# SPDX-License-Identifier: AGPL-3.0-only # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0 """ Pydantic schemas for Export API. """ from pydantic import BaseModel, Field from typing import List, Optional, Literal, Dict, Any class LoadCheckpointRequest(BaseModel): """Request for loading a checkpoint into the export backend.""" checkpoint_path: str = Field(..., description = "Path to the checkpoint directory") max_seq_length: int = Field( 2048, ge = 128, le = 32768, description = "Maximum sequence length for loading the model", ) load_in_4bit: bool = Field( True, description = "Whether to load the model in 4-bit quantization", ) trust_remote_code: bool = Field( False, description = "Allow loading models with custom code. Only enable for checkpoints/base models you trust.", ) class ExportStatusResponse(BaseModel): """Current export backend status.""" current_checkpoint: Optional[str] = Field( None, description = "Path to the currently loaded checkpoint, if any", ) is_vision: bool = Field( False, description = "True if the loaded checkpoint is a vision model", ) is_peft: bool = Field( False, description = "True if the loaded checkpoint is a PEFT (LoRA) model", ) class ExportOperationResponse(BaseModel): """Generic response for export operations.""" success: bool = Field(..., description = "True if the operation succeeded") message: str = Field(..., description = "Human-readable status or error message") details: Optional[Dict[str, Any]] = Field( default = None, description = "Optional extra details about the operation", ) class ExportCommonOptions(BaseModel): """Common options for export operations that save locally and/or push to Hub.""" save_directory: str = Field( ..., description = "Local directory where the exported artifacts will be written", ) push_to_hub: bool = Field( False, description = "If True, also push the exported model to the Hugging Face Hub", ) repo_id: Optional[str] = Field( None, description = "Hugging Face Hub repository ID (username/model-name)", ) hf_token: Optional[str] = Field( None, description = "Hugging Face access token used for Hub operations", ) private: bool = Field( False, description = "If True, create a private repository on the Hub (where applicable)", ) base_model_id: Optional[str] = Field( None, description = "HuggingFace model ID of the base model (for model card metadata)", ) class ExportMergedModelRequest(ExportCommonOptions): """Request for exporting a merged PEFT model.""" format_type: Literal["16-bit (FP16)", "4-bit (FP4)"] = Field( "16-bit (FP16)", description = "Export precision / format for the merged model", ) class ExportBaseModelRequest(ExportCommonOptions): """Request for exporting a non-PEFT (base) model.""" # Uses fields from ExportCommonOptions only class ExportGGUFRequest(BaseModel): """Request for exporting the current model to GGUF format.""" save_directory: str = Field( ..., description = "Directory where GGUF files will be saved", ) quantization_method: str = Field( "Q4_K_M", description = 'GGUF quantization method (e.g. "Q4_K_M")', ) push_to_hub: bool = Field( False, description = "If True, also push GGUF artifacts to the Hugging Face Hub", ) repo_id: Optional[str] = Field( None, description = "Hugging Face Hub repository ID for GGUF upload", ) hf_token: Optional[str] = Field( None, description = "Hugging Face token for GGUF upload", ) class ExportLoRAAdapterRequest(ExportCommonOptions): """Request for exporting only the LoRA adapter (not merged).""" # Uses fields from ExportCommonOptions only