opencode-config/tests/test_search.py
Sergey 6005c88203
feat: migrate src/ second-brain + tests + python tooling (#17)
* feat(src): migrate second-brain RAG CLI + tests

* fix(embedder): strip hardcoded ai.slaid098.dev endpoint

* refactor: rename slaid098/opencode to opencode-config

* docs(handoff): add pr-5 handoff + ADR-001

* fix(docs): rebase handoff/ADR naming to PR number + drop dangling ADR-009 refs

* fix(tests): update script paths + assertions for opencode-config migration

* fix(pyproject): update cov + ruff paths config/scripts -> .opencode/scripts

* docs: update project map + handoff + ADR

---------

Co-authored-by: opencode-agent <agent@slaid098.dev>
2026-07-23 23:17:18 +03:00

58 lines
1.7 KiB
Python

import json
from argparse import Namespace
from pathlib import Path
from unittest.mock import patch
import numpy as np
import pytest
import src.memory.search as search_mod
from src.memory.search import _cosine_sim
class TestCosineSim:
def test_identical(self) -> None:
v = np.array([1.0, 2.0, 3.0])
assert _cosine_sim(v, v) == pytest.approx(1.0)
def test_orthogonal(self) -> None:
a = np.array([1.0, 0.0])
b = np.array([0.0, 1.0])
assert _cosine_sim(a, b) == pytest.approx(0.0)
def test_zero_vector(self) -> None:
a = np.array([0.0, 0.0])
b = np.array([1.0, 1.0])
assert _cosine_sim(a, b) == pytest.approx(0.0)
def test_parallel(self) -> None:
a = np.array([1.0, 2.0])
b = np.array([2.0, 4.0])
assert _cosine_sim(a, b) == pytest.approx(1.0)
def test_opposite(self) -> None:
a = np.array([1.0, 1.0])
b = np.array([-1.0, -1.0])
assert _cosine_sim(a, b) == pytest.approx(-1.0)
class TestSearchOutput:
def test_search_json_format(self, tmp_path: Path) -> None:
index_dir = tmp_path / ".rag"
index_dir.mkdir()
index = {
"files": [
{
"source": "test.md",
"text": "hello world",
"embedding": [1.0, 0.0, 0.0],
},
],
}
(index_dir / "index.json").write_text(json.dumps(index))
def fake_embed_texts(texts):
return [[1.0, 0.0, 0.0]]
with patch.object(search_mod, "embed_texts", fake_embed_texts):
args = Namespace(index_dir=str(index_dir), query="hello", k=5, json=True)
search_mod.run_search(args)