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feat: enhance search, ranking, reranker and CLI tooling across ccw and codex-lens

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Major improvements to smart-search, chain-search cascade, ranking pipeline,
reranker factory, CLI history store, codex-lens integration, and uv-manager.
Simplify command-generator skill by inlining phases. Add comprehensive tests.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
catlog22
2026-03-16 20:35:08 +08:00
parent 1cd96b90e8
commit 5a4b18d9b1
73 changed files with 14684 additions and 2442 deletions
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33
codex-lens/src/codexlens/semantic/ann_index.py
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@@ -383,8 +383,37 @@ class ANNIndex:
if self._index is None or self._current_count == 0:
return [], [] # Empty index
# Perform kNN search
labels, distances = self._index.knn_query(query, k=top_k)
effective_k = min(max(int(top_k), 0), self._current_count)
if effective_k == 0:
return [], []
try:
self._index.set_ef(max(self.ef, effective_k))
except Exception:
pass
while True:
try:
labels, distances = self._index.knn_query(query, k=effective_k)
break
except Exception as exc:
if "contiguous 2D array" in str(exc) and effective_k > 1:
next_k = max(1, effective_k // 2)
logger.debug(
"ANN search knn_query failed for k=%d; retrying with k=%d: %s",
effective_k,
next_k,
exc,
)
if next_k == effective_k:
raise
effective_k = next_k
try:
self._index.set_ef(max(self.ef, effective_k))
except Exception:
pass
continue
raise
# Convert to lists and flatten (knn_query returns 2D arrays)
ids = labels[0].tolist()