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feat(kividb): add KiviDB backend - #884
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KiviDB is a multi-threaded, Redis-compatible store with RediSearch-style FT.* vector search built in. The client speaks RESP2 with raw FT.* commands, supports HNSW and FLAT indexes with L2/IP/cosine, and the NumGE and label-equality filters. optimize() waits until FT.INFO num_docs covers the corpus before searching. Tests: unit tests for registration, metric mapping and TAG escaping; integration tests (skipped without a server) check recall >= 0.95 against brute force with no filter, an int filter and a label filter, and that every result satisfies its filter. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01WdtvAfcNSzV85y5jAHMVr8
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/assign @XuanYang-cn |
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KiviDB is a multi-threaded, Redis-compatible store with RediSearch-style FT.* vector search built in. The client speaks RESP2 with raw FT.* commands, supports HNSW and FLAT indexes with L2/IP/cosine, and the NumGE and label-equality filters. optimize() waits until FT.INFO num_docs covers the corpus before searching.
Tests: unit tests for registration, metric mapping and TAG escaping; integration tests (skipped without a server) check recall >= 0.95 against brute force with no filter, an int filter and a label filter, and that every result satisfies its filter.
Claude-Session: https://claude.ai/code/session_01WdtvAfcNSzV85y5jAHMVr8