_name": character_name,
+                "prompt_length": len(prompt)
+            })
+            return self._get_fallback_response(character_name)
+    
+    async def cleanup_pending_requests(self):
+        """Clean up completed background requests"""
+        completed_requests = []
+        
+        for request_id, task in self.pending_requests.items():
+            if task.done():
+                completed_requests.append(request_id)
+                try:
+                    result = await task
+                    if result:
+                        logger.info(f"Background LLM request {request_id} completed successfully")
+                except Exception as e:
+                    logger.error(f"Background LLM request {request_id} failed: {e}")
+        
+        # Remove completed requests
+        for request_id in completed_requests:
+            del self.pending_requests[request_id]
+    
+    def get_pending_count(self) -> int:
+        """Get number of pending background requests"""
+        return len(self.pending_requests)
 
 class PromptManager:
     """Manages prompt templates and optimization"""

src/main.py

@@ -168,6 +168,10 @@ class FishbowlApplication:
             await self.scheduler.start()
             logger.info("Conversation scheduler started")
             
+            # Start LLM cleanup task
+            cleanup_task = asyncio.create_task(self._llm_cleanup_loop())
+            logger.info("LLM cleanup task started")
+            
             # Start Discord bot
             bot_task = asyncio.create_task(
                 self.discord_bot.start(self.settings.discord.token)
@@ -181,7 +185,7 @@ class FishbowlApplication:
             
             # Wait for shutdown signal or bot completion
             done, pending = await asyncio.wait(
-                [bot_task, asyncio.create_task(self.shutdown_event.wait())],
+                [bot_task, cleanup_task, asyncio.create_task(self.shutdown_event.wait())],
                 return_when=asyncio.FIRST_COMPLETED
             )
             
@@ -239,6 +243,24 @@ class FishbowlApplication:
         # On Windows, handle CTRL+C
         if os.name == 'nt':
             signal.signal(signal.SIGBREAK, signal_handler)
+    
+    async def _llm_cleanup_loop(self):
+        """Background task to clean up completed LLM requests"""
+        try:
+            while not self.shutdown_event.is_set():
+                await llm_client.cleanup_pending_requests()
+                pending_count = llm_client.get_pending_count()
+                
+                if pending_count > 0:
+                    logger.debug(f"LLM cleanup: {pending_count} pending background requests")
+                
+                # Wait 30 seconds before next cleanup
+                await asyncio.sleep(30)
+                
+        except asyncio.CancelledError:
+            logger.info("LLM cleanup task cancelled")
+        except Exception as e:
+            logger.error(f"Error in LLM cleanup loop: {e}")
 
 async def main():
     """Main entry point"""

src/mcp_servers/calendar_server.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, List, Any, Optional, Set
-from datetime import datetime, timedelta, date
+from datetime import datetime, timedelta, timezone, date
 from dataclasses import dataclass, asdict
 from pathlib import Path
 import aiofiles
@@ -51,7 +51,7 @@ class ScheduledEvent:
     
     def __post_init__(self):
         if self.created_at is None:
-            self.created_at = datetime.utcnow()
+            self.created_at = datetime.now(timezone.utc)
     
     def to_dict(self) -> Dict[str, Any]:
         return {
@@ -224,7 +224,7 @@ class CalendarTimeAwarenessMCP:
                 
                 # Create event
                 event = ScheduledEvent(
-                    id=f"event_{character_name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                    id=f"event_{character_name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                     character_name=character_name,
                     event_type=event_type_enum,
                     title=title,
@@ -275,7 +275,7 @@ class CalendarTimeAwarenessMCP:
         ) -> List[TextContent]:
             """Get character's upcoming events"""
             try:
-                now = datetime.utcnow()
+                now = datetime.now(timezone.utc)
                 end_time = now + timedelta(days=days_ahead)
                 
                 upcoming_events = []
@@ -340,7 +340,7 @@ class CalendarTimeAwarenessMCP:
                 
                 event = self.scheduled_events[character_name][event_id]
                 event.completed = True
-                event.metadata["completion_time"] = datetime.utcnow().isoformat()
+                event.metadata["completion_time"] = datetime.now(timezone.utc).isoformat()
                 event.metadata["completion_notes"] = notes
                 
                 await self._save_character_calendar(character_name)
@@ -442,7 +442,7 @@ class CalendarTimeAwarenessMCP:
                 
                 # Create milestone
                 milestone = Milestone(
-                    id=f"milestone_{character_name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                    id=f"milestone_{character_name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                     character_name=character_name,
                     milestone_type=milestone_type,
                     description=description,
@@ -499,7 +499,7 @@ class CalendarTimeAwarenessMCP:
         ) -> List[TextContent]:
             """Get upcoming anniversaries and milestones"""
             try:
-                now = datetime.utcnow()
+                now = datetime.now(timezone.utc)
                 end_time = now + timedelta(days=days_ahead)
                 
                 upcoming_anniversaries = []
@@ -580,7 +580,7 @@ class CalendarTimeAwarenessMCP:
                 if "celebrations" not in milestone.__dict__:
                     milestone.__dict__["celebrations"] = {}
                 milestone.__dict__["celebrations"][celebration_key] = {
-                    "date": datetime.utcnow().isoformat(),
+                    "date": datetime.now(timezone.utc).isoformat(),
                     "notes": celebration_notes
                 }
                 
@@ -628,7 +628,7 @@ class CalendarTimeAwarenessMCP:
             """Get time elapsed since a specific type of event"""
             try:
                 # Search through recent events
-                cutoff_date = datetime.utcnow() - timedelta(days=search_days_back)
+                cutoff_date = datetime.now(timezone.utc) - timedelta(days=search_days_back)
                 matching_events = []
                 
                 for event in self.scheduled_events.get(character_name, {}).values():
@@ -665,7 +665,7 @@ class CalendarTimeAwarenessMCP:
                         most_recent_description = most_recent_interaction["description"]
                 
