Three fixes in encoding.py:

1. TupleEncodable.encode() returns a TupleItems model instance (not a
   raw tuple), and deserialize() returns the model directly. This fixes
   pydantic validation in litellm integration tests for NamedTuple and
   fixed-tuple types. Extract shared field access into _extract_items().

2. Add _TupleSafeJsonSchema that overrides pydantic's tuple_schema() to
   produce object schemas (item_0, item_1 properties) instead of
   prefixItems arrays. Applied via _BoxEncoding.model_json_schema() so
   dataclasses containing tuple fields produce OpenAI-compatible schemas.
   Can be removed once #584 replaces the Encodable system.

3. SequenceEncodable.encode()/deserialize() return lists (not tuples) to
   preserve encode idempotency — nested_type on a list dispatches to the
   sequence encoder, avoiding a mismatch with TupleEncodable.

Use Pydantic's Annotated extension points (PlainValidator, PlainSerializer,
WithJsonSchema) to handle tuples — adapted from _pydantic_type_tuple in #584.

- _safe_tuple_type: rewrites fixed-length tuple[T1, T2, ...] into an
  Annotated type with custom validation (item_N dict → tuple), serialization
  (tuple → item_N dict), and JSON schema (object with item_0/item_1
  properties instead of prefixItems). Single mechanism for schema, validation,
  and serialization.

- _rewrite_tuple_annotations: recursively applies _safe_tuple_type to
  dataclass fields, creating an Annotated proxy so nested tuples inside
  objects also get safe schemas.

- TupleEncodable.encode() returns TupleItems model instances; deserialize()
  returns the model directly. Shared field access via _extract_items().

- SequenceEncodable.encode()/deserialize() return lists to preserve encode
  idempotency with the new TupleEncodable return type.