ModelBuilder.deploy(update_endpoint=True) raises AttributeError on Session.create_endpoint_config()

**PySDK Version**

- [ ] PySDK V2 (2.x)
- [x] PySDK V3 (3.x)

**Describe the bug**

`ModelBuilder.deploy(update_endpoint=True)` raises `AttributeError: 'Session' object has no attribute 'create_endpoint_config'`.

In the installed V3 packages, `ModelBuilder._deploy_core_endpoint()` calls `self.sagemaker_session.create_endpoint_config(...)` on the update path, but `sagemaker.core.helper.session_helper.Session` does not implement that method.

**To reproduce**

Run the following script:

```python
from types import SimpleNamespace

import boto3
from sagemaker.core.helper.session_helper import Session
from sagemaker.serve.model_builder import ModelBuilder

builder = ModelBuilder(
s3_model_data_url={
"S3DataSource": {
"S3Uri": "s3://example-bucket/model/",
"S3DataType": "S3Prefix",
"CompressionType": "None",
}
},
image_uri="123456789012.dkr.ecr.us-west-2.amazonaws.com/example:latest",
role_arn="arn:aws:iam::123456789012:role/SageMakerExecutionRole",
sagemaker_session=Session(boto_session=boto3.Session(region_name="us-west-2")),
instance_type="ml.g5.xlarge",
env_vars={},
)

builder.model_name = "demo-model"
builder.region = "us-west-2"
builder.endpoint_name = "demo-endpoint"
builder.built_model = SimpleNamespace(model_name="demo-model")

builder._deploy_core_endpoint(
endpoint_name="demo-endpoint",
instance_type="ml.g5.xlarge",
initial_instance_count=1,
wait=False,
update_endpoint=True,
)
```

**Steps**

1. Create a Python environment with the V3 SageMaker packages listed below.
2. Save the script above.
3. Run `python minimal_repro_model_builder_update_endpoint.py`.

**Expected behavior**

One of the following should happen:

- `ModelBuilder.deploy(update_endpoint=True)` should work with the default `Session` implementation used by V3 packages.
- Or `ModelBuilder` should use a session method that actually exists on `sagemaker.core.helper.session_helper.Session`.

**Screenshots or logs**

Actual error:

```text
AttributeError: 'Session' object has no attribute 'create_endpoint_config'
```

I also confirmed locally that:

- `hasattr(Session, "create_endpoint_config") == False`
- `ModelBuilder._deploy_core_endpoint()` contains a call to `self.sagemaker_session.create_endpoint_config(...)`

In my real deployment code, this was triggered from `ModelBuilder.build(...); ModelBuilder.deploy(..., update_endpoint=True)` while updating an existing SageMaker endpoint.

**System information**

- **SageMaker Python SDK version**: V3 packages; `sagemaker-core==2.5.0`, `sagemaker-serve==1.5.0`
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: N/A for repro; issue is in `ModelBuilder` update flow
- **Framework version**: N/A
- **Python version**: 3.14.3
- **CPU or GPU**: Repro itself is local and does not require either; production usage was GPU-backed SageMaker endpoint deployment
- **Custom Docker image (Y/N)**: N

**Additional context**

- Avoiding `update_endpoint=True` and recreating the endpoint instead works around the issue.
- This looks related to the ongoing V3 API/session transition, and may be adjacent to issue #5336, but this report is specifically about the missing `create_endpoint_config()` method on the session object used by `ModelBuilder`.

まず最小限のスクリプトで失敗を再現し、次に ModelBuilder._deploy_core_endpoint と sagemaker.core.helper.session_helper.Session を調べ、update_endpoint パスと欠落している create_endpoint_config 呼び出しに注目します。再現スクリプトを実行し、デフォルトの V3 Session 実装で既存のエンドポイントの更新が機能することを確認して、修正を検証します。

索引モデルが issue の本文から書いたものです。