import os
import json
from core import utils
from ai import models as ai_models


def generate_blurb(bp, folder):
    utils.log("MARKETING", "Generating blurb...")
    meta = bp.get('book_metadata', {})

    beats = bp.get('plot_beats', [])
    beats_text = "\n".join(f"  - {b}" for b in beats[:6]) if beats else "  - (no beats provided)"

    chars = bp.get('characters', [])
    protagonist = next((c for c in chars if 'protagonist' in c.get('role', '').lower()), None)
    protagonist_desc = f"{protagonist['name']} — {protagonist.get('description', '')}" if protagonist else "the protagonist"

    prompt = f"""
    ROLE: Marketing Copywriter
    TASK: Write a compelling back-cover blurb for a {meta.get('genre', 'fiction')} novel.

    BOOK DETAILS:
    - TITLE: {meta.get('title')}
    - GENRE: {meta.get('genre')}
    - AUDIENCE: {meta.get('target_audience', 'General')}
    - PROTAGONIST: {protagonist_desc}
    - LOGLINE: {bp.get('manual_instruction', '(none)')}
    - KEY PLOT BEATS:
{beats_text}

    BLURB STRUCTURE:
    1. HOOK (1-2 sentences): Open with the protagonist's world and the inciting disruption. Make it urgent.
    2. STAKES (2-3 sentences): Raise the central conflict. What does the protagonist stand to lose?
    3. TENSION (1-2 sentences): Hint at the impossible choice or escalating danger without revealing the resolution.
    4. HOOK CLOSE (1 sentence): End with a tantalising question or statement that demands the reader open the book.

    RULES:
    - 150-200 words total.
    - DO NOT reveal the ending or resolution.
    - Match the genre's marketing tone ({meta.get('genre', 'fiction')}: e.g. thriller = urgent/terse, romance = emotionally charged, fantasy = epic/wondrous, horror = dread-laden).
    - Use present tense for the blurb voice.
    - No "Blurb:", no title prefix, no labels — marketing copy only.
    """
    try:
        response = ai_models.model_writer.generate_content(prompt)
        utils.log_usage(folder, ai_models.model_writer.name, response.usage_metadata)
        blurb = response.text.strip()

        # Trim to 220 words if model overshot the 150-200 word target
        words = blurb.split()
        if len(words) > 220:
            blurb = " ".join(words[:220])
            # End at the last sentence boundary within those 220 words
            for end_ch in ['.', '!', '?']:
                last_sent = blurb.rfind(end_ch)
                if last_sent > len(blurb) // 2:
                    blurb = blurb[:last_sent + 1]
                    break
            utils.log("MARKETING", f"  -> Blurb trimmed to {len(blurb.split())} words.")

        with open(os.path.join(folder, "blurb.txt"), "w", encoding='utf-8') as f:
            f.write(blurb)
        with open(os.path.join(folder, "back_cover.txt"), "w", encoding='utf-8') as f:
            f.write(blurb)
        utils.log("MARKETING", f"  -> Blurb: {len(blurb.split())} words.")
    except Exception as e:
        utils.log("MARKETING", f"Failed to generate blurb: {e}")