"""Universal Office Tools Mixin - Format-agnostic tools that work across all Office document types."""

import time
from typing import Any

from fastmcp.contrib.mcp_mixin import MCPMixin, mcp_tool
from pydantic import Field

from ..utils import (
    OfficeFileError,
    classify_document_type,
    detect_format,
    get_supported_extensions,
    resolve_office_file_path,
    validate_office_file,
)


class UniversalMixin(MCPMixin):
    """Mixin containing format-agnostic tools that work across Word, Excel, PowerPoint, and CSV files."""

    @mcp_tool(
        name="extract_text",
        description="Extract text content from Office documents with intelligent method selection. Supports Word (.docx, .doc), Excel (.xlsx, .xls), PowerPoint (.pptx, .ppt), and CSV files. Uses multi-library fallback for maximum compatibility."
    )
    async def extract_text(
        self,
        file_path: str = Field(description="Path to Office document or URL"),
        preserve_formatting: bool = Field(default=False, description="Preserve text formatting and structure"),
        include_metadata: bool = Field(default=True, description="Include document metadata in output"),
        method: str = Field(default="auto", description="Extraction method: auto, primary, fallback")
    ) -> dict[str, Any]:
        start_time = time.time()

        try:
            # Resolve file path (download if URL)
            local_path = await resolve_office_file_path(file_path)

            # Validate file
            validation = await validate_office_file(local_path)
            if not validation["is_valid"]:
                raise OfficeFileError(f"Invalid file: {', '.join(validation['errors'])}")

            # Get format info
            format_info = await detect_format(local_path)
            category = format_info["category"]
            extension = format_info["extension"]

            # Extract text based on category with fallback
            text_result = await self._extract_text_by_category(local_path, extension, category, preserve_formatting, method)

            # Build response
            result = {
                "text": text_result["text"],
                "metadata": {
                    "original_file": file_path,
                    "format": format_info["format_name"],
                    "extraction_method": text_result["method_used"],
                    "extraction_time": round(time.time() - start_time, 3),
                    "methods_tried": text_result.get("methods_tried", [text_result["method_used"]])
                }
            }

            # Add formatted sections if preserved
            if preserve_formatting and "formatted_sections" in text_result:
                result["structure"] = text_result["formatted_sections"]

            # Add metadata if requested
            if include_metadata:
                doc_metadata = await self._extract_basic_metadata(local_path, extension, category)
                result["document_metadata"] = doc_metadata

            return result

        except OfficeFileError:
            raise
        except Exception as e:
            raise OfficeFileError(f"Text extraction failed: {str(e)}")

    @mcp_tool(
        name="extract_images",
        description="Extract images from Office documents with size filtering and format conversion."
    )
    async def extract_images(
        self,
        file_path: str = Field(description="Path to Office document or URL"),
        min_width: int = Field(default=100, description="Minimum image width in pixels"),
        min_height: int = Field(default=100, description="Minimum image height in pixels"),
        output_format: str = Field(default="png", description="Output image format: png, jpg, jpeg"),
        include_metadata: bool = Field(default=True, description="Include image metadata")
    ) -> dict[str, Any]:
        start_time = time.time()

        try:
            # Resolve file path
            local_path = await resolve_office_file_path(file_path)

            # Validate file
            validation = await validate_office_file(local_path)
            if not validation["is_valid"]:
                raise OfficeFileError(f"Invalid file: {', '.join(validation['errors'])}")

            # Get format info
            format_info = await detect_format(local_path)
            category = format_info["category"]
            extension = format_info["extension"]

            # Extract images based on category
            images = await self._extract_images_by_category(local_path, extension, category, output_format, min_width, min_height)

            return {
                "images": images,
                "metadata": {
                    "original_file": file_path,
                    "format": format_info["format_name"],
                    "image_count": len(images),
                    "extraction_time": round(time.time() - start_time, 3),
                    "filters_applied": {
                        "min_width": min_width,
                        "min_height": min_height,
                        "output_format": output_format
                    }
                }
            }

        except OfficeFileError:
            raise
        except Exception as e:
            raise OfficeFileError(f"Image extraction failed: {str(e)}")

    @mcp_tool(
        name="extract_metadata",
        description="Extract comprehensive metadata from Office documents."
    )
    async def extract_metadata(
        self,
        file_path: str = Field(description="Path to Office document or URL")
    ) -> dict[str, Any]:
        start_time = time.time()

        try:
            # Resolve file path
            local_path = await resolve_office_file_path(file_path)

            # Validate file
            validation = await validate_office_file(local_path)
            if not validation["is_valid"]:
                raise OfficeFileError(f"Invalid file: {', '.join(validation['errors'])}")

            # Get format info
            format_info = await detect_format(local_path)
            category = format_info["category"]
            extension = format_info["extension"]

            # Extract metadata based on category
            metadata = await self._extract_metadata_by_category(local_path, extension, category)

            # Add extraction info
            metadata["extraction_info"] = {
                "extraction_time": round(time.time() - start_time, 3),
                "format_detected": format_info["format_name"]
            }

            return metadata

        except OfficeFileError:
            raise
        except Exception as e:
            raise OfficeFileError(f"Metadata extraction failed: {str(e)}")

    @mcp_tool(
        name="detect_office_format",
        description="Intelligent Office document format detection and analysis."
    )
    async def detect_office_format(
        self,
        file_path: str = Field(description="Path to Office document or URL")
    ) -> dict[str, Any]:
        try:
            # Resolve file path
            local_path = await resolve_office_file_path(file_path)