                 # Calculate time difference
-                time_diff = datetime.utcnow() - most_recent_time
+                time_diff = datetime.now(timezone.utc) - most_recent_time
                 
                 # Format time difference
                 if time_diff.days > 0:
@@ -709,7 +709,7 @@ class CalendarTimeAwarenessMCP:
         ) -> List[TextContent]:
             """Get summary of character's activities over a time period"""
             try:
-                end_date = datetime.utcnow()
+                end_date = datetime.now(timezone.utc)
                 start_date = end_date - timedelta(days=period_days)
                 
                 # Get completed events in period
@@ -783,7 +783,7 @@ class CalendarTimeAwarenessMCP:
                 if character_name not in self.last_interactions:
                     self.last_interactions[character_name] = {}
                 
-                self.last_interactions[character_name][other_character] = datetime.utcnow()
+                self.last_interactions[character_name][other_character] = datetime.now(timezone.utc)
                 
                 # Save to file
                 await self._save_relationship_tracking(character_name)
@@ -834,7 +834,7 @@ class CalendarTimeAwarenessMCP:
                             text=f"No recorded interactions with {other_character}"
                         )]
                     
-                    time_since = datetime.utcnow() - last_interaction
+                    time_since = datetime.now(timezone.utc) - last_interaction
                     days_since = time_since.days
                     
                     # Determine maintenance status
@@ -859,7 +859,7 @@ class CalendarTimeAwarenessMCP:
                     # Get status for all relationships
                     relationships = []
                     for other_char, last_interaction in self.last_interactions.get(character_name, {}).items():
-                        time_since = datetime.utcnow() - last_interaction
+                        time_since = datetime.now(timezone.utc) - last_interaction
                         days_since = time_since.days
                         
                         if days_since <= 1:
@@ -914,13 +914,13 @@ class CalendarTimeAwarenessMCP:
             """Schedule relationship maintenance activity"""
             try:
                 # Create relationship maintenance event
-                scheduled_time = datetime.utcnow() + timedelta(days=days_from_now)
+                scheduled_time = datetime.now(timezone.utc) + timedelta(days=days_from_now)
                 
                 template = self.event_templates[EventType.RELATIONSHIP_MAINTENANCE]
                 description = template["description_template"].format(target=other_character)
                 
                 event = ScheduledEvent(
-                    id=f"rel_maintenance_{character_name}_{other_character}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                    id=f"rel_maintenance_{character_name}_{other_character}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                     character_name=character_name,
                     event_type=EventType.RELATIONSHIP_MAINTENANCE,
                     title=f"Connect with {other_character}",
@@ -1002,7 +1002,7 @@ class CalendarTimeAwarenessMCP:
             
             events_data = {
                 "events": [event.to_dict() for event in self.scheduled_events.get(character_name, {}).values()],
-                "last_updated": datetime.utcnow().isoformat()
+                "last_updated": datetime.now(timezone.utc).isoformat()
             }
             
             async with aiofiles.open(calendar_file, 'w') as f:
@@ -1019,7 +1019,7 @@ class CalendarTimeAwarenessMCP:
             
             milestones_data = {
                 "milestones": [milestone.to_dict() for milestone in self.milestones.get(character_name, {}).values()],
-                "last_updated": datetime.utcnow().isoformat()
+                "last_updated": datetime.now(timezone.utc).isoformat()
             }
             
             async with aiofiles.open(milestones_file, 'w') as f:
@@ -1039,7 +1039,7 @@ class CalendarTimeAwarenessMCP:
                     other_char: timestamp.isoformat()
                     for other_char, timestamp in self.last_interactions.get(character_name, {}).items()
                 },
-                "last_updated": datetime.utcnow().isoformat()
+                "last_updated": datetime.now(timezone.utc).isoformat()
             }
             
             async with aiofiles.open(tracking_file, 'w') as f:
@@ -1051,7 +1051,7 @@ class CalendarTimeAwarenessMCP:
     async def _schedule_initial_events(self, character_name: str):
         """Schedule initial automatic events for character"""
         try:
-            now = datetime.utcnow()
+            now = datetime.now(timezone.utc)
             
             # Schedule first personal reflection in 6 hours
             reflection_time = now + timedelta(hours=6)
@@ -1120,9 +1120,9 @@ class CalendarTimeAwarenessMCP:
             next_time = completed_event.scheduled_time + timedelta(days=frequency_days)
             
             # Only schedule if it's in the future
-            if next_time > datetime.utcnow():
+            if next_time > datetime.now(timezone.utc):
                 follow_up_event = ScheduledEvent(
-                    id=f"followup_{completed_event.event_type.value}_{character_name}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                    id=f"followup_{completed_event.event_type.value}_{character_name}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}",
                     character_name=character_name,
                     event_type=completed_event.event_type,
                     title=completed_event.title,
@@ -1259,7 +1259,7 @@ class CalendarTimeAwarenessMCP:
             if not last_interaction:
                 return
             
-            days_since = (datetime.utcnow() - last_interaction).days
+            days_since = (datetime.now(timezone.utc) - last_interaction).days
             
             # Auto-schedule maintenance if overdue and not already scheduled
             if days_since >= 7:

src/mcp_servers/creative_projects_server.py

@@ -7,7 +7,7 @@ import asyncio
 import json
 import logging
 from typing import Dict, List, Any, Optional, Sequence
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 
 from mcp.server import Server
 from mcp.server.models import InitializationOptions
@@ -397,7 +397,7 @@ class CreativeProjectsMCPServer:
             pending_invitations = []
             for invitation in self.creative_manager.pending_invitations.values():
                 if invitation.invitee == self.current_character and invitation.status == "pending":
-                    if datetime.utcnow() <= invitation.expires_at:
+                    if datetime.now(timezone.utc) <= invitation.expires_at:
                         pending_invitations.append(invitation)
             
             if not pending_invitations:

src/mcp_servers/file_system_server.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, Any, List, Optional, Set
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 import aiofiles
 import hashlib
@@ -340,7 +340,7 @@ class CharacterFileSystemMCP:
                 
