"""
Tool_OCR - Task Management Schemas
"""

from typing import Optional, List
from datetime import datetime
from pydantic import BaseModel, Field
from enum import Enum

from app.schemas.base import UTCDatetimeBaseModel


class TaskStatusEnum(str, Enum):
    """Task status enumeration"""
    PENDING = "pending"
    PROCESSING = "processing"
    COMPLETED = "completed"
    FAILED = "failed"


class ProcessingTrackEnum(str, Enum):
    """Processing track enumeration for dual-track processing"""
    OCR = "ocr"           # PaddleOCR PP-StructureV3 for scanned documents
    DIRECT = "direct"     # PyMuPDF for editable PDFs
    HYBRID = "hybrid"     # Mixed processing
    AUTO = "auto"         # Auto-detect best track


class LayoutModelEnum(str, Enum):
    """Layout detection model selection for OCR track.

    Different models are optimized for different document types:
    - CHINESE: PP-DocLayout_plus-L (83.2% mAP), optimized for complex Chinese documents
    - DEFAULT: PubLayNet-based (~94% mAP), optimized for English academic papers
    - CDLA: CDLA model (~86% mAP), specialized Chinese document layout analysis
    """
    CHINESE = "chinese"   # PP-DocLayout_plus-L - Best for Chinese documents (recommended)
    DEFAULT = "default"   # PubLayNet-based - Best for English documents
    CDLA = "cdla"         # CDLA model - Alternative for Chinese layout


class PreprocessingModeEnum(str, Enum):
    """Preprocessing mode for layout detection enhancement.

    - AUTO: Analyze image quality and automatically apply optimal preprocessing
    - MANUAL: Use user-specified preprocessing configuration
    - DISABLED: Skip preprocessing entirely
    """
    AUTO = "auto"         # Analyze and apply automatically (default)
    MANUAL = "manual"     # Use specified configuration
    DISABLED = "disabled" # Skip preprocessing


class PreprocessingContrastEnum(str, Enum):
    """Contrast enhancement method for preprocessing.

    - NONE: No contrast enhancement
    - HISTOGRAM: Standard histogram equalization
    - CLAHE: Contrast Limited Adaptive Histogram Equalization (recommended for most cases)
    - DOCUMENT: Background normalization + CLAHE (recommended for scanned documents)
      Removes uneven illumination before enhancement. Best for scans with
      yellowed paper, shadow, or scanner lighting issues.
    """
    NONE = "none"
    HISTOGRAM = "histogram"
    CLAHE = "clahe"
    DOCUMENT = "document"


class PreprocessingConfig(BaseModel):
    """Preprocessing configuration for layout detection enhancement.

    Used to configure image preprocessing before PP-Structure layout detection.
    Preprocessing helps detect tables with faint lines or low contrast borders.
    Original image is preserved for element extraction.
    """
    contrast: PreprocessingContrastEnum = Field(
        default=PreprocessingContrastEnum.CLAHE,
        description="Contrast enhancement method"
    )
    contrast_strength: float = Field(
        default=1.0,
        ge=0.5,
        le=3.0,
        description="Contrast enhancement strength (0.5=subtle, 1.0=normal, 2.0=strong, 3.0=maximum)"
    )
    sharpen: bool = Field(
        default=True,
        description="Enable sharpening for faint lines"
    )
    sharpen_strength: float = Field(
        default=1.0,
        ge=0.5,
        le=2.0,
        description="Sharpening strength (0.5=subtle, 1.0=normal, 1.5=strong, 2.0=maximum)"
    )
    binarize: bool = Field(
        default=False,
        description="Enable binarization (aggressive, for very low contrast). Not recommended for most documents."
    )
    remove_scan_artifacts: bool = Field(
        default=True,
        description="Remove horizontal scan line artifacts. Recommended for scanned documents to prevent misdetection of scanner light bar lines as table borders."
    )


class ImageQualityMetrics(BaseModel):
    """Image quality metrics from auto-analysis."""
    contrast: float = Field(..., description="Contrast level (std dev of grayscale)")
    edge_strength: float = Field(..., description="Edge strength (Sobel gradient mean)")


