"""Tesseract OCR helper.

Pure-Python wrapper that uses pytesseract. Tesseract binary must be
installed separately (Windows installer from UB-Mannheim). The
captcha solver falls back to this if Florence-2 is unavailable.

Install: pip install pytesseract
Windows: https://github.com/UB-Mannheim/tesseract/wiki (use the .exe installer)
Linux:   apt install tesseract-ocr
macOS:   brew install tesseract
"""

from __future__ import annotations

import os
import shutil
from typing import Optional

import pytesseract
from PIL import Image


def is_available() -> bool:
    """Return True if tesseract binary is on PATH, in TESSERACT_CMD env, or in standard locations."""
    if shutil.which("tesseract") or shutil.which("tesseract.exe"):
        return True
    if os.environ.get("TESSERACT_CMD") and os.path.exists(os.environ["TESSERACT_CMD"]):
        return True
    for p in (
        r"C:\Program Files\Tesseract-OCR\tesseract.exe",
        r"C:\Program Files (x86)\Tesseract-OCR\tesseract.exe",
        "/usr/bin/tesseract",
        "/usr/local/bin/tesseract",
    ):
        if os.path.exists(p):
            pytesseract.pytesseract.tesseract_cmd = p
            return True
    return False


def _preprocess_for_ocr(pil_image: Image.Image) -> Image.Image:
    """Upscale + add padding to help tesseract read cramped captcha images.

    Tesseract needs significant whitespace between characters and at borders.
    Small captchas (220x70) often bleed characters together, producing OCR errors
    like "3+5=?" -> "34+5=?". Scaling 2-3x and adding 20px padding fixes most of these.
    """
    w, h = pil_image.size
    # Upscale if smaller than 400px wide
    if w < 400:
        scale = 3 if w < 300 else 2
        new_size = (w * scale, h * scale)
        pil_image = pil_image.resize(new_size, Image.LANCZOS)
    # Add 20px white border all around
    if pil_image.mode != "RGB":
        pil_image = pil_image.convert("RGB")
    bordered = Image.new("RGB", (pil_image.size[0] + 40, pil_image.size[1] + 40), (255, 255, 255))
    bordered.paste(pil_image, (20, 20))
    return bordered


def ocr_image(
    pil_image: Image.Image,
    psm: int = 7,
    lang: str = "eng",
    whitelist: Optional[str] = None,
) -> str:
    """Run Tesseract on a PIL image.

    psm=7: single line
    psm=8: single word
    psm=6: assume uniform block
    """
    config_parts = [f"--psm {psm}", f"-l {lang}"]
    if whitelist:
        config_parts.append(f"-c tessedit_char_whitelist={whitelist}")
    return pytesseract.image_to_string(pil_image, config=" ".join(config_parts)).strip()


def ocr_captcha_math(pil_image: Image.Image) -> str:
    """OCR a math captcha. Upscales, then tries psm modes in priority order.

    Returns the first non-empty result. PSM 7 (single line) is the most reliable
    for math captchas after upscaling; falls back to others if empty.
    """
    pil_image = _preprocess_for_ocr(pil_image)
    for psm in (7, 6, 13, 8, 11):
        try:
            txt = ocr_image(pil_image, psm=psm, whitelist="0123456789+-*/=()xX? ").strip()
            if txt:
                return txt
        except Exception:
            continue
    return ""


def ocr_captcha_text(pil_image: Image.Image) -> str:
    """OCR a text-only captcha (alphanumeric)."""
    pil_image = _preprocess_for_ocr(pil_image)
    return ocr_image(pil_image, psm=7, whitelist="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789")