[Docs] MessagePack IDL, Pydantic Support, and Attribute Access

docs/user_guide/data_types_and_io/dataclass.md

@@ -12,7 +12,16 @@ Flytekit uses the [Mashumaro library](https://github.com/Fatal1ty/mashumaro)
 to serialize and deserialize dataclasses.
 
 :::{important}
-If you're using Flytekit version below v1.11.1, you will need to add `from dataclasses_json import dataclass_json` to your imports and decorate your dataclass with `@dataclass_json`.
+If you're using Flytekit version < v1.11.1, you will need to add `from dataclasses_json import dataclass_json` to your imports and decorate your dataclass with `@dataclass_json`.
+:::
+
+:::{important}
+Flytekit version < v1.14.0 will produce protobuf struct literal for dataclasses.
+
+Flytekit version >= v1.14.0 will produce msgpack bytes literal for dataclasses.
+
+If you're using Flytekit version >= v1.14.0 and you want to produce protobuf struct literal for dataclasses, you can 
+set environment variable  `FLYTE_USE_OLD_DC_FORMAT` to `true`.
 :::
 
 ```{note}

docs/user_guide/data_types_and_io/index.md

@@ -144,6 +144,7 @@ flytefile
 flytedirectory
 structureddataset
 dataclass
+pydantic
 accessing_attributes
 pytorch_type
 enum_type

docs/user_guide/data_types_and_io/pydantic.md

@@ -0,0 +1,21 @@
+(pydantic)=
+
+# Pydantic BaseModel
+
+```{eval-rst}
+.. tags:: Basic
+```
+
+When you've multiple values that you want to send across Flyte entities, and you want them to have, you can use a `pydantic.BaseModel`.
+Note:
+You can put Dataclass and FlyteTypes (FlyteFile, FlyteDirectory, FlyteSchema, and StructuredDataset) in a pydantic BaseModel.
+
+:::{important}
+Pydantic BaseModel V2 only works when you are using flytekit version >= v1.14.0.
+:::
+
+:::{important}
+If you're using Flytekit version >= v1.14.0 and you want to produce protobuf struct literal for pydantic basemodels,
+you can set environment variable  `FLYTE_USE_OLD_DC_FORMAT` to `true`.
+:::
+