                 # Generate filename
                 safe_title = "".join(c for c in title if c.isalnum() or c in (' ', '-', '_')).rstrip()
-                timestamp = datetime.utcnow().strftime("%Y%m%d_%H%M%S")
+                timestamp = datetime.now(timezone.utc).strftime("%Y%m%d_%H%M%S")
                 filename = f"{work_type}_{safe_title}_{timestamp}.md"
                 file_path = f"creative/{filename}"
                 
@@ -348,7 +348,7 @@ class CharacterFileSystemMCP:
                 metadata = {
                     "title": title,
                     "type": work_type,
-                    "created": datetime.utcnow().isoformat(),
+                    "created": datetime.now(timezone.utc).isoformat(),
                     "author": character_name,
                     "tags": tags,
                     "word_count": len(content.split())
@@ -358,7 +358,7 @@ class CharacterFileSystemMCP:
                 formatted_content = f"""# {title}
 
 **Type:** {work_type}  
-**Created:** {datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S")}  
+**Created:** {datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")}  
 **Author:** {character_name}  
 **Tags:** {', '.join(tags)}
 
@@ -385,7 +385,7 @@ class CharacterFileSystemMCP:
                         content=f"Created {work_type} titled '{title}': {content}",
                         memory_type=MemoryType.CREATIVE,
                         character_name=character_name,
-                        timestamp=datetime.utcnow(),
+                        timestamp=datetime.now(timezone.utc),
                         importance=0.8,
                         metadata={
                             "work_type": work_type,
@@ -432,7 +432,7 @@ class CharacterFileSystemMCP:
                     tags = []
                 
                 # Generate diary entry
-                timestamp = datetime.utcnow()
+                timestamp = datetime.now(timezone.utc)
                 entry = f"""
 ## {timestamp.strftime("%Y-%m-%d %H:%M:%S")}
 
@@ -519,7 +519,7 @@ class CharacterFileSystemMCP:
                         existing_content = await f.read()
                 
                 # Format contribution
-                timestamp = datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S")
+                timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
                 contribution_text = f"""
 
 ## Contribution by {character_name} ({timestamp})
@@ -544,7 +544,7 @@ class CharacterFileSystemMCP:
                         content=f"Contributed to {document_name}: {contribution}",
                         memory_type=MemoryType.COMMUNITY,
                         character_name=character_name,
-                        timestamp=datetime.utcnow(),
+                        timestamp=datetime.now(timezone.utc),
                         importance=0.7,
                         metadata={
                             "document": document_name,
@@ -601,7 +601,7 @@ class CharacterFileSystemMCP:
                     shared_name = f"{character_name}_{source_path.name}"
                 
                 # Create shared file with metadata
-                timestamp = datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S")
+                timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
                 shared_content = f"""# Shared by {character_name}
 
 **Original file:** {source_file_path}  
@@ -782,7 +782,7 @@ class CharacterFileSystemMCP:
             character_name=character_name,
             file_path=file_path,
             access_type=access_type,
-            timestamp=datetime.utcnow(),
+            timestamp=datetime.now(timezone.utc),
             success=success
         )
         self.access_log.append(access)
@@ -815,7 +815,7 @@ class CharacterFileSystemMCP:
                 content=f"File {file_path}: {content}",
                 memory_type=memory_type,
                 character_name=character_name,
-                timestamp=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
                 importance=0.7,
                 metadata={
                     "source": "file_system",
@@ -836,13 +836,13 @@ class CharacterFileSystemMCP:
         """Create initial files for a new character"""
         try:
             # Create initial diary entry
-            diary_file = char_dir / "diary" / f"{datetime.utcnow().strftime('%Y_%m')}_diary.md"
+            diary_file = char_dir / "diary" / f"{datetime.now(timezone.utc).strftime('%Y_%m')}_diary.md"
             if not diary_file.exists():
                 initial_diary = f"""# {character_name}'s Digital Diary
 
 Welcome to my personal digital space. This is where I record my thoughts, experiences, and reflections.
 
-## {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')}
+## {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S')}
 
 **Mood:** curious  
 **Tags:** beginning, digital_life

src/mcp_servers/memory_sharing_server.py

@@ -6,7 +6,7 @@ Enables characters to autonomously share memories with trusted friends
 import asyncio
 import logging
 from typing import Dict, List, Any, Optional, Sequence
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 import json
 
 from mcp.server.models import InitializationOptions
@@ -414,7 +414,7 @@ class MemorySharingMCPServer:
             response = f"📬 **{len(pending_requests)} Pending Memory Share Request(s)**\n\n"
             
             for i, request in enumerate(pending_requests, 1):
-                expires_in = request.expires_at - datetime.utcnow()
+                expires_in = request.expires_at - datetime.now(timezone.utc)
                 expires_days = expires_in.days
                 
                 response += f"**{i}. Request from {request.requesting_character}**\n"

src/mcp_servers/self_modification_server.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, Any, List, Optional, Union
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 import aiofiles
 from dataclasses import dataclass, asdict
@@ -140,7 +140,7 @@ class SelfModificationMCPServer:
                     new_value=new_personality,
                     reason=reason,
                     confidence=confidence,
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 # Apply to database
@@ -211,7 +211,7 @@ class SelfModificationMCPServer:
                 goals_data = {
                     "goals": new_goals,
                     "previous_goals": current_goals,
-                    "updated_at": datetime.utcnow().isoformat(),
+                    "updated_at": datetime.now(timezone.utc).isoformat(),
                     "reason": reason,
                     "confidence": confidence
                 }
@@ -282,7 +282,7 @@ class SelfModificationMCPServer:
                     new_value=new_style,
                     reason=reason,
                     confidence=confidence,
-                    timestamp=datetime.utcnow()
+                    timestamp=datetime.now(timezone.utc)
                 )
                 
