# Import required libraries
import pandas as pd
from pathlib import Path
from typing import List
from langchain.schema import Document
from .config import logger
from langchain_pymupdf4llm import PyMuPDF4LLMLoader
from langchain_community.document_loaders.parsers import TesseractBlobParser


def load_pdf_documents(pdf_path: Path) -> List[Document]:
    """
    Load and process PDF documents from medical guidelines using PyMuPDF4LLMLoader.
    Uses Tesseract for image extraction and optimized table extraction for medical documents.
    Extracts disease and provider from directory structure.
   
    Directory structure expected: Data/Disease Name/Provider Name/file.pdf
   
    Args:
        pdf_path: Path to the PDF file
       
    Returns:
        List of Document objects
    """
    try:
       
        # Validate file exists
        if not pdf_path.exists():
            raise FileNotFoundError(f"PDF file not found at {pdf_path}")
       
        # Extract disease and provider from directory structure
        path_parts = pdf_path.parts
        disease = "unknown"
        provider = "unknown"
       
        if len(path_parts) >= 3:
            # Get disease (parent's parent directory)
            disease = path_parts[-3] if path_parts[-3].lower() != "data" else path_parts[-2]
            # Get provider (parent directory)  
            provider = path_parts[-2]
       
        # Initialize PyMuPDF4LLMLoader
        loader = PyMuPDF4LLMLoader(
            str(pdf_path),
            mode="page",
            extract_images=True,
            images_parser=TesseractBlobParser(),
            table_strategy="lines"
        )
       
        raw_documents = loader.load()
       
        documents = []
        for idx, doc in enumerate(raw_documents):
            if doc.page_content.strip():
                # Extract actual page number from metadata, default to sequential numbering
                # PyMuPDF4LLMLoader uses 0-indexed pages, so we add 1 for human-readable page numbers
                actual_page = doc.metadata.get("page")
                if actual_page is not None:
                    # If page is 0-indexed, add 1 to make it 1-indexed
                    page_num = actual_page + 1 if actual_page == idx else actual_page
                else:
                    # Fallback to 1-indexed sequential numbering
                    page_num = idx + 1
                
                processed_doc = Document(
                    page_content=doc.page_content,
                    metadata={
                        "source": pdf_path.stem,
                        "disease": disease,
                        "provider": provider,
                        "page_number": page_num
                    }
                )
                documents.append(processed_doc)

        logger.info(f"Loaded {len(documents)} document pages from PDF - Disease: {disease}, Provider: {provider}")
        return documents
       
    except Exception as e:
        logger.error(f"Error loading PDF documents: {str(e)}")
        raise
    
    
def load_markdown_documents(md_path: Path) -> List[Document]:
    """
    Load and process Markdown medical guidelines.
    Extracts disease and provider from directory structure.

    Directory structure expected: Data/Disease Name/Provider Name/file.md

    Args:
        md_path: Path to the Markdown file

    Returns:
        List of Document objects (single document split by sections if needed)
    """
    try:
        # Validate file exists
        if not md_path.exists():
            raise FileNotFoundError(f"Markdown file not found at {md_path}")

        # Extract disease and provider from directory structure
        path_parts = md_path.parts
        disease = "unknown"
        provider = "unknown"

        if len(path_parts) >= 3:
            # Get disease (parent's parent directory)
            disease = path_parts[-3] if path_parts[-3].lower() != "data" else path_parts[-2]
            # Get provider (parent directory)  
            provider = path_parts[-2]

        # Read markdown content
        with open(md_path, 'r', encoding='utf-8') as f:
            content = f.read()

        # Create document with minimal metadata for RAG
        doc = Document(
            page_content=content,
            metadata={
                "source": md_path.stem,
                "disease": disease,
                "provider": provider,
                "page_number": 1
            }
        )

        logger.info(f"Loaded Markdown document - Disease: {disease}, Provider: {provider}")
        return [doc]

    except Exception as e:
        logger.error(f"Error loading Markdown document: {str(e)}")
        raise