Schema

Schema package for gllm_training.

This module re-exports all schema components from various modules for backward compatibility.

Authors

Alfan Dinda Rahmawan (alfan.d.rahmawan@gdplabs.id)

Reviewer

Muhammad Afif Al Hawari (muhammad.a.a.hawari@gdplabs.id)

References

NONE

`ColumnMappingConfig`

Bases: BaseModel

Defines the structure for column mapping configuration.

Attributes:

Name	Type	Description
`input_columns`	`Dict[str, str]`	Mapping of template variables to DataFrame column names.
`output_columns`	`List[str]`	List of column names for output.
`label_columns`	`Optional[str]`	Column name for labels.

`ExperimentConfig`

Bases: BaseModel

Defines the configuration for a single fine-tuning experiment.

Attributes:

Name	Type	Description
`experiment_id`	`str`	The ID of the experiment.
`hyperparameters`	`Hyperparameters`	The hyperparameters for the experiment.
`hyperparameters_id`	`str`	The ID of the hyperparameters.
`topic`	`str`	The topic of the experiment.
`model_name`	`str`	The name of the model.
`framework`	`FinetuningLibraryTypes`	The fine-tuning framework to use.
`multimodal`	`bool`	Whether the model is multimodal.
`datasets_path`	`str \| None`	The path to the datasets directory.
`train_filename`	`str \| None`	CSV filename for training data.
`validation_filename`	`str \| None`	CSV filename for validation data.
`prompt_filename`	`str \| None`	CSV filename for prompt templates.
`spreadsheet_id`	`str \| None`	The ID of the Google Sheets spreadsheet.
`google_sheets_client_email`	`str \| None`	Google Sheets client email.
`google_sheets_private_key`	`str \| None`	Google Sheets private key.
`google_scopes`	`list[str] \| None`	Google scopes for service account.
`google_token_uri`	`str \| None`	Google token URI for service account.
`train_sheet`	`str`	The name of the training sheet.
`validation_sheet`	`str \| None`	The name of the validation sheet.
`prompt_sheet`	`str`	The name of the prompt sheet.
`prompt_name`	`str \| None`	The name of the prompt.
`dataset_text_field`	`str`	The text field in the dataset.
`column_mapping_config`	`dict[str, Any] \| None`	Custom configuration for column mappings.
`save_processed_dataset`	`bool`	Whether to save the processed dataset.
`output_processed_dir`	`str`	The output directory for the processed dataset.
`model_path`	`str \| None`	The path to the fine-tuned adapter or full model.

`FinetunedHyperparameters`

Bases: BaseModel

Defines the hyperparameters for a fine-tuning experiment.

Attributes:

Name	Type	Description
`hyperparameters_id`	`str`	The ID of the hyperparameters.
`model_settings`	`ModelConfig`	The model configuration.
`lora_config`	`LoraConfig`	The LoRA configuration.
`training_config`	`TrainingConfig`	The training configuration.
`storage_config`	`StorageConfig`	The storage configuration.

`FrameworkType`

Bases: StrEnum

Defines valid fine-tuning frameworks.

`GoogleSheetsAuthentication`

Bases: BaseModel

Defines valid authentication parameters for Google Sheets API interaction.

Attributes:

Name	Type	Description
`spreadsheet_id`	`str`	The ID of the Google Sheets spreadsheet.
`client_email`	`str`	The client email for the Google Sheets API.
`private_key`	`str`	The private key for the Google Sheets API.
`google_token_uri`	`str`	The Google token URI for the Google Sheets API.

`StorageConfig`

Bases: BaseModel

Defines the storage configuration for model uploads.

Attributes:

Name	Type	Description
`bucket_name`	`str`	The name of the bucket.
`upload_to_cloud`	`bool`	Whether to upload the model to the cloud.
`object_prefix`	`str`	The object prefix in the bucket.
`endpoint_url`	`str \| None`	The complete URL to use for the storage client.
`access_key_id`	`str \| None`	The access key ID for cloud storage account.
`secret_access_key`	`str \| None`	The secret access key for cloud storage account.
`region`	`str \| None`	The region to use when creating the storage client.
`provider`	`str`	The cloud provider.