Optional Message Fields Generated as Non-Optional with default_factory

[aniketpalu]

Describe the bug
When protobuf messages have optional message-typed fields, protobuf_to_pydantic generates non-optional fields with default_factory=MessageClass() instead of Optional[MessageClass] with default=None. This makes it impossible to distinguish between "field not set" and "field set to empty message", which is semantically different in protobuf.

Dependencies

############# dependencies ############## 
    grpc:            1.62.3
    pydantic:        2.10.6

########## Expand dependencies ########## 
    mypy-protobuf:   3.3.0
    toml:            0.10.2

########## Format dependencies ########## 
    autoflake:       Not Install
    black:           Not Install
    isort:           Not Install

Protobuf File Content

Filename: feast/core/DataSource.proto

syntax = "proto3";
package feast.core;

message DataSource {
string name = 1;
string description = 2;
}

Filename: feast/core/FeatureView.proto

syntax = "proto3";
package feast.core;

import "feast/core/DataSource.proto";

message FeatureView {
string name = 1;
optional DataSource batch_source = 2;
optional DataSource stream_source = 3;
}

CLI(if use plugin mode)

python -m grpc_tools.protoc \
-I. \
--protobuf-to-pydantic_out=. \
feast/core/DataSource.proto feast/core/FeatureView.proto

Output content

Filename: feast/core/FeatureView_p2p.py

from pydantic import BaseModel, Field
import typing
from .DataSource_p2p import DataSource

class FeatureView(BaseModel):
name: str = Field(default="")
batch_source: DataSource = Field(default_factory=DataSource)
stream_source: DataSource = Field(default_factory=DataSource)

Expected behavior

from pydantic import BaseModel, Field
import typing
from .DataSource_p2p import DataSource

class FeatureView(BaseModel):
name: str = Field(default="")
batch_source: typing.Optional[DataSource] = Field(default=None)
stream_source: typing.Optional[DataSource] = Field(default=None)

Reproduction

# Current behavior
fv = FeatureView(name="test")
print(fv.batch_source)  # DataSource(name='', description='')
# Problem: Can't tell if batch_source was explicitly set or just defaulted

# Expected behavior
fv = FeatureView(name="test")
print(fv.batch_source)  # None
# Clear indication that batch_source was not provided

# When explicitly set
fv = FeatureView(name="test", batch_source=DataSource(name="source1"))
print(fv.batch_source)  # DataSource(name='source1', description='')

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Additional context
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