fix(python): instruct dimension probe for instructor embeddings (#3874)

## Summary

- pass an Instructor-compatible `[instruction, text]` pair when
detecting embedding dimensions
- add a regression test that verifies the dimension probe uses the
configured source instruction

## Root cause

`InstructorEmbeddingFunction.ndims()` encoded a bare string even though
Instructor models require instruction/text pairs. With affected
`sentence-transformers` versions, the bare input omitted
`instruction_mask` and raised `KeyError` while defining the LanceDB
schema.

## Validation

- `uv run --extra tests pytest python/tests/test_embeddings.py -q` (`14
passed, 9 skipped`)
- `uv run --project python --extra tests --extra dev ruff format --check
python/python/lancedb/embeddings/instructor.py
python/python/tests/test_embeddings.py`
- `uv run --project python --extra tests --extra dev ruff check .`

Fixes #2041

<!-- lance-gatekeeper-fix:v1 agent=4b05e0d9f3eef17bccfb446e788294f4
generation=1 -->

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>

python/python/lancedb/embeddings/instructor.py

@@ -101,8 +101,7 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):
 
     @weak_lru(maxsize=1)
     def ndims(self):
-        model = self.get_model()
-        return model.encode("foo").shape[0]
+        return len(self.generate_embeddings([[self.source_instruction, "foo"]])[0])
 
     def compute_query_embeddings(self, query: str, *args, **kwargs) -> List[np.array]:
         return self.generate_embeddings([[self.query_instruction, query]])

python/python/tests/test_embeddings.py

@@ -64,6 +64,23 @@ def test_embedding_function(tmp_path):
     assert np.allclose(actual, expected)
 
 
+def test_instructor_ndims_uses_instruction():
+    instructor = get_registry().get("instructor").create()
+    model = MagicMock()
+    model.encode.return_value = np.zeros((1, 384))
+
+    with patch.object(type(instructor), "get_model", return_value=model):
+        assert instructor.ndims() == 384
+
+    model.encode.assert_called_once_with(
+        [[instructor.source_instruction, "foo"]],
+        batch_size=instructor.batch_size,
+        show_progress_bar=instructor.show_progress_bar,
+        normalize_embeddings=instructor.normalize_embeddings,
+        device=instructor.device,
+    )
+
+
 def test_embedding_function_variables():
     @register("variable-testing")
     class VariableTestingFunction(TextEmbeddingFunction):