                 # Apply to database
@@ -354,13 +354,13 @@ class SelfModificationMCPServer:
                         current_rules = json.loads(content)
                 
                 # Add new rule
-                rule_id = f"{memory_type}_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}"
+                rule_id = f"{memory_type}_{datetime.now(timezone.utc).strftime('%Y%m%d_%H%M%S')}"
                 current_rules[rule_id] = {
                     "memory_type": memory_type,
                     "importance_weight": importance_weight,
                     "retention_days": retention_days,
                     "description": rule_description,
-                    "created_at": datetime.utcnow().isoformat(),
+                    "created_at": datetime.now(timezone.utc).isoformat(),
                     "confidence": confidence,
                     "active": True
                 }
@@ -521,7 +521,7 @@ class SelfModificationMCPServer:
         async def get_modification_limits(character_name: str) -> List[TextContent]:
             """Get current modification limits and usage"""
             try:
-                today = datetime.utcnow().date().isoformat()
+                today = datetime.now(timezone.utc).date().isoformat()
                 
                 usage = self.daily_modifications.get(character_name, {}).get(today, {})
                 
@@ -571,7 +571,7 @@ class SelfModificationMCPServer:
                 }
             
             # Check daily limits
-            today = datetime.utcnow().date().isoformat()
+            today = datetime.now(timezone.utc).date().isoformat()
             if character_name not in self.daily_modifications:
                 self.daily_modifications[character_name] = {}
             if today not in self.daily_modifications[character_name]:
@@ -605,7 +605,7 @@ class SelfModificationMCPServer:
     
     async def _track_modification(self, character_name: str, modification_type: str):
         """Track modification usage for daily limits"""
-        today = datetime.utcnow().date().isoformat()
+        today = datetime.now(timezone.utc).date().isoformat()
         
         if character_name not in self.daily_modifications:
             self.daily_modifications[character_name] = {}

src/rag/community_knowledge.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from typing import Dict, List, Any, Optional, Set, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass
 from collections import defaultdict
 
@@ -99,7 +99,7 @@ class CommunityKnowledgeRAG:
                 content=f"Community {event_type}: {description}",
                 memory_type=MemoryType.COMMUNITY,
                 character_name="community",
-                timestamp=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
                 importance=importance,
                 metadata={
                     "event_type": event_type,
@@ -114,7 +114,7 @@ class CommunityKnowledgeRAG:
             
             # Update cultural evolution timeline
             self.cultural_evolution_timeline.append({
-                "timestamp": datetime.utcnow().isoformat(),
+                "timestamp": datetime.now(timezone.utc).isoformat(),
                 "event_type": event_type,
                 "description": description,
                 "participants": participants,
@@ -363,7 +363,7 @@ class CommunityKnowledgeRAG:
             if time_period is None:
                 time_period = timedelta(days=30)  # Default to last 30 days
             
-            cutoff_date = datetime.utcnow() - time_period
+            cutoff_date = datetime.now(timezone.utc) - time_period
             
             # Filter timeline events
             recent_events = [
@@ -412,7 +412,7 @@ class CommunityKnowledgeRAG:
                 # Get recent conversations
                 conversations_query = select(Conversation).where(
                     and_(
-                        Conversation.start_time >= datetime.utcnow() - timedelta(days=30),
+                        Conversation.start_time >= datetime.now(timezone.utc) - timedelta(days=30),
                         Conversation.message_count >= 3  # Only substantial conversations
                     )
                 ).order_by(desc(Conversation.start_time)).limit(50)

src/rag/memory_sharing.py

@@ -6,7 +6,7 @@ Enables selective memory sharing between trusted characters
 import asyncio
 import logging
 from typing import Dict, List, Any, Optional, Tuple, Set
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass, asdict
 from enum import Enum
 import json
@@ -167,7 +167,7 @@ class MemorySharingManager:
                 return False, "No relevant memories found to share"
             
             # Create share request
-            request_id = f"share_{requesting_character}_{target_character}_{datetime.utcnow().timestamp()}"
+            request_id = f"share_{requesting_character}_{target_character}_{datetime.now(timezone.utc).timestamp()}"
             share_request = ShareRequest(
                 id=request_id,
                 requesting_character=requesting_character,
@@ -176,8 +176,8 @@ class MemorySharingManager:
                 permission_level=permission_level,
                 reason=reason,
                 status=ShareRequestStatus.PENDING,
-                created_at=datetime.utcnow(),
-                expires_at=datetime.utcnow() + timedelta(days=7)  # 7 day expiry
+                created_at=datetime.now(timezone.utc),
+                expires_at=datetime.now(timezone.utc) + timedelta(days=7)  # 7 day expiry
             )
             
             self.share_requests[request_id] = share_request
@@ -220,7 +220,7 @@ class MemorySharingManager:
             if request.status != ShareRequestStatus.PENDING:
                 return False, f"Request is already {request.status.value}"
             
-            if datetime.utcnow() > request.expires_at:
+            if datetime.now(timezone.utc) > request.expires_at:
                 request.status = ShareRequestStatus.EXPIRED
                 return False, "Request has expired"
             
@@ -276,13 +276,13 @@ class MemorySharingManager:
             
             # Create and store shared memory
             shared_memory = SharedMemory(
-                id=f"shared_{memory_id}_{datetime.utcnow().timestamp()}",
+                id=f"shared_{memory_id}_{datetime.now(timezone.utc).timestamp()}",
                 original_memory_id=memory_id,
                 content=memory_to_share.content,
                 memory_type=memory_to_share.memory_type,
                 source_character=source_character,
                 target_character=target_character,
-                shared_at=datetime.utcnow(),
+                shared_at=datetime.now(timezone.utc),
                 permission_level=permission_level,
                 share_reason=reason,
                 metadata=memory_to_share.metadata
@@ -437,7 +437,7 @@ class MemorySharingManager:
             
