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
67 lines
837 B
SQL
67 lines
837 B
SQL
-- 在 platform_schema.users 中创建 mock 用户
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-- 用于 PKB 等模块的测试
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-- 首先需要一个默认租户
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INSERT INTO platform_schema.tenants (id, code, name, type, status, created_at, updated_at)
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VALUES (
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'tenant-mock-001',
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'mock-tenant',
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'测试租户',
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'INTERNAL',
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'ACTIVE',
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NOW(),
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NOW()
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)
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ON CONFLICT (id) DO NOTHING;
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-- 创建 mock 用户
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INSERT INTO platform_schema.users (
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id,
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phone,
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email,
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password,
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is_default_password,
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name,
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role,
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status,
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tenant_id,
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kb_quota,
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kb_used,
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is_trial,
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created_at,
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updated_at
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)
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VALUES (
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'user-mock-001',
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'13800000000',
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'mock@test.com',
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'$2b$10$mockhashedpassword123456789',
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true,
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'测试用户',
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'USER',
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'active',
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'tenant-mock-001',
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3,
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0,
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false,
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NOW(),
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NOW()
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)
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ON CONFLICT (id) DO NOTHING;
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