import fitz  # PyMuPDF
import easyocr
from pdf2image import convert_from_path
from typing import Optional
import tempfile
import os


def extract_text_from_pdf(file_path: str) -> str:
    """
    Extract text from PDF using hybrid approach:
    1. First try PyMuPDF for searchable PDFs
    2. If minimal text, fall back to OCR for scanned PDFs
    """

    # Step 1: Try PyMuPDF extraction
    try:
        doc = fitz.open(file_path)
        text = ""

        for page_num in range(doc.page_count):
            page = doc.load_page(page_num)
            text += page.get_text()

        doc.close()

        # Check if we got meaningful text (more than 100 characters)
        if len(text.strip()) > 100:
            return text.strip()

    except Exception as e:
        print(f"PyMuPDF extraction failed: {e}")

    # Step 2: Fall back to OCR for scanned PDFs
    try:
        # Convert PDF to images
        images = convert_from_path(file_path)

        # Initialize EasyOCR for English and Hindi
        reader = easyocr.Reader(['en', 'hi'])

        ocr_text = ""
        for image in images:
            # Perform OCR on each page
            results = reader.readtext(image)

            # Extract text from OCR results
            for (bbox, text, confidence) in results:
                if confidence > 0.5:  # Only include high-confidence text
                    ocr_text += text + " "

        return ocr_text.strip()

    except Exception as e:
        print(f"OCR extraction failed: {e}")
        raise Exception(f"Failed to extract text from PDF: {e}")

    return ""