Swift Implementation#1
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…CP server Replace Python stub with production-ready Swift implementation: - Store.swift: GRDB-backed SQLite schema (metadata/files/chunks/vectors), WAL mode, cascade deletes, vector blob storage, SHA-256 incremental skip - Indexer.swift: walk→chunk→embed→store actor pipeline with progress callbacks and batch MLX embedding (32 chunks/call) - Search.swift: cosine similarity semantic, LIKE regex, RRF hybrid (k=60) - CkMLX.swift: IndexCmd, SearchCmd (--mode/--threshold/--jsonl), StatusCmd with model/dimension/counts/updated/size reporting - CkMLXMCPServer: JSON-RPC 2.0 stdio MCP server (ck-mlx-mcp binary) with 4 tools: semantic_search, hybrid_search, regex_search, index_status; reads embedding_model from index metadata to avoid dimension mismatch - 9/9 tests passing; swift build + swift build -c release both clean - fix(server.py): handle Store init ValueError when embedding dim unknown Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019rS8sKKTSAFpT3x2tEBBgD
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Replace Python stub with production-ready Swift implementation:
WAL mode, cascade deletes, vector blob storage, SHA-256 incremental skip
and batch MLX embedding (32 chunks/call)
with model/dimension/counts/updated/size reporting
4 tools: semantic_search, hybrid_search, regex_search, index_status;
reads embedding_model from index metadata to avoid dimension mismatch