fix: add unit tests for memory/embeddings.py

Tests cover _simple_hash_embedding, cosine_similarity, _keyword_overlap,
embed_text, and _get_embedding_model with proper mocking of the global
model state.

Fixes #431

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

tests/unit/test_embeddings.py

@@ -0,0 +1,154 @@
+"""Unit tests for timmy.memory.embeddings — embedding, similarity, and keyword overlap."""
+
+import math
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+import timmy.memory.embeddings as emb
+from timmy.memory.embeddings import (
+    _keyword_overlap,
+    _simple_hash_embedding,
+    cosine_similarity,
+    embed_text,
+)
+
+# ── _simple_hash_embedding ───────────────────────────────────────────────────
+
+
+class TestSimpleHashEmbedding:
+    """Tests for the deterministic hash-based fallback embedding."""
+
+    def test_returns_128_floats(self):
+        vec = _simple_hash_embedding("hello world")
+        assert len(vec) == 128
+        assert all(isinstance(x, float) for x in vec)
+
+    def test_deterministic(self):
+        """Same input always produces the same vector."""
+        assert _simple_hash_embedding("test") == _simple_hash_embedding("test")
+
+    def test_normalized(self):
+        """Output vector has unit magnitude."""
+        vec = _simple_hash_embedding("some text for testing")
+        mag = math.sqrt(sum(x * x for x in vec))
+        assert mag == pytest.approx(1.0, abs=1e-6)
+
+    def test_empty_string(self):
+        """Empty string doesn't crash — returns a zero-ish vector."""
+        vec = _simple_hash_embedding("")
+        assert len(vec) == 128
+
+    def test_different_inputs_differ(self):
+        a = _simple_hash_embedding("alpha")
+        b = _simple_hash_embedding("beta")
+        assert a != b
+
+
+# ── cosine_similarity ────────────────────────────────────────────────────────
+
+
+class TestCosineSimilarity:
+    """Tests for cosine similarity calculation."""
+
+    def test_identical_vectors(self):
+        v = [1.0, 2.0, 3.0]
+        assert cosine_similarity(v, v) == pytest.approx(1.0)
+
+    def test_orthogonal_vectors(self):
+        a = [1.0, 0.0]
+        b = [0.0, 1.0]
+        assert cosine_similarity(a, b) == pytest.approx(0.0)
+
+    def test_opposite_vectors(self):
+        a = [1.0, 0.0]
+        b = [-1.0, 0.0]
+        assert cosine_similarity(a, b) == pytest.approx(-1.0)
+
+    def test_zero_vector_returns_zero(self):
+        assert cosine_similarity([0.0, 0.0], [1.0, 2.0]) == 0.0
+        assert cosine_similarity([1.0, 2.0], [0.0, 0.0]) == 0.0
+
+    def test_different_length_uses_zip(self):
+        """zip(strict=False) truncates to shortest — verify no crash."""
+        result = cosine_similarity([1.0, 0.0], [1.0, 0.0, 9.9])
+        # mag_b includes the extra element, so result < 1.0
+        assert isinstance(result, float)
+
+
+# ── _keyword_overlap ─────────────────────────────────────────────────────────
+
+
+class TestKeywordOverlap:
+    """Tests for keyword overlap scoring."""
+
+    def test_full_overlap(self):
+        assert _keyword_overlap("hello world", "hello world extra") == pytest.approx(1.0)
+
+    def test_partial_overlap(self):
+        assert _keyword_overlap("hello world", "hello there") == pytest.approx(0.5)
+
+    def test_no_overlap(self):
+        assert _keyword_overlap("alpha", "beta") == pytest.approx(0.0)
+
+    def test_empty_query(self):
+        assert _keyword_overlap("", "some content") == 0.0
+
+    def test_case_insensitive(self):
+        assert _keyword_overlap("Hello", "hello world") == pytest.approx(1.0)
+
+
+# ── embed_text ───────────────────────────────────────────────────────────────
+
+
+class TestEmbedText:
+    """Tests for the main embed_text entry point."""
+
+    def test_uses_fallback_when_model_false(self):
+        """When _get_embedding_model returns False, use hash fallback."""
+        with patch.object(emb, "EMBEDDING_MODEL", False):
+            with patch.object(emb, "_get_embedding_model", return_value=False):
+                vec = embed_text("hello")
+                assert len(vec) == 128
+
+    def test_uses_model_when_available(self):
+        """When a real model is loaded, call model.encode()."""
+        mock_model = MagicMock()
+        mock_model.encode.return_value = MagicMock(tolist=MagicMock(return_value=[0.1, 0.2]))
+        with patch.object(emb, "_get_embedding_model", return_value=mock_model):
+            vec = embed_text("hello")
+            assert vec == [0.1, 0.2]
+            mock_model.encode.assert_called_once_with("hello")
+
+
+# ── _get_embedding_model ─────────────────────────────────────────────────────
+
+
+class TestGetEmbeddingModel:
+    """Tests for lazy model loading."""
+
+    def setup_method(self):
+        """Reset global state before each test."""
+        emb.EMBEDDING_MODEL = None
+
+    def test_skip_embeddings_setting(self):
+        """When settings.timmy_skip_embeddings is True, model is set to False."""
+        mock_settings = MagicMock()
+        mock_settings.timmy_skip_embeddings = True
+        with patch.dict("sys.modules", {"config": MagicMock(settings=mock_settings)}):
+            emb.EMBEDDING_MODEL = None
+            result = emb._get_embedding_model()
+            assert result is False
+
+    def test_sentence_transformers_import_error(self):
+        """When sentence-transformers is missing, falls back to False."""
+        mock_settings = MagicMock()
+        mock_settings.timmy_skip_embeddings = False
+        with patch.dict("sys.modules", {"config": MagicMock(settings=mock_settings)}):
+            with patch.dict("sys.modules", {"sentence_transformers": None}):
+                emb.EMBEDDING_MODEL = None
+                result = emb._get_embedding_model()
+                assert result is False
+
+    def teardown_method(self):
+        emb.EMBEDDING_MODEL = None