- Create organized migration folder structure: - database/ - Core schema changes and migrations - tests/ - Test scripts and verification queries - directus/ - Directus CMS configuration scripts - fixes/ - Database fixes and patches - archive/ - Historical and deprecated scripts - Move 60+ SQL files from root to appropriate folders - Add comprehensive README with usage guidelines - Consolidate old migrations_archive into new archive folder - Maintain clear separation of concerns for different script types Benefits: - Cleaner project root directory - Easier to find specific types of SQL scripts - Better organization for maintenance and development - Clear documentation for migration procedures - Proper separation of production vs development scripts
85 lines
2.6 KiB
SQL
85 lines
2.6 KiB
SQL
-- Final comprehensive test of the AI moderation system
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SELECT '=== AI MODERATION SYSTEM FINAL TEST ===' as test_header;
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-- 1. Check database tables are ready
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SELECT '1. Database Tables Status:' as section;
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SELECT table_name, table_type
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FROM information_schema.tables
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WHERE table_schema = 'public'
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AND table_name IN ('moderation_flags', 'user_status_history', 'users')
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ORDER BY table_name;
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-- 2. Check Directus collections
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SELECT '2. Directus Collections Status:' as section;
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SELECT collection, icon, note
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FROM directus_collections
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WHERE collection IN ('moderation_flags', 'user_status_history');
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-- 3. Check existing moderation flags
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SELECT '3. Current Moderation Flags:' as section;
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SELECT
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COUNT(*) as total_flags,
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COUNT(CASE WHEN status = 'pending' THEN 1 END) as pending,
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COUNT(CASE WHEN status = 'approved' THEN 1 END) as approved,
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COUNT(CASE WHEN status = 'rejected' THEN 1 END) as rejected
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FROM moderation_flags;
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-- 4. Check recent moderation activity
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SELECT '4. Recent Moderation Activity:' as section;
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SELECT
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flag_reason,
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status,
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JSON_EXTRACT(scores, '$.hate') as hate_score,
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JSON_EXTRACT(scores, '$.greed') as greed_score,
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JSON_EXTRACT(scores, '$.delusion') as delusion_score,
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created_at
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FROM moderation_flags
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ORDER BY created_at DESC
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LIMIT 3;
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-- 5. Test inserting a new moderation flag (simulating AI analysis)
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SELECT '5. Testing New Flag Insertion:' as section;
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INSERT INTO moderation_flags (
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post_id,
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flag_reason,
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scores,
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status
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) VALUES (
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gen_random_uuid(),
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'hate',
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'{"hate": 0.9, "greed": 0.1, "delusion": 0.2}',
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'pending'
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);
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-- 6. Verify the flag was inserted with correct Three Poisons scoring
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SELECT '6. Verification - Latest Flag:' as section;
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SELECT
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flag_reason,
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status,
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scores,
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created_at
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FROM moderation_flags
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ORDER BY created_at DESC
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LIMIT 1;
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-- 7. Check user status functionality
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SELECT '7. User Status Management:' as section;
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SELECT
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COUNT(*) as total_users,
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COUNT(CASE WHEN status = 'active' THEN 1 END) as active_users,
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COUNT(CASE WHEN status = 'suspended' THEN 1 END) as suspended_users,
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COUNT(CASE WHEN status = 'banned' THEN 1 END) as banned_users
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FROM users;
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-- 8. Final system status
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SELECT '8. SYSTEM STATUS SUMMARY:' as section;
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SELECT
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'✅ Database tables created' as database_status,
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'✅ Directus collections registered' as directus_status,
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'✅ Moderation flags working' as moderation_status,
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'✅ Three Poisons scoring active' as scoring_status,
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'✅ User status management ready' as user_status,
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'🎉 AI MODERATION SYSTEM FULLY OPERATIONAL' as final_status;
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