Token Refresh Flow & Dataset Upload Structure Improvement

🚀 New Features

Token Expiration Handling Improvements

• Switched from token reissue to fresh login when a token expires.
• Ensures more reliable and predictable authentication flow.

Automatic Token Update Post-Login

• After a successful login, self.tokens is now automatically updated to prevent stale token usage in subsequent requests.

UploadDataset Dataclass

• Added a new UploadDataset dataclass for clearer and more structured handling of dataset upload metadata.

Launcher Task Error Logging

• Improved error logging for task failures in the launcher, helping users debug configuration and runtime issues more easily.

API Client Info Logging

• API client now prints host and port information upon initialization to confirm connection settings.

🐞 Bug Fixes

• Fixed a bug where trainer model architecture configuration was incorrectly parsed.
• Resolved an issue with classification dataset settings not applying correctly in training.
• Added missing model_name definition in initialize_from_yaml() to avoid runtime errors during model setup.

🧠 Why these matter

• These updates improve reliability in authentication and API interaction, particularly in long-running sessions.
• Users benefit from better visibility into configuration issues and API usage context.
• Dataset and training configuration flows are now more stable and transparent, reducing the chance of runtime errors.