feat(embeddings): add native embed_batch to 5 embedders (LMStudio, Together, HuggingFace, VertexAI, GoogleGenAI) (#5609)

tests/embeddings/test_together_embeddings.py

@@ -0,0 +1,67 @@
+from unittest.mock import Mock, patch
+
+import pytest
+
+from mem0.configs.embeddings.base import BaseEmbedderConfig
+from mem0.embeddings.together import TogetherEmbedding
+
+
+@pytest.fixture
+def mock_together_client():
+    with patch("mem0.embeddings.together.Together") as mock_together:
+        mock_client = Mock()
+        mock_together.return_value = mock_client
+        yield mock_client
+
+
+def test_embed_text(mock_together_client):
+    config = BaseEmbedderConfig(model="togethercomputer/m2-bert-80M-8k-retrieval", embedding_dims=768)
+    embedder = TogetherEmbedding(config)
+
+    mock_together_client.embeddings.create.return_value = Mock(data=[Mock(embedding=[0.1, 0.2, 0.3, 0.4, 0.5])])
+
+    text = "Sample text to embed."
+    embedding = embedder.embed(text)
+
+    mock_together_client.embeddings.create.assert_called_once_with(
+        model="togethercomputer/m2-bert-80M-8k-retrieval", input=text
+    )
+    assert embedding == [0.1, 0.2, 0.3, 0.4, 0.5]
+
+
+def test_embed_batch_single_call(mock_together_client):
+    config = BaseEmbedderConfig(model="togethercomputer/m2-bert-80M-8k-retrieval", embedding_dims=768)
+    embedder = TogetherEmbedding(config)
+
+    mock_item0 = Mock(index=0, embedding=[0.1, 0.2, 0.3])
+    mock_item1 = Mock(index=1, embedding=[0.4, 0.5, 0.6])
+    mock_together_client.embeddings.create.return_value = Mock(data=[mock_item0, mock_item1])
+
+    texts = ["First text.", "Second text."]
+    embeddings = embedder.embed_batch(texts)
+
+    mock_together_client.embeddings.create.assert_called_once_with(
+        model="togethercomputer/m2-bert-80M-8k-retrieval", input=texts
+    )
+    assert embeddings == [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]
+
+
+def test_embed_batch_empty_list(mock_together_client):
+    config = BaseEmbedderConfig(model="togethercomputer/m2-bert-80M-8k-retrieval", embedding_dims=768)
+    embedder = TogetherEmbedding(config)
+
+    result = embedder.embed_batch([])
+
+    assert result == []
+    mock_together_client.embeddings.create.assert_not_called()
+
+
+def test_embed_batch_count_mismatch_raises(mock_together_client):
+    config = BaseEmbedderConfig(model="togethercomputer/m2-bert-80M-8k-retrieval", embedding_dims=768)
+    embedder = TogetherEmbedding(config)
+
+    mock_item0 = Mock(index=0, embedding=[0.1, 0.2, 0.3])
+    mock_together_client.embeddings.create.return_value = Mock(data=[mock_item0])
+
+    with pytest.raises(ValueError, match="returned 1 embeddings for 2 texts"):
+        embedder.embed_batch(["first text", "second text"])