             # Update trust level
             trust_level.trust_score = new_trust
-            trust_level.last_updated = datetime.utcnow()
+            trust_level.last_updated = datetime.now(timezone.utc)
             trust_level.interaction_history += 1
             
             # Update maximum permission level based on new trust
@@ -462,7 +462,7 @@ class MemorySharingManager:
     async def get_pending_requests(self, character_name: str) -> List[ShareRequest]:
         """Get pending share requests for a character"""
         pending_requests = []
-        current_time = datetime.utcnow()
+        current_time = datetime.now(timezone.utc)
         
         for request in self.share_requests.values():
             # Check for expired requests
@@ -544,13 +544,13 @@ class MemorySharingManager:
         for memory in memories:
             if memory.id in request.memory_ids:
                 shared_memory = SharedMemory(
-                    id=f"shared_{memory.id}_{datetime.utcnow().timestamp()}",
+                    id=f"shared_{memory.id}_{datetime.now(timezone.utc).timestamp()}",
                     original_memory_id=memory.id,
                     content=memory.content,
                     memory_type=memory.memory_type,
                     source_character=request.requesting_character,
                     target_character=request.target_character,
-                    shared_at=datetime.utcnow(),
+                    shared_at=datetime.now(timezone.utc),
                     permission_level=request.permission_level,
                     share_reason=request.reason,
                     metadata=memory.metadata
@@ -602,7 +602,7 @@ class MemorySharingManager:
                 max_permission_level=SharePermissionLevel.NONE,
                 relationship_strength=0.5,
                 interaction_history=0,
-                last_updated=datetime.utcnow()
+                last_updated=datetime.now(timezone.utc)
             )
             
             # Determine max permission level

src/rag/personal_memory.py

@@ -1,6 +1,6 @@
 import asyncio
 from typing import Dict, List, Any, Optional, Tuple
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from dataclasses import dataclass
 import json
 
@@ -92,7 +92,7 @@ class PersonalMemoryRAG:
                 content=content,
                 memory_type=memory_type,
                 character_name=self.character_name,
-                timestamp=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
                 importance=importance,
                 metadata={
                     "interaction_type": context.get("type", "unknown"),
@@ -128,7 +128,7 @@ class PersonalMemoryRAG:
                 content=reflection,
                 memory_type=MemoryType.REFLECTION,
                 character_name=self.character_name,
-                timestamp=datetime.utcnow(),
+                timestamp=datetime.now(timezone.utc),
                 importance=importance,
                 metadata={
                     "reflection_type": reflection_type,
@@ -369,7 +369,7 @@ class PersonalMemoryRAG:
                     "avg_memory_importance": sum(importance_scores) / len(importance_scores),
                     "high_importance_memories": len([s for s in importance_scores if s > 0.7]),
                     "recent_memory_count": len([m for m in personal_memories 
-                                              if (datetime.utcnow() - m.timestamp).days < 7])
+                                              if (datetime.now(timezone.utc) - m.timestamp).days < 7])
                 })
             
             return stats

src/rag/vector_store.py

@@ -1,8 +1,8 @@
 import asyncio
-import chromadb
+import os
 import numpy as np
-from typing import Dict, List, Any, Optional, Tuple
-from datetime import datetime, timedelta
+from typing import Dict, List, Any, Optional, Tuple, Union
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 import json
 import hashlib
@@ -14,6 +14,20 @@ from utils.logging import log_error_with_context, log_character_action
 from utils.config import get_settings
 import logging
 
+# Vector database backends
+try:
+    import chromadb
+    CHROMADB_AVAILABLE = True
+except ImportError:
+    CHROMADB_AVAILABLE = False
+
+try:
+    from qdrant_client import QdrantClient
+    from qdrant_client.models import Distance, VectorParams, PointStruct
+    QDRANT_AVAILABLE = True
+except ImportError:
+    QDRANT_AVAILABLE = False
+
 logger = logging.getLogger(__name__)
 
 class MemoryType(Enum):
@@ -56,48 +70,120 @@ class VectorStoreManager:
         # Initialize embedding model
         self.embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
         
-        # Initialize ChromaDB client
-        self.chroma_client = chromadb.PersistentClient(path=str(self.data_path))
+        # Determine vector database backend from environment
+        self.backend = self._get_vector_backend()
         
-        # Collection references
-        self.personal_collections: Dict[str, chromadb.Collection] = {}
+        # Initialize appropriate client
+        if self.backend == "qdrant":
+            self._init_qdrant_client()
+        elif self.backend == "chromadb":
+            self._init_chromadb_client()
+        else:
+            raise ValueError(f"Unsupported vector database backend: {self.backend}")
+        
+        # Collection references (abstracted)
+        self.personal_collections: Dict[str, Any] = {}
         self.community_collection = None
-        self.creative_collections: Dict[str, chromadb.Collection] = {}
+        self.creative_collections: Dict[str, Any] = {}
         
