rebase

tests/unit/test_embeddings.py

@@ -0,0 +1,69 @@
+"""Tests for `app.core.embeddings.HashEmbedder`."""
+
+from __future__ import annotations
+
+import math
+
+import pytest
+
+from app.core.embeddings import HashEmbedder
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_returns_correct_dimension():
+    emb = HashEmbedder(dimension=128)
+    vecs = await emb.embed(["hello world"])
+    assert len(vecs) == 1
+    assert len(vecs[0]) == 128
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_empty_text_returns_zero_vector():
+    emb = HashEmbedder(dimension=64)
+    vecs = await emb.embed([""])
+    assert vecs[0] == [0.0] * 64
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_deterministic():
+    emb = HashEmbedder(dimension=64)
+    v1 = (await emb.embed(["the quick brown fox"]))[0]
+    v2 = (await emb.embed(["the quick brown fox"]))[0]
+    assert v1 == v2
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_normalized():
+    emb = HashEmbedder(dimension=64)
+    v = (await emb.embed(["some text with multiple words for hashing"]))[0]
+    norm = math.sqrt(sum(x * x for x in v))
+    assert abs(norm - 1.0) < 1e-6
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_similar_texts_have_overlap():
+    """Texts sharing tokens should have non-zero cosine similarity."""
+    emb = HashEmbedder(dimension=256)
+    v1 = (await emb.embed(["the dragon attacks the village"]))[0]
+    v2 = (await emb.embed(["the dragon breathes fire"]))[0]
+    v3 = (await emb.embed(["quantum mechanics equations"]))[0]
+    # Cosine similarity (vectors are already normalized)
+    sim_12 = sum(a * b for a, b in zip(v1, v2))
+    sim_13 = sum(a * b for a, b in zip(v1, v3))
+    # Shared-token texts should be more similar than disjoint ones
+    assert sim_12 > sim_13
+
+
+@pytest.mark.asyncio
+async def test_hash_embedder_batch():
+    emb = HashEmbedder(dimension=32)
+    vecs = await emb.embed(["a", "b", "c"])
+    assert len(vecs) == 3
+    assert all(len(v) == 32 for v in vecs)
+
+
+def test_hash_embedder_invalid_dimension():
+    with pytest.raises(ValueError):
+        HashEmbedder(dimension=0)
+    with pytest.raises(ValueError):
+        HashEmbedder(dimension=-1)