Add local search quality evaluation harness

Add an optional local evaluator that compares a baseline revision against a candidate checkout, computes deterministic stability metrics, and can call Gemini for judged ranking metrics when configured.

The harness isolates child runs with a temporary HOME and a node-free PATH so historical revisions cannot trigger Bird browser-cookie auth during evaluation.

Validation: uv run python -m unittest and local smoke/full deterministic eval runs.
This commit is contained in:
Jeffrey Sperling
2026-03-13 19:21:33 -07:00
parent 946af84f9a
commit 8eda5fad5c
5 changed files with 732 additions and 0 deletions
+17
View File
@@ -79,6 +79,23 @@ class TestConfigPrecedence(unittest.TestCase):
config = env.get_config()
self.assertEqual(config['BRAVE_API_KEY'], 'env-key')
def test_gemini_keys_load_from_project_env(self):
import tempfile
with tempfile.TemporaryDirectory() as tmpdir:
project_dir = Path(tmpdir) / ".claude"
project_dir.mkdir()
project_env = project_dir / "last30days.env"
project_env.write_text("GEMINI_API_KEY=gem-key\nGEMINI_MODEL=gemini-3-pro-preview\n")
with patch.object(Path, 'cwd', return_value=Path(tmpdir)), \
patch.object(env, 'CONFIG_FILE', None), \
patch.dict(os.environ, {}, clear=False):
os.environ.pop('GEMINI_API_KEY', None)
os.environ.pop('GEMINI_MODEL', None)
config = env.get_config()
self.assertEqual(config['GEMINI_API_KEY'], 'gem-key')
self.assertEqual(config['GEMINI_MODEL'], 'gemini-3-pro-preview')
class TestConfigSource(unittest.TestCase):
"""Tests for _CONFIG_SOURCE tracking."""
+81
View File
@@ -0,0 +1,81 @@
"""Tests for the local search-quality evaluation harness."""
import sys
import unittest
from pathlib import Path
from unittest.mock import patch
sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
import evaluate_search_quality as evalsq
class TestMetrics(unittest.TestCase):
def test_jaccard(self):
self.assertAlmostEqual(evalsq.jaccard({"a", "b"}, {"b", "c"}), 1 / 3)
def test_retention(self):
self.assertAlmostEqual(evalsq.retention({"a", "b"}, {"b", "c"}), 0.5)
def test_precision_at_k(self):
ranking = [
{"key": "a", "source": "reddit"},
{"key": "b", "source": "x"},
{"key": "c", "source": "youtube"},
]
judgments = {"a": 3, "b": 1, "c": 2}
self.assertAlmostEqual(evalsq.precision_at_k(ranking, judgments, 2), 0.5)
def test_ndcg_at_k(self):
ranking = [
{"key": "a", "source": "reddit"},
{"key": "b", "source": "x"},
{"key": "c", "source": "youtube"},
]
judgments = {"a": 3, "b": 0, "c": 2}
self.assertGreater(evalsq.ndcg_at_k(ranking, judgments, 3), 0.8)
def test_source_coverage_recall_uses_union_pool(self):
judged_pool = [
{"key": "a", "source": "reddit"},
{"key": "b", "source": "x"},
{"key": "c", "source": "youtube"},
]
ranking = [
{"key": "a", "source": "reddit"},
{"key": "b", "source": "x"},
]
judgments = {"a": 3, "b": 0, "c": 2}
self.assertAlmostEqual(evalsq.source_coverage_recall(ranking, judged_pool, judgments), 0.5)
class TestRankedItems(unittest.TestCase):
def test_build_ranked_items_sorts_by_score(self):
report = {
"reddit": [{"id": "R1", "title": "Low", "url": "r1", "score": 20}],
"x": [{"id": "X1", "text": "High", "url": "x1", "score": 90}],
"youtube": [],
"tiktok": [],
"instagram": [],
"hackernews": [],
"bluesky": [],
"truthsocial": [],
"polymarket": [],
"websearch": [],
}
ranked = evalsq.build_ranked_items(report, per_source_limit=5)
self.assertEqual(ranked[0]["key"], "x1")
class TestPathWithoutNode(unittest.TestCase):
def test_removes_node_entries(self):
path = "/usr/bin:/tmp/node-bin:/opt/homebrew/bin"
def fake_exists(path_obj):
return str(path_obj).endswith("/tmp/node-bin/node")
with patch.object(evalsq.Path, "exists", fake_exists):
filtered = evalsq.path_without_node(path)
self.assertEqual(filtered, "/usr/bin:/opt/homebrew/bin")
if __name__ == "__main__":
unittest.main()