fix(python): accept VoyageAI text batch containers (#4558)

Direct VoyageAI `compute_source_embeddings()` calls reject `list[str]`
and NumPy text batches before reaching the provider, although both
belong to the declared `TEXT` input type. For example, `["first",
"second"]` raises `ValueError: Input type <class 'list'> not allowed
with text model.`

Normalize these containers to a list before the existing string-entry
validation. The regression cases exercise the public embedding API with
a stub provider: input order, list/NumPy batches, Arrow controls, empty
batches, and rejection of non-text entries and ordinary two-dimensional
arrays. The VoyageAI integration page now documents the accepted text
containers.

Verified on current main `7b3ba4c` with a locally compiled native
extension (0.41.0b7, Python 3.12.12):

- VoyageAI suite: 7 failed / 20 passed before the fix; 27 passed
afterward.
- Adjacent embedding suite: 13 passed, 4 skipped, 8 slow cases
deselected.
- Python CI's pinned Ruff 0.9.9 lint/format checks pass; configured
Pyright reports zero errors/warnings; all applicable pre-commit hooks
pass.

The provider is stubbed; no live Voyage API request or model-quality
evaluation was performed.

AI disclosure: I used Codex for investigation, implementation, tests,
review, and drafting this description.

docs/web/integrations/embedding/voyageai.mdx

@@ -45,6 +45,8 @@ Supported parameters (to be passed in `create` method) are:
 | `output_dimension` | `int` | `None` | Output embedding dimension. Only supported by `voyage-multimodal-3.5`. Valid options: 256, 512, 1024 (default), 2048. |
 
 
+For text models, `compute_source_embeddings()` accepts a single string, a list of strings, a one-dimensional NumPy array, or a PyArrow `Array` or `ChunkedArray`. Batch inputs retain their order.
+
 Usage Example:
 
 <CodeGroup>
@@ -61,4 +63,4 @@ The `voyage-multimodal-3.5` model can embed text alongside images. You can use i
   <CodeBlock filename="Python" language="Python" icon="python">
     {PyEmbeddingVoyageaiMultimodal}
   </CodeBlock>
-</CodeGroup>
+</CodeGroup>

python/python/lancedb/embeddings/voyageai.py

@@ -145,6 +145,8 @@ def sanitize_text_input(inputs: TEXT) -> List[str]:
     """
     if isinstance(inputs, str):
         inputs = [inputs]
+    elif isinstance(inputs, (list, np.ndarray)):
+        inputs = list(inputs)
     elif isinstance(inputs, pa.Array):
         inputs = inputs.to_pylist()
     elif isinstance(inputs, pa.ChunkedArray):

python/python/tests/test_voyageai_embeddings.py

@@ -6,6 +6,8 @@
 These tests verify model registration and configuration without requiring API calls.
 """
 
+import numpy as np
+import pyarrow as pa
 import pytest
 from unittest.mock import MagicMock, patch
 
@@ -122,3 +124,58 @@ class TestVoyageAIModelRegistration:
         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
+
+
+@pytest.mark.parametrize(
+    "inputs",
+    [
+        ["first", "second"],
+        np.array(["first", "second"]),
+        pa.array(["first", "second"]),
+        pa.chunked_array([["first"], ["second"]]),
+    ],
+    ids=["list", "numpy", "arrow", "chunked-arrow"],
+)
+def test_text_source_embeddings_accept_batch_containers(inputs):
+    from lancedb.embeddings.voyageai import VoyageAIEmbeddingFunction
+
+    client = MagicMock()
+    client.tokenize.return_value = [[1], [2]]
+    client.embed.return_value.embeddings = [[0.1, 0.2], [0.3, 0.4]]
+    VoyageAIEmbeddingFunction.client = client
+    func = get_registry().get("voyageai").create(name="voyage-3")
+
+    assert func.compute_source_embeddings(inputs) == [[0.1, 0.2], [0.3, 0.4]]
+    client.embed.assert_called_once_with(
+        texts=["first", "second"], model="voyage-3", input_type="document"
+    )
+
+
+@pytest.mark.parametrize("inputs", [[], np.array([], dtype=str)])
+def test_text_source_embeddings_accept_empty_batch(inputs):
+    from lancedb.embeddings.voyageai import VoyageAIEmbeddingFunction
+
+    client = MagicMock()
+    VoyageAIEmbeddingFunction.client = client
+    func = get_registry().get("voyageai").create(name="voyage-3")
+
+    assert func.compute_source_embeddings(inputs) == []
+    client.tokenize.assert_not_called()
+    client.embed.assert_not_called()
+
+
+@pytest.mark.parametrize(
+    "inputs",
+    [["text", 42], np.array(["text", None]), np.array([["first", "second"]])],
+)
+def test_text_source_embeddings_reject_non_text_batch_entries(inputs):
+    from lancedb.embeddings.voyageai import VoyageAIEmbeddingFunction
+
+    client = MagicMock()
+    VoyageAIEmbeddingFunction.client = client
+    func = get_registry().get("voyageai").create(name="voyage-3")
+
+    with pytest.raises(ValueError, match="Each input should be str"):
+        func.compute_source_embeddings(inputs)
+    client.tokenize.assert_not_called()
+    client.embed.assert_not_called()