fix(python): support typed embedding vector fields (#3826)

## Summary

- infer fixed-size float32 Arrow vectors from `VectorField` metadata
when a model uses the standard `list[float]` annotation
- document the mypy-compatible embedding-field declaration while
preserving the existing `Vector(dim)` runtime API
- add regression coverage for schema conversion and model construction

## Root cause

`Vector(dim)` is a runtime constrained-type factory, but Python's static
typing rules do not permit call expressions in annotation positions.
Mypy's suggested `Vector[...]` spelling also cannot represent a
dimension computed at runtime and fails because `Vector` is a function.
`VectorField` already carries the embedding function and its dimension,
but schema conversion previously ignored that metadata for a statically
valid `list[float]` annotation.

The runtime factory remains available for dimension-constrained Pydantic
validation. Embedding-backed models that require mypy compatibility can
now use `list[float] = embedding.VectorField()`; LanceDB derives the
same nullable fixed-size float32 Arrow type from the field metadata.

## Validation

- `cd python && uv run --extra tests pytest
python/tests/test_pydantic.py -q` (23 passed)
- focused mypy check reproducing the original error and accepting the
new `LanceModel` declaration
- isolated schema checks with Pydantic 1.10.24 and 2.11.7
- `ruff format .`
- `ruff check .`

Fixes #1982

<!-- lance-gatekeeper-fix:v1 agent=877facbc659cdc9424bd367e12426366
generation=1 -->

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

python/python/tests/test_pydantic.py

@@ -9,6 +9,7 @@ from typing import List, Optional, Tuple
 import pyarrow as pa
 import pydantic
 import pytest
+from lancedb.conftest import MockTextEmbeddingFunction
 from lancedb.pydantic import (
     LanceModel,
     MultiVector,
@@ -425,6 +426,25 @@ def test_bare_vector_raises_clear_error():
         exec("class TestModel(LanceModel):\n    vector: Vector", namespace)
 
 
+def test_embedding_vector_list_annotation():
+    embedding = MockTextEmbeddingFunction.create()
+
+    class StaticTypingModel(LanceModel):
+        text: str = embedding.SourceField()
+        vector: list[float] = embedding.VectorField()
+
+    schema = pydantic_to_schema(StaticTypingModel)
+    assert schema == pa.schema(
+        [
+            pa.field("text", pa.utf8(), False),
+            pa.field("vector", pa.list_(pa.float32(), embedding.ndims()), True),
+        ]
+    )
+
+    model = StaticTypingModel(text="hello", vector=[0.0] * embedding.ndims())
+    assert model.vector == [0.0] * embedding.ndims()
+
+
 def test_fixed_size_list_field():
     class TestModel(pydantic.BaseModel):
         vec: Vector(16)