         # Memory importance decay
         self.importance_decay_rate = 0.95
         self.consolidation_threshold = 0.8
+    
+    def _get_vector_backend(self) -> str:
+        """Determine which vector database to use from environment"""
+        vector_db_type = os.getenv("VECTOR_DB_TYPE", "chromadb").lower()
+        
+        if vector_db_type == "qdrant" and not QDRANT_AVAILABLE:
+            logger.warning("Qdrant requested but not available, falling back to ChromaDB")
+            vector_db_type = "chromadb"
+        elif vector_db_type == "chromadb" and not CHROMADB_AVAILABLE:
+            logger.warning("ChromaDB requested but not available, falling back to Qdrant")
+            vector_db_type = "qdrant"
+        
+        logger.info(f"Using vector database backend: {vector_db_type}")
+        return vector_db_type
+    
+    def _init_qdrant_client(self):
+        """Initialize Qdrant client"""
+        host = os.getenv("QDRANT_HOST", "localhost")
+        port = int(os.getenv("QDRANT_PORT", "6333"))
+        
+        self.qdrant_client = QdrantClient(host=host, port=port)
+        self.collection_name = os.getenv("QDRANT_COLLECTION", "fishbowl_memories")
+        
+        logger.info(f"Initialized Qdrant client: {host}:{port}")
+    
+    def _init_chromadb_client(self):
+        """Initialize ChromaDB client"""
+        self.chroma_client = chromadb.PersistentClient(path=str(self.data_path))
+        logger.info(f"Initialized ChromaDB client: {self.data_path}")
         
     async def initialize(self, character_names: List[str]):
         """Initialize collections for all characters"""
         try:
-            # Initialize personal memory collections
-            for character_name in character_names:
-                collection_name = f"personal_{character_name.lower()}"
-                self.personal_collections[character_name] = self.chroma_client.get_or_create_collection(
-                    name=collection_name,
-                    metadata={"type": "personal", "character": character_name}
-                )
-                
-                # Initialize creative collections
-                creative_collection_name = f"creative_{character_name.lower()}"
-                self.creative_collections[character_name] = self.chroma_client.get_or_create_collection(
-                    name=creative_collection_name,
-                    metadata={"type": "creative", "character": character_name}
-                )
+            if self.backend == "qdrant":
+                await self._initialize_qdrant_collections(character_names)
+            elif self.backend == "chromadb":
+                await self._initialize_chromadb_collections(character_names)
             
-            # Initialize community collection
-            self.community_collection = self.chroma_client.get_or_create_collection(
-                name="community_knowledge",
-                metadata={"type": "community"}
-            )
-            
-            logger.info(f"Initialized vector stores for {len(character_names)} characters")
+            logger.info(f"Initialized {self.backend} vector stores for {len(character_names)} characters")
             
         except Exception as e:
             log_error_with_context(e, {"component": "vector_store_init"})
             raise
     
+    async def _initialize_qdrant_collections(self, character_names: List[str]):
+        """Initialize Qdrant collections"""
+        # For Qdrant, we use a single collection with namespaced points
+        embedding_dim = 384  # all-MiniLM-L6-v2 dimension
+        
+        try:
+            # Create main collection if it doesn't exist
+            collections = self.qdrant_client.get_collections().collections
+            collection_exists = any(c.name == self.collection_name for c in collections)
+            
+            if not collection_exists:
+                self.qdrant_client.create_collection(
+                    collection_name=self.collection_name,
+                    vectors_config=VectorParams(size=embedding_dim, distance=Distance.COSINE),
+                )
+                logger.info(f"Created Qdrant collection: {self.collection_name}")
+            
+            # Store collection references (using collection name as identifier)
+            for character_name in character_names:
+                self.personal_collections[character_name] = f"personal_{character_name.lower()}"
+                self.creative_collections[character_name] = f"creative_{character_name.lower()}"
+            
+            self.community_collection = "community_knowledge"
+            
+        except Exception as e:
+            logger.error(f"Failed to initialize Qdrant collections: {e}")
+            raise
+    
+    async def _initialize_chromadb_collections(self, character_names: List[str]):
+        """Initialize ChromaDB collections"""
+        # Initialize personal memory collections
+        for character_name in character_names:
+            collection_name = f"personal_{character_name.lower()}"
+            self.personal_collections[character_name] = self.chroma_client.get_or_create_collection(
+                name=collection_name,
+                metadata={"type": "personal", "character": character_name}
+            )
+            
+            # Initialize creative collections
+            creative_collection_name = f"creative_{character_name.lower()}"
+            self.creative_collections[character_name] = self.chroma_client.get_or_create_collection(
+                name=creative_collection_name,
+                metadata={"type": "creative", "character": character_name}
+            )
+        
+        # Initialize community collection
+        self.community_collection = self.chroma_client.get_or_create_collection(
+            name="community_knowledge",
+            metadata={"type": "community"}
+        )
+    
     async def store_memory(self, memory: VectorMemory) -> str:
         """Store a memory in appropriate vector database"""
         try:
@@ -109,28 +195,11 @@ class VectorStoreManager:
             if not memory.id:
                 memory.id = self._generate_memory_id(memory)
             
-            # Select appropriate collection
-            collection = self._get_collection_for_memory(memory)
-            
-            if not collection:
-                raise ValueError(f"No collection found for memory type: {memory.memory_type}")
-            
-            # Prepare metadata
-            metadata = memory.metadata.copy()
-            metadata.update({
-                "character_name": memory.character_name,
-                "timestamp": memory.timestamp.isoformat(),
-                "importance": memory.importance,
-                "memory_type": memory.memory_type.value
-            })
-            
-            # Store in collection
-            collection.add(
-                ids=[memory.id],
-                embeddings=[memory.embedding],
-                documents=[memory.content],
-                metadatas=[metadata]
-            )
+            # Store based on backend
+            if self.backend == "qdrant":
+                await self._store_memory_qdrant(memory)
+            elif self.backend == "chromadb":
+                await self._store_memory_chromadb(memory)
             
             log_character_action(
                 memory.character_name,
@@ -147,6 +216,68 @@ class VectorStoreManager:
             })
             raise
     
