import json
import logging
import os
import re

from services.llm import send_message, send_message_with_model
from services.personas import get_persona

logger = logging.getLogger(__name__)

PROMPT_BUILDER_SYSTEM = """You are a Stable Diffusion prompt engineer for anime illustration models.
Given a roleplay chat excerpt, output ONLY valid JSON (no markdown):
{
  "should_generate": true,
  "shot_type": "first_person_pov" | "landscape" | "third_person",
  "action_tags": "booru-style tags for pose/action/expression, e.g. 'sitting, smiling, holding_cup'",
  "environment_tags": "booru-style tags for location/lighting/time, e.g. 'indoors, kitchen, sunlight, daytime'"
}
Rules:
- ONLY use real danbooru/e621 tags. Multi-word concepts MUST be underscore_joined: 'fox_ears' not 'fox ears'.
- Do NOT include appearance/character tags — those are provided separately.
- Do NOT include quality tags, model names, style words, 'pov', or category/metadata words.
- Do NOT invent tags. If unsure — omit.
- Keep each field to 3-6 tags."""


def extract_image_prompt_tag(text: str) -> str | None:
    if "[IMAGE_PROMPT:" not in text:
        return None
    try:
        start = text.index("[IMAGE_PROMPT:") + len("[IMAGE_PROMPT:")
        end = text.index("]", start)
        return text[start:end].strip()
    except ValueError:
        return None


def strip_image_prompt_tag(text: str) -> str:
    return re.sub(r"\[IMAGE_PROMPT:.*?\]", "", text, flags=re.DOTALL).strip()


SD_CHECKPOINT = os.getenv("SD_CHECKPOINT", "")
SD_UNET = os.getenv("SD_UNET", "")
SD_PROMPT_MODEL = os.getenv("SD_PROMPT_MODEL", "").strip()

PONY_CHECKPOINTS = {"ponyDiffusionV6XL_v6StartWithThisOne.safetensors"}
PONY_NEGATIVE  = "score_1, score_2, score_3, score_4, worst quality, low quality, blurry, bad anatomy, watermark, text, censored"
ANIMA_NEGATIVE = "worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia"


def _is_pony() -> bool:
    return SD_CHECKPOINT in PONY_CHECKPOINTS


def _is_anima() -> bool:
    return bool(SD_UNET) and not SD_CHECKPOINT


def build_positive_prompt(scene: dict, persona: dict | None, outfit_tags: str = "") -> str:
    if _is_pony():
        quality = "score_9, score_8_up, score_7_up, source_anime, highres"
    elif _is_anima():
        quality = "masterpiece, best quality, score_7, anime"
    else:
        quality = "masterpiece, best quality, highres"

    parts = [quality]

    appearance = (persona or {}).get("appearance_tags", "")
    if appearance:
        parts.append(appearance)
    if outfit_tags:
        parts.append(outfit_tags)

    if scene.get("shot_type") == "landscape":
        parts.append(scene.get("environment_tags", ""))
    else:
        if scene.get("shot_type") == "first_person_pov":
            parts.append("pov, first-person view, looking at viewer")
        parts.append(scene.get("action_tags", ""))
        parts.append(scene.get("environment_tags", ""))

    lora = (persona or {}).get("lora_name", "")
    weight = (persona or {}).get("lora_weight", 0.8)
    if lora:
        parts.append(f"<lora:{lora}:{weight}>")

    positive = ", ".join(p.strip() for p in parts if p and p.strip())
    seen, deduped = set(), []
    for tag in positive.split(", "):
        t = tag.strip()
        if t and t not in seen:
            seen.add(t)
            deduped.append(t)
    return ", ".join(deduped)


async def generate_sd_prompt(
    messages: list,
    persona_id: str,
    outfit_json: str = "[]",
) -> tuple[str | None, str | None]:
    persona = await get_persona(persona_id)
    # Generate only if persona has appearance tags
    if not persona or not (persona.get("appearance_tags") or "").strip():
        logger.debug("sd_prompt skip: persona=%s no appearance_tags", persona_id)
        return None, None

    recent = [m for m in messages if m["role"] in ("user", "assistant")][-6:]
    if not recent:
        return None, None

    excerpt = "\n".join(f"{m['role']}: {strip_image_prompt_tag(m['content'])}" for m in recent)

    builder_messages = [
        {"role": "system", "content": PROMPT_BUILDER_SYSTEM},
        {"role": "user", "content": f"Chat:\n{excerpt}"},
    ]

    try:
        if SD_PROMPT_MODEL:
            raw = await send_message_with_model(builder_messages, SD_PROMPT_MODEL)
        else:
            raw = await send_message(builder_messages)
        raw = raw.strip()
        if raw.startswith("```"):
            raw = re.sub(r"^```\w*\n?", "", raw)
            raw = re.sub(r"\n?```$", "", raw)
        scene = json.loads(raw)
        if not isinstance(scene, dict):
            logger.warning("sd_prompt: LLM returned non-dict: %.100s", raw)
            return None, None
    except Exception as e:
        logger.warning("sd_prompt failed: %s raw=%.200s", e, locals().get("raw", ""))
        return None, None

    try:
        outfit_list = json.loads(outfit_json or "[]")
        outfit_tags = ", ".join(outfit_list) if isinstance(outfit_list, list) else ""
    except Exception:
        outfit_tags = ""

    positive = build_positive_prompt(scene, persona, outfit_tags)

    if _is_pony():
        negative = PONY_NEGATIVE
    elif _is_anima():
        negative = ANIMA_NEGATIVE
    else:
        negative = "low quality, blurry, bad anatomy, watermark, text"

    if scene.get("shot_type") == "first_person_pov":
        negative += ", third person, over the shoulder"

    full = positive + f"\n\nNegative prompt: {negative}"
    return full, negative