class PreprocessingPreviewRequest(BaseModel):
    """Request for preprocessing preview."""
    page: int = Field(default=1, ge=1, description="Page number to preview")
    mode: PreprocessingModeEnum = Field(
        default=PreprocessingModeEnum.AUTO,
        description="Preprocessing mode"
    )
    config: Optional[PreprocessingConfig] = Field(
        None,
        description="Manual configuration (only used when mode='manual')"
    )


class PreprocessingPreviewResponse(BaseModel):
    """Response for preprocessing preview."""
    original_url: str = Field(..., description="URL to original image")
    preprocessed_url: str = Field(..., description="URL to preprocessed image")
    quality_metrics: ImageQualityMetrics = Field(..., description="Image quality analysis")
    auto_config: PreprocessingConfig = Field(..., description="Auto-detected configuration")
    mode_used: PreprocessingModeEnum = Field(..., description="Mode that was applied")


class TaskCreate(BaseModel):
    """Task creation request"""
    filename: Optional[str] = Field(None, description="Original filename")
    file_type: Optional[str] = Field(None, description="File MIME type")


class TaskUpdate(BaseModel):
    """Task update request"""
    status: Optional[TaskStatusEnum] = None
    error_message: Optional[str] = None
    processing_time_ms: Optional[int] = None
    result_json_path: Optional[str] = None
    result_markdown_path: Optional[str] = None
    result_pdf_path: Optional[str] = None


class TaskFileResponse(UTCDatetimeBaseModel):
    """Task file response schema"""
    id: int
    original_name: Optional[str] = None
    stored_path: Optional[str] = None
    file_size: Optional[int] = None
    mime_type: Optional[str] = None
    file_hash: Optional[str] = None
    created_at: datetime


class TaskResponse(UTCDatetimeBaseModel):
    """Task response schema"""
    id: int
    user_id: int
    task_id: str
    filename: Optional[str] = None
    file_type: Optional[str] = None
    status: TaskStatusEnum
    result_json_path: Optional[str] = None
    result_markdown_path: Optional[str] = None
    result_pdf_path: Optional[str] = None
    error_message: Optional[str] = None
    processing_time_ms: Optional[int] = None
    created_at: datetime
    updated_at: datetime
    completed_at: Optional[datetime] = None
    file_deleted: bool = False


class TaskDetailResponse(TaskResponse):
    """Detailed task response with files"""
    files: List[TaskFileResponse] = []
    # Dual-track processing field (extracted from result metadata)
    processing_track: Optional[ProcessingTrackEnum] = None
    # Visualization availability (OCR Track only)
    has_visualization: bool = False


class TaskListResponse(BaseModel):
    """Paginated task list response"""
    tasks: List[TaskResponse]
    total: int
    page: int
    page_size: int
    has_more: bool


class TaskStatsResponse(BaseModel):
    """User task statistics"""
    total: int
    pending: int
    processing: int
    completed: int
    failed: int


class TaskHistoryQuery(BaseModel):
    """Task history query parameters"""
    status: Optional[TaskStatusEnum] = None
    filename: Optional[str] = None
    date_from: Optional[datetime] = None
    date_to: Optional[datetime] = None
    page: int = Field(default=1, ge=1)
    page_size: int = Field(default=50, ge=1, le=100)
    order_by: str = Field(default="created_at")
    order_desc: bool = Field(default=True)


class UploadFileInfo(BaseModel):
    """Uploaded file information"""
    filename: str
    file_size: int
    file_type: str


class UploadResponse(BaseModel):
    """File upload response"""
    task_id: str = Field(..., description="Created task ID")
    filename: str = Field(..., description="Original filename")
    file_size: int = Field(..., description="File size in bytes")
    file_type: str = Field(..., description="File MIME type")
    status: TaskStatusEnum = Field(..., description="Initial task status")


# ===== Dual-Track Processing Schemas =====

class PPStructureV3Params(BaseModel):
    """PP-StructureV3 fine-tuning parameters for OCR track.

