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Add benchmark results and tests for LSP graph builder and staged search

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- Introduced a new benchmark results file for performance comparison on 2026-02-09.
- Added a test for LspGraphBuilder to ensure it does not expand nodes at maximum depth.
- Created a test for the staged search pipeline to validate fallback behavior when stage 1 returns empty results.
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catlog22
2026-02-09 21:43:13 +08:00
parent 4344e79e68
commit 362f354f1c
25 changed files with 2613 additions and 51 deletions
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466
codex-lens/benchmarks/results/compare_2026-02-09_dir_rr_fast5.json Normal file
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codex-lens/benchmarks/results/compare_2026-02-09_dir_rr_fast6.json Normal file
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}

5
codex-lens/src/codexlens/lsp/lsp_graph_builder.py
View File

@@ -134,7 +134,10 @@ class LspGraphBuilder:
# Skip if already visited or at max depth
if node.id in visited:
return []
if depth > self.max_depth:
# Depth is 0 for seeds. To limit expansion to N hops from seeds,
# we expand nodes with depth < max_depth.
if depth >= self.max_depth:
visited.add(node.id)
return []
if len(graph.nodes) >= self.max_nodes:
return []

36
codex-lens/tests/test_lsp_graph_builder_depth.py Normal file
View File

@@ -0,0 +1,36 @@
from __future__ import annotations
import asyncio
from unittest.mock import AsyncMock
import pytest
from codexlens.hybrid_search.data_structures import CodeAssociationGraph, CodeSymbolNode, Range
from codexlens.lsp.lsp_graph_builder import LspGraphBuilder
@pytest.mark.asyncio
async def test_lsp_graph_builder_does_not_expand_at_max_depth() -> None:
"""Depth semantics: max_depth is the number of hops from seeds."""
builder = LspGraphBuilder(max_depth=1, max_nodes=10, max_concurrent=1, resolve_symbols=False)
bridge = AsyncMock()
bridge.get_references.side_effect = RuntimeError("should not call references")
bridge.get_call_hierarchy.side_effect = RuntimeError("should not call call hierarchy")
node = CodeSymbolNode(
id="x.py:foo:1",
name="foo",
kind="function",
file_path="x.py",
range=Range(start_line=1, start_character=1, end_line=1, end_character=1),
)
graph = CodeAssociationGraph()
visited: set[str] = set()
sem = asyncio.Semaphore(1)
# Seeds are depth=0. A node at depth==max_depth should not be expanded.
new_nodes = await builder._expand_node(node, 1, graph, bridge, visited, sem) # type: ignore[attr-defined]
assert new_nodes == []
assert node.id in visited

49
codex-lens/tests/test_staged_stage1_fallback_seed.py Normal file
View File

@@ -0,0 +1,49 @@
from __future__ import annotations
import json
from pathlib import Path
from unittest.mock import MagicMock
from codexlens.config import Config
from codexlens.entities import SearchResult
from codexlens.search.chain_search import ChainSearchEngine, ChainSearchResult, SearchOptions
def _extract_stage_stats(result: ChainSearchResult) -> dict:
for item in result.stats.errors or []:
if isinstance(item, str) and item.startswith("STAGE_STATS:"):
return json.loads(item[len("STAGE_STATS:") :])
raise AssertionError("missing STAGE_STATS payload")
def test_staged_pipeline_seeds_from_fts_when_stage1_empty(monkeypatch) -> None:
cfg = Config.load()
cfg.enable_staged_rerank = False
cfg.staged_stage2_mode = "realtime" # ensure we pass through stage2 wrapper
cfg.staged_clustering_strategy = "score"
engine = ChainSearchEngine(registry=MagicMock(), mapper=MagicMock(), config=cfg)
# Avoid touching registry/mapper/index stores.
monkeypatch.setattr(engine, "_find_start_index", lambda *_a, **_k: Path("X:/fake/_index.db"))
monkeypatch.setattr(engine, "_collect_index_paths", lambda *_a, **_k: [Path("X:/fake/_index.db")])
# Force Stage 1 to return empty so the FTS seeding path is exercised.
monkeypatch.setattr(engine, "_stage1_binary_search", lambda *_a, **_k: ([], Path("X:/fake")))
seed_results = [SearchResult(path="D:/p/a.py", score=1.0), SearchResult(path="D:/p/b.py", score=0.9)]
# Provide a stable SearchStats instance for the fallback search call.
from codexlens.search.chain_search import SearchStats
monkeypatch.setattr(engine, "search", lambda *_a, **_k: ChainSearchResult(query="q", results=seed_results, symbols=[], stats=SearchStats()))
# Make later stages no-ops so we only validate plumbing.
monkeypatch.setattr(engine, "_stage2_lsp_expand", lambda results, *_a, **_k: results)
monkeypatch.setattr(engine, "_stage3_cluster_prune", lambda results, *_a, **_k: results)
result = engine.staged_cascade_search("q", Path("."), k=2, coarse_k=5, options=SearchOptions())
stage_stats = _extract_stage_stats(result)
assert stage_stats["stage_counts"].get("stage1_fallback_used") == 1
assert result.results and [r.path for r in result.results] == ["D:/p/a.py", "D:/p/b.py"]