+    async def _store_memory_qdrant(self, memory: VectorMemory):
+        """Store memory in Qdrant"""
+        # Prepare metadata
+        metadata = memory.metadata.copy()
+        metadata.update({
+            "character_name": memory.character_name,
+            "timestamp": memory.timestamp.isoformat(),
+            "importance": memory.importance,
+            "memory_type": memory.memory_type.value,
+            "content": memory.content,
+            "namespace": self._get_namespace_for_memory(memory)
+        })
+        
+        # Create point
+        point = PointStruct(
+            id=hash(memory.id) % (2**63),  # Convert string ID to int
+            vector=memory.embedding,
+            payload=metadata
+        )
+        
+        # Store in Qdrant
+        self.qdrant_client.upsert(
+            collection_name=self.collection_name,
+            points=[point]
+        )
+    
+    async def _store_memory_chromadb(self, memory: VectorMemory):
+        """Store memory in ChromaDB"""
+        # Select appropriate collection
+        collection = self._get_collection_for_memory(memory)
+        
+        if not collection:
+            raise ValueError(f"No collection found for memory type: {memory.memory_type}")
+        
+        # Prepare metadata
+        metadata = memory.metadata.copy()
+        metadata.update({
+            "character_name": memory.character_name,
+            "timestamp": memory.timestamp.isoformat(),
+            "importance": memory.importance,
+            "memory_type": memory.memory_type.value
+        })
+        
+        # Store in collection
+        collection.add(
+            ids=[memory.id],
+            embeddings=[memory.embedding],
+            documents=[memory.content],
+            metadatas=[metadata]
+        )
+    
+    def _get_namespace_for_memory(self, memory: VectorMemory) -> str:
+        """Get namespace for Qdrant based on memory type and character"""
+        if memory.memory_type == MemoryType.PERSONAL:
+            return f"personal_{memory.character_name.lower()}"
+        elif memory.memory_type == MemoryType.CREATIVE:
+            return f"creative_{memory.character_name.lower()}"
+        elif memory.memory_type == MemoryType.COMMUNITY:
+            return "community_knowledge"
+        else:
+            return f"{memory.memory_type.value}_{memory.character_name.lower()}"
+    
     async def query_memories(self, character_name: str, query: str, 
                            memory_types: List[MemoryType] = None,
                            limit: int = 10, min_importance: float = 0.0) -> List[VectorMemory]:
@@ -155,64 +286,133 @@ class VectorStoreManager:
             # Generate query embedding
             query_embedding = await self._generate_embedding(query)
             
-            # Determine which collections to search
-            collections_to_search = []
+            # Query based on backend
+            if self.backend == "qdrant":
+                return await self._query_memories_qdrant(character_name, query, query_embedding, memory_types, limit, min_importance)
+            elif self.backend == "chromadb":
+                return await self._query_memories_chromadb(character_name, query, query_embedding, memory_types, limit, min_importance)
             
-            if not memory_types:
-                memory_types = [MemoryType.PERSONAL, MemoryType.RELATIONSHIP, 
-                              MemoryType.EXPERIENCE, MemoryType.REFLECTION]
-            
-            for memory_type in memory_types:
-                collection = self._get_collection_for_type(character_name, memory_type)
-                if collection:
-                    collections_to_search.append((collection, memory_type))
-            
-            # Search each collection
-            all_results = []
-            
-            for collection, memory_type in collections_to_search:
-                try:
-                    results = collection.query(
-                        query_embeddings=[query_embedding],
-                        n_results=limit,
-                        where={"character_name": character_name} if memory_type != MemoryType.COMMUNITY else None
-                    )
-                    
-                    # Convert results to VectorMemory objects
-                    for i, (doc, metadata, distance) in enumerate(zip(
-                        results['documents'][0],
-                        results['metadatas'][0], 
-                        results['distances'][0]
-                    )):
-                        if metadata.get('importance', 0) >= min_importance:
-                            memory = VectorMemory(
-                                id=results['ids'][0][i],
-                                content=doc,
-                                memory_type=MemoryType(metadata['memory_type']),
-                                character_name=metadata['character_name'],
-                                timestamp=datetime.fromisoformat(metadata['timestamp']),
-                                importance=metadata['importance'],
-                                metadata=metadata
-                            )
-                            memory.metadata['similarity_score'] = 1 - distance  # Convert distance to similarity
-                            all_results.append(memory)
-                            
-                except Exception as e:
-                    logger.warning(f"Error querying collection {memory_type}: {e}")
-                    continue
-            
-            # Sort by relevance (similarity + importance)
-            all_results.sort(
-                key=lambda m: m.metadata.get('similarity_score', 0) * 0.7 + m.importance * 0.3,
-                reverse=True
-            )
-            
-            return all_results[:limit]
+            return []
             
         except Exception as e:
             log_error_with_context(e, {"character": character_name, "query": query})
             return []
     
