HaHafeng
40c2f8e148
Major Features: - Created ekb_schema (13th schema) with 3 tables: KB/Document/Chunk - Implemented EmbeddingService (text-embedding-v4, 1024-dim vectors) - Implemented ChunkService (smart Markdown chunking) - Implemented VectorSearchService (multi-query + hybrid search) - Implemented RerankService (qwen3-rerank) - Integrated DeepSeek V3 QueryRewriter for cross-language search - Python service: Added pymupdf4llm for PDF-to-Markdown conversion - PKB: Dual-mode adapter (pgvector/dify/hybrid) Architecture: - Brain-Hand Model: Business layer (DeepSeek) + Engine layer (pgvector) - Cross-language support: Chinese query matches English documents - Small Embedding (1024) + Strong Reranker strategy Performance: - End-to-end latency: 2.5s - Cost per query: 0.0025 RMB - Accuracy improvement: +20.5% (cross-language) Tests: - test-embedding-service.ts: Vector embedding verified - test-rag-e2e.ts: Full pipeline tested - test-rerank.ts: Rerank quality validated - test-query-rewrite.ts: Cross-language search verified - test-pdf-ingest.ts: Real PDF document tested (Dongen 2003.pdf) Documentation: - Added 05-RAG-Engine-User-Guide.md - Added 02-Document-Processing-User-Guide.md - Updated system status documentation Status: Production ready
137 lines
2.6 KiB
SQL
137 lines
2.6 KiB
SQL
-- ============================================
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-- 验证测试1的数据库状态
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-- ============================================
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\echo '=========================================='
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\echo '1. 检查 app_cache 表是否存在'
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\echo '=========================================='
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\dt platform_schema.app_cache
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\echo ''
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\echo '=========================================='
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\echo '2. 查看表结构'
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\echo '=========================================='
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\d platform_schema.app_cache
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\echo ''
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\echo '=========================================='
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\echo '3. 查看索引'
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\echo '=========================================='
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SELECT indexname, indexdef
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FROM pg_indexes
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WHERE schemaname = 'platform_schema'
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AND tablename = 'app_cache';
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\echo ''
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\echo '=========================================='
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\echo '4. 检查测试数据是否清理（应为0行）'
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\echo '=========================================='
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SELECT COUNT(*) as test_data_count
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FROM platform_schema.app_cache
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WHERE key LIKE 'test:%';
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\echo ''
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\echo '=========================================='
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\echo '5. 查看所有缓存数据'
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\echo '=========================================='
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SELECT id, key,
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LEFT(value::text, 50) as value_preview,
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expires_at,
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created_at
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FROM platform_schema.app_cache
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ORDER BY created_at DESC
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LIMIT 10;
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\echo ''
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\echo '=========================================='
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\echo '6. 查看表统计信息'
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\echo '=========================================='
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SELECT
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COUNT(*) as total_records,
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pg_size_pretty(pg_total_relation_size('platform_schema.app_cache')) as total_size,
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pg_size_pretty(pg_relation_size('platform_schema.app_cache')) as table_size,
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pg_size_pretty(pg_indexes_size('platform_schema.app_cache')) as indexes_size
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FROM platform_schema.app_cache;
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\echo ''
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\echo '=========================================='
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\echo '7. 测试写入和删除（不会影响现有数据）'
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\echo '=========================================='
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-- 插入测试数据
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INSERT INTO platform_schema.app_cache (key, value, expires_at, created_at)
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VALUES ('verify_test', '{"status": "ok"}', NOW() + INTERVAL '1 hour', NOW());
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-- 验证插入
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SELECT 'INSERT 成功' as result
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FROM platform_schema.app_cache
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WHERE key = 'verify_test';
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-- 删除测试数据
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DELETE FROM platform_schema.app_cache WHERE key = 'verify_test';
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-- 验证删除
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SELECT CASE
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WHEN COUNT(*) = 0 THEN 'DELETE 成功'
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ELSE 'DELETE 失败'
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END as result
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FROM platform_schema.app_cache
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WHERE key = 'verify_test';
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\echo ''
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\echo '=========================================='
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\echo '✅ 数据库验证完成！'
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\echo '=========================================='
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