import os
import re
from PIL import Image, ImageDraw, ImageFont
from modules.markovmemory import load_markov_model
from modules.sentenceprocessing import improve_sentence_coherence, rephrase_for_coherence
# add comments l8r
generated_sentences = set()

async def gen_image(input_image_path, sentence_size=5, max_attempts=10):
    markov_model = load_markov_model()
    if not markov_model:
        return None
    if not os.path.isfile(input_image_path):
        return None
    def load_font(size):
        return ImageFont.truetype("assets/fonts/Impact.ttf", size=size)
    def draw_text_with_outline(draw, text, x, y, font):
        outline_offsets = [(-2, -2), (-2, 2), (2, -2), (2, 2), (0, -2), (0, 2), (-2, 0), (2, 0)]
        for ox, oy in outline_offsets:
            draw.text((x + ox, y + oy), text, font=font, fill="black")
        draw.text((x, y), text, font=font, fill="white")
    def fits_in_width(text, font, max_width, draw):
        bbox = draw.textbbox((0, 0), text, font=font)
        text_width = bbox[2] - bbox[0]
        return text_width <= max_width
    def split_text_to_fit(text, font, max_width, draw):
        words = text.split()
        for i in range(len(words), 0, -1):
            top_text = " ".join(words[:i])
            bottom_text = " ".join(words[i:])
            if fits_in_width(top_text, font, max_width, draw) and fits_in_width(bottom_text, font, max_width, draw):
                return top_text, bottom_text
        midpoint = len(words) // 2
        return " ".join(words[:midpoint]), " ".join(words[midpoint:])

    attempt = 0
    while attempt < max_attempts:
        with Image.open(input_image_path).convert("RGBA") as img:
            draw = ImageDraw.Draw(img)
            width, height = img.size

            font_size = int(height / 10)
            font = load_font(font_size)

            response = None
            for _ in range(20):
                if sentence_size == 1:
                    candidate = markov_model.make_short_sentence(max_chars=100, tries=100)
                    if candidate:
                        candidate = candidate.split()[0]
                else:
                    candidate = markov_model.make_sentence(tries=100, max_words=sentence_size)

                if candidate and candidate not in generated_sentences:
                    if sentence_size > 1:
                        candidate = improve_sentence_coherence(candidate)
                    generated_sentences.add(candidate)
                    response = candidate
                    break

            if not response:
                response = "no text generated"

            cleaned_response = re.sub(r'[^\w\s]', '', response).lower()
            coherent_response = rephrase_for_coherence(cleaned_response).upper()

            bbox = draw.textbbox((0, 0), coherent_response, font=font)
            text_width = bbox[2] - bbox[0]
            text_height_px = bbox[3] - bbox[1]
            max_text_height = height // 4

            if text_width <= width and text_height_px <= max_text_height:
                draw_text_with_outline(draw, coherent_response, (width - text_width) / 2, 0, font)
                img.save(input_image_path)
                return input_image_path
            else:
                top_text, bottom_text = split_text_to_fit(coherent_response, font, width, draw)

                top_bbox = draw.textbbox((0, 0), top_text, font=font)
                bottom_bbox = draw.textbbox((0, 0), bottom_text, font=font)

                top_height = top_bbox[3] - top_bbox[1]
                bottom_height = bottom_bbox[3] - bottom_bbox[1]

                if top_height <= max_text_height and bottom_height <= max_text_height:
                    draw_text_with_outline(draw, top_text, (width - (top_bbox[2] - top_bbox[0])) / 2, 0, font)
                    y_bottom = height - bottom_height - int(height * 0.04)
                    draw_text_with_outline(draw, bottom_text, (width - (bottom_bbox[2] - bottom_bbox[0])) / 2, y_bottom, font)
                    img.save(input_image_path)
                    return input_image_path

        attempt += 1


    with Image.open(input_image_path).convert("RGBA") as img:
        draw = ImageDraw.Draw(img)
        width, height = img.size
        font_size = int(height / 10)
        font = load_font(font_size)

        truncated = coherent_response[:100]
        bbox = draw.textbbox((0, 0), truncated, font=font)
        text_width = bbox[2] - bbox[0]
        draw_text_with_outline(draw, truncated, (width - text_width) / 2, 0, font)
        img.save(input_image_path)
        return input_image_path