Docs/Core: Low-Resource Setups, SkyPilot Option, and No-Recompute (#45)

* docs: add SkyPilot template and instructions for running embeddings/index build on cloud GPU

* docs: add low-resource note in README; point to config guide; suggest OpenAI embeddings, SkyPilot remote build, and --no-recompute

* docs: consolidate low-resource guidance into config guide; README points to it

* cli: add --no-recompute and --no-recompute-embeddings flags; docs: clarify HNSW requires --no-compact when disabling recompute

* docs: dedupe recomputation guidance; keep single Low-resource setups section

* sky: expand leann-build.yaml with configurable params and flags (backend, recompute, compact, embedding options)

* hnsw: auto-disable compact when --no-recompute is used; docs: expand SkyPilot with -e overrides and copy-back example

* docs+sky: simplify SkyPilot flow (auto-build on launch, rsync copy-back); clarify HNSW auto non-compact when no-recompute

* feat: auto compact for hnsw when recompute

* reader: non-destructive portability (relative hints + fallback); fix comments; sky: refine yaml

* cli: unify flags to --recompute/--no-recompute for build/search/ask; docs: update references

* chore: remove

* hnsw: move pruned/no-recompute assertion into backend; api: drop global assertion; docs: will adjust after benchmarking

* cli: use argparse.BooleanOptionalAction for paired flags (--recompute/--compact) across build/search/ask

* docs: a real example on recompute

* benchmarks: fix and extend HNSW+DiskANN recompute vs no-recompute; docs: add fresh numbers and DiskANN notes

* benchmarks: unify HNSW & DiskANN into one clean script; isolate groups, fixed ports, warm-up, param complexity

* docs: diskann recompute

* core: auto-cleanup for LeannSearcher/LeannChat (__enter__/__exit__/__del__); ensure server terminate/kill robustness; benchmarks: use searcher.cleanup(); docs: suggest uv run

* fix: hang on warnings

* docs: boolean flags

* docs: leann help

packages/leann-backend-diskann/leann_backend_diskann/diskann_backend.py

@@ -441,9 +441,14 @@ class DiskannSearcher(BaseSearcher):
         else:  # "global"
             use_global_pruning = True
 
-        # Perform search with suppressed C++ output based on log level
-        use_deferred_fetch = kwargs.get("USE_DEFERRED_FETCH", True)
-        recompute_neighors = False
+        # Strategy:
+        # - Traversal always uses PQ distances
+        # - If recompute_embeddings=True, do a single final rerank via deferred fetch
+        #   (fetch embeddings for the final candidate set only)
+        # - Do not recompute neighbor distances along the path
+        use_deferred_fetch = True if recompute_embeddings else False
+        recompute_neighors = False  # Expected typo. For backward compatibility.
+
         with suppress_cpp_output_if_needed():
             labels, distances = self._index.batch_search(
                 query,