fix: add unit tests for memory/embeddings.py (#437)

Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>

tests/unit/test_memory_embeddings.py

@@ -0,0 +1,162 @@
+"""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:
+    def test_returns_128_dim_vector(self):
+        vec = _simple_hash_embedding("hello world")
+        assert len(vec) == 128
+
+    def test_normalized(self):
+        vec = _simple_hash_embedding("some text for embedding")
+        mag = math.sqrt(sum(x * x for x in vec))
+        assert mag == pytest.approx(1.0, abs=1e-6)
+
+    def test_deterministic(self):
+        a = _simple_hash_embedding("same input")
+        b = _simple_hash_embedding("same input")
+        assert a == b
+
+    def test_different_texts_differ(self):
+        a = _simple_hash_embedding("hello world")
+        b = _simple_hash_embedding("goodbye moon")
+        assert a != b
+
+    def test_empty_string(self):
+        vec = _simple_hash_embedding("")
+        assert len(vec) == 128
+        # All zeros normalised stays zero (mag fallback to 1.0)
+        assert all(x == 0.0 for x in vec)
+
+    def test_long_text_truncates_at_50_words(self):
+        """Words beyond 50 should not change the result."""
+        short = " ".join(f"word{i}" for i in range(50))
+        long = short + " extra1 extra2 extra3"
+        assert _simple_hash_embedding(short) == _simple_hash_embedding(long)
+
+
+# ── cosine_similarity ────────────────────────────────────────────────────────
+
+
+class TestCosineSimilarity:
+    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_both_zero_vectors(self):
+        assert cosine_similarity([0.0], [0.0]) == 0.0
+
+
+# ── _keyword_overlap ─────────────────────────────────────────────────────────
+
+
+class TestKeywordOverlap:
+    def test_full_overlap(self):
+        assert _keyword_overlap("hello world", "hello world") == pytest.approx(1.0)
+
+    def test_partial_overlap(self):
+        assert _keyword_overlap("hello world", "hello moon") == pytest.approx(0.5)
+
+    def test_no_overlap(self):
+        assert _keyword_overlap("hello", "goodbye") == pytest.approx(0.0)
+
+    def test_empty_query(self):
+        assert _keyword_overlap("", "anything") == 0.0
+
+    def test_case_insensitive(self):
+        assert _keyword_overlap("Hello World", "hello world") == pytest.approx(1.0)
+
+
+# ── embed_text ───────────────────────────────────────────────────────────────
+
+
+class TestEmbedText:
+    def setup_method(self):
+        self._saved_model = emb.EMBEDDING_MODEL
+        emb.EMBEDDING_MODEL = None
+
+    def teardown_method(self):
+        emb.EMBEDDING_MODEL = self._saved_model
+
+    def test_uses_fallback_when_model_disabled(self):
+        emb.EMBEDDING_MODEL = False
+        vec = embed_text("test")
+        assert len(vec) == 128  # hash fallback dimension
+
+    def test_uses_model_when_available(self):
+        import numpy as np
+
+        mock_model = MagicMock()
+        mock_model.encode.return_value = np.array([0.1, 0.2, 0.3])
+        emb.EMBEDDING_MODEL = mock_model
+
+        result = embed_text("test")
+        assert result == pytest.approx([0.1, 0.2, 0.3])
+        mock_model.encode.assert_called_once_with("test")
+
+
+# ── _get_embedding_model ─────────────────────────────────────────────────────
+
+
+class TestGetEmbeddingModel:
+    def setup_method(self):
+        self._saved_model = emb.EMBEDDING_MODEL
+        emb.EMBEDDING_MODEL = None
+
+    def teardown_method(self):
+        emb.EMBEDDING_MODEL = self._saved_model
+
+    def test_skip_embeddings_setting(self):
+        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_fallback_when_transformers_missing(self):
+        mock_settings = MagicMock()
+        mock_settings.timmy_skip_embeddings = False
+        with patch.dict(
+            "sys.modules",
+            {
+                "config": MagicMock(settings=mock_settings),
+                "sentence_transformers": None,
+            },
+        ):
+            emb.EMBEDDING_MODEL = None
+            result = emb._get_embedding_model()
+        assert result is False
+
+    def test_returns_cached_model(self):
+        sentinel = object()
+        emb.EMBEDDING_MODEL = sentinel
+        assert emb._get_embedding_model() is sentinel