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chore: import upstream snapshot with attribution
2026-07-13 12:59:56 +08:00

99 lines
3.2 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Dataset Pydantic models for API requests and responses."""
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field, model_validator
class CheckFormatRequest(BaseModel):
"""Request for dataset format check"""
dataset_name: str # HuggingFace dataset name or local path
is_vlm: bool = False
hf_token: Optional[str] = None
subset: Optional[str] = None
train_split: Optional[str] = "train"
@model_validator(mode = "before")
@classmethod
def _compat_split(cls, values: Any) -> Any:
"""Accept legacy 'split' field as alias for 'train_split'."""
if isinstance(values, dict) and "split" in values:
values.setdefault("train_split", values.pop("split"))
return values
class CheckFormatResponse(BaseModel):
"""Response for dataset format check"""
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
chat_column: Optional[str] = None
preview_samples: Optional[List[Dict]] = None
total_rows: Optional[int] = None
warning: Optional[str] = None
class AiAssistMappingRequest(BaseModel):
"""Request for LLM-assisted column classification (user-triggered)."""
columns: List[str]
samples: List[Dict[str, Any]] # Preview rows already loaded in the dialog
dataset_name: Optional[str] = None # For LLM context
hf_token: Optional[str] = None # For fetching dataset card
model_name: Optional[str] = None
model_type: Optional[str] = None
class AiAssistMappingResponse(BaseModel):
"""Response from LLM-assisted column classification and conversion advice."""
success: bool
suggested_mapping: Optional[Dict[str, str]] = None
warning: Optional[str] = None
# Conversion advisor fields
system_prompt: 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):
"""Response with stored dataset path for training."""
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
rows: Optional[int] = None
updated_at: Optional[float] = None
metadata: Optional[Metadata] = None
class LocalDatasetsResponse(BaseModel):
datasets: List[LocalDatasetItem] = Field(default_factory = list)