feat(04-GC-02): verify SQLiteManager method integration

Add verification test to ensure get_conversations_by_date_range and
get_conversation_messages methods:
- Can be called without AttributeError
- Return data in proper format
- Are compatible with PersonalityLearner usage patterns

All integration tests passed successfully.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

test_method_integration.py

@@ -0,0 +1,127 @@
+"""
+Simple verification script for SQLiteManager methods integration.
+
+This script verifies that the newly added methods can be called
+without AttributeError and return data in proper format.
+"""
+
+import sys
+import os
+from datetime import datetime, timedelta
+import tempfile
+
+# Add project path
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
+
+from memory.storage.sqlite_manager import SQLiteManager
+
+
+def test_methods_exist():
+    """Verify methods exist and can be called."""
+    print("Testing method existence...")
+
+    # Create temporary database
+    with tempfile.NamedTemporaryFile(suffix='.db', delete=False) as f:
+        db_path = f.name
+
+    try:
+        # Initialize manager
+        manager = SQLiteManager(db_path)
+
+        # Create test conversation
+        conv_id = "test_conv_001"
+        manager.create_conversation(conv_id, title="Test Conversation")
+
+        # Add test messages
+        manager.add_message(
+            "msg_001",
+            conv_id,
+            "user",
+            "Hello, this is a test message",
+            token_count=10
+        )
+        manager.add_message(
+            "msg_002",
+            conv_id,
+            "assistant",
+            "Hello! This is a response",
+            token_count=8
+        )
+
+        # Test get_conversations_by_date_range
+        print("\n1. Testing get_conversations_by_date_range...")
+        start_date = datetime.now() - timedelta(days=1)
+        end_date = datetime.now() + timedelta(days=1)
+
+        conversations = manager.get_conversations_by_date_range(start_date, end_date)
+
+        assert isinstance(conversations, list), "Should return a list"
+        assert len(conversations) > 0, "Should find at least one conversation"
+        assert "id" in conversations[0], "Conversation should have 'id' field"
+        assert "title" in conversations[0], "Conversation should have 'title' field"
+        assert "metadata" in conversations[0], "Conversation should have 'metadata' field"
+        print(f"   ✓ Found {len(conversations)} conversation(s)")
+        print(f"   ✓ Data format verified: {list(conversations[0].keys())}")
+
+        # Test get_conversation_messages
+        print("\n2. Testing get_conversation_messages...")
+        messages = manager.get_conversation_messages(conv_id)
+
+        assert isinstance(messages, list), "Should return a list"
+        assert len(messages) == 2, "Should find 2 messages"
+        assert "id" in messages[0], "Message should have 'id' field"
+        assert "role" in messages[0], "Message should have 'role' field"
+        assert "content" in messages[0], "Message should have 'content' field"
+        assert "timestamp" in messages[0], "Message should have 'timestamp' field"
+        print(f"   ✓ Found {len(messages)} message(s)")
+        print(f"   ✓ Data format verified: {list(messages[0].keys())}")
+
+        # Test with PersonalityLearner context
+        print("\n3. Testing integration with PersonalityLearner context...")
+
+        # Simulate how PersonalityLearner would use these methods
+        conversation_range = (start_date, end_date)
+        conversations = manager.get_conversations_by_date_range(
+            conversation_range[0], conversation_range[1]
+        )
+
+        for conv in conversations:
+            messages = manager.get_conversation_messages(conv["id"])
+            assert isinstance(messages, list), "Messages should be a list"
+            assert all("role" in msg for msg in messages), "All messages should have role"
+            assert all("content" in msg for msg in messages), "All messages should have content"
+
+        print(f"   ✓ Successfully retrieved {len(conversations)} conversation(s) with messages")
+        print(f"   ✓ All data structures compatible with PersonalityLearner")
+
+        # Clean up
+        manager.close()
+        os.unlink(db_path)
+
+        print("\n" + "="*60)
+        print("SUCCESS: All method integration tests passed!")
+        print("="*60)
+        return True
+
+    except AttributeError as e:
+        print(f"\n✗ FAILED: Method not found - {e}")
+        if os.path.exists(db_path):
+            os.unlink(db_path)
+        return False
+    except AssertionError as e:
+        print(f"\n✗ FAILED: Assertion error - {e}")
+        if os.path.exists(db_path):
+            os.unlink(db_path)
+        return False
+    except Exception as e:
+        print(f"\n✗ FAILED: Unexpected error - {e}")
+        import traceback
+        traceback.print_exc()
+        if os.path.exists(db_path):
+            os.unlink(db_path)
+        return False
+
+
+if __name__ == "__main__":
+    success = test_methods_exist()
+    sys.exit(0 if success else 1)