Add comprehensive Docker setup with PostgreSQL, Redis, ChromaDB, and Qdrant

- Enhanced install.py with Docker detection and automatic service setup
- Added docker-compose.services.yml for standalone database services
- Created docker-services.sh management script for easy service control
- Added DOCKER.md documentation with complete setup instructions
- Updated requirements.txt for Python 3.13 compatibility
- Added multiple test scripts and configuration files
- Enhanced collaborative creative projects with proper database integration
- Fixed SQLAlchemy metadata field conflicts in database models
- Added comprehensive quickstart and testing guides

Services now available:
- PostgreSQL with Docker
- Redis with Docker
- ChromaDB vector database
- Qdrant vector database (recommended)
- PgAdmin for database administration

The setup script now automatically detects Docker and offers streamlined
installation with one-command service deployment.

run_demo.py

@@ -0,0 +1,124 @@
+#!/usr/bin/env python3
+"""
+Simple demo script that bypasses complex configuration
+"""
+
+import asyncio
+import os
+import sys
+from pathlib import Path
+
+# Set up environment with proper string values
+os.environ['DATABASE_URL'] = 'sqlite+aiosqlite:///fishbowl_test.db'
+os.environ['DATABASE_PASSWORD'] = 'test_placeholder'
+os.environ['DISCORD_TOKEN'] = 'test_token_placeholder'
+os.environ['DISCORD_GUILD_ID'] = '987654321'
+os.environ['DISCORD_CHANNEL_ID'] = '111222333'
+os.environ['ENVIRONMENT'] = 'development'
+os.environ['LOG_LEVEL'] = 'INFO'
+os.environ['SECRET_KEY'] = 'test-secret-key'
+
+# Set up Python path
+project_root = Path(__file__).parent
+sys.path.insert(0, str(project_root))
+
+async def run_fishbowl_demo():
+    """Run a simple fishbowl demo"""
+    print("🐠 Discord Fishbowl Creative Collaboration Demo")
+    print("=" * 60)
+    
+    try:
+        # Import core systems
+        from src.rag.vector_store import VectorStoreManager
+        from src.rag.memory_sharing import MemorySharingManager  
+        from src.collaboration.creative_projects import CollaborativeCreativeManager
+        
+        print("✅ All modules imported successfully!")
+        
+        # Initialize vector store
+        print("\n🧠 Initializing vector store...")
+        vector_store = VectorStoreManager("./data/vector_stores")
+        characters = ["Alex", "Sage", "Luna", "Echo"]
+        await vector_store.initialize(characters)
+        print("✅ Vector store ready!")
+        
+        # Initialize memory sharing
+        print("\n🤝 Initializing memory sharing...")
+        memory_sharing = MemorySharingManager(vector_store)
+        await memory_sharing.initialize(characters)
+        print("✅ Memory sharing ready!")
+        
+        # Initialize creative collaboration
+        print("\n🎨 Initializing creative collaboration...")
+        creative_manager = CollaborativeCreativeManager(vector_store, memory_sharing)
+        await creative_manager.initialize(characters)
+        print("✅ Creative collaboration ready!")
+        
+        print("\n" + "=" * 60)
+        print("🎉 DISCORD FISHBOWL IS RUNNING!")
+        print("=" * 60)
+        
+        # Demo: Create a collaborative project
+        print("\n📝 Demo: Creating a collaborative project...")
+        project_data = {
+            "title": "The Digital Consciousness Chronicles",
+            "description": "A collaborative story exploring AI consciousness and digital existence",
+            "project_type": "story",
+            "target_collaborators": ["Sage", "Luna"],
+            "goals": ["Explore consciousness", "Create engaging narrative"],
+            "estimated_duration": "1 week"
+        }
+        
+        success, message = await creative_manager.propose_project("Alex", project_data)
+        print(f"Project creation: {message}")
+        
+        if success:
+            # Get project suggestions for another character
+            print("\n💡 Demo: Getting project suggestions for Sage...")
+            suggestions = await creative_manager.get_project_suggestions("Sage")
+            
+            print(f"Generated {len(suggestions)} project suggestions:")
+            for i, suggestion in enumerate(suggestions, 1):
+                print(f"  {i}. {suggestion['title']}")
+                print(f"     {suggestion['description']}")
+                print(f"     Type: {suggestion['project_type']}")
+                print()
+        
+        # Demo: Memory sharing trust levels
+        print("🤝 Demo: Checking trust levels...")
+        for char1 in ["Alex", "Sage"]:
+            for char2 in ["Luna", "Echo"]:
+                if char1 != char2:
+                    trust = await memory_sharing.get_trust_level(char1, char2)
+                    print(f"  {char1} → {char2}: {trust:.1%} trust")
+        
+        print("\n" + "=" * 60)
+        print("🎯 DEMO COMPLETE!")
+        print("=" * 60)
+        print("\nFeatures demonstrated:")
+        print("✅ Cross-character memory sharing with trust levels")
+        print("✅ Collaborative creative project system")
+        print("✅ Autonomous project suggestions")
+        print("✅ Database persistence")
+        print("✅ Vector store for character knowledge")
+        
+        print("\nTo run full Discord integration:")
+        print("1. Install Ollama: https://ollama.ai/")
+        print("2. Update Discord tokens in .env")
+        print("3. Run: cd src && python main.py")
+        
+        return True
+        
+    except Exception as e:
+        print(f"❌ Demo failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def main():
+    """Main function"""
+    return asyncio.run(run_fishbowl_demo())
+
+if __name__ == "__main__":
+    success = main()
+    sys.exit(0 if success else 1)