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Add benchmark results for fast3 and fast4, implement KeepAliveLspBridge, and add tests for staged strategies

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- Added new benchmark result files: compare_2026-02-09_score_fast3.json and compare_2026-02-09_score_fast4.json.
- Implemented KeepAliveLspBridge to maintain a persistent LSP connection across multiple queries, improving performance.
- Created unit tests for staged clustering strategies in test_staged_stage3_fast_strategies.py, ensuring correct behavior of score and dir_rr strategies.
This commit is contained in:
catlog22
2026-02-09 20:45:29 +08:00
parent c62d26183b
commit 4344e79e68
64 changed files with 6154 additions and 123 deletions
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8
codex-lens/benchmarks/compare_staged_realtime_vs_dense_rerank.py
View File

@@ -249,6 +249,12 @@ def main() -> None:
parser.add_argument("--k", type=int, default=10, help="Final result count (default 10)")
parser.add_argument("--coarse-k", type=int, default=100, help="Coarse candidates (default 100)")
parser.add_argument("--warmup", type=int, default=1, help="Warmup runs per strategy (default 1)")
parser.add_argument(
"--staged-cluster-strategy",
type=str,
default=None,
help="Override Config.staged_clustering_strategy for staged pipeline (e.g. auto, dir_rr, score, path)",
)
parser.add_argument(
"--output",
type=Path,
@@ -271,6 +277,8 @@ def main() -> None:
config.cascade_strategy = "staged"
config.staged_stage2_mode = "realtime"
config.enable_staged_rerank = True
if args.staged_cluster_strategy:
config.staged_clustering_strategy = str(args.staged_cluster_strategy)
# Stability: on some Windows setups, fastembed + DirectML can crash under load.
# Dense_rerank uses the embedding backend that matches the index; force CPU here.
config.embedding_use_gpu = False

356
codex-lens/benchmarks/results/compare_2026-02-09_dir_rr_fast4.json Normal file
View File

@@ -0,0 +1,356 @@
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"staged": {
"success": 7,
"avg_latency_ms": 2471.239057132176
},
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}
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171
codex-lens/benchmarks/results/compare_2026-02-09_keepalive3.json Normal file
View File

@@ -0,0 +1,171 @@
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