# SPDX-License-Identifier: AGPL-3.0-only # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0 from __future__ import annotations from typing import Any, Dict, List, Literal, Optional from pydantic import BaseModel, Field, model_validator class CheckFormatRequest(BaseModel): dataset_name: str is_vlm: bool = False subset: Optional[str] = None train_split: Optional[str] = "train" prefer_local_cache: bool = False local_path: Optional[str] = None @model_validator(mode = "before") @classmethod def _compat_split(cls, values: Any) -> Any: if isinstance(values, dict) and "split" in values: merged = {**values} merged.setdefault("train_split", merged.pop("split")) return merged return values class CheckFormatResponse(BaseModel): requires_manual_mapping: bool detected_format: str columns: List[str] is_image: bool = False is_audio: bool = False multimodal_columns: Optional[List[str]] = None suggested_mapping: Optional[Dict[str, str]] = None detected_image_column: Optional[str] = None detected_audio_column: Optional[str] = None detected_text_column: Optional[str] = None detected_speaker_column: Optional[str] = None preview_samples: Optional[List[Dict]] = None total_rows: Optional[int] = None warning: Optional[str] = None class AiAssistMappingRequest(BaseModel): columns: List[str] samples: List[Dict[str, Any]] dataset_name: Optional[str] = None model_name: Optional[str] = None model_type: Optional[str] = None class AiAssistMappingResponse(BaseModel): success: bool suggested_mapping: Optional[Dict[str, str]] = None warning: Optional[str] = None system_prompt: Optional[str] = None user_template: Optional[str] = None assistant_template: Optional[str] = None label_mapping: Optional[Dict[str, Dict[str, str]]] = None dataset_type: Optional[str] = None is_conversational: Optional[bool] = None user_notification: Optional[str] = None class UploadDatasetResponse(BaseModel): filename: str = Field(..., description = "Original filename") stored_path: str = Field(..., description = "Absolute path stored on backend") class LocalDatasetItem(BaseModel): class Metadata(BaseModel): actual_num_records: Optional[int] = None target_num_records: Optional[int] = None total_num_batches: Optional[int] = None num_completed_batches: Optional[int] = None columns: Optional[List[str]] = None id: str label: str path: str source: Literal["recipe", "upload"] rows: Optional[int] = None updated_at: Optional[float] = None metadata: Optional[Metadata] = None class LocalDatasetsResponse(BaseModel): datasets: List[LocalDatasetItem] = Field(default_factory = list) class CachedDatasetItem(BaseModel): repo_id: str size_bytes: int = 0 cache_path: Optional[str] = None processed_cache: bool = False partial: bool = False partial_transport: Optional[str] = None class CachedDatasetsResponse(BaseModel): cached: List[CachedDatasetItem] = Field(default_factory = list) class DeleteCachedDatasetResponse(BaseModel): status: str repo_id: str