feat(rag): port augment module from lancedb to leann-rs#897
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Replace lancedb vector storage with leann-rs HNSW-based indexing for the RAG pipeline. This removes heavyweight lancedb/arrow dependencies in favor of leann-core which provides HNSW vector indexing, sentence-based chunking, and passage management. Key changes: - Remove storage.rs (lancedb VecDB wrapper) and windowing.rs (line-based chunking), replaced by leann-rs equivalents - Add SpnlEmbeddingProvider adapter bridging spnl's async embed() to leann-core's sync EmbeddingProvider trait - Rewrite layer1.rs to use LeannBuilder with chunk_text() chunking - Rewrite retrieve.rs to use HNSW search with stored vectors - Rewrite raptor.rs with two-phase batch-rebuild approach (documented in RAPTOR_LEANN_PLAN.md) - Replace vecdb_uri/vecdb_table options with index_dir, chunk_size, chunk_overlap Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Signed-off-by: Nick Mitchell <nickm@us.ibm.com>
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Summary
storage.rs(lancedb VecDB wrapper) andwindowing.rs(line-based chunking), replaced by leann-rs equivalentsSpnlEmbeddingProvideradapter bridging spnl's asyncembed()to leann-core's syncEmbeddingProvidertraitRAPTOR_LEANN_PLAN.md)Test plan
cargo build --features ragcompiles without lancedbcargo clippyclean on bothspnlandspnl-cliwith full CI feature setscargo test -p spnl --features ...per core.yml)retrievetest exercises full index→search pipeline with local embedding model.index,.ids.txt,.leann.meta.json,.leann.passages.jsonl,.leann.passages.idx)🤖 Generated with Claude Code