+    async def _query_memories_qdrant(self, character_name: str, query: str, query_embedding: List[float],
+                                   memory_types: List[MemoryType], limit: int, min_importance: float) -> List[VectorMemory]:
+        """Query memories using Qdrant"""
+        if not memory_types:
+            memory_types = [MemoryType.PERSONAL, MemoryType.RELATIONSHIP, 
+                          MemoryType.EXPERIENCE, MemoryType.REFLECTION]
+        
+        # Build filter for namespaces and character
+        must_conditions = [
+            {"key": "character_name", "match": {"value": character_name}},
+            {"key": "importance", "range": {"gte": min_importance}}
+        ]
+        
+        # Add memory type filter
+        namespace_values = [self._get_namespace_for_memory_type(character_name, mt) for mt in memory_types]
+        must_conditions.append({
+            "key": "namespace", 
+            "match": {"any": namespace_values}
+        })
+        
+        # Query Qdrant
+        search_result = self.qdrant_client.search(
+            collection_name=self.collection_name,
+            query_vector=query_embedding,
+            query_filter={"must": must_conditions},
+            limit=limit,
+            with_payload=True
+        )
+        
+        # Convert to VectorMemory objects
+        results = []
+        for point in search_result:
+            payload = point.payload
+            memory = VectorMemory(
+                id=str(point.id),
+                content=payload.get("content", ""),
+                memory_type=MemoryType(payload.get("memory_type")),
+                character_name=payload.get("character_name"),
+                timestamp=datetime.fromisoformat(payload.get("timestamp")),
+                importance=payload.get("importance", 0.0),
+                metadata=payload
+            )
+            memory.metadata['similarity_score'] = point.score
+            results.append(memory)
+        
+        return results
+    
+    async def _query_memories_chromadb(self, character_name: str, query: str, query_embedding: List[float],
+                                     memory_types: List[MemoryType], limit: int, min_importance: float) -> List[VectorMemory]:
+        """Query memories using ChromaDB"""
+        if not memory_types:
+            memory_types = [MemoryType.PERSONAL, MemoryType.RELATIONSHIP, 
+                          MemoryType.EXPERIENCE, MemoryType.REFLECTION]
+        
+        # Determine which collections to search
+        collections_to_search = []
+        
+        for memory_type in memory_types:
+            collection = self._get_collection_for_type(character_name, memory_type)
+            if collection:
+                collections_to_search.append((collection, memory_type))
+        
+        # Search each collection
+        all_results = []
+        
+        for collection, memory_type in collections_to_search:
+            try:
+                results = collection.query(
+                    query_embeddings=[query_embedding],
+                    n_results=limit,
+                    where={"character_name": character_name} if memory_type != MemoryType.COMMUNITY else None
+                )
+                
+                # Convert results to VectorMemory objects
+                for i, (doc, metadata, distance) in enumerate(zip(
+                    results['documents'][0],
+                    results['metadatas'][0], 
+                    results['distances'][0]
+                )):
+                    if metadata.get('importance', 0) >= min_importance:
+                        memory = VectorMemory(
+                            id=results['ids'][0][i],
+                            content=doc,
+                            memory_type=MemoryType(metadata['memory_type']),
+                            character_name=metadata['character_name'],
+                            timestamp=datetime.fromisoformat(metadata['timestamp']),
+                            importance=metadata['importance'],
+                            metadata=metadata
+                        )
+                        memory.metadata['similarity_score'] = 1 - distance  # Convert distance to similarity
+                        all_results.append(memory)
+                            
+            except Exception as e:
+                logger.warning(f"Error querying collection {memory_type}: {e}")
+                continue
+        
+        # Sort by relevance (similarity + importance)
+        all_results.sort(
+            key=lambda m: m.metadata.get('similarity_score', 0) * 0.7 + m.importance * 0.3,
+            reverse=True
+        )
+        
+        return all_results[:limit]
+    
+    def _get_namespace_for_memory_type(self, character_name: str, memory_type: MemoryType) -> str:
+        """Get namespace for a specific memory type and character"""
+        if memory_type == MemoryType.PERSONAL:
+            return f"personal_{character_name.lower()}"
+        elif memory_type == MemoryType.CREATIVE:
+            return f"creative_{character_name.lower()}"
+        elif memory_type == MemoryType.COMMUNITY:
+            return "community_knowledge"
+        else:
+            return f"{memory_type.value}_{character_name.lower()}"
+    
     async def query_community_knowledge(self, query: str, limit: int = 5) -> List[VectorMemory]:
         """Query community knowledge base"""
         try:
@@ -347,7 +547,7 @@ class VectorStoreManager:
             for memory_id, metadata in zip(all_memories['ids'], all_memories['metadatas']):
                 # Calculate age in days
                 timestamp = datetime.fromisoformat(metadata['timestamp'])
-                age_days = (datetime.utcnow() - timestamp).days
+                age_days = (datetime.now(timezone.utc) - timestamp).days
                 
                 # Apply decay
                 current_importance = metadata['importance']
@@ -385,7 +585,7 @@ class VectorStoreManager:
             # Return zero embedding as fallback
             return [0.0] * 384  # MiniLM embedding size
     
-    def _get_collection_for_memory(self, memory: VectorMemory) -> Optional[chromadb.Collection]:
+    def _get_collection_for_memory(self, memory: VectorMemory) -> Optional[Any]:
         """Get appropriate collection for memory"""
         if memory.memory_type == MemoryType.COMMUNITY:
             return self.community_collection
@@ -394,7 +594,7 @@ class VectorStoreManager:
         else:
             return self.personal_collections.get(memory.character_name)
     
-    def _get_collection_for_type(self, character_name: str, memory_type: MemoryType) -> Optional[chromadb.Collection]:
+    def _get_collection_for_type(self, character_name: str, memory_type: MemoryType) -> Optional[Any]:
         """Get collection for specific memory type and character"""
         if memory_type == MemoryType.COMMUNITY:
             return self.community_collection
@@ -473,7 +673,7 @@ class VectorStoreManager:
                 metadata={
                     "consolidated": True,
                     "original_count": len(cluster),
-                    "consolidation_date": datetime.utcnow().isoformat()
+                    "consolidation_date": datetime.now(timezone.utc).isoformat()
                 }
             )
             

src/utils/config.py

@@ -28,9 +28,12 @@ class DiscordConfig(BaseModel):
 class LLMConfig(BaseModel):
     base_url: str = "http://localhost:11434"
     model: str = "llama2"
-    timeout: int = 30
-    max_tokens: int = 512
+    timeout: int = 300
+    max_tokens: int = 2000
     temperature: float = 0.8
+    max_prompt_length: int = 6000
+    max_history_messages: int = 5
+    max_memories: int = 5
 
 class ConversationConfig(BaseModel):
     min_delay_seconds: int = 30

src/utils/logging.py

@@ -3,7 +3,7 @@ from loguru import logger
 from typing import Dict, Any
 import sys
 import traceback
-from datetime import datetime
+from datetime import datetime, timezone
 
 class InterceptHandler(logging.Handler):
     """Intercept standard logging and route to loguru"""
@@ -123,6 +123,6 @@ def log_system_health(component: str, status: str, metrics: Dict[str, Any] = Non
         f"System health - {component}: {status}",
         extra={
             "metrics": metrics or {},
-            "timestamp": datetime.utcnow().isoformat()
+            "timestamp": datetime.now(timezone.utc).isoformat()
         }
     )