"""
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",
    )


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
    pass


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
    pass