            # Get comprehensive format detection
            format_info = await detect_format(local_path)

            # Add classification
            classification = await classify_document_type(local_path)
            format_info.update(classification)

            return format_info

        except Exception as e:
            raise OfficeFileError(f"Format detection failed: {str(e)}")

    @mcp_tool(
        name="analyze_document_health",
        description="Comprehensive document health and integrity analysis."
    )
    async def analyze_document_health(
        self,
        file_path: str = Field(description="Path to Office document or URL")
    ) -> dict[str, Any]:
        start_time = time.time()

        try:
            # Resolve file path
            local_path = await resolve_office_file_path(file_path)

            # Validate file thoroughly
            validation = await validate_office_file(local_path)

            # Get format detection
            format_info = await detect_format(local_path)

            # Build health report
            health_report = {
                "overall_health": "healthy" if validation["is_valid"] else "unhealthy",
                "validation": validation,
                "format_info": format_info,
                "analysis_time": round(time.time() - start_time, 3)
            }

            # Add recommendations
            if not validation["is_valid"]:
                health_report["recommendations"] = [
                    "File validation failed - check for corruption",
                    "Try opening file in native application",
                    "Consider file recovery tools if data is critical"
                ]
            else:
                health_report["recommendations"] = [
                    "File appears healthy and readable",
                    "All validation checks passed"
                ]

            return health_report

        except Exception as e:
            return {
                "overall_health": "error",
                "error": str(e),
                "analysis_time": round(time.time() - start_time, 3),
                "recommendations": [
                    "File could not be analyzed",
                    "Check file path and permissions",
                    "Verify file is not corrupted"
                ]
            }

    @mcp_tool(
        name="get_supported_formats",
        description="Get list of all supported Office document formats and their capabilities."
    )
    async def get_supported_formats(self) -> dict[str, Any]:
        extensions = get_supported_extensions()

        format_details = {}
        for ext in extensions:
            if ext.startswith('.doc'):
                category = "word"
                legacy = ext == ".doc"
            elif ext.startswith('.xls') or ext == '.csv':
                category = "excel"
                legacy = ext == ".xls"
            elif ext.startswith('.ppt'):
                category = "powerpoint"
                legacy = ext == ".ppt"
            else:
                category = "other"
                legacy = False

            format_details[ext] = {
                "category": category,
                "legacy_format": legacy,
                "text_extraction": True,
                "image_extraction": ext != ".csv",
                "metadata_extraction": True,
                "markdown_conversion": category == "word"
            }

        return {
            "supported_extensions": extensions,
            "format_details": format_details,
            "categories": {
                "word": [ext for ext, info in format_details.items() if info["category"] == "word"],
                "excel": [ext for ext, info in format_details.items() if info["category"] == "excel"],
                "powerpoint": [ext for ext, info in format_details.items() if info["category"] == "powerpoint"]
            },
            "total_formats": len(extensions)
        }

    # Helper methods - these will be imported from the original server.py
    async def _extract_text_by_category(self, file_path: str, extension: str, category: str, preserve_formatting: bool, method: str) -> dict[str, Any]:
        """Extract text based on document category."""
        # Import the appropriate extraction function
        from ..server_monolithic import _extract_word_text, _extract_excel_text, _extract_powerpoint_text

        if category == "word":
            return await _extract_word_text(file_path, extension, preserve_formatting, method)
        elif category == "excel":
            return await _extract_excel_text(file_path, extension, preserve_formatting, method)
        elif category == "powerpoint":
            return await _extract_powerpoint_text(file_path, extension, preserve_formatting, method)
        else:
            raise OfficeFileError(f"Unsupported document category: {category}")

    async def _extract_images_by_category(self, file_path: str, extension: str, category: str, output_format: str, min_width: int, min_height: int) -> list[dict[str, Any]]:
        """Extract images based on document category."""
        from ..server_monolithic import _extract_word_images, _extract_excel_images, _extract_powerpoint_images

        if category == "word":
            return await _extract_word_images(file_path, extension, output_format, min_width, min_height)
        elif category == "excel":
            return await _extract_excel_images(file_path, extension, output_format, min_width, min_height)
        elif category == "powerpoint":
            return await _extract_powerpoint_images(file_path, extension, output_format, min_width, min_height)
        else:
            return []  # CSV and other formats don't support images

    async def _extract_metadata_by_category(self, file_path: str, extension: str, category: str) -> dict[str, Any]:
        """Extract metadata based on document category."""
        from ..server_monolithic import _extract_word_metadata, _extract_excel_metadata, _extract_powerpoint_metadata, _extract_basic_metadata

        # Get basic metadata first
        metadata = await _extract_basic_metadata(file_path, extension, category)

        # Add category-specific metadata
        if category == "word":
            specific_metadata = await _extract_word_metadata(file_path, extension)
        elif category == "excel":
            specific_metadata = await _extract_excel_metadata(file_path, extension)
        elif category == "powerpoint":
            specific_metadata = await _extract_powerpoint_metadata(file_path, extension)
        else:
            specific_metadata = {}

        metadata.update(specific_metadata)
        return metadata

    async def _extract_basic_metadata(self, file_path: str, extension: str, category: str) -> dict[str, Any]:
        """Extract basic metadata common to all documents."""
        from ..server_monolithic import _extract_basic_metadata
        return await _extract_basic_metadata(file_path, extension, category)