Integrate self-hosted Supabase with mem0 system

- Configure mem0 to use self-hosted Supabase instead of Qdrant for vector storage
- Update docker-compose to connect containers to localai network
- Install vecs library for Supabase pgvector integration
- Create comprehensive test suite for Supabase + mem0 integration
- Update documentation to reflect Supabase configuration
- All containers now connected to shared localai network
- Successful vector storage and retrieval tests completed

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

test_openai.py

@@ -0,0 +1,77 @@
+#!/usr/bin/env python3
+"""
+Test OpenAI integration with mem0
+"""
+
+import os
+from dotenv import load_dotenv
+from mem0 import Memory
+from config import load_config, get_mem0_config
+
+# Load environment variables from .env file if it exists
+load_dotenv()
+
+def test_openai_integration():
+    """Test mem0 with OpenAI integration"""
+    
+    # Load configuration
+    config = load_config()
+    
+    if not config.llm.openai_api_key:
+        print("❌ OPENAI_API_KEY not found in environment variables")
+        print("Please set your OpenAI API key in .env file or environment")
+        return False
+    
+    try:
+        print("Testing mem0 with OpenAI integration...")
+        
+        # Get mem0 configuration for OpenAI
+        mem0_config = get_mem0_config(config, "openai")
+        print(f"✅ Configuration loaded: {list(mem0_config.keys())}")
+        
+        # Initialize Memory with OpenAI
+        print("Initializing mem0 Memory with OpenAI...")
+        memory = Memory.from_config(config_dict=mem0_config)
+        print("✅ Memory initialized successfully")
+        
+        # Test basic memory operations
+        print("\nTesting basic memory operations...")
+        
+        # Add a memory
+        print("Adding test memory...")
+        messages = [
+            {"role": "user", "content": "I love machine learning and AI. My favorite framework is PyTorch."},
+            {"role": "assistant", "content": "That's great! PyTorch is indeed a powerful framework for AI development."}
+        ]
+        
+        result = memory.add(messages, user_id="test_user")
+        print(f"✅ Memory added: {result}")
+        
+        # Search memories
+        print("\nSearching memories...")
+        search_results = memory.search(query="AI framework", user_id="test_user")
+        print(f"✅ Search results: {len(search_results)} memories found")
+        for i, result in enumerate(search_results):
+            print(f"  {i+1}. {result['memory'][:100]}...")
+        
+        # Get all memories
+        print("\nRetrieving all memories...")
+        all_memories = memory.get_all(user_id="test_user")
+        print(f"✅ Total memories: {len(all_memories)}")
+        
+        return True
+        
+    except Exception as e:
+        print(f"❌ Error during OpenAI integration test: {e}")
+        return False
+
+if __name__ == "__main__":
+    success = test_openai_integration()
+    if success:
+        print("\n🎉 OpenAI integration test passed!")
+    else:
+        print("\n💥 OpenAI integration test failed!")
+        print("\nTo run this test:")
+        print("1. Copy .env.example to .env")
+        print("2. Add your OpenAI API key to .env")
+        print("3. Run: python test_openai.py")