feat(python): adding VoyageAI v4 models (#2959)

Adding VoyageAI v4 models
 - with these, i added unit tests
 - added example code (tested!)

python/python/lancedb/embeddings/voyageai.py

@@ -21,6 +21,9 @@ if TYPE_CHECKING:
 
 # Token limits for different VoyageAI models
 VOYAGE_TOTAL_TOKEN_LIMITS = {
+    "voyage-4": 320_000,
+    "voyage-4-lite": 1_000_000,
+    "voyage-4-large": 120_000,
     "voyage-context-3": 32_000,
     "voyage-3.5-lite": 1_000_000,
     "voyage-3.5": 320_000,
@@ -167,6 +170,9 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
     name: str
         The name of the model to use. List of acceptable models:
 
+            * voyage-4 (1024 dims, general-purpose and multilingual retrieval)
+            * voyage-4-lite (1024 dims, optimized for latency and cost)
+            * voyage-4-large (1024 dims, best retrieval quality)
             * voyage-context-3
             * voyage-3.5
             * voyage-3.5-lite
@@ -215,6 +221,9 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
     _FLEXIBLE_DIM_MODELS: ClassVar[list] = ["voyage-multimodal-3.5"]
     _VALID_DIMENSIONS: ClassVar[list] = [256, 512, 1024, 2048]
     text_embedding_models: list = [
+        "voyage-4",
+        "voyage-4-lite",
+        "voyage-4-large",
         "voyage-3.5",
         "voyage-3.5-lite",
         "voyage-3",
@@ -252,6 +261,9 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
         elif self.name == "voyage-code-2":
             return 1536
         elif self.name in [
+            "voyage-4",
+            "voyage-4-lite",
+            "voyage-4-large",
             "voyage-context-3",
             "voyage-3.5",
             "voyage-3.5-lite",

python/python/tests/test_embeddings_slow.py

@@ -517,19 +517,36 @@ def test_ollama_embedding(tmp_path):
 @pytest.mark.skipif(
     os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
 )
-def test_voyageai_embedding_function():
-    voyageai = get_registry().get("voyageai").create(name="voyage-3", max_retries=0)
+@pytest.mark.parametrize(
+    "model_name,expected_dims",
+    [
+        ("voyage-3", 1024),
+        ("voyage-4", 1024),
+        ("voyage-4-lite", 1024),
+        ("voyage-4-large", 1024),
+    ],
+)
+def test_voyageai_embedding_function(model_name, expected_dims, tmp_path):
+    """Integration test for VoyageAI text embedding models with real API calls."""
+    voyageai = get_registry().get("voyageai").create(name=model_name, max_retries=0)
 
     class TextModel(LanceModel):
         text: str = voyageai.SourceField()
         vector: Vector(voyageai.ndims()) = voyageai.VectorField()
 
     df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
-    db = lancedb.connect("~/lancedb")
+    db = lancedb.connect(tmp_path)
     tbl = db.create_table("test", schema=TextModel, mode="overwrite")
 
     tbl.add(df)
     assert len(tbl.to_pandas()["vector"][0]) == voyageai.ndims()
+    assert voyageai.ndims() == expected_dims, (
+        f"{model_name} should have {expected_dims} dimensions"
+    )
+
+    # Test search functionality
+    result = tbl.search("hello").limit(1).to_pandas()
+    assert result["text"][0] == "hello world"
 
 
 @pytest.mark.slow

python/python/tests/test_voyageai_embeddings.py

@@ -0,0 +1,108 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Unit tests for VoyageAI embedding function.
+
+These tests verify model registration and configuration without requiring API calls.
+"""
+
+import pytest
+from unittest.mock import MagicMock, patch
+
+from lancedb.embeddings import get_registry
+
+
+@pytest.fixture(autouse=True)
+def reset_voyageai_client():
+    """Reset VoyageAI client before and after each test to avoid state pollution."""
+    from lancedb.embeddings.voyageai import VoyageAIEmbeddingFunction
+
+    VoyageAIEmbeddingFunction.client = None
+    yield
+    VoyageAIEmbeddingFunction.client = None
+
+
+class TestVoyageAIModelRegistration:
+    """Tests for VoyageAI model registration and configuration."""
+
+    @pytest.fixture
+    def mock_voyageai_client(self):
+        """Mock VoyageAI client to avoid API calls."""
+        with patch.dict("os.environ", {"VOYAGE_API_KEY": "test-key"}):
+            with patch("lancedb.embeddings.voyageai.attempt_import_or_raise") as mock:
+                mock_client = MagicMock()
+                mock_voyageai = MagicMock()
+                mock_voyageai.Client.return_value = mock_client
+                mock.return_value = mock_voyageai
+                yield mock_client
+
+    def test_voyageai_registered(self):
+        """Test that VoyageAI is registered in the embedding function registry."""
+        registry = get_registry()
+        assert registry.get("voyageai") is not None
+
+    @pytest.mark.parametrize(
+        "model_name,expected_dims",
+        [
+            # Voyage-4 series (all 1024 dims)
+            ("voyage-4", 1024),
+            ("voyage-4-lite", 1024),
+            ("voyage-4-large", 1024),
+            # Voyage-3 series
+            ("voyage-3", 1024),
+            ("voyage-3-lite", 512),
+            # Domain-specific models
+            ("voyage-finance-2", 1024),
+            ("voyage-multilingual-2", 1024),
+            ("voyage-law-2", 1024),
+            ("voyage-code-2", 1536),
+            # Multimodal
+            ("voyage-multimodal-3", 1024),
+        ],
+    )
+    def test_model_dimensions(self, model_name, expected_dims, mock_voyageai_client):
+        """Test that each model returns the correct dimensions."""
+        registry = get_registry()
+        func = registry.get("voyageai").create(name=model_name)
+        assert func.ndims() == expected_dims, (
+            f"Model {model_name} should have {expected_dims} dimensions"
+        )
+
+    def test_unsupported_model_raises_error(self, mock_voyageai_client):
+        """Test that unsupported models raise ValueError."""
+        registry = get_registry()
+        func = registry.get("voyageai").create(name="unsupported-model")
+        with pytest.raises(ValueError, match="not supported"):
+            func.ndims()
+
+    @pytest.mark.parametrize(
+        "model_name",
+        [
+            "voyage-4",
+            "voyage-4-lite",
+            "voyage-4-large",
+        ],
+    )
+    def test_voyage4_models_are_text_models(self, model_name, mock_voyageai_client):
+        """Test that voyage-4 models are classified as text models (not multimodal)."""
+        registry = get_registry()
+        func = registry.get("voyageai").create(name=model_name)
+        assert not func._is_multimodal_model(model_name), (
+            f"{model_name} should be a text model, not multimodal"
+        )
+
+    def test_voyage4_models_in_text_embedding_list(self, mock_voyageai_client):
+        """Test that voyage-4 models are in the text_embedding_models list."""
+        registry = get_registry()
+        func = registry.get("voyageai").create(name="voyage-4")
+        assert "voyage-4" in func.text_embedding_models
+        assert "voyage-4-lite" in func.text_embedding_models
+        assert "voyage-4-large" in func.text_embedding_models
+
+    def test_voyage4_models_not_in_multimodal_list(self, mock_voyageai_client):
+        """Test that voyage-4 models are NOT in the multimodal_embedding_models list."""
+        registry = get_registry()
+        func = registry.get("voyageai").create(name="voyage-4")
+        assert "voyage-4" not in func.multimodal_embedding_models
+        assert "voyage-4-lite" not in func.multimodal_embedding_models
+        assert "voyage-4-large" not in func.multimodal_embedding_models