    DEPRECATED: This class is deprecated and will be removed in a future version.
    Use `layout_model` parameter in ProcessingOptions instead.
    """
    layout_detection_threshold: Optional[float] = Field(
        None, ge=0, le=1,
        description="Layout block detection score threshold (lower=more blocks, higher=high confidence only)"
    )
    layout_nms_threshold: Optional[float] = Field(
        None, ge=0, le=1,
        description="Layout NMS IoU threshold (lower=aggressive overlap removal, higher=allow more overlap)"
    )
    layout_merge_bboxes_mode: Optional[str] = Field(
        None, pattern="^(union|large|small)$",
        description="Bbox merging strategy: 'small'=conservative, 'large'=aggressive, 'union'=middle"
    )
    layout_unclip_ratio: Optional[float] = Field(
        None, gt=0,
        description="Layout bbox expansion ratio (larger=looser boxes, smaller=tighter boxes)"
    )
    text_det_thresh: Optional[float] = Field(
        None, ge=0, le=1,
        description="Text detection score threshold (lower=detect more small/low-contrast text, higher=cleaner)"
    )
    text_det_box_thresh: Optional[float] = Field(
        None, ge=0, le=1,
        description="Text box candidate threshold (lower=more text boxes, higher=fewer false positives)"
    )
    text_det_unclip_ratio: Optional[float] = Field(
        None, gt=0,
        description="Text box expansion ratio (larger=looser boxes, smaller=tighter boxes)"
    )


class ProcessingOptions(BaseModel):
    """Processing options for dual-track OCR"""
    use_dual_track: bool = Field(default=True, description="Enable dual-track processing")
    force_track: Optional[ProcessingTrackEnum] = Field(None, description="Force specific track (ocr/direct)")
    language: str = Field(default="ch", description="OCR language code")
    include_layout: bool = Field(default=True, description="Include layout analysis")
    include_images: bool = Field(default=True, description="Extract and save images")
    confidence_threshold: Optional[float] = Field(None, ge=0, le=1, description="OCR confidence threshold")

    # Layout model selection (OCR track only)
    layout_model: Optional[LayoutModelEnum] = Field(
        default=LayoutModelEnum.CHINESE,
        description="Layout detection model: 'chinese' (recommended for Chinese docs), 'default' (English docs), 'cdla' (Chinese layout)"
    )

    # Layout preprocessing (OCR track only)
    preprocessing_mode: PreprocessingModeEnum = Field(
        default=PreprocessingModeEnum.AUTO,
        description="Preprocessing mode: 'auto' (analyze and apply), 'manual' (use config), 'disabled'"
    )
    preprocessing_config: Optional[PreprocessingConfig] = Field(
        None,
        description="Manual preprocessing config (only used when preprocessing_mode='manual')"
    )


class AnalyzeRequest(BaseModel):
    """Document analysis request"""
    use_dual_track: bool = Field(default=True, description="Enable dual-track processing")
    force_track: Optional[ProcessingTrackEnum] = Field(None, description="Force specific track")
    language: str = Field(default="ch", description="OCR language")
    include_layout: bool = Field(default=True, description="Include layout analysis")


class DocumentAnalysisResponse(BaseModel):
    """Document type analysis response"""
    task_id: str
    filename: str
    recommended_track: ProcessingTrackEnum
    confidence: float = Field(..., ge=0, le=1, description="Detection confidence")
    reason: str = Field(..., description="Reason for recommendation")
    document_info: dict = Field(default_factory=dict, description="Document metadata")
    is_editable: bool = Field(..., description="Whether document has extractable text")
    text_coverage: Optional[float] = Field(None, description="Percentage of text coverage")
    page_count: Optional[int] = Field(None, description="Number of pages")


class ProcessingMetadata(BaseModel):
    """Processing metadata included in responses"""
    processing_track: ProcessingTrackEnum
    processing_time_seconds: float
    language: str
    page_count: int
    total_elements: int
    total_text_regions: int
    total_tables: int
    total_images: int
    average_confidence: Optional[float] = None
    unified_format: bool = True


class TaskResponseWithMetadata(TaskResponse):
    """Extended task response with processing metadata"""
    processing_track: Optional[ProcessingTrackEnum] = None
    processing_metadata: Optional[ProcessingMetadata] = None


class ExportOptions(BaseModel):
    """Export format options"""
    format: str = Field(default="json", description="Export format: json, markdown, pdf, unified")
    include_metadata: bool = Field(default=True, description="Include processing metadata")
    include_statistics: bool = Field(default=True, description="Include document statistics")
    legacy_format: bool = Field(default=False, description="Use legacy JSON format for compatibility")