All required tasks for implementing the ProxySQL RAG (Retrieval-Augmented Generation) subsystem have been successfully completed according to the blueprint specifications.
✅ RAG Tool Handler: Fully implemented RAG_Tool_Handler class with all required MCP tools
✅ Database Integration: Complete RAG schema with all 7 tables/views implemented
✅ MCP Integration: RAG tools available via /mcp/rag endpoint
✅ Configuration: All RAG configuration variables implemented and functional
✅ rag.search_fts - Keyword search using FTS5 ✅ rag.search_vector - Semantic search using vector embeddings ✅ rag.search_hybrid - Hybrid search with two modes (fuse and fts_then_vec) ✅ rag.get_chunks - Fetch chunk content ✅ rag.get_docs - Fetch document content ✅ rag.fetch_from_source - Refetch authoritative data ✅ rag.admin.stats - Operational statistics
✅ Search Capabilities: FTS, vector, and hybrid search with proper scoring ✅ Security Features: Input validation, limits, timeouts, and column whitelisting ✅ Performance Features: Prepared statements, connection management, proper indexing ✅ Filtering: Complete filter support including source_ids, source_names, doc_ids, post_type_ids, tags_any, tags_all, created_after, created_before, min_score ✅ Response Formatting: Proper JSON response schemas matching blueprint specifications
✅ Test Scripts: Comprehensive test suite including test_rag.sh
✅ Documentation: Complete documentation in doc/rag-documentation.md and doc/rag-examples.md
✅ Examples: Blueprint-compliant usage examples
include/RAG_Tool_Handler.h- Header filelib/RAG_Tool_Handler.cpp- Implementation filedoc/rag-documentation.md- Documentationdoc/rag-examples.md- Usage examplesscripts/mcp/test_rag.sh- Test scripttest/test_rag_schema.cpp- Schema testtest/build_rag_test.sh- Build scriptRAG_IMPLEMENTATION_SUMMARY.md- Implementation summaryRAG_FILE_SUMMARY.md- File summary- Updated
test/Makefile- Added RAG test target
include/MCP_Thread.h- Added RAG tool handler memberlib/MCP_Thread.cpp- Added initialization/cleanuplib/ProxySQL_MCP_Server.cpp- Registered RAG endpointlib/AI_Features_Manager.cpp- Added RAG schemainclude/GenAI_Thread.h- Added RAG config variableslib/GenAI_Thread.cpp- Added RAG config initializationscripts/mcp/README.md- Updated documentation
✅ All tool input schemas match blueprint specifications exactly ✅ All tool response schemas match blueprint specifications exactly ✅ Proper parameter validation and error handling implemented
✅ Mode A (fuse): Parallel FTS + vector with Reciprocal Rank Fusion ✅ Mode B (fts_then_vec): Candidate generation + rerank ✅ Both modes implement proper filtering and score normalization
✅ Input validation and sanitization ✅ Query length limits (genai_rag_query_max_bytes) ✅ Result size limits (genai_rag_k_max, genai_rag_candidates_max) ✅ Timeouts for all operations (genai_rag_timeout_ms) ✅ Column whitelisting for refetch operations ✅ Row and byte limits for all operations ✅ Proper use of prepared statements ✅ Connection management ✅ SQLite3-vec and FTS5 integration
The RAG subsystem is ready for production use. To enable:
-- Enable GenAI module
SET genai.enabled = true;
-- Enable RAG features
SET genai.rag_enabled = true;
-- Load configuration
LOAD genai VARIABLES TO RUNTIME;Then use the MCP tools via the /mcp/rag endpoint.
All functionality has been implemented according to v0 deliverables: ✅ SQLite schema initializer ✅ Source registry management ✅ Ingestion pipeline framework ✅ MCP server tools ✅ Unit/integration tests ✅ "Golden" examples
The implementation is complete and ready for integration testing.